Florida Commission on Hurricane Loss Projection Methodology

Submitted: November 5, 2018 Revised: January 21, 2019 Revised: February 13, 2019 Revised: March 22, 2019 Revised: April 9, 2019 Revised: July 12, 2019

HurLoss Version 9.0

2017 Hurricane Standards

Prepared for:

Florida Commission on Hurricane Loss Projection Methodology State Board of Administration 1801 Hermitage Boulevard Tallahassee, Florida 32308

Prepared by:

Applied Research Associates, Inc. IntraRisk Division 8537 Six Forks Road, Suite 600 Raleigh, North Carolina 27615

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Florida Commission on Hurricane Loss Projection Methodology

Model Identification

Name of Hurricane Model: HurLoss Florida Model Hurricane Model Version Identification: 9.0 Interim Hurricane Model Update Version Identification: N/A

Hurricane Model Platform Name and Identifications: HurLoss Software Platform

Interim Data Update Designation: N/A Name of Modeling Organization: Applied Research Associates, Inc. Street Address: 8537 Six Forks Road, Suite 600 City, State, Zip Code: Raleigh, NC, 27615 Mailing Address, if different from above: N/A Contact Person: Frank Lavelle Phone Number: (919) 582-3350 Fax Number: (919) 582-3401 E-mail Address: [email protected] Date: April 9, 2019

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November 5, 2018 Floyd Yager, FCAS Chair, Florida Commission on Hurricane Loss Projection Methodology 1801 Hermitage Boulevard, Suite 100 Tallahassee, FL 32308

Re: ARA Model Submission under the November 1, 2017 Standards

Dear Mr. Yager: Applied Research Associates is pleased to submit our hurricane loss projection model for review by the Florida Commission on Hurricane Loss Projection Methodology. The model has been reviewed by professionals having credentials and/or experience in the areas of meteorology, statistics, engineering, actuarial science, and computer/information science, as indicated by the signed Expert Certification Forms G-1, G-2, G-3, G-4, G-5 and G-6. Our submission has been reviewed for editorial compliance, as indicated by the signed Form G-7. Attached to this letter are the Model Submission Checklist and a summary statement of compliance with each individual standard. Enclosed are 7 bound copies of our submission. Electronic copies of our submission can be downloaded from an ARA ftp site. Details regarding accessing this site will be emailed to the Commission. ARA is prepared to review proprietary data, model documentation, model validation, and any additional questions by the Professional Team during their visit. If you have any additional questions regarding this submission, please contact me.

Sincerely,

Francis M. Lavelle, Ph.D., P.E. Principal Engineer

FML/lw

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Hurricane Model Submission Checklist

1. Please indicate by checking below that the following has been included in your submission to the Florida Commission on Hurricane Loss Projection Methodology. Yes No Item X 1. Letter to the Commission X a. Refers to the signed Expert Certification forms and states that professionals having credentials and/or experience in the areas of meteorology, statistics, structural engineering, actuarial science, and computer/information science have reviewed the model for compliance with the standards X b. States model is ready to be reviewed by the Professional Team X c. Any caveats to the above statements noted with a complete explanation X 2. Summary statement of compliance with each individual standard and the data and analyses required in the disclosures and forms X 3. General description of any trade secret information the modeling organization intends to present to the Professional Team and the Commission X 4. Hurricane Model Identification X 5. Seven bound copies (duplexed) X 6. Link emailed to SBA staff containing all required documentation that can be downloaded from a single ZIP file X a. Submission document and Form A-1, Zero Deductible Personal Residential Hurricane Loss Costs by Zip Code in PDF format X b. PDF submission file supports highlighting and hyperlinking, and is bookmarked by standard, form, and section X c. Data file names include abbreviated name of modeling organization, standards year, and form name (when applicable) X d. Form S-6, Hypothetical Events for Sensitivity and Uncertainty Analysis, if required, in ASCII and PDF format X e. Forms M-1, Annual Occurrence Rates, M-3, Radius of Maximum Winds and Radii of Standard Wind Thresholds, V-2, Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage, V-4, Differences in Hurricane Mitigation Measures and Secondary Characteristics, A-1, Zero Deductible Personal Hurricane Residential Loss Costs by ZIP Code, A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), A-3A, 2004 Hurricane Season Losses (2012 FHCF Exposure Data), A-3B, 2004 Hurricane Season Losses (2017 FHCF Exposure Data), A-4A, Hurricane Output Ranges (2012 FHCF Exposure Data), A-4B, Hurricane Output Ranges (2017 FHCF Exposure Data), A-5, Percentage Change in Hurricane Output Ranges, A-7, Percentage Change in Logical Relationship to Hurricane Risk, and A-8A, Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data), and A-8B, Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data), in Excel format X f. Form V-3, hurricane Mitigation measures and Secondary Characteristics, Mean Damage Ratios and Hurricane Loss Costs (Trade Secret Item), Form V-5, Differences in Hurricane Mitigation Measures and Secondary Characteristics, Mean Damage Ratios and Hurricane Loss Costs (Trade Secret Item, and Form A-6, Logical Relationship to hurricane Risk (trade Secret Item), in Excel format if not considered as Trade Secret X 7. All hyperlinks to the locations of forms are functional X 8. Table of Contents X 9. Materials consecutively numbered from beginning to end starting with the first page (including cover) using a single numbering system, including date and time in footnote X 10. All tables, graphs, and other non-text items consecutively numbered using whole numbers, listed in Table of Contents, and clearly labeled with abbreviations defined

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Yes No Item X 11. All column headings shown and repeated at the top of every subsequent page for forms and tables X 12. Standards, disclosures, and forms in italics, modeling organization responses in non-italic X 13. All graph and maps conform to guidelines in II. Notification Requirements A.4.e. X 14. All units of measurement clearly identified with appropriate units used X 15. All forms included in submission document appendix except Trade Secret Items. If forms designated as a Trade Secret Item are not considered as trade secret, those forms are to be included in the submission appendix X 16. Hard copy documentation identical to the electronic version X 17. Signed Expert Certification Forms G-1 to G-7 X 18. All acronyms listed and defined in submission appendix 2. Explanation of “No” responses indicated above. (Attach additional pages if needed.)

Form S-6 is not required

HurLoss 9.0 11/5/2018 Model Name Modeler Signature Date

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ARA Summary Statement of Compliance

Standard Standard Met? General Standards G-1 Scope of the Hurricane Model and Its Implementation Yes G-2 Qualifications of Modeling Organization Personnel and Consultants Engaged in Yes Development of the Hurricane Model G-3 Insured Exposure Location Yes G-4 Independence of Hurricane Model Components Yes G-5 Editorial Compliance Yes Meteorological Standards M-1 Base Hurricane Storm Set Yes M-2 Hurricane Parameters and Characteristics Yes M-3 Hurricane Probability Distributions Yes M-4 Hurricane Windfield Structure Yes M-5 Hurricane Landfall and Over-Land Weakening Methodologies Yes M-6 Logical Relationships of Hurricane Characteristics Yes Statistical Standards S-1 Modeled Results and Goodness-of-Fit Yes S-2 Sensitivity Analysis for Hurricane Model Output Yes S-3 Uncertainty Analysis for Hurricane Model Output Yes S-4 County Level Aggregation Yes S-5 Replication of Known Hurricane Losses Yes S-6 Comparison of Projected Hurricane Loss Costs Yes Vulnerability Standards V-1 Derivation of Building Hurricane Vulnerability Functions Yes V-2 Derivation of Contents and Time Element Hurricane Vulnerability Functions Yes V-3 Hurricane Mitigation Measures and Secondary Characteristics Yes Actuarial Standards A-1 Hurricane Modeling Input Data and Output Reports Yes A-2 Hurricane Events Resulting in Modeled Hurricane Losses Yes A-3 Hurricane Coverages Yes A-4 Modeled Hurricane Loss Cost and Hurricane Probable Maximum Loss Level Yes Considerations A-5 Hurricane Policy Conditions Yes A-6 Hurricane Loss Outputs and Logical Relationship to Risk Yes Computer Standards C-1 Hurricane Model Documentation Yes C-2 Hurricane Model Requirements Yes C-3 Hurricane Model Architecture and Component Design Yes C-4 Hurricane Model Implementation Yes C-5 Hurricane Model Verification Yes C-6 Hurricane Model Maintenance and Revision Yes C-7 Hurricane Model Security Yes

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ARA Checklist Item 3

Item 3. General description of any trade secrets the modeling organization intends to present to the Professional Team. The Professional Team will be shown documentation binders, validation studies and supporting information related to the model changes listed in our response to Disclosure 5 under Standard G-1. Any other materials will be dependent upon requests or suggestions from the Professional Team.

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Table of Contents

Page General Standards ...... 21 G-1 Scope of the Hurricane Computer Model and Its Implementation ...... 21 G-2 Qualifications of Modeling Organization Personnel and Consultants Engaged in Development of the Hurricane Model ...... 31 G-3 Insured Exposure Location ...... 41 G-4 Independence of Hurricane Model Components ...... 43 G-5 Editorial Compliance ...... 48 Meteorological Standards ...... 49 M-1 Base Hurricane Storm Set* (Significant Revision) ...... 49 M-2 Hurricane Parameters and Characteristics ...... 50 M-3 Hurricane Probability Distributions ...... 56 M-4 Hurricane Windfield Structure ...... 58 M-5 Hurricane Landfall and Over-Land Weakening Methodologies ...... 61 M-6 Logical Relationships of Hurricane Characteristics ...... 66 Statistical Standards ...... 67 S-1 Modeled Results and Goodness of Fit ...... 67 S-2 Sensitivity Analysis for Hurricane Model Output ...... 73 S-3 Uncertainty Analysis for Hurricane Model Output ...... 75 S-4 County Level Aggregation ...... 77 S-5 Replication of Known Hurricane Losses ...... 78 S-6 Comparison of Projected Hurricane Loss Costs ...... 80 Vulnerability Standards ...... 83 V-1 Derivation of Bulding Hurricane Vulnerability Functions ...... 83 V-2 Derivation of Contents and Time Element Hurricane Vulnerability Functions* (Significant Revision) ...... 91 V-3 Hurricane Mitigation Measures and Secondary Characteristics* (Significant Revision) ...... 97 Actuarial Standards ...... 99 A-1 Hurricane Modeling Input Data and Output Reports ...... 99 A-2 Hurricane Events Resulting in Modeled Hurricane Losses* (Significant Revision) ...... 107 A-3 Hurricane Coverages ...... 108

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A-4 Modeled Hurricane Loss Cost and Hurricane Probable Maximum Loss Level Considerations ...... 110 A-5 Hurricane Policy Conditions ...... 113 A-6 Hurricane Loss Outputs and Logical Relationship to Risk ...... 115 Computer/Information Standards ...... 119 CI-1 Hurricane Model Documentation* (Significant Revision) ...... 119 CI-2 Hurricane Model Requirements ...... 121 CI-3 Hurricane Model Architecture and Component Design* (Significant Revision) ...... 122 CI-4 Hurricane Model Implementation ...... 123 CI-5 Hurricane Model Verification ...... 125 CI-6 Hurricane Model Maintenance and Revision ...... 127 CI-7 Hurricane Model Security ...... 128 References ...... 129 Meteorological Standards ...... 129 Statistical Standards ...... 134 Vulnerability Standards ...... 134 Actuarial Standards ...... 139 Computer/Information Standards ...... 140 Appendix A ...... 141 Form G-1: General Standards Expert Certification ...... 141 Form G-2: Meteorological Standards Expert Certification ...... 142 Form G-3: Statistical Standards Expert Certification ...... 143 Form G-4: Vulnerability Standards Expert Certification ...... 144 Form G-5: Actuarial Standards Expert Certification ...... 145 Form G-6: Computer/Information Standards Expert Certification ...... 146 Form G-7: Editorial Certification ...... 147 Form M-1: Annual Occurrence Rates ...... 148 Form M-2: Maps of Maximum Winds ...... 153 Form M-3: Radius of Maximum Winds and Radii of Standard Wind Thresholds ...... 158 Form S-1: Probability and Frequency of Florida Landfalling Hurricanes per Year ...... 161 Form S-2A: Examples of Hurricane Loss Exceedance Estimates (2012 FHCF Exposure Data) ...... 162

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Form S-2B: Examples of Hurricane Loss Exceedance Estimates (2017 FHCF Exposure Data) ...... 163 Form S-3: Distributions of Stochastic Hurricane Parameters ...... 164 Form S-4: Validation Comparisons ...... 178 Form S-5: Average Annual Zero Deductible Statewide Hurricane Loss Costs – Historical versus Modeled ...... 184 Form V-1: One Hypothetical Event ...... 186 Form V-2: Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage ...... 189 Form V-4: Differences in Hurricane Mitigation Measures and Secondary Characteristics ...... 191 Form A-1: Zero Deductible Personal Residential Hurricane Loss Costs by ZIP Code ...... 193 Form A-2A: Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data) ...... 196 Form A-2B: Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data) ...... 199 Form A-3A: 2004 Hurricane Season Losses (2012 FHCF Exposure Data) ...... 202 Form A-3B: 2004 Hurricane Season Losses (2017 FHCF Exposure Data) ...... 222 Form A-4A: Hurricane Output Ranges (2012 FHCF Exposure Data) ...... 242 Form A-4B: Hurricane Output Ranges (2017 FHCF Exposure Data) ...... 253 Form A-5: Percentage Change in Hurricane Output Ranges (2012 FHCF Exposure Data) ...... 264 Form A-7: Percentage Change in Logical Relationship to Hurricane Risk ...... 271 Form A-8A: Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data) ...... 279 Form A-8B: Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data) ...... 284 Appendix B – Acronyms ...... 289 Appendix C – Actuarial Review Letter ...... 291

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List of Figures

Page Figure 1. Overview of Hurricane Damage and Loss Modeling ...... 24 Figure 2. High Level Flowchart of Portfolio (Multiple Buildings – Multiple Sites) Computer Model ...... 26 Figure 3. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to Changes in Surface Roughness from Version 7.0.a to 7.0.b ...... 28 Figure 4. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to Updated Stochastic Event Set ...... 28 Figure 5. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to ZIP Code Centroid Update ...... 29 Figure 6. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to Land Use/Land Cover Update ...... 29 Figure 7. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to All Changes Combined ...... 30 Figure 8. ARA Office Locations and Technical Specialties ...... 32 Figure 9. Model Workflow ...... 38 Figure 10. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Inland Locations ...... 43 Figure 11. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Coastal and Near Coastal Locations ...... 45 Figure 12. Radial Profile of Azimuthally Averaged Horizontal Windspeeds ...... 59 Figure 13. Comparison of Modeled and Observed Windspeeds for Hurricane Jeanne. (Windspeeds are 3 Second Gust Values at a Height of 10m in Flat, Open Terrain and Storm is Decayed Using the ARA Filling Model) ...... 63 Figure 14. Example Comparisons of Modeled Decay Rates to Kaplan-DeMaria Decay Rates (Windspeeds are 1-Minute Sustained Windspeeds at a Height of 10 m in Open Terrain) ...... 64 Figure 15. Comparison of Historical and Modeled Distributions of the Translations Speed of all Tropical Cyclones Passing Within 155 miles of Milepost 1450 ...... 67 Figure 16. Comparison of Historical and Modeled Distributions of the Translation Speed of all Tropical Cyclones Passing Within 155 miles of Milepost 1450 ...... 68 Figure 17. Comparison of Modeled and Historical Hurricane Landfall Pressures ...... 70 Figure 18. Comparison of Modeled and Historical Probabilities of Multiple Landfalls in a Year ...... 71 Figure 19. Comparison of Modeled and Historical Landfall Rates as a Function of Hurricane Category ...... 71 Figure 20. Distribution of AAL Associated with a 1% CoV in the Windspeed Model ...... 74

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Figure 21. Standard Errors in County Weighted Average Loss Costs ...... 77 Figure 22. Comparison of Modeled and Observed Losses for Homeowner Policies ...... 78 Figure 23. Comparison of Modeled and Actual Losses as a Function of Peak Gust Windspeed in Open Terrain ...... 79 Figure 24. Flow Chart for Development of Building Vulnerability Functions ...... 85 Figure 25. Flow Chart for Development of Contents Vulnerability Functions ...... 92 Figure 26. Comparison of Modeled and Observed Mean Content Damage vs. Mean Building Damage ...... 93 Figure 27. Flow Chart for Development of Time Element Vulnerability Functions ...... 94 Figure 28. Comparison of Modeled and Observed Mean Time Element Losses (Additional Living Expenses) vs. Mean Building Damage ...... 95 Figure 29. Model Output Report Files ...... 105 Figure 30. Input Control File for Form A-1 ...... 106 Figure 31. State of Florida and Neighboring States By Region ...... 151 Figure 32. Comparison of Modeled and Observed Landfalling Counts of Hurricanes by Category (defined by windspeed) and Region ...... 152 Figure 33. Maximum One-Minute Sustained Windspeed at a Height of 10 m in Open Terrain (upper map) and Local Terrain (lower map) Derived from the Historical Storm Set ...... 155 Figure 34. 100-Year Return Period Sustained Windspeeds at a Height of 10 m Above Ground in Open Terrain (upper plot) and Local Terrain (lower plot) ...... 156 Figure 35. 250-Year Return Period Sustained Windspeeds at a Height of 10 m Above Ground in Open Terrain (upper plot) and Local Terrain (lower plot) ...... 157 Figure 36. Simulated Distribution of Rmax vs. Central Pressure Derived from 5,000 Florida Landfalling Model Hurricanes ...... 159 Figure 37. Histograms of Central Pressure (upper plot) and Radius to Maximum Winds (lower plot) for all Model Hurricanes Making Landfall in Florida ...... 160 Figure 38. Modeled and Historical Basin Wide Storm Frequencies ...... 165 Figure 39. Locations of Coastal Segments Used to Compare Modeled and Historical Properties of Hurricanes at Landfall ...... 165 Figure 40. Comparisons of Modeled and Observed Translation Speed at Landfall for Segments Along the Florida Coast Line ...... 166 Figure 41. Comparisons of Modeled and Observed Storm Headings at Landfall for Segments Along the Florida Coast Line ...... 167 Figure 42. Comparisons of Modeled and Observed Storm Headings at Landfall for Segments Along the Florida Coast Line ...... 168 Figure 43. Comparisons of Modeled and Observed Landfall Central Pressures for Segments along the Florida Coast Line ...... 169

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Figure 44. Comparisons of Modeled and Observed Landfall Central Pressures for Segments along the Florida Coast Line Plotted as a function of Return Period ...... 170 Figure 45. Comparisons of Modeled and Observed Translation Speed at Landfall Along the Coasts of the Four Florida Regions ...... 171 Figure 46. Comparisons of Modeled and Observed Storm Heading at Landfall Along the Coasts of the Four Florida Regions ...... 172 Figure 47. Comparisons of Modeled and Observed Landfall Rates Along the Coasts of the Four Florida Regions ...... 173 Figure 48. Comparisons of Modeled and Observed Distributions of Landfall Central Pressure Along the Coasts of the Four Florida Regions ...... 174 Figure 49. Comparisons of Modeled and Observed Distributions of Landfall Central Pressure Plotted as a Function of Return Period Along the Coasts of the Four Florida Regions ...... 175 Figure 50. Comparisons of Modeled and Observed Distributions of Translation Speed, Heading, Landfall Rates, and Central Pressure Plotted vs. Return Period for the Entire Florida Coastline ...... 176 Figure 51. Comparisons of Modeled and Historical Values of B (left) and RMW (right) Along the Coast of Florida and Adjoining States ...... 177 Figure 52. Validation Comparisons ...... 182 Figure 53. Losses vs. Windspeed for Form V-1, Part A ...... 188 Figure 54. Ground-Up Loss Cost Wood Frame Houses ...... 194 Figure 55. Ground-Up Loss Cost for Masonry Wall Houses ...... 195 Figure 56. Ground-Up Loss Cost for Manufactured Home ...... 195 Figure 57. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Charley ...... 219 Figure 58. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Frances ...... 219 Figure 59. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Ivan ...... 220 Figure 60. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Jeanne ...... 220 Figure 61. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for All Four of the 2004 Hurricanes ...... 221 Figure 62. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Charley ...... 239 Figure 63. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Frances ...... 239 Figure 64. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Ivan ...... 240

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Figure 65. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Jeanne ...... 240 Figure 66. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for All Four of the 2004 Hurricanes ...... 241 Figure 67. State of Florida by North/Central/South Regions ...... 265 Figure 68. State of Florida by Coastal/Inland Counties ...... 265 Figure 69. Frame Owners ...... 267 Figure 70. Masonry Owners ...... 267 Figure 71. Manufactured Homes ...... 268 Figure 72. Frame Renters ...... 268 Figure 73. Masonry Renters ...... 269 Figure 74. Frame Condo Unit Owners ...... 269 Figure 75. Masonry Condo Unit Owners ...... 270 Figure 76. Commercial Residential ...... 270 Figure 77. Comparison of Form A-8A Results to Prior Year’s Submission ...... 282 Figure 78. Comparison of Form A-8B Results to Prior Year’s Submission ...... 287

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List of Tables

Page Table 1. Professional Credentials ...... 33 Table 2. Example of Insurer Loss Calculation ...... 114 Table 3. Annual Occurrence Rates...... 150

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GENERAL STANDARDS

G-1 Scope of the Hurricane Model and Its Implementation

A. The hurricane model shall project loss costs and probable maximum loss levels for damage to insured residential property from hurricane events. B. The modeling organization shall maintain a documented process to assure continual agreement and correct correspondence of databases, data files, and computer source code to slides, technical papers, and modeling organization documents. C. All software and data (1) located within the hurricane model, (2) used to validate the hurricane model, (3) used to project modeled hurricane loss costs and hurricane probable maximum loss levels, and (4) used to create forms required by the Commission in the Hurricane Standards Report of Activities shall fall within the scope of the Computer/Information Standards and shall be located in centralized, model-level file areas.

A. The hurricane model developed by Applied Research Associates, Inc. (ARA) provides estimates of loss costs and probable maximum loss levels for residential property from hurricane events, excluding flood and storm surge, except as it applies to Additional Living Expenses (ALE). Losses are developed for buildings, the contents of a building, appurtenant structures, and additional living expenses. Gross losses are developed and insured losses are computed using policy information. The model begins to estimate damage to buildings when the peak gust windspeed (in open terrain) produced by a hurricane equals or exceeds 50 mph. This 50 mph peak gust threshold corresponds to a sustained (one-minute average) windspeed (in open terrain) of about 40 mph. The methodology used in the model to predict damage and loss, given a windspeed, has been presented to the Professional Team during previous visits. The historical data sets used in the development and validation of the model do not include loss from flood and storm surge. B. ARA maintains a documented process to assure continual agreement and correct correspondence of databases, data files, and computer source code to slides, technical papers, and/or modeling organization documents. C. All software and data related to the model are stored in centralized, model-level file areas including revision control systems for software, documents, and data files and file server systems for large data files.

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1. Specify the hurricane model version identification. If the hurricane model submitted for review is implemented on more than one platform, specify each hurricane model platform. Specify which platform is the primary platform and verify how any other platforms produce the same hurricane model output results or are otherwise functionally equivalent as provided for in the “Process for Determining the Acceptability of a Computer Simulation Hurricane Model” in VI. Review by the Commission, I. Review and Acceptance Criteria for Functionally Equivalent Hurricane Model Platforms. Our current submittal is for HurLoss Florida model version 9.0 as implemented on the HurLoss software platform version 9.0. 2. Provide a comprehensive summary of the hurricane model. This summary should include a technical description of the hurricane model including each major component of the model used to project loss costs and probable maximum loss levels for damage to insured residential property from hurricane events causing damage in Florida. Describe the theoretical basis of the hurricane model and include a description of the methodology, particularly the wind components, the vulnerability components, and the insured loss components used in the hurricane model. The description should be complete and must not reference unpublished work. ARA’s hurricane model has been developed using wind engineering principles to enable detailed estimates of damage and loss to buildings and their contents due to wind storms. The model uses a peer reviewed (reviewed by both meteorologists and wind engineers) hurricane hazard model that enables the modeling of the entire track of a hurricane or tropical storm. The hurricane windfield model has been more extensively validated than any other published hurricane windfield model. The results of ARA’s hurricane hazard model are used directly in the design windspeed map given in the American Society of Civil Engineers Standard 7-10 (ASCE 7-10), Minimum Design Loads for Buildings and Other Structures. Since the hurricane model simulates the entire hurricane track, whether the storm makes landfall or not, computation of loss does not require that a storm make landfall, but simply requires that the windspeed produced by the storm at any point exceed a predefined minimum value. The model has the ability to treat storms that make multiple landfalls. ARA’s physical damage model is based on load and resistance analysis of building components. The physical damage model estimates the damage to the building in terms of failure of building envelope components. Insured loss is estimated from the building damage states using empirical cost estimation techniques for building repair and replacement. Contents loss is based on an empirical model that relates contents damage to building envelope performance. The building, appurtenance, contents, and loss of use components have been validated with insurance loss data. For portfolio assessments, a fast-running loss function is developed for each building class. These functions are used to estimate losses for each coverage type and deductible in each simulated storm. The computational procedure is straightforward Monte Carlo simulation. The model can produce losses by coverage, policy, site, zip code, county, state, and portfolio levels. The storm- by-storm and year-by-year output data can be easily post-processed to obtain average annual loss (AAL), as well as the loss distribution statistics (Probable Maximum Loss, etc.) on a per occurrence or per year basis. Hurricane Hazard Model. The two key components of the hurricane hazard model are: (i) the hurricane windfield model (Vickery et al., 2009a) and (ii) the probabilistic models describing the occurrence rates, storm tracks, and intensities (Vickery et al., 2009b). The probabilistic portion of

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the hurricane hazard model is described in detail in Vickery, et al. (2000b). The key features of the storm track model are the coupling of the modeling of the central pressure with sea surface temperature, and the ability to model curved tracks that can make multiple landfalls. The entire track of a storm is modeled, from the time of storm initiation over the water, until the storm dissipates. The starting times (hour, day, and month) and locations of the storms are taken directly from the Atlantic basin hurricane database (HURDAT). Using the actual starting times and locations ensures that any climatological preference for storms to initiate in different parts of the Atlantic Basin at different times of the year is maintained. The coupling of the central pressure modeling to sea surface temperature ensures that intense storms (such as category 5 storms) cannot occur in regions in which they physically could not exist (such as the New England area) and, as shown in Vickery, et al. (2000b), the approach reproduces the variation in the central pressure characteristics along the United States coastline. In the hurricane hazard model, the storm’s intensity is modeled as a function of the sea surface temperature and wind shear until the storm makes landfall. At the time of landfall, the filling models described in Vickery (2005) are used to exponentially decay the intensity of the storm over land. Over land, following the approach outlined in Vickery, et al. (2009b), the storm size is modeled as a function of central pressure and latitude. If the storm exits land into the water, the storm intensity is again modeled as a function of sea surface temperature, allowing the storm to possibly re-intensify and make landfall again elsewhere. The validity of the modeling approach for storms near the coastal United States is shown through comparisons of the statistics historical and modeled key hurricane parameters along the North American coast. These comparisons are given in Vickery, et al. (2009b), where comparisons of occurrence rate, heading, translation speed, distance of closest approach, etc., are given. These comparisons are made using the statistics derived from historical and modeled storms that pass within 250 kilometers of a coastal milepost location. The comparisons are given for mileposts spaced 50 nautical miles apart along the entire United States Gulf and Atlantic coastlines. Hurricane Windfield Model. The hurricane windfield model used in our simulation model is described in detail in Vickery, et al. (2009a). The vortex model uses the results of the numerical solution of the 2-D, vertically integrated equations of motion of a translating hurricane. The asymmetries in a moving storm are a function of the translation speed of the storm and the nonlinear interactions between the wind velocity vectors and the frictional effects of the surface of the earth. The numerical solutions of the equations of motion of the hurricane have been solved separately for a storm translating over the ocean and for a storm translating over land. The separate solutions were developed for the over land case and the over water case, since in the over water case, the magnitude of the surface drag coefficient is a function of the windspeed itself, whereas in the over land case the magnitude of the surface drag coefficient is windspeed independent. The outputs of the numerical model represent the integrated boundary layer averaged windspeeds, representative of a long duration average wind, taken as having an averaging time of one hour. The mean, one-hour average, integrated windspeeds are then combined with a boundary layer model to produce estimates of windspeeds for any height and averaging time. The variation of the mean windspeed with height is modeled using a variation of the log law derived from an analysis of hurricane dropsonde data. Turbulence near the surface is modeled as described in Vickery and Skerlj (2005) and is based primarily on the ESDU (1982, 1983) models for the atmospheric boundary layer. The boundary layer model can deal with arbitrary terrain conditions (any surface roughness) changing both the properties of the mean flow field (i.e., the mean windspeed at a given height decreases with increasing surface roughness), as well as the gustiness of the wind (i.e., the gust factor increases with increasing surface roughness). The gust

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factor portion of the ESDU-based model has been validated through comparisons to gust factors derived from hurricane windspeed traces, as described in Vickery and Skerlj (2005). The entire hurricane windfield model (overall flow field, boundary layer model and gust factor model) has been validated through comparisons of simulated and observed windspeeds. These windspeed comparisons have been performed through comparisons of both the peak gust windspeeds and the average windspeeds. The comparisons show the windfield model reproduces observed windspeeds well, matching both the gusts and the long period average winds. The model has been validated separately at offshore, coastal and inland stations, taking into account the effects of local terrain and anemometer height on the measured and simulated windspeeds. Damage and Loss Model. ARA’s modeling approach for damage and loss employs two separate models. A building performance model, using engineering-based load and resistance models, is used to quantify physical damage. The building physical damage model takes into account the effects of wind direction changes, progressive damage, and storm duration. Economic loss, given physical damage, is estimated using repair and reconstruction cost estimation methods. This process is therefore similar to how an insurance adjuster would estimate the claim, given observed damage to the building. Through direct simulations of thousands of storms with representative buildings, the building performance model produces outputs that are post-processed into loss functions for building, contents, and loss of use. The damage and loss modeling methodology is shown schematically in Figure 1. The loss projection model uses these fast-running loss functions (vulnerability functions) with the hurricane model to produce insured loss. Both the physical damage model and the loss model developed by ARA have been validated through comparisons of modeled and observed damage data collected after hurricane events. Separate models have been developed to estimate the financial losses to the building, the building’s contents, additional living expenses, and losses to appurtenant and exterior structures.

Figure 1. Overview of Hurricane Damage and Loss Modeling

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Software, Hardware, and Program Structure. ARA’s detailed hurricane, building performance, and loss analysis models used to develop the fast-running hurricane loss modules were developed in FORTRAN and C++. The databases supporting the models include binary data, flat text files, and Microsoft Access files. These tools are run in-house and are not currently licensed to users. The applications run on personal computers running the Windows® operating systems with a minimum Random Access Memory (RAM) requirement of 2 GB. Translation from Model Structure to Program Structure. ARA uses a modular design approach in converting from model structure to program structure. The analysis process is broken into distinct phases or modules: i.e., Wind, Damage, and Loss. Each of these modules is a stand- alone program. The architecture and program flow of each module are established in a structured design process through the creation of flow charts and/or “pseudo-code.” Each model element is translated into subroutines or functions on a one-to-one basis. Changes to the models are reflected by one-to-one changes in the software code. Although this approach is not a pure object-oriented design approach, it does incorporate some of the features, such as data encapsulation, that make the object-oriented approach successful. Theoretical Basis. As indicated earlier, the hurricane hazard model is developed using the historical database of storms given in the HURDAT. ARA’s model has been peer reviewed and accepted for publication in the American Society of Civil Engineers publication, The Journal of Structural Engineering (Vickery et al., 2009b). The model, in its entirety, was used to develop the design windspeeds given in ASCE-7-98 for the hurricane prone coastline of the United States. ARA’s hurricane model is routinely used by two of the three major North American Boundary Layer Wind Tunnel Laboratories to determine the site-specific hurricane climate risks in terms of directionally-dependent speed frequencies for determining design wind loads for major buildings along the United States coastline, Caribbean, and Asia. The physical damage methodology was developed using a load and resistance modeling approach. Load and resistance analysis methods are fundamental to an evaluation of building performance to extreme winds and are used extensively in the analysis and design of structural systems, including codified design. Some important theoretical and application references are given by Twisdale and Vickery (1995) in Chapter 20, “Extreme Wind Risk Assessment,” of the Probabilistic Structural Mechanics Handbook. 3. Provide a flowchart that illustrates interactions among major hurricane model components. The main program analysis modules used in the multiple building model are shown in Figure 2. More detailed, proprietary flow-charts have been presented to the Professional Team.

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Figure 2. High Level Flowchart of Portfolio (Multiple Buildings – Multiple Sites) Computer Model 4. Provide a comprehensive list of complete references pertinent to the hurricane model by standard grouping using professional citation standards. A complete list of references by standard grouping is provided in the References section. 5. Provide the following information related to changes in the hurricane model from the previously accepted hurricane model to the initial submission this year: A. Hurricane model changes: 1. A summary description of changes that affect the personal or commercial residential hurricane loss costs or hurricane probable maximum loss levels, 2. A list of all other changes, and 3. The rationale for each change. B. Percentage difference in average annual zero deductible statewide hurricane loss costs based on the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2012c.exe” for: 1. All changes combined, and 2. Each individual hurricane model component change.

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C. Color-coded maps by county reflecting the percentage difference in average annual zero deductible statewide hurricane loss costs based on the 2007 Florida Hurricane Catastrophe’s Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2012c.exe” for each hurricane model component change. D. Color-coded map by county reflecting the percentage difference in average annual zero deductible statewide hurricane loss costs based on the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2012c.exe” for all hurricane model components changed. A. For the current submission, there are four changes in the model: 1. We have developed a new stochastic track set that combines our US, Caribbean and Canadian models into one North Atlantic hurricane model. The track set includes historical SST data, troposphere temperature data, storm initiation data, and environmental flow data through 12/31/2017. We have also modified the manner in which the hurricane wind field handles fast moving hurricanes. This change reduces modeled wind speeds for fast moving hurricanes. On a statewide basis, these changes produced a downward effect on modeled losses (-9.2%). 2. We have updated the ZIP Code centroids and average surface roughnesses using June 2018 ZIP Code data. On a statewide basis, this update has a small downward effect on modeled loss costs (-1.4%). 3. We have improved the methodology used in the financial module to compute and allocate insured losses to individual coverages in cases when the ground-up loss is between the policy limit and the policy limit plus the deductible. This update has a small effect on modeled insured loss costs but no effect on zero deductible loss costs (0.0%) 4. We have improved the building stock regions, eras, and weights for post-1994 construction to better reflect building design requirements in Florida during this period. On a statewide basis, this update has a small downward effect on modeled loss costs (- 2.5%). B. Percentage changes in average annual zero deductible statewide loss costs The percentage change in the statewide loss costs associated with the four changes combined is -12.7% (see Form S-5). The percentage change in the statewide loss costs associated with the individual model changes are provided above in Part A. C. Color coded maps showing the incremental percentage changes in the 2012 FHCF zero deductible average annual loss costs by county for each of the four changes are provided in Figure 3 through Figure 6. D. The combined effect of all four changes is shown in Figure 7.

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Figure 3. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to Changes in Hurricane Hazard Model

Figure 4. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to ZIP Code Centroid and Average Surface Roughness Updates

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Figure 5. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to the Financial Model Update

Figure 6. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to Vulnerability Model Updates April 9, 2019 Applied Research Associates, Inc. 29 General Standards 4/9/2019 10:15 AM

Figure 7. Percentage Change in 2012 FHCF Zero Deductible Average Annual Losses by County due to All Changes Combined 6. Provide a list and description of any potential interim updates to underlying data relied upon by the hurricane model. State whether the time interval for the update has a possibility of occurring during the period of time the hurricane model could be found acceptable by the Commission under the review cycle in this Hurricane Standards Report of Activities. No interim updates to underlying data relied upon by the model are anticipated at this time.

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G-2 Qualifications of Modeling Organization Personnel and Consultants Engaged in Development of the Hurricane Model A. Hurricane model construction, testing, and evaluation shall be performed by modeling organization personnel or consultants who possess the necessary skills, formal education, or experience to develop the relevant components for hurricane loss projection methodologies. B. The hurricane model and hurricane model submission documentation shall be reviewed by modeling organization personnel or consultants in the following professional disciplines with requisite experience: structural/wind engineering (licensed Professional Engineer), statistics (advanced degree), actuarial science (Associate or Fellow of Casualty Actuarial Society or Society of Actuaries), meteorology (advanced degree), and computer/information science (advanced degree or equivalent experience and certifications). These individuals shall certify Expert Certification Forms G-1 through G-6 as applicable. A. ARA’s staff involved in the development of the hurricane model has extensive experience in wind engineering and hurricane loss projection. The wind engineering field includes meteorology, structural engineering, bluff body aerodynamics, probability, statistics, and risk analysis. Members of our staff are considered experts in the field of wind engineering and hurricane modeling, as demonstrated through publishing of peer reviewed papers, acting as reviewers for papers related to hurricane modeling submitted to respected professional journals, and through their active involvement in the development of wind-related codes and standards in the United States. B. Modifications to the model have been reviewed by modeler personnel or independent experts in each of the required disciplines. All of the reviewers abide by standards of professional conduct adopted by their professions. 1. Organization Background A. Describe the ownership structure of the modeling organization engaged in the development of the hurricane model. Describe affiliations with other companies and the nature of the relationship, if any. Indicate if the organization has changed its name and explain the circumstances. Applied Research Associates, Inc. is an employee-owned company. ARA is not affiliated with any other company. B. If the hurricane model is developed by an entity other than the modeling organization, describe its organizational structure and indicate how proprietary rights and control over the hurricane model and its components are exercised. If more than one entity is involved in the development of the hurricane model, describe all involved. The model was developed by ARA. No other entities were involved in the model development. C. If the hurricane model is developed by an entity other than the modeling organization, describe the funding source for the development of the hurricane model. Not applicable.

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D. Describe any services other than hurricane modeling provided by the modeling organization. ARA is a diversified engineering and applied science research, consulting, and software development firm. ARA has approximately 1,200 employees with offices throughout the United States, as shown in Figure 8. The risk analysis, wind engineering, and building performance capabilities are located in Raleigh, NC.

ARA’s Technical Capabilities  Probabilistic Risk and Decision Analysis  Software Development  Wind Engineering  Environmental Engineering  Structural Engineering  Risk Management  Engineering Reliability  Facility/Security Engineering  Pavements and Geotechnical Engineering  Tests and Measurements  Explosive Effects Figure 8. ARA Office Locations and Technical Specialties E. Indicate if the modeling organization has ever been involved directly in litigation or challenged by a governmental authority where the credibility of one of its U.S. hurricane model versions for projection of hurricane loss costs or hurricane probable maximum loss levels was disputed. Describe the nature of each case and its conclusion. None. 2. Professional Credentials A. Provide in a tabular format (a) the highest degree obtained (discipline and University), (b) employment or consultant status and tenure in years, and (c) relevant experience and responsibilities of individuals currently involved in the acceptability process or in any of the following aspects of the hurricane model: 1. Meteorology 2. Statistics 3. Vulnerability

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4. Actuarial Science 5. Computer/Information Science The individuals currently involved in the primary development of the model are listed in Table 1. The requested information on experience and responsibilities is provided in the following paragraphs. Table 1. Professional Credentials Aspect Individuals Degr Discipline University Status Tenure ee Peter J. Vickery Ph.D. Eng. Sci. Western Ontario Employee 30 years Lawrence Twisdale Ph.D. Civil Eng. Illinois Employee 36 years Francis M. Lavelle Ph.D. Civil Eng. Rice Employee 28 years Meteorology Jeffrey C. Sciaudone M.S. Civil Eng. Clemson Employee 14 years David R. Mizzen M.S. Civil Eng. Purdue Employee 7 years Lauren Mudd Ph.D. Civil Eng. Rensselaer Employee 4 years Fangqian Liu Ph.D. Civil Eng. Clemson Employee 4 years Peter J. Vickery Ph.D. Eng. Sci. Western Ontario Employee 30 years Marshall B. Hardy M.S. Statistics Kentucky Employee 33 years Statistics Francis M. Lavelle Ph.D. Civil Eng. Rice Employee 28 years Lawrence Twisdale Ph.D. Civil Eng. Illinois Employee 36 years Lauren Mudd Ph.D. Civil Eng. Rensselaer Employee 4 years Peter J. Vickery Ph.D. Eng. Sci. Western Ontario Employee 30 years Lawrence Twisdale Ph.D. Civil Eng. Illinois Employee 36 years Vulnerabilit Chris Driscoll B.S. Civil Eng. South Florida Employee 19 years y Francis M. Lavelle Ph.D. Civil Eng. Rice Employee 28 years Jeffrey C. Sciaudone M.S. Civil Eng. Clemson Employee 18 years Peter J. Vickery Ph.D. Eng. Sci. Western Ontario Employee 30 years Marshall B. Hardy M.S. Statistics Kentucky Employee 33 years Actuarial Lawrence Twisdale Ph.D. Civil Eng. Illinois Employee 36 years Science Francis M. Lavelle Ph.D. Civil Eng. Rice Employee 28 years Jeffrey C. Sciaudone M.S. Civil Eng. Clemson Employee 14 years Laura Maxwell B.S. Mathematics Moravian Consultant N/A Peter J. Vickery Ph.D. Eng. Sci. Western Ontario Employee 30 years Francis M. Lavelle Ph.D. Civil Eng. Rice Employee 28 years Chris Driscoll B.S. Civil Eng. South Florida Employee 19 years Computer Jeffrey C. Sciaudone M.S. Civil Eng. Clemson Employee 14 years Science Brian Grant M.S. Comp. Sci. North Carolina Employee 18 years Chris Gorski B.S. Comp. Sci. North Carolina Employee 6 years St. Shujun Li Ph.D. Civil & Env. Eng. Utah St. Employee 2 years Lawrence A. Twisdale, Jr., Ph.D., P.E., Civil Engineering, University of Illinois. Dr. Lawrence A. Twisdale, Jr., joined ARA in 1982. He is a Principal Engineer and Senior Vice President and has more than 36 years of experience directing and performing research and engineering analyses for extreme wind effects and structural response. Dr. Twisdale has 23 years’ experience in the application of hurricane modeling relevant to insurance loss analysis and rate making. Dr. Twisdale has been involved in developing methodology and applications to extreme wind risk analysis and wind-borne debris hazard analysis since 1974. Dr. Twisdale has performed

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numerous site-specific wind analyses, including tornado, hurricane, and extratropical cyclones. Dr. Twisdale was Co-Principal Investigator with Dr. Peter Vickery on the National Science Foundation (NSF) research project “Hurricane Wind Hazards and Design Risk in the United States.” This research developed a physics and meteorology-based numerical windfield model as part of a wind hazard risk assessment methodology. Dr. Twisdale was Principal Investigator on an NSF funded project to test a “Predictive Methodology for Building Cladding Performance Using a Sample of Hurricane Bertha Damage Data.” He also led the efforts on the “Residential Construction Mitigation Program (RCMP)” from 1998-2000 in Southeast Florida that involved engineering mitigation analysis of over 2200 houses. He was Principal Investigator on loss mitigation studies in 2001-2002 for the State of Florida for both single-family residences and multi-family buildings. Dr. Twisdale was a Co-Principal Investigator for the Federal Emergency Management Agency’s (FEMA) HAZUS Wind Loss Estimation Methodology. He was Principal Investigator on several industry-funded research projects on the “Analysis of Hurricane Windborne Debris Impact Risks for Residential Structures” that influenced the SSTD 12 and American Society of Testing and Materials (ASTM) Standards. He is a member of the Wind Engineering Research Council, IBHS Wind Committee, and the American Society of Civil Engineers (ASCE). He has served on several ASCE technical committees on wind effects, structural reliability, and dynamic structure response. Dr. Twisdale has over 70 technical papers in wind engineering, risk analysis, response of structures to extreme wind, and wind-borne debris effects. Dr. Twisdale was an invited author to prepare the chapter on “Extreme Wind Risk Assessment” in the Probabilistic Structural Mechanics Handbook, published in 1995. Peter Vickery, Ph.D., P.E., Engineering Science, University of Western Ontario. Dr. Peter Vickery joined Applied Research Associates in 1988. Prior to joining ARA, Dr. Vickery completed both his Masters and Doctoral studies at the University of Western Ontario, working with Dr. Alan Davenport, an internationally recognized expert and leader of modern wind engineering technology. Dr. Vickery has over 34 years of experience in wind engineering. He has 23 years’ experience in the application of hurricane modeling relevant to insurance loss analysis/rate making. Dr. Vickery has published multiple peer-reviewed journal papers related to hurricane risk as well as papers related to wind loads on buildings and other structures. Dr. Vickery serves on the ASCE-7 wind load task committee developing wind loading provisions for use in the United States, and has served on the Board of Directors of the American Association for Wind Engineering. In 1996, Dr. Vickery received the Collingswood Prize from ASCE for the best paper published by a younger member. With Dr. Lawrence Twisdale, Dr. Vickery developed the hurricane missile models used in the wind load damage tools. The hurricane missile model results were instrumental in defining the windborne debris risk criteria as given in the SSTD-12 missile protection standard and the new ASTM wind borne debris standard. He is a Fellow of the American Society of Civil Engineers and a Licensed Engineer in the state of North Carolina. Dr. Vickery has performed post-storm damage surveys following Hurricanes Andrew, Erin, Opal, Fran, Bertha, Bonnie, Isabel and Charley. Following Hurricane Andrew, Dr. Vickery served as an expert witness testifying to the windspeeds produced by the storm. He was responsible for developing the wind load and damage portion of the loss model used for residential structures and played the primary role in the development of ARA’s hurricane simulation model. Dr. Vickery was Co-Principal Investigator on ARA’s effort to develop the HAZUS Wind Loss Estimation methodology and software and ARA’s Mitigation Grant Feasibility Study for the Hawaii Hurricane Relief Fund.

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Francis M. Lavelle, Ph.D., P.E., Civil Engineering, Rice University. Dr. Francis M. Lavelle joined ARA in 1990 and was the Division Manager of ARA’s IntraRisk Division from 2003 to 2009. He is a Principal Engineer and Vice President with over 28 years of research, development, and project management experience in the areas of extreme loading effects, risk analysis of structures, and software development. Dr. Lavelle is currently leading ARA’s software integration efforts for FEMA’s HAZUS-MH Hurricane Loss Estimation Model and ARA’s proprietary HurLoss insurance loss estimation model. HAZUS-MH is a joint effort between the Federal Emergency Management Agency (FEMA) and the National Institute of Building Sciences (NIBS) to produce a nationally applicable software program for estimating potential losses from earthquake, flood, and wind hazards. Dr. Lavelle has performed post-storm damage surveys following Hurricanes Isabel (2003), Charley (2004) and Harvey (2017); and he was Principal Investigator on a statewide hazard mitigation study for the Hawaii Hurricane Relief Fund. He has also performed ratemaking studies for the Florida Hurricane Catastrophe Fund and contributed to the development and testing of a Mitigation Incentives web site for the Florida Department of Community Affairs. Prior to joining ARA’s IntraRisk Division, Dr. Lavelle was a Principal Investigator in ARA’s Southeast Division for a number of government-sponsored research projects, including an $8.0M, 3-year contract involving both structural engineering research and software development. During the same period, he was also responsible for managing ARA’s Advanced Modeling and Software Systems (AMSS) group, a group of 15 civil, mechanical, aerospace, and software engineers. Before heading the AMSS group, Dr. Lavelle was responsible for developing reliability-based design safety factors for structural response to extreme loads. His graduate research at Rice University included studies on the dynamic response of locally nonlinear structures, the seismic response of secondary systems, and retrofitting techniques for reducing earthquake-induced pounding damage in adjacent buildings. Dr. Lavelle is a member of the American Society of Civil Engineers and has been a registered professional engineer in the state of North Carolina since 1994. Chris Driscoll, B.S., Civil Engineering, University of South Florida. Mr. Driscoll joined ARA in 1999. He has 19 years of experience in residential/commercial construction, structural engineering, and computer programming. He earned his B.S. in Civil Engineering from the University of South Florida. He has been working on residential/commercial hurricane inspection and mitigation programs for the Department of Community Affairs, FEMA, and for small municipalities. Mr. Driscoll has evaluated post-hurricane wind damage surveys for Erin (1995), Opal (1995), Georges (1998), Isabel (2003) and Charley (2004). He has performed building stock analysis using data collected from Florida Panhandle and South Florida building surveys. He is a developer of wind damage assessment computer modeling tools. Mr. Driscoll has 10 years’ experience in hurricane modeling and 11 years in structural engineering. Jeffrey C. Sciaudone, M.S., Civil Engineering, Clemson University. Mr. Sciaudone joined ARA in 2004. He has 19 years of experience in wind engineering and hurricane modeling relevant to insurance risk. He earned a Bachelors (1994) and Masters (1996) of Science in Civil Engineering from Clemson University and is a registered Professional Engineer in the state of Massachusetts. He has participated in post-hurricane damage surveys following Hurricanes Opal (1995), Isabel (2003), Charley (2004), and Katrina (2005). He has performed analyses of land-use/land cover data and remotely-sensed data for estimating aerodynamic surface roughness (z0). He currently manages the content and development of the Wind Insurance Savings Calculator website for the Florida Division of Emergency Management, which tracks discounts offered by personal lines insurers in Florida for wind mitigation-related features of homes. He performs Probable Maximum Loss and Average Annual Loss studies for insurance company clients. He has also developed a tree debris collection model for HAZUS-MH and teaches advanced level classes on the use of the

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HAZUS-MH hurricane model. He regularly produces Geographical Information Systems (GIS) maps to communicate natural disaster risk-related information to support ARA projects as well as using GIS and remotely-sensed data to enhance natural disaster risk analyses. Prior to joining ARA, Mr. Sciaudone was the Director of Engineering for the Institute for Business & Home Safety (IBHS) from 1999 to 2004, where he was responsible for developing and implementing mitigation research and outreach projects on behalf of the U.S. property/casualty insurance industry for the perils of earthquake, hurricane, tornado, wildfire, flood, and hail. Projects included development of an inspection-based, code-plus residential construction program (Fortified…for safer living); redesign and continual management of a Catastrophe Loss Database; and post-disaster damage inspections following hurricanes, tornadoes, and earthquakes. Prior to joining IBHS, Mr. Sciaudone was a project engineer with Impact Forecasting L.L.C. (1996-1999), which is a division of the AON Corporation. While with Impact Forecasting, he was involved with the development of wind damage functions for an in-house hurricane loss modeling system and performing ratemaking analyses for insurance company clients. Marshall B. Hardy, M.S., Statistics, University of Kentucky. Mr. Marshall B. Hardy joined ARA in 1983 and has 35 years’ experience in applied statistical analysis and probabilistic risk assessment. He has a Master’s degree in Statistics from the University of Kentucky. He has approximately 19 years’ experience in support of hurricane modeling relevant to insurance loss analysis and rate making. Mr. Hardy performs multivariate statistical analysis and tests for ARA’s wind engineering applications. He has aided in the design of simulations, analyzed loss distributions, and performed multivariate analyses of hurricane damage and loss data sets. He has aided in the development of loss functions. He was a key developer of ARA’s TORSCR code that is now the nuclear power industry standard for Probabilistic Risk Assessments (PRA) for extreme wind and tornado-missile hazard. He has applied the TORSCR code and statistically characterized distribution parameters for ten nuclear power plant PRAs. Mr. Hardy also served as lead statistical analyst on numerous DoD, NSF, NIST, and EPA projects. This experience involved statistical modeling of uncertainty in nonlinear elasto-plastic response to wind, blast, or airplane strike, or multivariate analysis-of-variance (ANOVA) to identify dominant uncertainties in the predictive methodologies, and cluster analysis for code validation. Mr. Hardy is an expert in the SAS statistical analysis system that will be used in this work and is also an experienced FORTRAN programmer on a number of systems including the Defense Nuclear Agency (DNA) Cray computer at Los Alamos, DEC minicomputers, and PCs. The Air Force published his 1997 paper on sequential design of experiments for simulations. Chris Gorski, B.S., Computer Science, North Carolina State University. Mr. Christopher Gorski joined ARA in 2011 and has over 18 years of experience in the software field. Mr. Gorski is currently a Staff Computer Scientist at Applied Research Associates and has a B.S. in Computer Science. Prior to joining ARA, much of Mr. Gorski's experience is as an independent contractor. At the UNC School of Medicine he was responsible for putting the examination system online in a system similar to the Board exams, but on the students' own computers with appropriate automatic countermeasures against student cheating. While at CrossComm Inc. Mr. Gorski was responsible for the development of several early iPhone applications for clients and supervised a junior engineer assigned to the task. Mr. Gorski has also spent several years working on database software for such diverse projects as education, retail, and remote monitoring software. His experience in his various contracts has put him at every part of the software development cycle, from design to coding to QA and release. Mr. Gorski joined the IntraRisk division of ARA in January 2011. Since coming to ARA, he has worked on both development and QA on projects including the HurLoss hurricane modeling project, the VAPO project, the IRIS wind mitigation project.

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David Mizzen, M.S.C.E., Civil Engineering, Purdue University. Mr. Mizzen joined ARA in 2011. He has 8 years of wind engineering research and practical experience. He earned a Bachelor’s in Civil and Structural Engineering with Professional Internship in 2009 from the University of Western Ontario (Canada), a Master’s of Science in Civil Engineering in 2011 from Purdue University, and is an Engineer-in-Training (EIT). He has completed dozens of wind tunnel tests on high-rise structures from around the world and conducted research to determine wind loads on typical historic covered bridges. Mr. Mizzen has also performed code-based wind pressure fragilities for dozens of structures at Nuclear Power Plants across North America. He is currently involved in managing a number of projects for the National Institute of Standards and Technology (NIST) in the areas of Disaster and Failure Studies, and Community Disaster Resilience. He has developed storm surge fragility functions, and performed analyses using GIS maps to determine zip code centroids and estimated aerodynamic surface roughness using (z0) using land-use/land- cover data. Lauren Mudd, Ph.D., E.I.T., Civil and Environmental Engineering, Rensselaer Polytechnic Institute. Dr. Lauren Mudd joined Applied Research Associates in 2014 and has 7 years of experience in wind engineering. Prior to joining ARA, Dr. Mudd completed her Doctoral Studies at Rensselaer Polytechnic Institute. She earned both her Master of Engineering and Bachelor of Science in Civil and Environmental Engineering at the University of Louisville. Her graduate research, at Rensselaer Polytechnic Institute, consisted of a multi-hazard assessment of climate change impacts on hurricanes, using state-of-the-art stochastic hurricane simulation procedures. She has published several peer-reviewed journal papers related to hurricane risk analysis and simulation. Dr. Mudd is a registered Engineer in Training in the state of Kentucky and she is a member of the American Society of Civil Engineers, as well as the American Association of Wind Engineers. Fangqian Liu, Ph.D., E.I.T., Civil Engineering, Clemson University. Dr. Fangqian Liu joined ARA in 2014, and has 9 years of experience in the field of wind engineering. She earned her B.S. in Civil Engineering from Beijing University of Civil Engineering and Architecture and then completed her Masters and Doctoral studies at Clemson University. During her post graduate studies, she investigated the statistical properties of historical hurricanes, from which she developed probabilistic hurricane models and a synthetic hurricane database for long-term risk assessment. She also evaluated the changes in design wind speeds and building vulnerabilities due to climate change impact. Her work in Clemson University has supported many other hurricane related researches inside Clemson University and collaborations with other institutions in the U.S. Shujun Li, Ph.D., Civil and Environmental Engineering, Utah State University. Dr. Shujun Li joined ARA in 2017. He has over 12 years of experience in software design and development with a strong academic background of scientific modeling. He earned his Bachelor’s degree in civil engineering from Tsinghua University, and completed his Doctoral studies in Civil and Environmental Engineering at Utah State University. During his post graduate studies, he worked on most aspects of hydro-meteorological modeling at Utah Water Research Laboratory. After graduation, he has been working on commercial software/system design and development in multiple industries. B. Identify any new employees or consultants (since the previous submission) engaged in the development of the hurricane model or the acceptability process. Shujun Li (Computer Science).

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C. Provide visual business workflow documentation connecting all personnel related to hurricane model design, testing, execution, maintenance, and decision-making. The organization of the model and supporting personnel are shown in Figure 9. Lead individuals are shown in bold. None of the employees identified in Table 1 was associated with the insurance industry, consumer advocacy groups, or government entities while working at ARA and contributing to the development of the model. Ms. Maxwell is a consultant to the insurance industry.

Figure 9. Model Workflow 3. Independent Peer Review A. Provide reviewer names and dates of external independent peer reviews that have been performed on the following components as currently functioning in the hurricane model: 1. Meteorology The windspeed (windfield) model was anonymously peer reviewed in the 1998-1999 time period prior to publication in the Journal of Structural Engineering by experts in the fields of wind engineering and meteorology. The current version of the model was anonymously peer reviewed in the 2007-2009 time period prior to publication in the Journal of Applied Meteorology and Climatology by experts in the field of hurricane meteorology. The statistical models for the Holland B parameter and the radius to maximum winds was anonymously peer reviewed in the

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2007-2009 time period prior to publication in the Journal of Applied Meteorology and Climatology by experts in the field of hurricane meteorology, and the filling model was also anonymously peer reviewed prior to the 2005 publication in the Journal of Applied Meteorology and Climatology. The windspeed frequency model was anonymously reviewed at the same time the windspeed model was reviewed, also for publication in the Journal of Structural Engineering. Dr. Steven Businger, a Professor of Meteorology at the University of Hawaii, performed a meteorological review in February 2005. The meteorological components were also peer reviewed by the HAZUS Wind Committee during the period 1998-2002. 2. Statistics The statistical aspects of the model have not been reviewed by personnel outside of ARA except through the review of publications cited above. 3. Vulnerability The vulnerability function parameters have not been reviewed by personnel outside of ARA, except that the HAZUS Wind Committee has reviewed the methodology and procedures used to develop the vulnerability functions during the period 1998-2002. 4. Actuarial Science The actuarial components and resulting annualized loss costs were reviewed by a consulting actuarial firm in November 2018. A copy of the consulting actuary’s letter report is provided in Appendix C. 5. Computer/Information Science The computer science aspects of the model have not been reviewed by personnel outside of ARA. B. Provide documentation of independent peer reviews directly relevant to the modeling organization responses to the current hurricane standards, disclosures, or forms. Identify any unresolved or outstanding issues as a result of these reviews. The actuarial review was performed by Laura A. Maxwell, FCAS, MAAA, CSPA, a consulting actuary with the firm Pinnacle Actuarial Resources, in October and November 2018. There are no unresolved or outstanding issues as a result of this review. C. Describe the nature of any on-going or functional relationship the organization has with any of the persons performing the independent peer reviews. None. The actuarial review of the model was paid for by our firm.

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4. Provide a completed Form G-1, General Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-1. 5. Provide a completed Form G-2, Meteorological Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-2. 6. Provide a completed Form G-3, Statistical Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-3. 7. Provide a completed Form G-4, Vulnerability Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-4. 8. Provide a completed Form G-5, Actuarial Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-5. 9. Provide a completed Form G-6, Computer Standards Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-6.

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G-3 Insured Exposure Location A. ZIP Codes used in the hurricane model shall not differ from the United States Postal Service publication date by more than 24 months at the date of submission of the hurricane model. ZIP Code information shall originate from the United States Postal Service. B. ZIP Code centroids, when used in the hurricane model, shall be based on population data. C. ZIP Code information purchased by the modeling organization shall be verified by the modeling organization for accuracy and appropriateness. D. If any hazard or any hurricane model vulnerability components are dependent on ZIP Code databases, the modeling organization shall maintain a logical process for ensuring these components are consistent with the recent ZIP Code database updates. E. Geocoding methodology shall be justified. A. ZIP Code centroids used in the model are updated at least every 24 months. The issue date of the current ZIP Code data set is July 2018. B. ZIP Code centroids used in the model are population centroids. C. The ZIP Code data has been verified for accuracy and appropriateness. Maps showing the zip code boundaries and the associated centroids will be available to the Professional Team. D. Logical processes are in place for maintaining and updating a database of out-of-date ZIP Codes and mapping each one to a current ZIP Code. E. The model includes a geocoding tool that estimates the latitude and longitude coordinates of a risk based on its input address and U.S. Census TIGER (Topologically Integrated Geographic Encoding and Referencing) data. 1. List the current ZIP Code databases used by the hurricane model and the hurricane model components to which they relate. Provide the effective (official United States Postal Service) date corresponding to the ZIP Code databases. The release date of the ZIP Code database used by the model is July 2018. The ZIP Code data are used by the Meteorological and Actuarial components of the model. The effective date of the current United States Postal Service ZIP Code data set is June 2018. 2. Describe in detail how invalid ZIP Codes are handled. If ZIP Codes are unidentified, we first attempt to map the zip code to one in our historical databases. If this is not successful, we use public domain information on historical ZIP Codes in an attempt to map the ZIP Code. If a policy with an older ZIP Code is found, it is mapped to the centroid of its new ZIP Code in the most current database. Finally, if ZIP Codes cannot be reassigned, they are removed from the analysis and reported as missing ZIP Codes.

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3. Describe the data, methods, and process used in the hurricane model to convert among street addresses, geocode locations (latitude-longitude), and ZIP Codes. Risk locations can be treated in the model using either a geocoded location or a ZIP Code. Geocoded locations can either be directly input to the model as a latitude and longitude or derived by geocoding an input street address. If a geocoded location is not provided in the input file and cannot be derived by the geocoding engine, the model will use the input ZIP Code to place the risk at a ZIP Code population centroid. For locations that have a valid latitude and longitude provided in the input data or for which a latitude and longitude have been returned from the geocoder, the closest wind grid location and terrain grid locations are assigned based on the input or geocoded latitude and longitude. The ZIP code is then determined based on the selected wind grid location. Geocoded latitude and longitude are computed from the input street address and the streets, address ranges, and coordinates in the US Census TIGER/Line shape files. 4. List and provide a brief description of each hurricane model ZIP Code-based database (e.g. ZIP Code centroids). The following ZIP Code-based data sets are used in the model: 1. ZIP Code centroids are population weighted centroid coordinates for each ZIP Code polygon. 2. ZIP Code mappings for out-of-date ZIP Codes allow locations with non-current ZIP Codes to be assigned to a current ZIP Code. 3. ZIP Code surface roughnesses are assigned to locations that have not had explicit latitude-longitude coordinates input or do not have street address information that has been successfully geocoded. 4. Design windspeed and windborne debris region indicators are assigned to each ZIP Code for various building code eras. 5. Describe the process for updating hurricane model ZIP Code-based databases. The ZIP Code-based data sets are updated as follows: 1. ZIP Code centroids are derived from census block centroids. 2. ZIP Code mappings for out-of-date ZIP Codes are updated by determining which current ZIP Code polygon contains the centroid of each out-of-date ZIP Code. 3. ZIP Code surface roughnesses are computed as an area-weighted average surface roughness within each ZIP. 4. Design windspeeds and windborne debris region indicators for each ZIP Code are derived via GIS from digitized building code maps.

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G-4 Independence of Hurricane Model Components The meteorological, vulnerability, and actuarial components of the hurricane model shall each be theoretically sound without compensation for potential bias from the other two components. All of the components of ARA’s hurricane model, including the windspeed, climatology, damage, and loss models have been individually developed and validated. The hurricane windfield model used in ARA’s hurricane model has been validated through comparisons of modeled and observed windspeed data using information collected from over 15 landfalling storms. Details describing the ARA windfield model and the efforts taken to validate the model are given in Vickery, et al. (2009a). Example hurricane windfield validation plots are given in Figure 10 and Figure 11. In Figure 10 and Figure 11, the solid line represents model results and the individual points represent the measured data. The damage and loss models used to produce vulnerability functions are based on first- principle approaches: engineering load and resistance analysis for physical damage estimation, and repair and reconstruction cost models for building loss estimation. These components have been independently validated. The actuarial components are theoretically sound and have also been validated separately without potential bias or compensation to the meteorology and vulnerability components. The relationships among the meteorological, vulnerability, and actuarial components of the model are reasonable. Hurricane Jeanne - FCMP T3 (Gainesville) Hurricane Jeanne - FCMP T3 (Gainesville) 80 360 70 315 60 270 50 225 40 180 (mph) 30 135

20 Direction Wind 90

Peak Speed Wind Gust 10 45 0 0 9/26/2004 12:00 9/27/2004 0:00 9/27/2004 12:00 9/28/2004 0:00 9/26/2004 12:00 9/27/2004 0:00 9/27/2004 12:00 9/28/2004 0:00 Time Time

Hurricane Jeanne - FCMP T3 (Gainesville) 50

10 Mean Wind Speed (mph) Speed Wind Mean 0 9/26/2004 12:00 9/27/2004 0:00 9/27/2004 12:00 9/28/2004 0:00 Time Figure 10. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Inland Locations

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Hurricane Katrina - KMOB Hurricane Katrina - KMOB 100 360 90 315 80 270 70 225 60 50 180 40 135

30 Direction Wind 90 20 45 10 0 Peak Gust Wind Speed Wind Peak Gust (mph) 0 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 0:00 6:00 12:00 18:00 0:00 6:00 0:00 6:00 12:00 18:00 0:00 6:00 Time (UTC) Time (UTC)

Hurricane Katrina - KMOB Hurricane Katrina - KMOB 70 1020 60 1010 50 1000 40 990 30 980 20 970 Pressure (mbar) 10 960 Mean Wind Speed Wind Mean (mph) 0 950 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 0:00 6:00 12:00 18:00 0:00 6:00 0:00 6:00 12:00 18:00 0:00 6:00 Time (UTC) Time (UTC) Hurricane Ivan - KMOB Hurricane Ivan - KMOB 100 360 315 80 270 60 225 180

(mph) 40 135

20 Direction Wind 90

Peak Gust Wind Speed Wind Peak Gust 45 0 0 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 12:00 18:00 0:00 6:00 12:00 18:00 12:00 18:00 0:00 6:00 12:00 18:00 Time Time

Hurricane Ivan - KMOB Hurricane Ivan - KMOB 80 1010 1000 60 990 980 40 970

20 960 950 Mean Wind Speed (mph) Speed Wind Mean Central Pressure (mbar) Pressure Central 0 940 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 12:00 18:00 0:00 6:00 12:00 18:00 12:00 18:00 0:00 6:00 12:00 18:00 Time Time Hurricane Jeanne - KMCO Hurricane Jeanne - KMCO 90 360 80 315 70 270 60 225 50 180 40 (mph) 135 30 20 Direction Wind 90

Peak Gust Wind Speed Wind Peak Gust 10 45 0 0 9/25/2004 18:00 9/26/2004 6:00 9/26/2004 18:00 9/27/2004 6:00 9/25/2004 18:00 9/26/2004 6:00 9/26/2004 18:00 9/27/2004 6:00 Time (UTC) Time (UTC)

Hurricane Jeanne - KMCO Hurricane Jeanne - KMCO 70 1010

60 1000 50 990 40 980 30 970 20

10 960 Central Pressure (mbar) Mean Wind Speed (mph) Wind Mean 0 950 9/25/2004 18:00 9/26/2004 6:00 9/26/2004 18:00 9/27/2004 6:00 9/25/2004 18:00 9/26/2004 6:00 9/26/2004 18:00 9/27/2004 6:00 Time (UTC) Time (UTC) Figure 10. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Inland Locations (concluded)

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Hurricane Jeanne - FCMP T3 Hurricane Jeanne - FCMP T3 120 360 315 100 270 80 225

60 180

(mph) 135 40 Wind Direction Wind 90 20 45 Peak Gust Wind SpeedPeak Wind Gust 0 0 9/25/2004 18:00 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 12:00 9/25/2004 18:00 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 12:00 Time (UTC) Time (UTC)

Hurricane Jeanne - FCMP T3 80 70 60 50 40 30 20 10 Mean Wind Speed Wind Mean (mph) 0 9/25/2004 18:00 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 12:00 Time (UTC) Hurricane Jeanne - FCMP T1 Hurricane Jeanne - FCMP T1 120 360

100 315 270 80 225 60 180

(mph) 135 40

Wind Direction Wind 90 20 45 Peak Gust Wind Speed Wind PeakGust 0 0 9/25/2004 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 9/26/2004 9/25/2004 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 9/26/2004 18:00 12:00 18:00 18:00 12:00 18:00 Time (UTC) Time (UTC)

Hurricane Jeanne - FCMP T1 Hurricane Jeanne - FCMP T1 80 1020 70 1000 60 50 980 40 30 960 20 Pressure (mbar) Pressure 940 10 Mean Wind Speed Wind Mean (mph) 0 920 9/25/2004 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 9/26/2004 9/25/2004 18:00 9/26/2004 0:00 9/26/2004 6:00 9/26/2004 12:00 9/26/2004 18:00 18:00 12:00 18:00 Time (UTC) Time (UTC)

Hurricane Charley - KPGD Hurricane Charley - KPGD 150 360 315 120 270 225 90 180

(mph) 60 135 90 Wind Direction Wind 30 45

Peak Gust Wind Speed Speed Wind Gust Peak 0 0 8/13/2004 8/13/2004 8/13/2004 8/13/2004 8/13/2004 8/13/2004 8/14/2004 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/14/04 18:00 19:00 20:00 21:00 22:00 23:00 0:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Time (UTC) Time (UTC) Hurricane Charley - KPGD Hurricane Charley - KPGD 1020 120 1010 100 1000 80 990 60 980 970 40 960 20 Pressure (mbar) 950 Mean Wind Speed (mph) Speed Wind Mean 0 940 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/14/04 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/13/04 8/14/04 18:00 19:00 20:00 21:00 22:00 23:00 0:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 Time (UTC) Time (UTC) Figure 11. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Coastal and Near Coastal Locations

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Hurricane Charley - KMLB Hurricane Charley - KMLB 120 360 100 270 80 60 180 (mph) 40

Wind Direction 90 20 Peak Gust Wind Speed Wind Peak Gust 0 0 8/13/04 8/13/04 8/13/04 8/14/04 8/14/04 8/14/04 8/14/04 8/13/04 8/13/04 8/13/04 8/14/04 8/14/04 8/14/04 8/14/04 18:00 20:00 22:00 0:00 2:00 4:00 6:00 18:00 20:00 22:00 0:00 2:00 4:00 6:00 Time (UTC) Time (UTC)

Hurricane Charley - KMLB Hurricane Charley - KMLB 80 1020 70 1010 60 1000 50 990 40 980 30 20 970 Pressure (mbar) 10 960

Mean Wind Speed (mph) Wind Mean 0 950 8/13/04 8/13/04 8/13/04 8/14/04 8/14/04 8/14/04 8/14/04 8/13/04 8/13/04 8/13/04 8/14/04 8/14/04 8/14/04 8/14/04 18:00 20:00 22:00 0:00 2:00 4:00 6:00 18:00 20:00 22:00 0:00 2:00 4:00 6:00 Time (UTC) Time (UTC)

Hurricane Ivan - GDIL1 Hurricane Ivan - GDIL1 80 360 70 315 60 270 50 225 40 180 (mph) 30 135 20 Wind Direction Wind 90 10 45 PeakSpeed Wind Gust 0 0 9/15/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/15/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 6:00 12:00 18:00 0:00 6:00 12:00 18:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 Time Time

Hurricane Ivan - GDIL1 Hurricane Ivan - GDIL1 60 1010 1000 50 990 40 980 30 970 20 960 10 950 Central Pressure (mbar) Pressure Central Mean Wind Speed (mph) Speed Wind Mean 0 940 9/15/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/15/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 6:00 12:00 18:00 0:00 6:00 12:00 18:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 Time Time

Hurricane Ivan - FCMP T1 Hurricane Ivan - FCMP T1 120 360 315 100 270 80 225 60 180 (mph) 40 135

Wind Direction Wind 90 20

Peak Gust Wind Speed Wind Peak Gust 45 0 0 9/15/2004 12:00 9/16/2004 0:00 9/16/2004 12:00 9/17/2004 0:00 9/15/2004 12:00 9/16/2004 0:00 9/16/2004 12:00 9/17/2004 0:00 Time (UTC) Time (UTC)

Hurricane Ivan - FCMP T1 80 70 60 50 40 30 20

Mean Wind Speed Wind (mph) Mean 10 0 9/15/2004 12:00 9/16/2004 0:00 9/16/2004 12:00 9/17/2004 0:00 Time (UTC) Figure 11. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Coastal and Near Coastal Locations (continued)

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Hurricane Ivan - KBIX Hurricane Ivan - KBIX 80 360 70 315 60 270 50 225 40 180 (mph) 30 135 20 90 Wind Direction 10 45 Peak Gust Wind Speed Speed Wind Gust Peak 0 0 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/17/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/17/2004 12:00 18:00 0:00 6:00 12:00 18:00 0:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00 Time Time

Hurricane Ivan - KBIX Hurricane Ivan - KBIX 60 1010 50 1000 990 40 980 30 970 20 960 10 950 Central Pressure (mbar) Central Mean Wind Speed (mph) Speed Wind Mean 0 940 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/17/2004 9/15/2004 9/15/2004 9/16/2004 9/16/2004 9/16/2004 9/16/2004 9/17/2004 12:00 18:00 0:00 6:00 12:00 18:00 0:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00 Time Time Hurricane Katrina - FCMP T1 Hurricane Katrina - FCMP T1 120 360

100 315 270 80 225 60 180 (mph) 135 40

Wind Direction Wind 90 20

Peak Gust Wind Speed Wind Gust Peak 45 0 0 8/29/2005 0:00 8/29/2005 6:00 8/29/2005 8/29/2005 8/30/2005 0:00 8/29/2005 0:00 8/29/2005 6:00 8/29/2005 8/29/2005 8/30/2005 0:00 12:00 18:00 12:00 18:00 Time (UTC) Time (UTC)

Hurricane Katrina - FCMP T1 Hurricane Katrina - FCMP T1 80 1020 70 1010 60 1000 50 990 40 980 30 970

20 Pressure (mbar) 960 10 950 Mean Wind Speed (mph) Wind Mean 0 940 8/29/2005 0:00 8/29/2005 6:00 8/29/2005 8/29/2005 8/30/2005 0:00 8/29/2005 0:00 8/29/2005 6:00 8/29/2005 8/29/2005 8/30/2005 0:00 12:00 18:00 12:00 18:00 Time (UTC) Time (UTC)

Hurricane Katrina - DPIA1 Hurricane Katrina - DPIA1 120 360 315 100 270 80 225 60 180

(mph) 135 40

Wind Direction 90 20 45 Peak Gust Wind Speed Wind Gust Peak 0 0 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 0:00 6:00 12:00 18:00 0:00 6:00 0:00 6:00 12:00 18:00 0:00 6:00 Time (UTC) Time (UTC)

Hurricane Katrina - DPIA1 Hurricane Katrina - DPIA1 80 1020 70 1010 60 1000 50 990 40 980 30 970

20 Pressure (mbar) 10 960 Mean Wind Speed (mph) Speed Wind Mean 0 950 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 8/29/2005 8/29/2005 8/29/2005 8/29/2005 8/30/2005 8/30/2005 0:00 6:00 12:00 18:00 0:00 6:00 0:00 6:00 12:00 18:00 0:00 6:00 Time (UTC) Time (UTC) Figure 11. Comparison of Modeled and Observed Windspeeds, Wind Directions, and Pressures at Coastal and Near Coastal Locations (concluded)

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G-5 Editorial Compliance The submission and any revisions provided to the Commission throughout the review process shall be reviewed and edited by a person or persons with experience in reviewing technical documents who shall certify on Form G-7, Editorial Review Expert Certification that the submission has been personally reviewed and is editorially correct. All documents provided to the Commission have been reviewed and edited by a person with experience in reviewing technical documents. 1. Describe the process used for document control of the submission. Describe the process used to ensure that the paper and electronic versions of specific files are identical in content. Control of the submission document was accomplished by maintaining a single Microsoft Word document for each section of the submission. The initial version of these documents included the 2017 FCHLPM standards and the ARA responses from the 2015 submission, where appropriate. After our initial submission to the Commission on November 1, 2016, all subsequent revisions will be made with the “track changes” feature turned on so that all changes could be consistently followed back to our initial submission. The track changes feature identifies all text that has been added, deleted, or changed and identifies the person making the change and the date and time it was made. Prior to printing the paper copies, the entire document is assembled as a single PDF. The paper copies are printed from the PDF. 2. Describe the process used by the signatories on Expert Certification Forms G-1 through G- 6, to ensure that the information contained under each set of standards is accurate and complete. Each signatory reviews the written portions of the submission that they are responsible for signing to ensure that the document reflects the implementation of the model. 3. Provide a completed Form G-7, Editorial Review Expert Certification. Provide a link to the location of the form [insert hyperlink here]. See Form G-7.

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METEOROLOGICAL STANDARDS

M-1 Base Hurricane Storm Set* (*Significant Revision) A. The Base Hurricane Storm Set is the National Hurricane Center HURDAT2 as of April 11, 2017 (or later), incorporating the period 1900-2016. Annual frequencies used in both hurricane model calibration and hurricane model validation shall be based upon the Base Hurricane Storm Set. Complete additional season increments based on updates to HURDAT2 approved by the Tropical Prediction Center/National Hurricane Center are acceptable modifications to these data. Peer reviewed atmospheric science literature may be used to justify modifications to the Base Hurricane Storm Set. B. Any trends, weighting, or partitioning shall be justified and consistent with current scientific and technical literature. Calibration and validation shall encompass the complete Base Hurricane Storm Set as well as any partitions. A. The storm set used by ARA to define the hurricane climatology includes all storms given in the HURDAT2 database. The storm database encompasses the period 1886 through 2017 as given in the May 2018 version of HURDAT2. B. The model does not include any weighting or partitioning of the historical data. 1. Specify the Base Hurricane Storm Set, release date, and the time period used to develop and implement landfall and by-passing hurricane frequencies into the hurricane model. The development of our hurricane model used all storms in the HURDAT2 database whether they made landfall in Florida or not, and thus our data set inherently includes all storms in the Hurricane Commission’s storm set. The base hurricane storm set is HURDAT2 encompassing the period 1886-2017, released in May 2018. 2. If the modeling organization has made any modifications to the Base Hurricane Storm Set related to hurricane landfall frequency and characteristics, provide justification for such modifications. Other than the inclusion of the 2017 hurricane season, no modifications to the Base Hurricane Storm Set have been made. 3. If the hurricane model incorporates short-term, long-term, or other systematic modification of the historical data leading to differences between modeled climatology and that in the Base Hurricane Storm Set, describe how this is incorporated. N/A. 4. Provide a completed Form M-1, Annual Occurrence Rates. Provide a link to the location of the form [insert hyperlink here]. See Form M-1.

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M-2 Hurricane Parameters and Characteristics Methods for depicting all modeled hurricane parameters and characteristics, including but not limited to windspeed, radial distributions of wind and pressure, minimum central pressure, radius of maximum winds, landfall frequency, tracks, spatial and time variant windfields, and conversion factors, shall be based on information documented by current scientific and technical literature. The windspeeds associated with a modeled hurricane are estimated using ARA’s peer reviewed hurricane simulation model, as described in Vickery, et al. (2009a, b). The following paragraphs summarize key elements. Hurricane Occurrence Rate and Storm Track Modeling. The number of storms to be simulated in any one year is obtained by sampling from a negative binomial distribution. The starting position, date, time, heading, and translation speed of all tropical storms, as given in the HURDAT database, are sampled and used to initiate the simulation. Using the historical starting positions of the storms (i.e., date and location) ensures that the climatology associated with any seasonal preferences for the point of storm initiation is retained. Given the initial storm heading, speed and intensity, the simulation model estimates the new position and speed of the storm based on the changes in the translation speed and storm heading over the current six-hour period. The changes in the translation speed, c, and storm heading, , between times i and i+1 are obtained from,

 lnca12 a  a 3  a 4 ln cii  a5  Eq. 1a

  b1  b2  b3  b4ci  b5i  b6i1   Eq. 1b

where a1, a2, etc., are constants, Ψ and λ are the storm latitude and longitude, respectively; ci is the storm translation speed at time step i; θi is the storm heading at time step i; i-1 is the heading of

the storm at time step i-1; and  is a random error term. The coefficients a1, a2, etc., have been developed using 5-degree by 5-degree grids over the entire Atlantic basin. A different set of coefficients for easterly and westerly headed storms is used. As the simulated storm moves into a different 5-degree by 5-degree square, the coefficients used to define the changes in heading and speed change accordingly. Hurricane Intensity Modeling. Hurricane intensity, as defined by central pressure difference, is modeled as a function of the relative intensity and thermodynamic and atmospheric environmental variables including sea surface temperature (SST), tropopause temperature and vertical wind shear. The relative intensity approach is based on the efficiency of a cyclone relative to a Carnot heat engine (Emanuel, 1988). The definition of the relative intensity used here is the ratio of the central pressure difference at the center of a cyclone to the maximum possible central pressure difference for the given meteorological conditions. The key parameters controlling the relative intensity are SST, tropopause temperature, To, and the relative humidity, taken here as a constant equal to 0.8. For each storm in the HURDAT (Jarvinen et al., 1984) database where central pressure data are available and the storm is over water, the relative intensity is computed using the central pressure difference, SST, tropopause temperature and relative humidity (assumed constant and equal to 0.8). The SST at the storm center is determined from the HadISST dataset, which provides monthly mean SST’s for the period of 1850-2017 on a 1 degree geographical grid. The To temperature data were obtained from the NCAR re-analysis To database (www.cdc.noaa.gov)

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which provides To data on a 2.5 degree geographical grid. A linear two dimensional interpolation method is used to obtain the value of To at the storm center. A simple one dimensional ocean model, described in Emanuel et al. (2006) is used to simulate the effect of ocean feedback on the relative intensity calculations. The ocean feedback model calculates the mixed layer depth based on the assumed constancy of a bulk Richardson number, while the mixed layer momentum is driven by the surface stress and entrainment. The mixed layer momentum equation is integrated over a circular region of 4 times the RMW. The ocean mixing model returns an estimate of the mixed layer depth which is then used to compute the reduction in sea surface temperature caused by the passage of a hurricane. This reduced temperature is used in the relative intensity calculations. The relative intensity values are subsequently used to develop regional statistical models in the form of Eq. 2, where the relative intensity at any time is modeled as a function of relative intensity at last three steps and the scaled vertical wind shear, Vs, (DeMaria and Kaplan, 1999). Eq. 2 ln(I i1 )  c1 ln(I i )  c2 ln(I i1 )  c3 ln(I i2 )  c4Vs  

where c1, c2, etc. are constants that vary with region in the Atlantic Basin, and  is a random error term. In the development of the dataset of historical values of I, the surface level wind speeds required for estimating c1, c2, etc., for use in the ocean mixing model were obtained using the simple windfield model described in Holland (1980), with the surface level mean wind speed equal to 80% of the gradient balance wind speed. A total of nine different regions are used to model the intensity changes of tropical cyclones in the Atlantic Basin. In the simulation process, hurricanes that make landfall are weakened (filled) with the filling model as described in Vickery (2005), and if the center of the hurricane re-enters the water, Eq. 2 is again used to model the change in I. On first re-entering the water, the values of Ii-1, Ii-2, etc., used in Eq. 2 are all set to the value computed upon re-entry into the water. Ocean mixing is computed using the same simple Holland (1980) wind model used in the model development. Estimates of wind speeds derived using the track and intensity simulation methodology model are coupled with the hurricane wind field model described in Vickery, et al. (2009a), statistical models for the Holland B parameter and RMW described in Vickery and Wadhera (2008), and a deterministic model used to decay the magnitude of B after a hurricane makes landfall. In the modeling of B and RMW an error term is sampled prior to the start of each simulated storm and is used throughout the simulation as a shift from the mean regression model. Using this approach, a storm that starts out larger than average remains larger than average throughout its modeled life. Similarly, a storm with a sampled value of B that is larger or smaller than average remains larger or smaller throughout its modeled life. Holland B Parameter Modeling. From Vickery and Wadhera (2008), the value of B over open water is modeled as:

2 B 1.76 1.21 A   ; r =0.345, σB = 0.226 Eq. 3 where RMW  f Eq. 4 A   p    2Rd Ts  ln1   pc  e 

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and  is the random error term, sampled from a normal distribution with a mean of zero and standard deviation equal to σB.

In Eq. 4, RMW is the radius to maximum winds (m), f is the Coriolis parameter, Rd is the gas constant for dry air, Ts is the sea surface temperature in degrees C, pc is the central pressure of the tropical cyclone, ∆p (mb) is the difference between the pc and the far field pressure (taken here as 1013 mb) and e is the base of natural logarithms. After landfall, B is modeled in the form:

B(t)  B0 exp(at) Eq. 5a

a  0.0291 0.0429B0 ; a≤-0.005 Eq. 5b

where B0 is the value of B at landfall. The reduction in the magnitude of B after landfall was derived from comparisons of modeled and observed pressures and wind speeds at both coastal and inland stations. In the wind field modeling comparisons discussed in detail in Vickery, et al. (2009a), the magnitudes of both B and RMW, (typically decreasing and increasing after landfall, respectively) are estimated along the track of the hurricane until reasonable matches between both the modeled and observed wind speed and pressure traces is obtained. The reduction in the modeled values of B after landfall were found to be adequately modeled using an equation in the form of Eq. 5. Note that Vickery and Wadhera (2008) suggest that for hurricanes approaching the Gulf of Mexico coastline that B decreases during the last 12 hours before landfall, and they suggest that this reduction in B requires further study to determine if this behavior is indicative of most hurricanes approaching the Gulf of Mexico coastline or just those in the sample. In this study, a reduction in B for Gulf of Mexico landfalling hurricanes was not included in the model. RMW Modeling. In Vickery and Wadhera (2008), two models are given for the RMW (km), one for Gulf of Mexico hurricanes and one for all hurricanes. Here, the all storms RMW model is applied to Atlantic basin hurricanes and the Gulf of Mexico RMW model is applied to storms in the Gulf of Mexico. The models for RMW used in the simulation are: 5 2 2 Eq. 6a ln(RMW Atlantic )  3.015  6.29110 p  0.0337   Atlantic ; r =0.297, σlnRMW = 0.441

5 2 2 Eq. 6b ln(RMWGulf )  3.859  7.700 10 p  Gulf ; r =0.290, σlnRMW = 0.390 The two statistical models for the RMW (Gulf of Mexico and Atlantic Ocean) are combined to yield one RMW model for each simulated storm in the form:

RMW  a1RMW Atlantic  (1 a1 )RMWGulf Eq. 7a Eq. 7b p Atlantic a1  p Atlantic  pGulf where Δp is the central pressure difference and the summation is performed over all six hour time steps from storm origination to the current time. All simulated storm tracks containing the storm location (latitude and longitude), heading, central pressure, RMW, B and translation speed are saved and later combined with the wind field model to compute wind speeds. 1. Identify the hurricane parameters (e.g., central pressure, radius of maximum winds) that are used in the hurricane model. The primary sources of information used to develop the statistical models for describing hurricane risk in the United States are: (i) the HURDAT database, used for developing the models describing storm tracks, heading, occurrence rates and central pressure; (ii) the data given in the

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publication NWS-38, used for developing the models describing central pressure and radius to maximum winds; and (iii) a database of upper level aircraft measurements provided by the Hurricane Research Division for developing statistical models defining the Holland Profile parameter, B. The characteristics of the hurricane that are needed to produce an estimate of windspeed at a site are as follows: i. Central Pressure Difference (HURDAT2 1886-2017, Ho, et al., 1987)(1) ii. Holland Pressure Profile Parameter (Aircraft Data, 1977-2001, H*Wind Data, 1998-2005)(2) iii. Radius to Maximum Winds (HRD H*Wind Analyses, 1988-2005; Flight Level data, 1977-2001)(2) iv. Hurricane Track (HURDAT, 1886-2007)(2) v. Latitude and Longitude of Site (N/A) vi. Surface Roughness at the Site (Proprietary based on NLCD 2011) vii. Distance of the Site from the Coast (N/A). a. Data used for landfall validation b. Data set used to develop indicated model component 2. Describe the dependencies among variables in the windfield component and how they are represented in the hurricane model, including the mathematical dependence of modeled windfield as a function of distance and direction from the center position. The storm central pressure over water is modeled as a function of the mixed sea surface temperature and vertical wind shear. The storm track, which defines storm heading, translation speed, and distance to site, is a function of latitude and longitude. The radius to maximum winds is modeled as a function of central pressure and latitude, and the Holland profile parameter is modeled as a function of latitude and radius to maximum winds. The variation of windspeed as a function of distance from the center position is a function of r/Rmax, translation speed, the Holland B parameter, and terrain. The effect of terrain on windspeeds is discussed in Vickery and Skerlj (2005). 3. Identify whether hurricane parameters are modeled as random variables, functions, or fixed values for the stochastic storm set. Provide rationale for the choice of parameter representations. The probability distributions for central pressure, heading, translation speed and coast crossing, or distance, are all empirical. The Rmax is log-normal, and the error term associated with the modeling of B is normal. The error terms in Equations (1) and (2) are modeled using bi-normal distributions. 4. Describe if and how any hurricane parameters are treated differently in the historical and stochastic storm sets and provide rationale. The main difference between the modeling of historical and actual hurricanes is that in the modeling of the historical hurricanes we use best estimates of the key hurricane parameters (e.g. Rmax, B, central pressure) and their observed variation with time rather than model values (e.g. modeled pressure, Rmax and B after landfall). The default far field pressure used in the stochastic

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set is 1013 mbar, whereas in the modeling of actual hurricanes this may vary, depending upon the available information. 5. State whether the hurricane model simulates surface winds directly or requires conversion between some other reference level or layer and the surface. Describe the source(s) of conversion factors and the rationale for their use. Describe the process for converting the modeled vortex winds to surface winds including the treatment of the inherent uncertainties in the conversion factor with respect to location of the site compared to the radius of maximum winds over time. Justify the variation in the surface winds conversion factor as a function of hurricane intensity and distance from the hurricane center. ARA’s windfield model is valid for any averaging time and height above ground. The windfield model has been validated using both peak gust windspeeds and windspeeds averaged over ten minutes. In the validation studies, all measured windspeed data were adjusted (when needed) to a height of 10 m above ground (in local terrain conditions) before windspeed comparisons were performed. The basic output of the model, for use in loss estimation, is the peak gust windspeed. The variation of the mean windspeed with height, storm intensity and distance from the center of the hurricane is treated using the hurricane boundary layer model described in Vickery, et al. (2009a). 6. Describe how the windspeeds generated in the windfield model are converted from sustained to gust and identify the averaging time. Conversions of windspeeds from hourly means to one-minute sustained and three-second gust averaging times are performed using the ESDU (1982, 1983) models for atmospheric turbulence. The ESDU models have been shown to be valid in hurricanes as discussed in Vickery and Skerlj (2005). 7. Describe the historical data used as the basis for the hurricane model’s hurricane tracks. Discuss the appropriateness of the hurricane model stochastic hurricane tracks with reference to the historical hurricane data. The modeling of the hurricane tracks in our model is similar to that described in Vickery, et al. (2000b), with the addition of ocean coupling and wind shear terms. The approach models a storm track beginning with its initial development over the ocean and ending with its final dissipation over land or in the open ocean. The approach has been validated through comparisons of simulated and observed key storm statistics along the coast of the United States. The development of the storm track model used the historical data given in the HURDAT database, encompassing the period 1886 through 2017. Starting positions of model storms are updated every year to include new historical storms. Model validation includes comparisons of modeled and observed hurricane land fall statistics using United States landfall data for the period encompassing 1900 through 2017. 8. If the historical data are partitioned or modified, describe how the hurricane parameters are affected. The historical data have not been partitioned or modified. 9. Describe how the coastline is segmented (or partitioned) in determining the parameters for hurricane frequency used in the hurricane model. Provide the hurricane frequency distribution by intensity for each segment. The model does not use coastline segments or partitions for determining parameters.

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10. Describe any evolution of the functional representation of hurricane parameters during an individual storm life cycle. The evolution of a model hurricane is described in the model overview presented in our introduction to Standard M-2.

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M-3 Hurricane Probability Distributions A. Modeled probability distributions of hurricane parameters and characteristics shall be consistent with historical hurricanes in the Atlantic basin. B. Modeled hurricane landfall frequency distributions shall reflect the Base Hurricane Storm Set used for category 1 to 5 hurricanes and shall be consistent with those observed for each coastal segment of Florida and neighboring states (Alabama, Georgia, and Mississippi). C. Hurricane models shall use maximum one-minute sustained 10-meter windspeed when defining hurricane landfall intensity. This applies both to the Base Hurricane Storm Set used to develop landfall frequency distributions as a function of coastal location and to the modeled winds in each hurricane which causes damage. The associated maximum one- minute sustained 10-meter windspeed shall be within the range of windspeeds (in statute miles per hour) categorized by the Saffir-Simpson Hurricane Wind Scale. Saffir-Simpson Hurricane Wind Scale:

Category Winds (mph) Damage

1 74 - 95 Minimal 2 96 - 110 Moderate 3 111 - 129 Extensive 4 130 - 156 Extreme 5 157 or higher Catastrophic

A. The modeled probability distributions of hurricane strength, forward speed, radii to maximum winds and storm heading are consistent with that derived from historical storms in the Atlantic Basin. The data used to derive the statistical models include the publication NWS-38, the HURDAT data base, and annual updates to the HURDAT database available from the National Hurricane Center/Tropical Prediction Center web site. Additional information on recent storms has been obtained from the Hurricane Research Division web site as well as detailed analyses of storms as published in American Meteorological Society (AMS) Journals including, Monthly Weather Review, Weather and Forecasting, etc. B. The modeled hurricane probabilities reasonably reflect the Official Storm Set for each coastal segment of Florida and neighboring states as demonstrated in Form M-1. C. The storm intensity at the time of landfall (or any other time), as defined by the Saffir- Simpson scale, can be computed using either the one-minute sustained windspeed or the central pressure. All comparisons of storm intensity presented herein are based on the maximum modeled one-minute sustained windspeed at a height of 10 meters over water at the time of landfall. In the case of modeled by-passing storms, the maximum one minute wind speed is computed at the time of closest approach to the land location in Florida having the maximum modeled peak gust wind speed.

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1. Provide a complete list of the assumptions used in creating the hurricane characteristics databases. No assumptions were made in the use or development of the above databases. With respect to hurricane intensity modeling, which is modeled as function of sea surface temperature, we have developed the model with the assumption that the outflow temperature varies with time and space as given in the NCEP/NCAR re-analysis data set. 2. Provide a brief rationale for the probability distributions used for all hurricane parameters and characteristics. Probability distributions are used to model the error terms describing the residuals in the regression models for B, RMW and the filling models. The errors are approximately normally distributed and have been modeled using truncated normal distributions. RMW is modeled in log space, hence the distribution of RMW is lognormal. The distributions of central pressure, translation speed and heading result from the track simulation model, but the resulting distributions are approximately Weibull, log-normal and bi-normal, respectively. In the track modeling process, the error terms for the logarithm of relative intensity, change in the heading and change in logarithm of translation speed are modeled using bi-normal distributions. The modeling approach is discussed in Vickery et al. (2000b)

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M-4 Hurricane Windfield Structure

A. Windfields generated by the hurricane model shall be consistent with observed historical storms affecting Florida. B. The land use and land cover (LULC) database shall be consistent with National Land Cover Database (NLCD) 2011 or later. Use of alternate data sets shall be justified. C. The translation of land use and land cover or other source information into a surface roughness distribution shall be consistent with current state-of- the-science and shall be implemented with appropriate geographic information system data. D. With respect to multi-story buildings, the hurricane model windfield shall account for the effects of the vertical variation of winds if not accounted for in the vulnerability functions. A. The windfields generated by ARA’s windfield model have been shown to be consistent with historical storms through the numerous comparisons of modeled and observed hurricane windspeed traces that have been performed and published in the open literature. B. The Land Use Land Cover (LULC) database used as the basis for estimating surface roughness values is the National Land Cover Database (NLCD) 2011, which is the most recently available version of the NLCD. C. The conversion of the LULC classifications to surface roughness values is performed using a combination of published and proprietary conversion factors. D. The vertical variation of winds is accounted for in the vulnerability functions. In the development of the damage functions the variation of wind speed with height was modeled using a logarithmic profile, which is discussed in Powell et al., (2003) and Vickery et al. (2009), provides a good description of the variation of wind speed with height within the hurricane boundary layer. 1. Provide a rotational windspeed (y-axis) versus radius (x-axis) plot of the average or default symmetric wind profile used in the hurricane model and justify the choice of this wind profile. If the windfield represents a modification from the previous submission, plot the old and new profiles on the same figure using consistent inputs. Describe variations between the old and new profiles with references to historical storms. Figure 12 presents a plot of the azimuthally averaged total horizontal windspeed at the surface for a model hurricane whose parameters (Rmax, B, central pressure and translation speed) represent the average values associated with all model hurricanes making landfall along the Florida coast. The radial profile of winds associated with the windfield model has been justified through the many comparisons of modeled and observed hurricane windspeed traces.

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p=68 mb, RMW=21.7 miles, B=1.37, c=6.2m/s 120

100

20 Sustained WindSpeed (mph)

0 0 100 200 300 Radius (miles) Figure 12. Radial Profile of Azimuthally Averaged Horizontal Windspeeds 2. Describe how the vertical variation of winds is accounted for in the hurricane model where applicable. Document and justify any difference in the methodology for treating historical and stochastic storm sets The vertical variation of the mean wind speed used in the model is described in detail in Vickery et al. (2009a). The turbulence is modeled using the ESDU (1983) models for atmospheric turbulence. The same wind field model is used in both the stochastic storm set and for the modeling of historical storms. 3. Describe the relevance of the formulation of gust factor(s) used in the hurricane model. The validity of the ESDU gust factor model as applied to hurricane used is verified as described in Vickery and Skerlj (2005). In open terrain (zo=0.03 m), the gust factor at a height of 10 m is about 1.52. In suburban terrain (zo=0.3 m) the gust factor at a height of 10 m is about 1.86. 4. Identify all non-meteorological variables (e.g., surface roughness, topography) that affect windspeed estimation. Given a hurricane with fixed values of central pressure, heading, position, translation speed, radius to maximum winds, pressure profile parameter, and a site located on land, the variable that has the greatest impact on windspeed is the local ground roughness. Other variables having minor effects include distance from the coast, and distance from the center of the storm. Topographic effects are not modeled in Florida. 5. Provide the collection and publication dates of the land use and land cover data used in the hurricane model and justify their timeliness for Florida. The land use and land cover (LULC) data used to compute surface roughness lengths was collected “circa 2010” with data from satellite passes between 2009 and 2011. The full National Land Cover Database (NLCD) 2011 LULC image used to determine surface roughness in Florida was published by the Multi-Resolution Land Use Consortium (MRLC) in 2011 (Fry, et al., 2011).

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6. Describe the methodology used to convert land use and land cover information into a spatial distribution of roughness coefficients in Florida and neighboring states. The LULC values are converted to roughness lengths using a combination of published and proprietary LULC-zo mapping schemes augmented with satellite derived estimates of tree cover. 7. Demonstrate the consistency of the spatial distribution of model-generated winds with observed windfields for hurricanes affecting Florida. Describe and justify the appropriateness of the databases used in the windfield validations. Comparisons of modeled and observed windspeeds associated with landfalling storms have demonstrated the spatial distribution of the modeled windspeeds is consistent with observations. The Hurricane Jeanne comparison provided in our response to Standard M-5 presents such an example. The wind data used for model validation are obtained from The National Climatic Data Center, the National Data Buoy Center and from the Florida Coastal Monitoring Project. Only data where we can assess the local terrain roughness, ascertain the anemometer height and instrument response times are used in the validation process. 8. Describe how the hurricane model windfield is consistent with the inherent differences in windfields for such diverse hurricanes as Hurricane King (1950), Hurricane Charley (2004), Hurricane Jeanne (2004), and Hurricane Wilma (2005).

The differences in the windfields are treated through the use of different values of B, Rmax, central pressure, and translation speed. 9. Describe any variations in the treatment of the hurricane model windfield for stochastic versus historical storms and justify this variation. The only difference between the modeling of stochastic storms and historical storms is that in modeling historical storms we use best estimates of the variation of Rmax, B and pressure after land fall rather than model estimates. 1. Provide a completed Form M-2, Maps of Maximum Winds. Explain the differences between the spatial distributions of maximum winds for open terrain and actual terrain for historical storms. Provide a link to the location of the form [insert hyperlink here]. See Form M-2. The distribution of the actual terrain winds shows much more variation than the open terrain winds as these actual terrains include the effect of zip-code average surface roughness that can vary markedly between zip codes. Differences between the historical and modeled spatial distribution of winds is due to the small sample period for historical storms.

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M-5 Hurricane Landfall and Over-Land Weakening Methodologies A. The hurricane over-land weakening rate methodology used by the hurricane model shall be consistent with historical records and with current state-of-the-science. B. The transition of winds from over-water to over-land within the hurricane model shall be consistent with current state-of-the-science. A. Upon making landfall, the intensity of the storm, as defined by central pressure, is reduced following the decay model described in Vickery (2005). An additional reduction in the magnitude of the pressure profile parameter is modeled using an exponential decay function. The windspeed at a height of 10 m is reduced due to the effects of friction following the methodology given in ESDU (1982, 1983). The approach has been validated through comparisons of modeled and observed marine and land based anemometers. B. The effect of land friction dominates the change in wind speed as the wind moves from blowing over water to blowing over land. The sea-land transition used in the model is described in detail in Vickery et al. (2009b) and is treated in the ARA hurricane windfield model through the use of widely accepted wind engineering boundary layer models. The windspeeds near the ground are reduced using a modified version of the ESDU (1982, 1983) models for atmospheric turbulence. The reduction in windspeeds associated with a hurricane making landfall is produced by the ground friction, which is modeled using the ESDU (1983) boundary layer models. The approach used to model the effects of ground friction in the ARA model has been validated through comparisons of measured and modeled windspeeds from hurricanes taken offshore, at the coast, and inland from the coast. 1. Describe and justify the functional form of hurricane decay rates used by the hurricane model. Once a simulated storm makes landfall, the central pressure difference, p, is decreased as the storm fills (or weakens). The filling of the storm is modeled using the approach described in Vickery (2005), where the central pressure difference at any time after landfall, p(t), is given as:

p(t)  p0 exp(at) Eq. 8 where po is the central pressure difference at the time of landfall; a is a filling parameter, which is a function of the storm intensity, translation speed and size at the time of landfall as well as the location (or region) of landfall; and t is the time in hours since the center of the storm crossed land. Using Eq. 8 to describe filling, large storms tend to fill slowly compared to small storms, weak storms fill more slowly than strong storms and slowly moving storms fill slower than fast moving storms. Four different representations of the filling parameter, a, are used – one for the Gulf of Mexico, one for the Florida Peninsula, and two for the Atlantic Coast. In performing studies for locations in Florida, only the first two filling model regions (different representations of the filling parameter, a) are applicable. In addition to the filling associated with the increase in the storm central pressure (or reduction in p), the windspeed at ground level is immediately decreased at the coastline because of frictional effects. This immediate decrease in windspeed is followed by a gradual decrease in windspeed at the surface associated with a change in the boundary layer characteristics of the storm in the region of the eyewall. Additional changes in the characteristics of the hurricane following landfall include a decrease in the value of the Holland profile parameter, B, modeled using an exponential decay function. An increase in the radius to maximum winds, Rmax, is brought about because Rmax is correlated with central pressure and/or latitude, both of which continue to change after landfall. March 21, 2019 Applied Research Associates, Inc. 61 Meteorological Standards 3/21/2019 2:35 PM

2. Provide a graphical representation of the modeled decay rates for Florida hurricanes over time compared to wind observations. The decay of Florida hurricanes is dominated by the reduction in central pressure and Holland B parameter (which is correlated with central pressure and radius to maximum winds). The rate of decay of a hurricane is a function of storm size, translation speed, and central pressure at the time of landfall. Therefore, the decay rate varies from storm to storm. Figure 13 shows the envelope of maximum windspeeds produced by the model for Hurricane Jeanne, with comparison of modeled and observed windspeeds at both coastal and inland stations. In this representation of the windfield for Hurricane Jeanne, the storm has been decayed using the pressure filling model and exponential Holland B decay model used in the stochastic simulation rather than the actual pressure data. Windspeeds are given as peak gust values at a height of 10 m in open terrain. Comparisons of decay rates with those estimated by Kaplan-DeMaria are given in Figure 14.

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120 y = 0.989x R2 = 0.876 ASOS Description Peak Gust Speed 100 (mph) Observed Modeled KDAB Daytona Beach ASOS 70 63 KFLL Fort Lauderdale ASOS 58 68 80 KFPR Fort Pierce ASOS 108 KGNV Gainesville ASOS 69 65 KJAX Jacksonville ASOS 62 50 KLEE Leesburg ASOS 77 76 60 KMCO Orlando International Airport ASOS 85 85 KMLB Melbourne ASOS 96 KPBI Palm Beach Airport ASOS 95 40 KSFB Orlando-Sanford International Airport ASOS 76 73 KTPA Tampa International Airport ASOS 64 71 KVDF Tampa Vandenburg ASOS 81 75 LKWF1 Lake Worth C-MAN Station 98

Peak Gust Wind Speed (mph) - Modeled - Speed (mph) Wind Peak Gust 20 T0 FCMP Tower T0 93 91 T1 FCMP Tower T1 103 106 T2 FCMP Tower T2 73 76 T3 FCMP Tower T3 106 109 0 T3 FCMP Tower T3 - Gainsville 69 65 0 20 40 60 80 100 120 Peak Gust Wind Speed (mph) - Observations Figure 13. Comparison of Modeled and Observed Windspeeds for Hurricane Jeanne. (Windspeeds are 3 Second Gust Values at a Height of 10m in Flat, Open Terrain and Storm is Decayed Using the ARA Filling Model)

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Hurricane Andrew - Wind Speed Reduction with Time Hurricane Erin - Wind Speed Reduction with Time ) ) 160 120 -20% 140 -20% Kaplan-DeMaria Mean 100 Kaplan-DeMaria Mean 120 20% 20% Andrew Simulation 80 Erin Simulation 100 80 60

60 40 40 20 20 Sustained Wind Speed (mph Speed Wind Sustained Sustained Wind Speed (mph Speed Wind Sustained 0 0 0 5 10 15 20 0 5 10 15 20 Time After Land Fall (hrs) Time After Land Fall (hrs)

Hurricane Opal - Wind Speed Reduction with Time

) 140 -20% 120 Kaplan-DeMaria Mean 20% 100 Opal Simulation 80 60 40 20

Sustained Wind Speed (mph Speed Wind Sustained 0 0 5 10 15 20 Time After Land Fall (hrs) Figure 14. Example Comparisons of Modeled Decay Rates to Kaplan-DeMaria Decay Rates (Windspeeds are 1-Minute Sustained Windspeeds at a Height of 10 m in Open Terrain) 3. Describe the transition from over-water to over-land boundary layer simulated in the hurricane model. The over-water windspeeds are converted to over-land windspeeds using a modified version of the terrain transition model given in ESDU (1982). The validity of the model has been demonstrated through comparisons of modeled and observed marine and land based windspeed measurements. 4. Describe any changes in hurricane parameters, other than intensity, resulting from the transition from over-water to over-land. The parameters that change as the hurricane moves from sea to land include the surface roughness which affects the inflow angle, turbulence and change in wind speed with height. The change in surface roughness also results in an increase in the boundary layer height, which, along with the surface roughness, is a key parameter in the formulation of the model describing the variation of wind speed with height. 5. Describe the representation in the hurricane model of passage over non-continental U.S. land masses on hurricanes affecting Florida.

Storms making land fall over non-continental US land masses are weakened using the filling model described in Vickery et al. (1995a). 6. Describe any differences in the treatment of decay rates in the hurricane model for stochastic hurricanes compared to historical hurricanes affecting Florida. The change in pressure following landfall for historical storms is modeled using historical data. The filling for stochastic storms is modeled using the filling model described in Vickery (2005). The changes in B are modeled using an exponential decay function. The change in the characteristics of the windfield associated with friction effects is the same for both historical and

March 21, 2019 Applied Research Associates, Inc. 64 Meteorological Standards 3/21/2019 2:35 PM stochastic storms. If the radius to maximum winds of a historical storm is not known, the statistical models relating the radius to maximum winds with central pressure and latitude are used to model the radius.

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M-6 Logical Relationships of Hurricane Characteristics A. The magnitude of asymmetry shall increase as the translation speed increases, all other factors held constant. B. The mean windspeed shall decrease with increasing surface roughness (friction), all other factors held constant. The hurricane windfield characteristics, including the radial distribution of windspeeds, storm symmetry characteristics, and reduction in windspeed as a function of surface friction, are consistent with accepted scientific principles. The radial distribution of windspeeds has been validated through comparisons of model and observed windspeeds compared throughout the entire passage of multiple storms and at multiple anemometer sites. The effect of land friction is modeled using the ESDU terrain roughness model, and the effect of storm symmetry is treated using the approach described in Vickery et al. (2000a). A. The magnitude of windfield asymmetry increases as the translation speed of the storm increases, all other factors held constant. B. Surface level windspeeds decrease with increasing surface roughness, all other factors held constant. 1. Describe how the asymmetric structure of hurricanes is represented in the hurricane model. The asymmetries are a function of the translation speed of the storm and the nonlinear interactions between the wind velocity vectors and the frictional effects associated with the interaction of the wind flow and surface friction. Examples are shown in Vickery et al. (2000a). 2. Provide a completed Form M-3, Radius of Maximum Winds and Radii of Standard Wind Thresholds. Provide a link to the location of the form [insert hyperlink here]. See Form M-3. 3. Discuss the radii values for each wind threshold in Form M-3, Radius of Maximum Winds and Radii of Standard Wind Thresholds, with reference to available hurricane observations such as those in HURDAT2. Justify the appropriateness of the databases used in the radii validations. As evident in the hundreds of comparisons of wind modeled and historical wind speeds, the radii are generally consistent with the observations, with a small tendency for the model to underestimate winds well away from the center of the hurricane, in some cases. The data used to develop the model for the radius to maximum winds was supplied by NOAA. The resulting model has been published in the peer reviewed literature (Vickery and Wadhera, 2008). Note that radii of standard wind thresholds cannot be used as validation data as the definition of a threshold radii used by NHC differs from that produced by a hurricane wind field model.

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STATISTICAL STANDARDS

S-1 Modeled Results and Goodness-of-Fit A. The use of historical data in developing the hurricane model shall be supported by rigorous methods published in current scientific and technical literature. B. Modeled and historical results shall reflect statistical agreement using current scientific and statistical methods for the academic disciplines appropriate for the various hurricane model components or characteristics. A. The use of historical data in developing the hurricane model has been demonstrated to be reasonable through publications in the scientific and technical literature. B. Goodness of fit tests, comparing modeled to historical data, have been performed using t tests, F tests, Chi-squared tests, and the Kolmogorov-Smirnoff test, for all historical data used to define the hurricane hazard. Example comparisons are given in Figure 15 for the distribution of storm translation speed for all tropical cyclones passing within 155 miles of a point centered on 26° N, 80°W (approximately 7 miles east of Hollywood, FL). Figure 16 shows a comparison of the modeled and historical distributions of storm heading of all tropical cyclones passing within 155 miles of the same location.

(26.0, ‐80.0) K‐S Test:Pass C‐S Test 1:Pass C‐S Test 2:Pass 50 Observed 45 Model 40 35 30 25 Count 20 15 10 5 0 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5 10.511.512.513.514.515.516.517.5 Translation Speed (m/sec)

Figure 15. Comparison of Historical and Modeled Distributions of the Translation Speed of all Tropical Cyclones Passing within 155 miles of a Point Centered on 26° N, 80°W

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(26.0, ‐80.0) K‐S Test:Pass C‐S Test 1:Pass C‐S Test 2:Pass 25 Observed Model 20

15 Count 10

0 ‐170‐150‐130‐110 ‐90 ‐70 ‐50 ‐30 ‐10 10 30 50 70 90 110 130 150 170 Heading (Degrees, Clockwise from North)

Figure 16. Comparison of Historical and Modeled Distributions of Storm Heading of all Tropical Cyclones Passing within 155 miles of a Point Centered on 26° N, 80°W 1. Provide a completed Form S-3, Distributions of Stochastic Hurricane Parameters. Identify the form of the probability distributions used for each function or variable, if applicable. Identify statistical techniques used for estimation and the specific goodness-of-fit tests applied along with the corresponding p-values. Describe whether the fitted distributions provide a reasonable agreement with the historical data. [insert hyperlink here]. The hurricane track modeling approach used does not sample from predefined distributions of central pressure, heading, etc. The model predicts the parameters (position and central pressure) of a storm at the next time step based on its position, speed and heading at the current time step and up to two prior time steps. The resulting distributions of translation speed, heading, distance of closest approach are approximately log-normal, a mixture of two normal distributions, and either uniform or trapezoidal, respectively. The distribution of the central pressure is approximately Weibull. The radius to maximum winds is modeled using a log-normal distribution, dependent on the central pressure difference and latitude, and the Holland profile parameter is modeled as being normally distributed about the regression line with a mean dependent on latitude, radius to maximum winds, sea surface temperature, and central pressure. All distributions have been evaluated through standard statistical tests using a 5% alpha level. Form S-3 provides comparisons of historical and modeled landfall headings, translation speeds, occurrence rates, and central pressures. p-values associated with the various statistical tests for equivalence are provided with each plot. 2. Describe the nature and results of the tests performed to validate the windspeeds generated. Windspeed validation studies have been performed using data obtained from Hurricanes Frederic (1979), Elena (1985), Hugo (1989), Bob (1991), Andrew (1992), Emily (1993), Erin and Opal (1995), Bertha and Fran (1996), Bonnie (1997), Georges (1998), Irene (1999), Charley, Frances, Ivan and Jeanne (2004), and Dennis, Katrina, Rita and Wilma (2005), Gustav and Ike in

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2008, Irma and Nate (2017) and Florence and Michael (2018). In all cases, quantitative comparisons of modeled and observed estimates of windspeeds are only made if the measured records of windspeeds are continuous (or contain daily maxima), the height of the anemometer is known, the averaging times of both the gust and long term average is known and the terrain surrounding the anemometer is known. Comparisons for many valid records are given in Vickery, et al. (2009a). 3. Provide the dates of hurricane loss of the insurance claims data used for validation and verification of the hurricane model. Insurance company data from the following hurricanes have been used to validate the model:  Hurricane Hugo (1989)  Hurricane Andrew (1992)  Hurricane Erin (1995)  Hurricane Opal (1995)  Hurricane Bertha (1996)  Hurricane Fran (1996)  Hurricane Bonnie (1998)  Hurricane Earl (1998)  Hurricane Georges (1998)  Hurricane Charley (2004)  Hurricane Frances (2004)  Hurricane Ivan (2004)  Hurricane Jeanne (2004)  Hurricane Wilma (2005) 4. Provide an assessment of uncertainty in hurricane probable maximum loss levels and hurricane loss costs for hurricane output ranges using confidence intervals or other scientific characterizations of uncertainty. The major modeling uncertainties include hurricane, terrain, building stock, and vulnerability. An example of our analysis of hurricane modeling uncertainty is provided in Twisdale, Vickery and Hardy (1993), where it is shown that the uncertainty in windspeed as a function of return period is relatively large (CoV~10%). Using this result as an example, the mean estimated 100- year return period peak gust windspeed in the Miami region is about 145 mph, with the 95% prediction interval ranging between about 116 mph and 175 mph. The uncertainties in the predicted windspeeds at a given location are amplified when propagated through the model to obtain predictions of loss costs. This amplification decreases with increasing uncertainty in the underlying distribution of windspeed and varies with location. In Alachua County, for example, a 1% uncertainty in the underlying distribution of windspeeds propagates through to a 7.3% uncertainty in loss costs, whereas as 10% uncertainty (expressed as a CoV) in windspeed propagates through to a 62% CoV in loss costs. Estimates of uncertainty associated with probably maximum loss levels are given in Form A- 8, Part D. 5. Justify any differences between the historical and modeled results using current scientific and statistical methods in the appropriate disciplines. There are no statistically significant differences between historical and modeled meteorological data.

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6. Provide graphical comparisons of modeled and historical data and goodness-of-fit tests. Examples to include are hurricane frequencies, tracks, intensities, and physical damage. The entire hurricane simulation model is validated through comparisons of statistics of storm heading, translation speed, intensity and frequencies using both historical information on landfalling hurricanes, as well as historical information on the statistics of all tropical cyclones passing within 155 miles (250 km) of milepost markers distributed along the entire US coastline (Figure 15 and Figure 16). Comparisons of the distribution of landfall frequency and intensity along various segments along the coastline of the US are given in Vickery et al. (2009b). In Vickery et al. (2009b), goodness of fit tests were presented where comparisons of the modeled and historical distributions of landfall intensity (defined by central pressure) were performed using the re-sampling technique described in James and Mason (2005). As discussed in James and Mason (2005), this re-sampling test is much more powerful than the Kolmogorov-Smirnov test. Figure 17 presents an example (for the South East Florida region) showing the historical data along with the mean modeled data along with the 5th and 95th percentile confidence interval as estimated from the re-sampling method described in James and Mason (2005). This example of landfall pressure plotted vs. return period combines the effects of both rate and intensity.

Figure 17. Comparison of Modeled and Historical Hurricane Landfall Pressures in Southeast Florida Figure 18 and Figure 19 present comparisons of modeled and observed landfall rates and intensities for hurricanes making landfall in Florida.

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0.7

0.6 Model 0.5 Historical 0.4 0.3

Probability 0.2 0.1 0.0 012345678910 Number of Landfalling Hurricanes/Year

Figure 18. Comparison of Modeled and Historical Probabilities of Multiple Landfalls in a Year

0.25

0.20 Modeled Historical 0.15

0.10

Annual Frequency Annual 0.05

0.00 12345

Hurricane Category

Figure 19. Comparison of Modeled and Historical Landfall Rates as a Function of Hurricane Category 7. Provide a completed Form S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year. Provide a link to the location of the form [insert hyperlink here]. See Form S-1. 8. Provide a completed Form S-2A, Examples of Hurricane Loss Exceedance Estimates (2012 FCHF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form S-2A.

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9. Provide a completed Form S-2B, Examples of Hurricane Loss Exceedance Estimates (2017 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form S-2B.

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S-2 Sensitivity Analysis for Hurricane Model Output The modeling organization shall have assessed the sensitivity of temporal and spatial outputs with respect to the simultaneous variation of input variables using current scientific and statistical methods in the appropriate disciplines and shall have taken appropriate action. The model has been tested and sensitivities estimated for cases of simultaneous variations of input parameters. The sensitivity study results have been presented to the Professional Team. 1. Identify the most sensitive aspect of the hurricane model and the basis for making this determination. The single most important element in loss estimation is the windspeed since the loads and, hence, physical damage to a building are proportional to the square of the windspeed. Thus, the estimation of losses is sensitive to the hurricane wind climate and the wind model. Loss results are particularly sensitive to the occurrence rate and area of the more intense hurricanes (Saffir- Simpson Category 3 or higher). 2. Identify other input variables that impact the magnitude of the output when the input variables are varied simultaneously. Describe the degree to which these sensitivities affect output results and illustrate with an example. Given a location (i.e., the hurricane wind climate is held fixed), another key variable is surface roughness and the manner in which the boundary layer is modeled for the sea-land transition. Loss predictions are, or course, sensitive to the building construction parameters and, hence, the vulnerability functions used. These observations of sensitivity are based on numerous detailed sensitivity analyses, theoretical considerations, as well as field observations. Figure 20 shows an example of the distribution of the average annual loss for a house located in Alachua County associated with an assumed distribution describing the variation in the extreme windspeed distribution. The coefficient of variation associated with the input windspeed model was 1%, with this propagating to yield a 7.3% CoV associated with the prediction of the AAL. Increasing the coefficient of variation of the hurricane hazard curve to 10%, yields a CoV in the AAL of 62% and increases the mean value of the AAL by 13%. Additional examples showing the impact of the different parameters used in the model on loss cost estimates have been presented to the Professional Team during past visits.

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AAL = 1.6 $/1000 CoV = 0.073 0.35

0.3 n 0.25

0.2

0.15

0.1 Relative Contributio

0.05

0 1.05 1.15 1.25 1.35 1.45 1.55 1.65 1.75 1.85 1.95 2.05 2.15 2.25 AAL $/1000 Figure 20. Distribution of AAL Associated with a 1% CoV in the Windspeed Model 3. Describe how other aspects of the hurricane model may have a significant impact on the sensitivities in output results and the basis for making this determination. The sensitivity studies have shown that the estimation of the average annual loss is most sensitive to the estimation of windspeed (i.e. the hurricane hazard curve). In following the development of the model for estimating the hurricane windspeed hazard, this leads to the fact that the modeling of the Holland pressure profile parameter and the modeling of central pressure are other parameters that have a significant impact on the sensitivities of model outputs. An additional item that the model may be sensitive to is relative humidity, which is held constant in the development of the hurricane intensity. A sensitivity study examining the sensitivity of the results to the number of simulated years was performed by simulating a new 100,000-year storm set with a new random seed. This study showed that the estimates of total loss costs could change by up to 8% in the low loss cost regions of Florida. 4. Describe and justify action or inaction as a result of the sensitivity analyses performed. At the current time, no changes have been made to the model as a result of the sensitivity analysis. In light of the sensitivity in the estimation of loss costs noted in 3, we increased our stochastic storm set to include 250,000 years of simulated hurricanes. 5. Provide a completed Form S-6, Hypothetical Events for Sensitivity and Uncertainty Analysis. (Requirement for hurricane models submitted by modeling organizations which have not previously provided the Commission with this analysis. For hurricane models previously found acceptable, the Commission will determine, at the meeting to review modeling organization submissions, if an existing modeling organization will be required to provide Form S-6 (Hypothetical Events for Sensitivity and Uncertainty Analysis) prior to the Professional Team on-site review). If applicable, provide a link to the location of the form [insert hyperlink here]. Not applicable.

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S-3 Uncertainty Analysis for Model Output The modeling organization shall have performed an uncertainty analysis on the temporal and spatial outputs of the model using currently accepted scientific and statistical methods in the appropriate disciplines and shall have taken appropriate action. The analysis shall identify and quantify the extent that input variables impact the uncertainty in model output as the input variables are simultaneously varied. Estimates of uncertainty are not a standard output of the model; however, an uncertainty analysis has been performed and has been presented to the Professional Team. 1. Identify the major contributors to the uncertainty in hurricane model outputs and the basis for making this determination. Provide a full discussion of the degree to which these uncertainties affect output results and illustrate with an example. The single most important element in loss estimation is the windspeed since the loads and, hence, physical damage to a building are proportional to the square of the windspeed. Thus, the estimation of losses is sensitive to the hurricane wind climate and the wind model. Loss results are particularly sensitive to the occurrence rate and area of the more intense hurricanes (Saffir- Simpson Category 3 or higher). Given a location (i.e., the hurricane wind climate is held fixed), another key variable is surface roughness and the manner in which the boundary layer is modeled for the sea-land transition. Loss predictions are, of course, sensitive to the building construction parameters and, hence, the vulnerability functions used. These observations of sensitivity are based on numerous detailed sensitivity analyses, theoretical considerations, as well as field observations. An example of the impact of a 1% uncertainty in the windspeed climate (as defined by the CoV) was presented in Figure 20, as to how this small uncertainty in windspeed propagates through to a large uncertainty in the prediction of average annual loss. The uncertainty studies performed by ARA personnel examining the impact of reasonable estimates in the uncertainties of key input parameters were performed by propagating the uncertainties through to the prediction of losses looking at the effects one at a time and in various combinations. The result of the studies clearly showed that the uncertainties in the windspeed risk dominates the uncertainties in the losses. Additional uncertainty studies have been performed in completing Form F under the 2002 Standards and Form S-6 under the 2009 Standards. 2. Describe how other aspects of the hurricane model may have a significant impact on the uncertainties in output results and the basis for making this determination. The uncertainty in the predicted loss costs is driven by the uncertainty in the underlying wind hazard curve, and hence, uncertainties in the modeling of central pressure, the Holland pressure profile parameter and the decay of storms as they travel inland. 3. Describe and justify action or inaction as a result of the uncertainty analyses performed. As of the current time, no changes to the model have been made as a result of the uncertainty analyses.

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4. Form S-6, Hypothetical Events for Sensitivity and Uncertainty Analysis, if disclosed under Standard S-2, Sensitivity Analysis for Hurricane Model Output, will be used in the verification of Standard S-3, Uncertainty Analysis for Hurricane Model Output. Not applicable.

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S-4 County Level Aggregation At the county level of aggregation, the contribution to the error in loss cost estimates attributable to the sampling process shall be negligible. Figure 21 shows the standard errors in the total ground-up owner frame loss costs induced by the sampling process as a percentage of the county weighted average loss costs. For a 250,000- year simulation, the standard errors associated with the sampling process range from 0.8% in the counties with the most hurricane activity to 2.2% in the counties with the least hurricane activity. These errors are negligible in comparison to the uncertainties in the model.

Figure 21. Standard Errors in County Weighted Average Loss Costs 1. Describe the sampling plan used to obtain the average annual hurricane loss costs and hurricane output ranges. For a direct Monte Carlo simulation, indicate steps taken to determine sample size. For importance sampling design, or other sampling scheme, describe the underpinnings of the design and how it achieves the required performance. The sampling plan used to obtain AALs and loss costs is a direct Monte Carlo simulation with a sample size 250,000 years. The sample size was selected by continuing to increase the number of simulated years and examining the standard error in the estimate of the mean loss costs. The sample set of 250,000 years produced a maximum standard error in the total owner frame ground- up loss costs of 2.2%.

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S-5 Replication of Known Hurricane Losses The model shall estimate incurred losses in an unbiased manner on a sufficient body of past hurricane events from more than one company, including the most current data available to the modeling organization. This standard applies separately to personal residential and, to the extent data are available, to commercial residential. Personal residential loss experience may be used to replicate structure-only and contents-only losses. The replications shall be produced on an objective body of loss data by county or an appropriate level of geographic detail and shall include loss data from both 2004 and 2005. Figure 22 presents a comparison of modeled and actual total losses by storm and company for residential coverage. The comparisons indicate reasonable agreement between the observed and modeled losses (r2 = 0.96 in linear space and r2 = 0.93 in logarithmic space). Demand surge is not included in the modeled losses. Additional, and more detailed, comparisons of modeled and actual incurred losses are given in Form S-4.

Figure 22. Comparison of Modeled and Observed Losses for Homeowner Policies 1. Describe the nature and results of the analyses performed to validate the loss projections generated for personal and commercial residential losses separately. Include analyses for the 2004 and 2005 hurricane season. Figure 22 and Figure 23 present example comparisons of simulated and observed losses from recent hurricanes

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(a) Personal Residential

Actual Ratio Modeled Loss

Peak Gust Wind Speed at 10 m in Open Terrain (mph)

(b) Commercial Residential Figure 23. Comparison of Modeled and Actual Losses as a Function of Peak Gust Windspeed in Open Terrain 2. Provide a completed Form S-4, Validation Comparisons. Provide a link to the location of the form [insert hyperlink here]. See Form S-4.

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S-6 Comparison of Projected Hurricane Loss Costs The difference, due to uncertainty, between historical and modeled annual average statewide loss costs shall be reasonable, given the body of data, by established statistical expectations and norms. The difference between historical and modeled annual average statewide loss costs is statistically reasonable, as demonstrated in Form S-5. 1. Describe the nature and results of the tests performed to validate the expected loss projections generated. If a set of simulated hurricanes or simulation trials was used to determine these loss projections, specify the convergence tests that were used and the results. Specify the number of hurricanes or trials that were used. A direct statistical validation of expected loss costs by region is not possible owing to the limited hurricane loss data at any given region, and thus indirect validation procedures are required. This validation process assumes that if the hurricane climatology, in terms of hurricane intensity, frequency, translation speed, filling and windspeed, is properly modeled, and if the prediction of loss given a hurricane is properly modeled, then the loss cost estimates should be valid. Comparisons of modeled and observed windspeeds were presented in the answer to Standard G- 4. These comparisons showed that given information describing a storm, including the central pressure difference, p, the radius to maximum winds, Rmax, translation speed, Holland pressure profile parameter, B, heading and location, the windfield model is able to provide good estimates of windspeed at a site. Figure 18 shows a comparison of the historical and modeled annual rate of hurricane landfalls in Florida. In the comparisons given in Figure 18, each hurricane that makes landfall in Florida is counted as a single event for both the modeled and historical storms. Figure 19 shows a comparison of the simulated and modeled landfall rate of hurricanes as a function of storm intensity in Florida. This comparison shows the combined effect of intensity and frequency modeling, indicating that the model is performing well in its ability to reproduce the statistics of landfall counts of storms as a function of intensity in Florida. The landfall counts given in Figure 19 represent the first landfall data for entering storms. The agreement between the annual rate historical and modeled hurricane landfalls is very good with the comparison of the landfall rate statistics passing both the Chi squared and Kolmogorov-Smirnov tests. Figure 22 showed separate examples of total losses experienced by different companies for various events. The ability of the model to produce reasonable estimates of loss as a function of windspeed was shown, for example, in Figure 23. As seen in this example, the model is able to reasonably reproduce the observed losses as a function of the peak windspeed in a storm. 2. Identify and justify differences, if any, in how the model produces loss costs for specific historical events versus loss costs for events in the stochastic hurricane set. Loss costs from historic storms can be produced using either the fast running loss functions developed for use in the portfolio model or with the building performance model (which takes into account storm duration, change of wind direction, etc.). The computation of loss costs from historical or stochastic storms is fundamentally the same. The losses are summed by territory, line of business, etc., and divided by the appropriate exposure and the number of years of storms.

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3. Provide a completed Form S-5, Average Annual Zero Deductible Statewide Loss Costs – Historical versus Modeled. Provide a link to the location of the form [insert hyperlink here].

See Form S-5.

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VULNERABILITY STANDARDS

V-1 Derivation of Building Hurricane Vulnerability Functions

A. Development of the building hurricane vulnerability functions shall be based on at least one of the following: (1) insurance claims data, (2) laboratory or field testing, (3) rational structural analysis, and (4) post-event site investigations. Any development of the building hurricane vulnerability functions based on rational structural analysis, post-event site investigations, and laboratory or field testing shall be supported by historical data. B. The derivation of the building hurricane vulnerability functions and their associated uncertainties shall be theoretically sound and consistent with fundamental engineering principles. C. Residential building stock classification shall be representative of Florida construction for personal and commercial residential buildings. D. Building height/number of stories, primary construction material, year of construction, location, building code, and other construction characteristics, as applicable, shall be used in the derivation and application of building hurricane vulnerability functions. E. Hurricane vulnerability functions shall be separately derived for commercial residential building structures, personal residential building structures, manufactured homes, and appurtenant structures. F. The minimum windspeed that generates damage shall be consistent with fundamental engineering principles. G. Building hurricane vulnerability functions shall include damage as attributable to windspeed and wind pressure, water infiltration, and missile impact associated with hurricanes. Building hurricane vulnerability functions shall not include explicit damage to the building due to flood, storm surge, or wave action. A. ARA’s vulnerability functions include elements of each of the following: (1) insurance claims data, (2) tests, (3) rational structural analysis, and (4) site inspections. The development of the building hurricane vulnerability functions is supported by historical data. The ARA personnel responsible for developing the damage and loss models have extensive experience in wind load modeling, structural analysis, post-hurricane damage surveys, and meteorology. B. ARA's vulnerability functions have been developed for residential buildings (including mobile homes) using a theoretically sound load and resistance modeling approach, coupled with empirically-derived elements. For each structure, the model estimates physical damage to the building, which incorporates the effects of uncertainties in the component loads and resistances. This physical damage is used in turn to estimate the loss to the building and contents separately. The building damage state is used in conjunction with a restoration model to estimate the costs associated with loss of use expenses. Uncertainties in restoration costs and times are included in the model.

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C. Variations in construction characteristics for personal and commercial residential properties are treated through the use of a statewide building stock model. The building stock model provides distributions (e.g. percentage of hip vs. non-hip roof shapes) to weight the baseline vulnerability functions when detailed information is not available. The building stock distributions vary by region and era of construction and are based on detailed building inspection data, building code criteria, and engineering judgment. D. The base vulnerability functions developed for the model are for buildings with known characteristics representing a broad range of conditions present in the Florida building stock. The vulnerability functions for buildings with known construction characteristics are evaluated using a detailed, three-dimensional, time-dependent building performance model that accounts for nonlinear interactions between multiple building parameters, such as building height, roof shape, roof cover strength, and opening protection. The building performance model yields a family of cumulative distribution functions for building loss as a function of peak gust wind speed in open terrain and local terrain roughness. Each unique combination of known building characteristics represents one model building class (e.g., two stories, wood frame, hip, hurricane straps, no shutters, etc.). In most cases, there is not enough information available in a book of business to map each property to a distinct base vulnerability function. For example, unless a 1980’s era house has been inspected, its roof deck attachment type, roof-wall connection type and other key characteristics will be unknown. To address this common scenario, we use location, year of construction, building code, construction type and occupancy to estimate the probability that each unknown characteristic will have a specific value. These probabilities are quantified in our building stock models (described above in Item C) and are used to develop probability-weighted vulnerability functions for locations with one or more unknown characteristics. E. ARA’s vulnerability functions have been separately derived for commercial residential building structures, personal residential building structures, mobile homes, and appurtenant structures. However, separate information is often not available on the specific types and values of appurtenant structures covered by an insurance policy. For this common case, a probabilistic model of the types and relative values of appurtenant structure is used. These results are combined with the primary structure losses to produce an overall structural loss and then back-allocated to the primary structure and appurtenant structure coverages in proportion to their input replacement values. In cases where detailed information is available for appurtenant structures, these structures are best modeled as separate locations covered under a single policy. F. ARA’s vulnerability functions produce damage for windspeeds above and below the hurricane threshold of 74 mph. The minimum peak gust windspeed that produces damage is about 50 mph. G. ARA’s vulnerability functions are developed using an engineering-based damage simulation methodology that explicitly models the effects of windspeed, wind direction, windborne debris impacts, and water infiltration through damaged and undamaged components of the building envelope. The vulnerability functions do not include damage due to flood, storm surge or wave action. 1. Describe any modifications to the building vulnerability component in the hurricane model since the previously accepted hurricane model. The building stock regions, eras, and weights for post-1994 construction have been revised to better reflect building design requirements in Florida during this period.

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2. Provide a flow chart documenting the process by which the building hurricane vulnerability functions are derived and implemented. Figure 24 shows the flow chart describing the approach used to develop the damage and loss functions.

Figure 24. Flow Chart for Development of Building Vulnerability Functions

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3. Describe the nature and extent of actual insurance claims data used to develop the building hurricane vulnerability functions. Describe in detail what is included, such as, number of policies, number of insurers, dates of hurricane loss, and number of units of dollar exposure, separated into personal residential, commercial residential, and manufactured homes. ARA has used insurance loss data from Hurricane Andrew (1992, 3 insurers), Hurricane Hugo (1989, 2 insurers), Hurricane Georges (1998, 1 insurer), Hurricane Fran (1996, 1 insurer), Hurricane Erin (1995, 1 insurer), Hurricane Bertha (1996, 1 insurer), Hurricane Bonnie (1998, 1 insurer), Hurricane Earl (1998, 1 insurer), Hurricane Opal (1995, 1 insurer), Hurricane Charley (2004, 3 insurers), Hurricane Frances (2004, 3 insurers), Hurricane Ivan, (2004, 3 insurers), Hurricane Jeanne (2004, 3 insurers), and Hurricane Wilma (2005, 3 insurers). In each case, personal lines data were available. Mobile home data were available for one storm-insurer combination. ARA has obtained and analyzed commercial residential insurance loss data from one insurer for Hurricanes Charley (2004), Frances (2004), Ivan (2004), and Wilma (2005). Due to non-disclosure agreements with the insurance companies, additional details cannot be disclosed. 4. Describe the assumptions, data (including insurance claims data), methods, and processes used for the development of the building hurricane vulnerability functions. ARA’s modeling approach for damage and loss employs two separate models. A building performance model, using engineering-based load and resistance models, is used to quantify physical damage. The building physical damage model takes into account the effects of wind direction changes, progressive damage, and storm duration. Economic loss, given physical damage, is estimated using repair and reconstruction cost estimation methods. This process is therefore similar to how an insurance adjuster would estimate the claim, given observed damage to the building. Through direct simulations of thousands of storms with representative buildings, the building performance model produces outputs that are post-processed into loss functions for building, contents, and loss of use. Both the physical damage model and the loss model developed by ARA have been validated through comparisons of modeled and observed damage data collected after hurricane events. Separate models have been developed to estimate the financial losses to the building, the building’s contents, additional living expenses, and losses to appurtenant and exterior structures. Some key assumptions we have made include associating most of interior and content damage with water infiltration, and the assumptions that the claims practices, such as repair and replacement thresholds upon which the loss given damage models were developed, are still valid. 5. Summarize post-event site investigations, including the sources, and provide a brief description of the resulting use of these data in the development or validation of building hurricane vulnerability functions. ARA has used information on building characteristics collected as a part of the Residential Construction Mitigation Program to determine distribution of the wind resistive characteristics of houses constructed in Florida. The details of the data collection and its use in the model are described in the March 2002 Florida Department of Community Affairs report entitled “Development of Loss Relativities for Wind Resistive Features of Residential Structures.” ARA engineers and scientists with significant experience in wind engineering, building performance, and post-storm damage surveys developed the vulnerability functions. Examples of some of the reports used directly in the development of the ARA damage and loss models include Stathopoulos (1979), Meecham (1988), FEMA (1992), Ho (1992), Crandall, et al. (1993), Cunningham (1993), Sparks, et al. (1994), Monroe (1996), Reed, et al. (1996, 1997), Uematsu and Isyumov (1998), and Twisdale, et al. (1996).

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ARA engineers have performed post-storm damage surveys following Hurricanes Andrew, Erin, Opal, Bertha, Fran, Bonnie, Isabel, Charley, Katrina, Harvey, and Florence. ARA engineers have also participated on FEMA Building Performance Assessment Teams (BPATs). In part because of our proven expertise in damage model development and validation, ARA was selected by a panel of wind engineering and meteorology experts to develop FEMA’s HAZUS model for wind loss estimation. 6. Describe the categories of the different building hurricane vulnerability functions. Specifically, include descriptions of the building types and characteristics, building height, number of stories, regions within the state of Florida, year of construction, and occupancy types for which a unique building hurricane vulnerability function is used. Provide the total number of building hurricane vulnerability functions available for use in the hurricane model for personal and commercial residential classifications. The building categories used in the model are built up from detailed engineering load and resistance models that take into account number of stories, building shape, roof shape, roof cover, garage doors, roof-wall connection, sheathing attachment, etc. For each building, damage and loss are estimated for the building, appurtenances, contents, and loss of use. Once the losses have been generated, fast-running vulnerability (loss) functions are developed for the different coverages, etc., for each building class, era, and region within the state of Florida. In this manner, the appropriate building vulnerability information is captured in the respective vulnerability functions used in the loss projection. The primary classification characteristics of the building vulnerability functions are: 1. Residential a. Construction: Frame, masonry, unknown b. Stories: One, two or more, unknown c. Roof shape: Hip, gable, unknown d. Roof slope: Low, high, unknown e. Roof cover: Tile, shingle, FBC tile, FBC shingle, unknown f. Roof deck: 6d@6/12, 8d@6/12, 8d@6/6, unknown g. Roof-wall: Toe nailed, clipped, strapped, unknown h. Opening protection: None, impact-rated, unknown i. Secondary water resistance: No, yes, unknown j. Eras: Pre-1966, 1966-1994, 1995-2002, 2003-2007, 2008-2012, 2013-present, unknown k. Regions: i. Pre-2003: Southeast, South, Central, North Florida ii. 2003-Present: Monroe, HVHZ, Palm Beach, WBDR, Non-WBDR 2. Mobile Homes a. Tie-downs: No, yes, unknown b. Opening protection: None, impact-rated, unknown c. Eras: Pre-HUD, HUD76, HUD94, unknown

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d. Regions: HUD Zone 1, 2, or 3 3. Steel or Reinforced Concrete Framed Buildings a. Construction: Steel, concrete, unknown b. Stories: 1-3, 4-6, 7 or more, unknown c. Roof cover: Built-up, single ply membrane, unknown d. Roof deck: Standard, superior, unknown e. Opening protection: None, impact-rated, unknown f. Eras and Regions: Same as Residential 4. Strip Mall Buildings a. Construction: Unreinforced masonry, reinforced masonry, unknown b. Roof frame: Wood truss, open web steel joist (OWSJ), unknown c. Roof deck connections: i. Wood frame: 6d@6/12, 8d@6/12, 8d@6/6, unknown ii. OWSJ: standard, superior d. Roof-wall: Toe nailed, strapped, unknown e. Roof cover: Built-up, single ply membrane, unknown f. Opening protection: None, impact-rated, unknown g. Eras: Pre-1966, 1966-1994, 1995-2002, 2003-present, unknown h. Regions: Southeast, South, Central, North Florida 5. Pre-Engineered Metal Buildings a. Size: Small, medium, large, unknown b. Roof deck: Standard, superior, unknown c. Opening protection: None, impact-rated, unknown d. Eras: Pre-1966, 1966-1994, 1995-2002, 2003-present, unknown e. Regions: Southeast, South, Central, North Florida 6. Masonry Low-Rise Industrial Buildings a. Construction: Unreinforced masonry, reinforced masonry, unknown b. Roof deck: Standard, superior, unknown c. Opening protection: None, impact-rated, unknown d. Eras: Pre-1966, 1966-1994, 1995-2002, 2003-present, unknown e. Regions: Southeast, South, Central, North Florida The total number of standard vulnerability functions available for use in the model for personal and commercial residential occupancies (Groups 1-3) is 27,545.

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7. Describe the process by which local construction practices and statewide and county building code adoption and enforcement are considered in the development of the building hurricane vulnerability functions. Variations in construction practices and building code criteria are treated through the use of a statewide building stock model comprising five regions and five construction eras. The building stock model is based on detailed building inspection data, building code criteria, and engineering judgment. The building stock model provides distributions (e.g. percentage of hip vs. non-hip roof shapes) to weight the baseline vulnerability functions when detailed information is not available. No assumptions specifically regarding building code enforcement are made in the model. Unless they are explicitly input as separate locations, appurtenant structures and attached exterior structures such as pool enclosures and carports are modeled statistically using distributions of frequencies, replacement values, and vulnerabilities derived from field surveys conducted by ARA for the Florida Office of Insurance Regulation in 2007. The vulnerability functions used for appurtenant structures reflect the fact that these structures are permitted to be designed to lower design wind loads than the dwellings to which they are attached or adjacent. 8. Describe the relationship between building structure and appurtenant structure hurricane vulnerability functions and their consistency with insurance claims data. Given that exterior structures may be either attached or detached from the main building and that this information is rarely known on a location by location basis, our approach for modeling unknown exterior structures is to model the combined building and appurtenant structures loss assuming statistical distributions for attached and detached exterior structures as described above in our response to Disclosure 6. The combined losses are then allocated back to the building structure and appurtenant structure coverages in proportion to the replacement values provided by the user. Therefore, although the final reported results from the model for building structure and appurtenant structure appear to be perfectly correlated, they are in fact modeled independently and then back allocated to the coverages in proportion to the replacement values provided by the user. Because insurers almost universally set the appurtenant structure coverage limit and the assumed replacement value to a fixed percentage of the building limit (e.g. 10%), it is generally not possible to validate appurtenant structure losses separately from building losses using typical claims data. A detailed analysis of attached and free-standing structure losses (Twisdale et al., 2007) provides the basis for the methodology implemented in the ARA model. 9. Describe the assumptions, data (including insurance claims data), methods, and processes used to develop building hurricane vulnerability functions for when: a. residential construction types are unknown, or b. one or more primary building characteristics are unknown, or c. one of more secondary characteristics are known, or d. building input characteristics are conflicting. When some or all of the building characteristics are unknown, the vulnerability distributions are modeled as regionally- and temporally-dependent weighted combinations of the vulnerability distributions of known building types. The weights are based on a combination of building wind mitigation inspection data, building code history analysis, building permit data, real estate data, tax assessor data, and engineering judgment. The same assumptions are used for both modeled losses and actual claims data. Conflicting input characteristics are handled by honoring the more specific input characteristic(s). For example, a house that has a complete set of input characteristics

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will use the opening protection and structural connections provided, even if they conflict with the model’s building stock assumptions for the house’s location and year of construction. 10. Identify the one-minute average sustained windspeed and the windspeed reference height at which the hurricane model begins to estimate damage. The damage model is initiated when the peak gust windspeed at a height of 10 m in open terrain exceeds 50 mph. This peak gust value corresponds to a sustained windspeed (one-minute average windspeed at a height of 10 m in open terrain) of about 40 mph. 11. Describe how the duration of windspeeds at a particular location over the life of a hurricane is considered. Duration of windspeeds is modeled in the load and resistance model via the cumulative damage algorithm illustrated previously in Figure 24. The fast-running damage functions represent the expected damage as a function of the peak gust windspeed averaged over many storms of varying durations. 12. Describe how the hurricane model addresses wind borne missile impact damage and water infiltration. The building performance model depicted above in Figure 24 includes an explicit probabilistic model for wind borne missile impacts and an explicit model for rainfall rate and rain water infiltration through breached openings. 13. Provide a completed Form V-1, One Hypothetical Event. Provide a link to the location of the form [insert hyperlink here]. See Form V-1.

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V-2 Derivation of Contents and Time Element Hurricane Vulnerability Functions* (*Significant Revision) A. Development of the contents and time element hurricane vulnerability functions shall be based on at least one of the following: (1) insurance claims data, (2) tests, (3) rational structural analysis, and (4) post-event site investigations. Any development of the contents and time element hurricane vulnerability functions based on rational structural analysis, post-event site investigations, and tests shall be supported by historical data. B. The relationship between the modeled building and contents hurricane vulnerability functions and historical building and contents hurricane losses shall be reasonable. C. Time element hurricane vulnerability function derivations shall consider the estimated time required to repair or replace the property. D. The relationship between the hurricane model building, contents, and time element hurricane vulnerability functions and historical building, contents, and time element hurricane losses shall be reasonable. E. Time element hurricane vulnerability functions used by the hurricane model shall include time element hurricane losses associated with wind, and missile impact, flood, and storm surge damage to the infrastructure caused by a hurricane. A. ARA’s vulnerability functions for contents and time element losses are derived from estimates of the physical damage to the building. The functions are based on: (1) insurance claims data, (2) tests, (3) rational structural analysis, and (4) site inspections. The development of the contents and time element hurricane vulnerability functions is supported by historical data. The ARA personnel responsible for developing the contents damage and time element loss models have extensive experience in wind load modeling, structural analysis, post-hurricane damage surveys, and insurance claims folder analysis. B. The relationship between modeled building and contents loss is reasonable, as demonstrated in our response to Disclosure 3. C. Direct time element losses are estimated using a sub-model that estimates the time required to rebuild a damaged building. The model does not initiate the computation for time element losses associated with direct wind-induced damage until the ground-up building loss exceeds a threshold value. D. The relationship between modeled building and time element loss costs is reasonable, as demonstrated in our response to Disclosure 6. E. The time element loss costs produced by the model also include a component for claims arising from indirect causes such as infrastructure damage. Time element losses associated with indirect causes can occur when there is no damage to the structure. 1. Describe any modification to the contents and time element vulnerability component in the hurricane model since the previously accepted hurricane model. There have been no modifications to the contents and time element vulnerability component as a function of building damage since the previously accepted hurricane model.

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2. Provide a flow chart documenting the process by which the contents hurricane vulnerability functions are derived and implemented. The derivation of the contents vulnerability functions follows from the building performance model illustrated above in Figure 24 and described below in Disclosure 3. After computing the physical damage state of the building produced by each simulated event, contents losses are estimated and tabulated using the process illustrated below in Figure 25.

Figure 25. Flow Chart for Development of Contents Vulnerability Functions 3. Describe the assumptions, data (including insurance claims data), methods, and processes used to develop and validate the contents hurricane vulnerability functions. The model used to estimate the vulnerability of contents is based on the physical damage and the resulting possibility of wind and water entering the building following damage. Thus, while the damage to contents is a function of the damage to the building, the model is constructed in

April 9, 2019 Applied Research Associates, Inc. 92 Vulnerability Standards 4/9/2019 8:45 AM such a way that damage to contents does not occur until sufficient physical damage to the building has occurred to allow wind and/or water to enter the building, causing damage to the contents. The contents model has been validated/calibrated separately from the building vulnerability model. Figure 26 shows a comparison of modeled and observed content loss as a function of the loss to the building. The value of the contents is assumed to be equal to the coverage limit.

Figure 26. Comparison of Modeled and Observed Mean Content Damage vs. Mean Building Damage 4. Provide the total number of contents hurricane vulnerability functions. Describe whether different contents hurricane vulnerability functions are used for personal residential, commercial residential, manufactured home, unit location for condo owners and apartment renters, and building classes. A unique contents vulnerability function has been developed and implemented in the model for each of the 27,545 personal and commercial residential building vulnerability functions. The content damage functions are largely a function of the amount of water that enters a unit, given physical damage to the building. In the case of high-rise buildings, the damage varies with unit floor level, relative to both the ground and the roof. 5. Provide a flow chart documenting the process by which the time element hurricane vulnerability functions are derived and implemented. The derivation of the time element vulnerability functions follows from the building performance model illustrated above in Figure 24 and described above in Disclosure 4. After computing the physical damage state of the building produced by each simulated event, time element losses are estimated and tabulated using the process illustrated below in Figure 27.

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Figure 27. Flow Chart for Development of Time Element Vulnerability Functions 6. Describe the assumptions, data (including insurance claims data), methods, and processes used to develop and validate the time element hurricane vulnerability functions. A time element loss model was developed using a restoration model that estimates the time building owners are unable to use the damaged structure. The model allows for time element losses to be incurred due to indirect causes such as infrastructure damage. The model has been calibrated through comparisons of actual insurance losses. Figure 28 shows a ZIP Code comparison of modeled and actual personal residential Additional Living Expense (ALE) losses as a function of building damage. Since the model allows for time element losses to be incurred due to infrastructure damage, there is no minimum threshold of building damage required for ALE losses.

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Modeled ALE Actual ALE Ratio

Damage

ALE

Building Damage Ratio

Figure 28. Comparison of Modeled and Observed Mean Time Element Losses (Additional Living Expenses) vs. Mean Building Damage 7. Describe how time element hurricane vulnerability functions take into consideration the damage (including damage due to storm surge, flood, and wind) to local and regional infrastructure. The impact of storm surge and flood damage to local and regional infrastructure is accounted for as an additional term in time element loss model to the extent that such losses were reflected in the insurance loss data used to account for un-modeled losses. 8. Describe the relationship between building structure and contents vulnerability functions. In the underlying HURDAM methodology used to develop our vulnerability functions, contents damage directly depends on the extent of building envelope damage and the resulting volume of rain water that enters the building. In the final tabulated ground-up loss distributions, contents losses are related to building loss (rather than windspeed) to preserve the strong correlation between building and contents losses. 9. Describe the relationship between building structure and time element hurricane vulnerability functions. In the underlying HURDAM methodology used to develop our vulnerability functions, the direct time element loss depends on the extent of building envelope damage, the resulting volume of rain water that enters the building, and the time require to repair or reconstruct the building. As discussed above in our response to Disclosure 8, an additional term for indirect time element losses due to causes such as infrastructure damage (to the extent such effects were included in the insurance data used to calibrate the ALE model) is then added to the direct time element loss. In the final tabulated ground-up loss distributions, time element losses are related to building loss to preserve the strong correlation between building and direct time element losses.

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10. Describe the assumptions, data (including insurance claims data), methods, and processes used to develop contents and time element hurricane vulnerability functions when: a. residential construction types are unknown, or b. one or more primary characteristics are unknown, or c. one or more secondary characteristics are known, or d. building input characteristics are conflicting. The contents and time element vulnerability functions are building stock weighted combinations of the vulnerability functions of known building types. The building stock weights vary by region within the state and construction era. When some primary characteristics are known and some are unknown, the contents and time element vulnerability curves are developed using the same approach as the unknown case discussed above in Standard V-1, Disclosure 9, except with the weighting assigned to each known characteristics fixed at 100%. An underlying assumption of the development, calibration and validation of the contents and time element vulnerability functions is that, unless otherwise specified, the contents limits in insurance company claims data represent the full replacement value of the building contents and the time element coverage limits are sufficient to cover a claim that would be associated with a total re-build of the structure.

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V-3 Hurricane Mitigation Measures and Secondary Characteristics* (*Significant Revision)

A. Modeling of hurricane mitigation measures to improve a building’s hurricane wind resistance, the corresponding effects on hurricane vulnerability, and their associated uncertainties shall be theoretically sound and consistent with fundamental engineering principles. These measures shall include fixtures or construction techniques that affect the performance of the building and the damage to contents and shall consider:  Roof strength  Roof covering performance  Roof-to-wall strength  Wall-to-floor-to-foundation strength  Opening protection  Window, door, and skylight strength The modeling organization shall justify all hurricane mitigation measures considered by the hurricane model. B. Application of hurricane mitigation measures that affect the performance of the building and the damage to contents shall be justified as to the impact on reducing damage whether done individually or in combination. C. Treatment of individual and combined secondary characteristics that affect the performance of the building and the damage to contents shall be justified.

A. ARA’s vulnerability model was originally developed to treat the wind resistive characteristics of buildings, including fixtures or construction techniques that reduce losses. The methods used for estimating the effects of individual and multiple mitigation measures are reasonable. The effects of primary mitigation factors (e.g., opening protection, roof shape, roof deck attachment strength, roof-to-wall connection strength, roof cover strength, and secondary water resistance) on expected vulnerability and its associated uncertainty distributions are explicitly analyzed using the engineering damage simulation methodology described in our responses to Standard G-1, Disclosure 2 and Standard V-1, Disclosure 1. B. ARA’s modeling of hurricane mitigation measures is reasonable both individually and in combination. C. ARA’s treatment of individual and combined secondary characteristics that affect the performance of the building and the damage to contents are based on engineering judgement of analysis. The effects of secondary characteristics (e.g., gable-end bracing and wall-to-foundation connection) on vulnerability are modeled as shifts in the entire vulnerability distribution to achieve a targeted change in mean vulnerability. 1. Describe any modifications to hurricane mitigation measures and secondary characteristics in the hurricane model since the previously-accepted hurricane model. There have been no modifications to the hurricane mitigation measures and secondary characteristics since the previously accepted hurricane model.

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2. Provide a completed Form V-2, Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage. Provide a link to the location of the form [insert hyperlink here]. See Form V-2. 3. Provide a description of the hurricane mitigation measures and secondary characteristics used by the hurricane model, whether or not they are listed in Form V-2 Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage. Additional mitigation measures available in the model include different roof deck nailing patterns (e.g., two different nailing patterns are provided in Form V-2) and different roof-to-wall straps (e.g., double wraps). 4. Describe how hurricane mitigation measures and secondary characteristics are implemented in the hurricane model. Identify any assumptions. Mitigation is implemented in the model by explicitly increasing the resistances of the mitigated components in the engineering models of the building and then re-computing the physical damage and economic losses. The increased losses associated with unbraced gable ends are modeled using a judgment-based modification function. 5. Describe how the effects of multiple hurricane mitigation measures are combined in the hurricane model and the process used to ensure that multiple hurricane mitigation measures and secondary characteristics are correctly combined. The interactions between multiple mitigation factors are explicitly analyzed through the engineering damage simulation methodology previously described in our responses to Standard G-1, Disclosure 2 and Standard V-1, Disclosure 1. 6. Describe how building and contents damage are affected by performance of hurricane mitigation measures and secondary characteristics. Identify any assumptions. Since mitigation features act to reduce physical damage to the building, the building losses, and consequently content and additional living expenses are reduced as well. 7. Describe how hurricane mitigation measures and secondary characteristics affect the uncertainty of the vulnerability. Identify any assumptions. Since our damage and loss models are developed using estimates of physical damage to a structure using a load and resistance model, the estimates of uncertainty associated with mitigation measures are developed the same way as for buildings without mitigation devices (e.g., we model uncertainty in the capacity of window protection, roof sheathing attachments, roof-wall connections, etc.). No additional uncertainty is added to take into account that some mitigation features (e.g., shutters) might not be installed during a hurricane. 8. Provide a completed Form V-4. Differences in Hurricane Mitigation Measures and Secondary Characteristics. Provide a link to the location of the form [insert hyperlink here]. See Form V-4.

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ACTUARIAL STANDARDS

A-1 Hurricane Modeling Input Data and Output Reports C. Adjustments, edits, inclusions, or deletions to insurance company or other input data used by the modeling organization shall be based upon generally accepted actuarial, underwriting, and statistical procedures. D. All modifications, adjustments, assumptions, inputs and input file identification, and defaults necessary to use the hurricane model shall be actuarially sound and shall be included with the hurricane model output report. Treatment of missing values for user inputs required to run the hurricane model shall be actuarially sound and described with the hurricane model output report. A. The amount and quality of insurance information on historical losses varies significantly. The assumptions involved in the comparisons of historical insured hurricane losses to model estimated losses are documented as part of each study. Any adjustments, edits, inclusions, or deletions are based upon accepted actuarial, underwriting, and statistical procedures. Sensitivity analyses are often used to assess how certain assumptions affect the estimated losses to ensure the reasonableness of comparisons. B. Modifications to input data, assumptions regarding input data, and treatment of missing values in the input data are actuarially sound. Specific actions are as follows:

Modifications/Adjustments: Out-of-date ZIP Codes are mapped to the current ZIP Code set used in the model. Records with ZIP Codes that cannot be mapped by the model must be revised by the user or omitted from the analysis. No other modifications are made to the user inputs. Assumptions/Defaults: Building stock models associated with construction type, year built, and occupancy are used to infer loss functions for risks with unknown or incompletely specified construction characteristics (e.g., “wood frame”). Further information is provided in V-1, Disclosure 9. Missing Values: Records with missing values are reported in an error log file where the user is prompted to fill in the missing values. If no values can be input, the record is removed from the analysis. The loss costs estimates do not include any assumptions with respect to depreciation. The validation of the model with actual insurance data indicates that this approach is reasonable. 1. Identify insurance-to-value assumptions and describe the methods and assumptions used to determine the property value and associated hurricane losses. Provide a sample calculation for determining the property value. Unless separately provided by the user, the loss model assumes that the insured limits are equal to the replacement values of the insured property and contents provided by the user. Therefore, no sample calculation for determining the property value can be provided.

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2. Identify depreciation assumptions and describe the methods and assumptions used to reduce insured hurricane losses on account of depreciation. Provide a sample calculation for determining the amount of depreciation and the actual cash value (ACV) hurricane losses. The loss costs estimates do not include any assumptions with respect to depreciation. Therefore, no sample calculation for determining depreciation and ACV losses can be provided. The validation of the model with actual insurance data indicates that this approach is reasonable. 3. Describe the methods used to distinguish among policy form types (e.g., homeowners, dwelling property, manufactured home, tenants, condo unit owners). Loss costs are produced separately by the model for structure, contents, and loss of use subject to the applicable homeowner, mobile home, renters, or condo unit owner policy limits. Aside from differences in the primary coverage and coverage limits, no further distinctions are made among policy form types in the model. Mobile homes are identified through the indicated structure type. 4. Provide a copy of the input form(s) used by the hurricane model with the hurricane model options available for selection by the user for the Florida hurricane model under review. Describe the process followed by the user to generate the hurricane model output produced from the input form. Include the hurricane model name and version identification on the input form. All items included in the input form submitted to the Commission should be clearly labeled and defined. ARA uses a modified version of UNICEDE®/px data exchange format developed by AIR for data input. As an alternative, users may input data as a comma separated file and map the data to UNICEDE/px fields in the web-based user interface. The first four lines of the input file for Notional Set 6 of Forms A-6 and A-7 are shown below. The text is wrapped for readability: ***1,9.0.0,20111201,X,X,X,X,FCHLPM,FML,20121015,PWH,HURLOSS_FLORIDA_VER9. 0,SL,USD,NS6 60,601001,X,X,X,X,X,X,X,X,X,20120101,20121231,USD,0,X,PWH,X,B,PP 63,601001,1,X,X,X,1003,12,1,0,1,29.679942,-82.603351,20120101,20121231,USD,0,1,100000, 10000,50000,20000,365,0,AIR,101,101,1,AIR,302,1980,1,1,1,0,1,PWH,C,100000,10000,50000, 20000,AA,0,0,0,0,0,0,0 64,601001,1,X,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,1,0,0,5,2,1990,0,0,0,0,1,0,0,0,0,0,0,0 … The first line in the UNICEDE/px (UPX) file is the header record. The fields in the header record are as follows: 1. Record type: ***1 (required) 2. Version: 9.0.0 (HurLoss 9.0 supports UPX versions 9.0.0 through 16.0.0) 3. Source date: YYYYMMDD 4. Source contact: optional text (30 characters) 5. Source company: optional text (60 characters) 6. Source phone: optional text (20 characters) 7. Source email: optional text (30 characters) 8. Project name: optional text (30 characters) 9. Project contact: optional text (30 characters)

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10. Inforce date: optional YYYYMMDD 11. Perils covered: optional text (30 characters) 12. Data for: HURLOSS_FLORIDA_VER9.0 (30 characters) 13. Policy type: SL (single location), ML (multiple location), EX (excess), FR (facultative/reinsurance) 14. Base currency: USD (U.S. dollars) 15. Comments: optional text (100 characters)

Record 60 is the policy record. The fields in the policy record are as follows: 1. Record type: 60 (required) 2. Policy ID: text (32 characters) 3. Location ID: text (60 characters) 4. Address: text (100 characters) 5. UDF1: options user defined field 1 (20 characters) 6. UDF2: options user defined field 2 (20 characters) 7. UDF3: options user defined field 3 (20 characters) 8. UDF4: options user defined field 4 (20 characters) 9. UDF5: options user defined field 5 (20 characters) 10. Insured ID Type: “X” (not used) 11. Insured ID: “X” (not used) 12. Effective start date: YYYYMMDD 13. Effective end date: YYYYMMDD 14. Currency: USD (U.S. dollars) 15. Exchange rate: “0” (not used) 16. User LOB: text (10 characters) 17. Peril Code: “PWH” (hurricane wind) 18. Policy Form: “X” (not used) 19. Status: “B” (bound) 20. Contract Type: “PP” (primary property)

Record 63 is the location record. The fields in the location record are as follows: 1. Record type: 63 (required) 2. Policy ID: text (32 characters) 3. Location ID: text (60 characters) 4. Name: text (60 characters) 5. Address: text (100 characters) 6. City: text (30 characters) 7. Area Scheme: “1003” (U.S. 5-digit ZIP Code) 8. State FIPS: up to two digits 9. County FIPS: up to three digits 10. Postal Code: up to five digits (0=unknown) 11. Country Code: 1 (U.S.) 12. Latitude 13. Longitude

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14. Effective start date: YYYYMMDD 15. Effective end date: YYYYMMDD 16. Currency: USD (U.S. dollars) 17. Exchange rate: “0” (not used) 18. Risk Count: positive integer 19. Building Replacement Value: text (30 characters) 20. Appurtenant Structures Replacement Value: text (30 characters) 21. Contents Replacement Value: text (30 characters) 22. Time Element Replacement Value: text (30 characters) 23. Time Element Days Covered: number of days 24. Premium: “0” (not used) 25. Construction Type: “AIR” 26. Construction Code - Building: 100-194 (100=unknown, 101=wood frame, …) 27. Construction Code – Other Structures: 100-194 (not used) 28. Damage Modification Factor: “1” (not used) 29. Occupancy Type: “AIR” 30. Occupancy: 300-373 (300=unknown, 301=general residential, 302=single family, …) 31. Year Built: YYYY or “0” for unknown 32. Stories: positive integer or “0” for unknown 33. Guaranteed Replacement Cost Factor for Building: “1” (not used) 34. Guaranteed Replacement Cost Factor for Contents: “1” (not used) 35. Gross Area of the Building: “0” (not used) 36. Number of Peril Combinations: “1” (insurance terms are the same for all perils) 37. Peril Code: “PWH” (hurricane wind) 38. Limit Type: “C” (limit applies by coverage), “S” (limit applies to sum of coverage), or “N” (none) 39. Building Limit: text (30 characters) 40. Other Structures Limit: text (30 characters) 41. Contents Limit: text (30 characters) 42. Time Element Limit: text (30 characters) 43. Deducible Type: Use “AA” (annual amount) for Florida rate filings 44. Hurricane Deductible: text (30 characters) – if less than 1.0 treat as percent (e.g., 0.02  2%); otherwise, treat as dollar amount 45. All Other Perils Deductible: text (30 characters) – if less than 1.0 treat as percent (e.g., 0.02  2%); otherwise, treat as dollar amount 46. Deductible 3: “0” (not used for Florida rate filings) 47. Deductible 4: “0” (not used for Florida rate filings) 48. User Defined Territory: “0” (not used) 49. Sublimit Area: “0” (not used) 50. Reinsurance Count: “0” (not used)

Record 64 is the optional location detail record. The fields of the location detail record are as follows:

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1. Record type: 64 (required) 2. Policy ID: text (32 characters) 3. Location ID: text (60 characters) 4. Seal of Approval: “X” (not used) 5. Floor of Interest: positive integer or “0” for unknown 6. Building Condition: “0” (not used) 7. Distance to Closest Structure: “0” (not used) 8. Tree Exposure: “0” (not used) 9. Small Debris Source within 200 feet: “0” (not used) 10. Large Debris Source within 100 feet: “0” (not used) 11. Terrain Roughness: “0” (not used) 12. Average Height of Adjacent Buildings: “0” (not used) 13. Building Orientation: “0” (not used) 14. Building Shape: “0” (not used) 15. Torsional Loads: “0” (not used) 16. Soft Story: “0” (not used) 17. Structural Irregularity: “0” (not used) 18. Special Earthquake-Resistive Systems: “0” (not used) 19. Earthquake Retrofit Measures: “0” (not used) 20. Roof Shape: 0-10 (0=unknown, 1=flat, …) 21. Roof Pitch: 0-3 (0=unknown, 1=low, 2=medium, 3=high) 22. Roof Cover: 0-11 (0=unknown, 1=asphalt shingles, …) 23. Roof Deck Material: 0-8 (0=unknown, 1=plywood, …) 24. Roof Cover Attachment: 0-4 (0=unknown, 1=screws, …) 25. Roof Deck Attachment: 0-7 (0=unknown, 1=screws/bolts, 2=nails, …) 26. Roof Anchorage: 0-7 (0=unknown, 1=hurricane ties, …) 27. Roof Built: YYYY or “0” for unknown 28. Wall Type: 0-9 (0=unknown, 1=unreinforced masonry, …) 29. Wall Siding: 0-7 (0=unknown, 1=masonry or brick veneer, …) 30. Glass Type: 0-5 (0=unknown, 1=annealed, …) 31. Glass Percent: 0-4 (0=unknown, 1=less than 5%, …) 32. Opening Protection: 0-3 (0=unknown, 1=none, 2=non-engineered, 3=engineered shutters) 33. Exterior Doors: 0-6 (0=unknown, 1=single width doors, …) 34. Building-Foundation Connection: 0-6 (0=unknown, 1=hurricane ties, …) 35. Foundation Type: 0-9 (0=unknown, 1=masonry basement, …) 36. Internal Partition Walls: 0-5 (0=unknown, 1=wood, …) 37. Attached Structures: 0, 1, 8 (0=unknown, 1=metal structures, 8=no metal structures) 38. Exterior Structures: 0, 1, 6 (0=unknown, 1=detached garage/shed, 6=no detached garage/shed) 39. Secondary Water Barrier: 0, 12, 13 (0=unknown, 12=yes, 13=no)

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5. Disclose, in a hurricane model output report, the specific inputs required to use the hurricane model and the options of the hurricane model selected for use in a residential property insurance rate filing. Include the hurricane model name and version identification on the hurricane model output report. All items included in the hurricane model output report submitted to the Commission should be clearly labeled and defined. The options in the model are event set (probabilistic or historic), demand surge (on/off), and deductible type (none, occurrence, or annual). Summaries of the input exposure data and selected analysis options are provided in three model output files. Examples of these files are shown in Figure 29. The first step in the analysis is to read in the exposure data and assign vulnerability functions to each site in the exposure data file. The log file at the top of Figure 29 reports the version number, date, and time of the analysis; the name of the input exposure file; a list of any skipped locations (none in this example); and the total number of locations retained in the model for analysis (2805 in this example). The second major step in the analysis is to assign loss functions to each location. The first few lines of the information file are shown in the middle of Figure 29. For each modeled location, a surface roughness (z04), wind grid identifier (igrid), and building type (iARAType1) are assigned by the model. Upon completion of the loss calculations, a results file is produced. A sample results file is shown at the bottom of Figure 29. The results file contains the version number of the software, the selected analysis options, a summary of the number of risks and exposures by county, the annual occurrence and annual aggregate PMLs for 10 return periods, and the AALs by county and by location.

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Figure 29. Model Output Report Files As summarized above in our response to Disclosure 4, exposure data is input to the model using the UNICEDE/px data file format. Detailed specifications for the exposure data are available at http://www.unicede.com/UnicedePX.aspx. The policy, location, and location detail record types are used by the model to assign a vulnerability function to each valid location in the input file. The model supports versions 9.0 through 16.0 of the UNICEDE/px data standard. The input file format version number must be specified on the first line of the input file. The process followed by the user to generate the model output is to create an input control file for the model run. The control file name is then specified by the user as parameter on the program command line. An example of an input control file is shown in Figure 30. The control file specifies the folder and name of the exposure data file, the folder containing the model vulnerability function

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files, the folder containing the model ZIP Code and terrain data files, and the folder containing the model wind hazard files. Four analysis options are also specified in the control file: (1) whether to use loss functions from a previous analysis (yes or no), (2) the analysis type (probabilistic or historic), (3) the deductible type (ground-up, per occurrence, or annual), and (4) demand surge (no or yes). The selected model options and the model version number are recorded in the output forms discussed above.

Figure 30. Input Control File for Form A-1 6. Describe actions performed to ensure the validity of insurer or other input data used for hurricane model inputs or for validation/verification. Aggregate exposures by county, coverage, and line of business reported in the model output are compared to control totals provided by the insurer. Out-of-date ZIP Codes are mapped to the current ZIP Code set used in the model. Records with ZIP Codes that cannot be mapped by the model must be revised by the user or omitted from the analysis. The fields in each record are checked for valid ranges (known construction types, nonnegative coverage limits, valid locations, etc.). Records with invalid or missing fields are reported to the user and must be revised by the user or omitted from the analysis. 7. Disclose if changing the order of the hurricane model input exposure data produces different hurricane model output or results. The order of input does not affect the results. 8. Disclose if removing and adding policies from the hurricane model input file affects the hurricane model output or results for the remaining policies. Adding or removing policies does not affect the outputs for the remaining policies.

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A-2 Hurricane Events Resulting in Modeled Hurricane Losses* (*Significant Revision) A. Modeled hurricane loss costs and hurricane probable maximum loss levels shall reflect all insured wind related damages from storms that reach hurricane strength and produce minimum damaging windspeeds or greater B. The modeling organization shall have a documented procedure for distinguishing wind-related hurricane losses from other peril losses. A. The computation of losses begins when damage is first caused by any modeled hurricane event that affects Florida. The computation of damage and loss includes all subsequent damage produced by the event. B. The HurLoss model does not model storm surge, inland flood, or any other peril losses besides wind-related hurricane losses. Therefore, there are no other peril losses to distinguish from the wind-related losses produced by the model. 1. Describe how damage from hurricane model generated storms (landfalling and by-passing hurricanes) is excluded or included in the calculation of hurricane loss costs and hurricane probable maximum loss levels for Florida. All damages from landfalling and by-passing storms are included in the calculation of loss costs provided the event reaches hurricane strength and produces minimum damaging windspeeds or greater on land in Florida. 2. Describe how damage resulting from concurrent or preceding flood or hurricane storm surge is treated in the calculation of hurricane loss costs and hurricane probable maximum loss levels in Florida. Damage resulting from concurrent or preceding flood or hurricane storm surge is not treated by the model, except for time element losses due to indirect causes such as infrastructure damage.

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A-3 Hurricane Coverages A. The methods used in the calculation of building hurricane loss costs shall be actuarially sound. B. The methods used in the calculation of appurtenant structure hurricane loss costs shall be actuarially sound. C. The methods used in the calculation of contents hurricane loss costs shall be actuarially sound. D. The methods used in the calculation of time element hurricane loss costs shall be actuarially sound.

A. The ARA model produces direct estimates of damage to buildings. The model has been validated through comparisons with actual physical damage and insured loss data, and the methods used in the development of loss costs are actuarially sound. B. The ARA model produces direct estimates of damage to appurtenant structures. The appurtenant structures model has been validated through comparisons with actual physical damage and insured loss data. The methods used in the development of loss costs are actuarially sound. C. The ARA model produces direct estimates of damage to contents. The model has been validated through comparisons with actual loss data. The methods used in the development of loss costs are actuarially sound. D. The ARA time element loss model is primarily based on the distribution of times required to repair or replace the direct physical damage to the building and bring it back to its pre-storm level of functionality. The time element model also includes an additional factor for loss of use due to damage to infrastructure. The model has been calibrated using insurance loss data and is actuarially sound. 1. Describe the methods used in the hurricane model to calculate hurricane loss costs for building coverage associated with personal and commercial residential properties. The model was developed through detailed probabilistic, 3-dimensional, time-dependent engineering analysis of a broad range of personal residential, commercial residential, and non- residential building construction types and eras. Loading conditions considered in the analysis include wind pressure, windborne debris impacts, and rainfall produced by the full spectrum of tropical cyclone intensities and durations. 2. Describe the methods used in the hurricane model to calculate hurricane loss costs for appurtenant structure coverage associated with personal and commercial residential properties. In most cases, separate information is not available on the specific types and values of appurtenant structures covered by an insurance policy. For this common case, a probabilistic model of the types and relative values of appurtenant structure is used. These results are combined with the primary structure losses to produce an overall structural loss and then back-allocated to the primary structure and appurtenant structure coverages in proportion to their input replacement values. In cases where detailed information is available for appurtenant structures, these structures are best modeled as separate locations covered under a single policy.

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3. Describe the methods used in the hurricane model to calculate hurricane loss costs for contents coverage associated with personal and commercial residential buildings. The model used to estimate the vulnerability of contents is based on the physical damage and the resulting possibility of wind and water entering the building following damage. Thus, while the damage to contents is a function of the damage to the building, the model is constructed in such a way that damage to contents does not occur until sufficient physical damage to the building has occurred to allow wind and/or water to enter the building, causing damage to the contents. The contents model has been validated/calibrated separately from the building vulnerability model. 4. Describe the methods used in the hurricane model to calculate hurricane loss costs for time element coverage associated with personal and commercial residential properties. The time element loss model was developed using a restoration model to estimate the time building owners are unable to use the damaged structure. The model allows for time element losses to be incurred due to indirect causes such as infrastructure damage. The model has been calibrated through comparisons of actual insurance losses.

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A-4 Modeled Hurricane Loss Cost and Hurricane Probable Maximum Loss Level Considerations A. Hurricane loss cost projections and hurricane probable maximum loss levels shall not include expenses, risk load, investment income, premium reserves, taxes, assessments, or profit margin. B. Hurricane loss cost projections and hurricane probable maximum loss levels shall not make a prospective provision for economic inflation. C. Hurricane loss cost projections and hurricane probable maximum loss levels shall not include any explicit provision for direct hurricane storm surge losses. D. Hurricane loss cost projections and hurricane probable maximum loss levels shall be capable of being calculated from exposures at a geocode (latitude- longitude) level of resolution. E. Demand surge shall be included in the hurricane model’s calculation of hurricane loss costs and hurricane probable maximum loss levels using relevant data and actuarially sound methods and assumptions. A. Loss costs projections and probable maximum loss levels include only the direct costs associated with rebuilding/replacing the damaged structures, contents, appurtenant structures, and the costs associated with additional living expenses. Additional costs such as expenses, risk load, investment income, premium reserves, taxes, assessments, or profit, are not included in the loss costs projections. B. Loss cost projections and probable maximum loss levels do not make prospective provisions for economic inflation. C. Loss cost projections and probable maximum loss levels do not include any provisions for direct hurricane storm surge losses. D. Loss cost projections and probable maximum loss levels can be computed for risks input at the ZIP Code or geocode levels of resolution. E. A demand surge factor is included in the modeled losses for each simulated event. Insured losses are computed using the factored ground-up loss for each location. 1. Describe the method(s) used to estimate annual hurricane loss costs and hurricane probable maximum loss levels. Identify any source documents used and any relevant research results. Using a straightforward simulation of N years of storms, expected annual losses are computed simply as the sum of all losses, net of policy conditions, divided by N. Loss costs for a given territory are computed by dividing the average annual loss by the appropriate exposure base. Probable maximum losses are determined by tabulating the annual maximum or annual aggregate losses for each simulated year, sorting the values, and selecting the appropriate value from the sorted list (e.g., the 2,500th largest annual maximum loss in a 250,000-year simulation as the 100- year occurrence PML).

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2. Identify the highest level of resolution for which hurricane loss costs and hurricane probable maximum loss levels can be provided. Identify all possible resolutions available for the reported output ranges. Loss costs can be produced at the coverage, policy, site, ZIP Code, county, state, and portfolio levels. The highest resolution is for a site and an individual building located at a latitude-longitude point. The resolution for the reported output ranges in this document is ZIP Codes. The model explicitly considers the location and terrain roughness of each area, such as beach/coastal, inland location, etc. For each simulated storm, the effects of terrain and location relative to the storm, distance from coast, and time since landfall are treated. 3. Describe how the hurricane model incorporates demand surge in the calculation of hurricane loss costs and hurricane probable maximum loss levels. A multiplicative demand surge factor is computed in the model for each simulated event. The demand surge factor is a function of the estimated industry-wide loss, and it is applied uniformly to each risk. The demand surge factor is applied to the ground-up building and time element losses at each site but not to contents losses. Additional details have been provided to the Professional Team. 4. Provide citations to published papers, if any, or modeling organization studies that were used to develop how the hurricane model estimates demand surge. The following references were used to guide the development of the demand surge model: Andrews, M. (2006), “Demand Surge After Hurricanes Katrina & Rita,” http://www.iii.org/disaster2/facts/demand_surge/. Baker, K. (2006), “The economic and construction outlook in the Gulf States after Hurricane Katrina,” http://ww.aia.org/econ_katrina_outlook , American Institute of Architects. Davis Langdon (2005), “Impact of Katrina on the construction market,” http://www.davislangdon.com (09/2005). Engineering News-Record, ENR Cost Indexes, http://www.enr.com, A McGraw-Hill Construction Group Publication. Grossi, P. and Kunreuther, H. (2005), Catastrophe Modeling: a New Approach to Managing Risk, Springer. Jain, V.K., Davidson, R., and Rosowsky, D. (2005), “Modeling changes in hurricane risk over time,” Natural Hazards Review, Vol.6, No.2, pp.88-96. Marshall & Swift / Boeckh (MS/B), http://www.msbinfo.com . Murray, R.A. (2005), “Hurricane Katrina: implications for the construction industry,” McGraw Hill Construction. Munich Re (2006), “The 1906 Earthquake and Hurricane Katrina,” http://www.munichre.com/. NAPCOLLC (2006), “The impact of changes to the RMS U.S. hurricane catastrophe model,” http://www.napcollc.com/articles/JuneReviewRMSHurricane.pdf. National Association of Home Builders (NAHB) (2005), “Impact of hurricane Katrina on Building Materials and Prices,” http://www.nahb.org (9/2/2005). RSMeans Company (2001), RS Means Building Construction Cost Data, Kinston, MA.

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Westfall, C. (2006), “Insurers Balance Supply and Demand (Surge),” http://www.kpmginsiders.com (03/17/2006). 5. Describe how economic inflation has been applied to past insurance experience to develop and validate hurricane loss costs and hurricane probable maximum loss levels. Losses are computed with respect to the insured value of the building at the time of the loss.

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A-5 Hurricane Policy Conditions A. The methods used in the development of mathematical distributions to reflect the effects of deductibles and policy limits shall be actuarially sound. B. The relationship among the modeled deductible hurricane loss costs shall be reasonable. C. Deductible hurricane loss costs shall be calculated in accordance with s. 627.701(5)(a), F.S. A. The model produces statistical distributions of losses that are treated mathematically to reflect deductibles and policy limits. The details of this approach and validation have been presented to the Professional Team. B. The relationships among the modeled deductible loss costs are reasonable, as demonstrated by our results for Forms A-4 and A-6. C. Deductible loss costs in Florida are calculated using a hurricane deductible and an all other perils deductible in accordance with s.627.701(5)(a), F.S. 1. Describe the methods used in the hurricane model to treat deductibles (both flat and percentage), policy limits, and insurance-to-value criteria when projecting hurricane loss costs and hurricane probable maximum loss levels. Discuss data or documentation used to validate the method used by the hurricane model. ARA has developed probability distributions of normalized ground-up loss given a building type, local terrain, and peak 3-second gust windspeed at 10 m above ground in open terrain. The distributions are modeled as piecewise linear probability density functions with the possibility of discrete probability masses at the lower and/or upper limits of each normalized loss interval. When computing the expected insured loss at a given location in a given event, the coverage limits, deductibles, coinsurance participation factor, and demand surge factor are applied to the ground- up loss distribution as it is being numerically integrated across the range of possible losses. Deductibles that are expressed as a percentage are converted to dollar equivalent and then applied. 2. Describe whether, and if so how, the hurricane model treats policy exclusions and loss settlement provisions. The model treats policy exclusions to the extent that such exclusions are not included in the estimates of insured value. The same applies to settlement provisions (e.g., ACV vs. replacement cost). 3. Complete the following table using the method implemented in the hurricane model. Discuss data or documentation used to validate the method used by the model. Table 2 is representative of a typical one-story house.

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Table 2. Example of Insurer Loss Calculations Building Policy Limit Deductible Damage Ground- Up Insurance Value Ratio Hurricane Loss Hurricane Loss $100,000 $90,000 $500 2% $2,000 $1,602 $100,000 $90,000 $500 50% $50,000 $46,434 $100,000 $90,000 $500 92% $92,000 $83,466 $100,000 $90,000 $500 100% $100,000 $90,000 $100,000 $100,000 $500 92% $92,000 $91,500 For any given windspeed, the damage is comprised of a wide range of losses ranging between 0 and 100%. To compute the mean loss for a given windspeed, the distribution of ground-up losses derived from the building performance model is used, and the deductible is subtracted from this total loss distribution to compute the net loss. The mean loss net of deductible is then obtained by through numerical integration of the insured loss distribution. The example paid losses given above change with the characteristics of the building. 4. Describe how the hurricane model treats annual deductibles. The model tracks the mean deductible applied to each policy in each event during a simulated year. After the hurricane deductible is exhausted (i.e., the unused portion of hurricane deductible for a given policy falls below the all other perils deductible), the model uses the all other perils deductible for that policy for the remainder of the year. When only a portion of the hurricane deductible has been expended and the remaining amount is larger than the all other perils deductible, the remaining portion of the hurricane deductible is used as the deductible for the next event in the same year. The minimum deductible used is the all other perils deductible.

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A-6 Hurricane Loss Outputs and Logical Relationships to Risk

A. The methods, data, and assumptions used in the estimation of hurricane probable maximum loss levels shall be actuarially sound. B. Hurricane loss costs shall not exhibit an illogical relation to risk, nor shall hurricane loss costs exhibit a significant change when the underlying risk does not change significantly. C. Hurricane loss costs produced by the hurricane model shall be positive and non-zero for all valid Florida ZIP Codes. D. Hurricane loss costs cannot increase as the quality of construction type, materials and workmanship increases, all other factors held constant. E. Hurricane loss costs cannot increase as the presence of fixtures or construction techniques designed for hazard mitigation increases, all other factors held constant. F. Hurricane loss costs cannot increase as the wind resistant design provisions increases, all other factors held constant. G. Hurricane loss costs cannot increase as building code enforcement increases, all other factors held constant H. Hurricane loss costs shall decrease as deductibles increase, all other factors held constant. I. The relationship of hurricane loss costs for individual coverages, (e.g., building, appurtenant structure, contents, and time element) shall be consistent with the coverages provided. J. Hurricane output ranges shall be logical for the type of risk being modeled and apparent deviations shall be justified. K. All other factors held constant, hurricane output ranges produced by the hurricane model shall in general reflect lower hurricane loss costs for: 1. masonry construction versus frame construction, 2. personal residential risk exposure versus manufactured home risk exposure, 3. inland counties versus coastal counties, 4. northern counties versus southern counties, and 5. newer construction versus older construction. L. For hurricane loss cost and hurricane probable maximum loss level estimates derived from and validated with historical insured hurricane losses, the assumptions in the derivations concerning (1) construction characteristics, (2) policy provisions, (3) coinsurance, and (4) contractual provisions shall be appropriate based on the type of risk being modeled. A. The model produces estimates of loss as a function of annual probability of exceedance or its inverse, return period. These loss estimates are commonly referred to as probable maximum

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loss levels. The methodology used to estimate probable maximum loss levels is described below in our response to Disclosure 12. The methodology is actuarially sound. B. The loss costs produced by the ARA model show no illogical relations with respect to risk, nor do loss costs exhibit a significant change when the underlying risk does not change significantly. C. Loss costs produced by the model are positive and non-zero for all Florida ZIP Codes. D. Loss costs decrease as “quality” of construction increases. E. Loss costs decrease as the presence of fixtures or construction techniques designed for hazard mitigation increases. F. Loss costs decrease as the wind resistant design provisions increase. The model does not explicitly treat “building code enforcement.” G. Loss costs do not increase as building code enforcement increases, all other factors held contstant. To the extent that building code enforcement is quantified in specific structural or building parameters, the model shows that loss costs decreases for stronger/higher quality construction, all other factors held constant. H. Loss costs decrease with increasing deductibles, all other factors held constant. I. The relationship of loss costs for individual coverage (A, B, C, D) is consistent with the coverage provided. J. The output ranges provided in Forms A-4A and A-4B are logical. There are no deviations. K. All other factors held constant, the output ranges are consistent with items 1-5 in this Standard. L. Assumptions in the derivation and validation of loss cost estimates using historical insured hurricane losses are discussed in the disclosures below. These assumptions are reasonable and appropriate. 1. Provide a completed Form A-1, Zero Deductible Personal Residential Hurricane Loss Costs by ZIP Code. Provide a link to the location of the form [insert hyperlink here]. See Form A-1. 2. Provide a completed Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FCHF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-2A. 3. Provide a completed Form A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FCHF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-2B. 4. Provide a completed form A-3A, 2004 Hurricane Season Losses (2012 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-3A.

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5. Provide a completed form A-3B, 2004 Hurricane Season Losses (2017 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-3B. 6. Provide a completed form A-4A, Hurricane Output Ranges (2012 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-4A. 7. Provide a completed form A-4B, Hurricane Output Ranges (2017 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-4B. 8. Provide a completed Form A-5, Percentage Change in Hurricane Output Ranges (2012 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-5. 9. Provide a completed Form A-7, Percentage Change in Logical Relationship to Hurricane Risk. Provide a link to the location of the form [insert hyperlink here]. See Form A-7. 10. Provide a completed Form A-8A, Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-8A. 11. Provide a completed Form A-8B, Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data). Provide a link to the location of the form [insert hyperlink here]. See Form A-8B. 12. Describe how the hurricane model produces hurricane probable maximum loss levels. The model uses a standard Monte Carlo simulation approach to estimate losses on an event by event basis. Upon completion of the simulation, the maximum event loss in each year (for annual occurrence PMLs) or the aggregate event losses in each year (for annual aggregate PMLs) are sorted in descending order. The annual probability of exceedance, p, associated with each simulated annual loss is simply its rank, r, divided by the number of simulation years, n. The return period is simply the inverse of the annual exceedance probability (e.g., the 100-year loss has an annual probability of exceedance of 1%). 13. Provide citations to published papers, if any, or modeling organization studies that were used to estimate hurricane probable maximum loss levels. N/A. 14. Describe how the hurricane probable maximum loss levels produced by the hurricane model include the effect of personal and commercial residential insurance coverage. Probable maximum loss levels can be computed separately by type of business (e.g., homeowners, mobile homes, renters, condominium unit owners, or commercial residential) or for all types of business combined using the appropriate event losses and methodology described above in Disclosure 8.

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15. Explain any difference between the values provided on Form A-8A, Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data), and those provided on Form S- 2A, Examples of Hurricane Loss Exceedance Estimates (2012 FHCF Exposure Data). N/A. 16. Explain any difference between the values provided on Form A-8B, Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data), and those provided on Form S- 2B, Examples of Hurricane Loss Exceedance Estimates (2017 FHCF Exposure Data). N/A. 17. Provide an explanation for all hurricane loss costs that are not consistent with the requirements of this standard. There are no anomalies in our estimates of loss costs compared to the requirements of this standard. The relationship between masonry and frame losses can vary by county depending on the risk locations within the county (e.g., open vs. suburban terrain and, to a much lesser extent, distance inland) and the additional risk characteristics associated with the risks (e.g., year built, opening protection, etc.). In general, losses are more sensitive to risk location and additional risk characteristics than to wall construction type. The relationship between modeled losses and year built varies with the type of construction, the applicable building codes, the applicable design terrain exposure, and the fraction of buildings that have been re-roofed with FBC-equivalent roof coverings. As a result, there are instances, for example, in which 1998 buildings or buildings with unknown year built will sustain higher loss costs than a similar 1980 building. This behavior has also been observed in claims data. 18. Provide an explanation of the differences in hurricane output ranges between the previously accepted hurricane model and the current hurricane model based on the 2012 FHCF Exposure Data. The differences in the output between the prior year and the current year submission are due to the model updates identified under Standard G-1, Disclosure 5 and statistical variability (less than 5%) associated with the generation of a new Monte Carlo simulation event set. The changes in average output ranges by region and policy type are summarized in Form A-5. 19. Identify the assumptions used to account for the effects of coinsurance on commercial residential hurricane loss costs. Coinsurance is modeled as a multiplicative participation factor at the location level on the distribution of ground-up loss after it has been capped at the coverage limits and reduced by the deductible. The participation factor represents the fraction of the net risk (i.e., after applying limits and deductibles) that has been accepted by the insurer.

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COMPUTER/INFORMATION STANDARDS

CI-1 Hurricane Model Documentation* (*Significant Revision) A. Hurricane model functionality and technical descriptions shall be documented formally in an archival format separate from the use of letters, slides, and unformatted text files. B. The modeling organization shall maintain a primary document repository, containing or referencing a complete set of documentation specifying the hurricane model structure, detailed software description, and functionality. Documentation shall be indicative of current model development and software engineering practices. C. All computer software (i.e., user interface, scientific, engineering, actuarial, data preparation, and validation) relevant to the hurricane model shall be consistently documented and dated. D. The modeling organization shall maintain (1) a table of all changes in the hurricane model from the previously-accepted hurricane model to the initial submission this year and (2) a table of all substantive changes since this year’s initial submission. E. Documentation shall be created separately from the source code. F. The modeling organization shall maintain a list of all externally acquired currently used hurricane model-specific software and data assets. The list shall include (1) asset name, (2) asset version number, (3) asset acquisition date, (4) asset acquisition source, (5) asset acquisition mode (e.g., lease, purchase, open source), and (6) length of time asset has been used by the modeling organization. A. ARA maintains documented technical descriptions and specifications of model functionality. These archival documents are separate from and in addition to letters, presentation slides, and other unformatted text files. B. ARA maintains a primary document binder and a complete set of document sub-binders for the components of the HurLoss suite of applications. The model documentation binders contain fully documented sections, based on accepted software engineering practices, for each computer standard. C. The documentation for all software components is consistently documented in both content and format. Version dates are maintained for living documents and publication dates are maintained for final documents. Document templates and guidelines are maintained to keep all new documentation consistent. D. ARA maintains a table of all changes in the model from the previously accepted submission to the current submission. We will also maintain a table of all substantive changes made after this year’s initial submission, if any such changes are made. E. The documentation has been created separately from the source code and is maintained under a revision control system.

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F. A list of all externally acquired software and data assets has been compiled and is maintained under a revision control system.

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CI-2 Hurricane Model Requirements The modeling organization shall maintain a complete set of requirements for each software component as well as for each database or data file accessed by a component. Requirements shall be updated whenever changes are made to the hurricane model. Requirements are specified and documented for each of the major components of the model. 1. Provide a description of the documentation for interface, human factors, functionality, documentation, data, human and material resources, security, and quality assurance. The documentation for each component specifies the required functionality of the component, the input data required by the component, and the output data produced by the component. The documentation for each database or data file specifies the file format or database schema, the producers of the data, and the intended consumers of the data. General requirements common to all components and the ARA policy for model revision are specified in the primary document binder.

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CI-3 Hurricane Model Architecture and Component Design* (*Significant Revision) A. The modeling organization shall maintain and document (1) detailed control and data flowcharts and interface specifications for each software component, and (2) schema definitions for each database and data file, (3) flowcharts illustrating hurricane model-related flow of information and its processing by modeling organization personnel or consultants, and (4) system model representations associated with (1)-(3). Documentation shall be to the level of components that make significant contributions to the hurricane model output. B. All flowcharts (e.g., software, data, and system models) shall be based on (1) a referenced industry standard (e.g., Unified Modeling Language (UML) Business Process model and Notation (BPMN). Systems Modeling Language (SysML)), or (2) a comparable internally-developed standard which is separately documented. Detailed control and data flow diagrams, interface specifications, data file specifications, and model-related information flow diagrams are included in the primary document binder and the supplemental documentation binders for each of the components that make significant contributions to the model output. New and revised flowcharts are developed using BPMN notation.

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CI-4 Hurricane Model Implementation

A. The modeling organization shall maintain a complete procedure of coding guidelines consistent with accepted software engineering practices. B. The modeling organization shall maintain a complete procedure used in creating, deriving, or procuring and verifying databases or data files accessed by components. C. All components shall be traceable, through explicit component identification in the hurricane model representations (e.g., flowcharts) down to the code level. D. The modeling organization shall maintain a table of all software components affecting hurricane loss costs and hurricane probable maximum loss levels, with the following table columns: (1) Component name, (2) Number of lines of code, minus blank and comment lines; and (3) Number of explanatory comment lines. E. Each component shall be sufficiently and consistently commented so that a software engineer unfamiliar with the code shall be able to comprehend the component logic at a reasonable level of abstraction. F. The modeling organization shall maintain the following documentation for all components or data modified by items identified in Standard G-1, Scope of the Hurricane Model and Its Implementation, Disclosure 5 and Audit 5: 1. A list of all equations and formulas used in documentation of the hurricane model with definitions of all terms and variables. 2. A cross-referenced list of implementation source code terms and variable names corresponding to items within F.1, above. A. ARA maintains coding guidelines that are consistent with accepted software engineering practices. B. ARA has developed a set of procedures for creating, deriving, or procuring and verifying external data files or databases. Each procedure specifically addresses an individual data source. C. Each major component of the model has been incrementally translated into a hierarchy of subcomponents, which have been implemented in source code. Documentation is provided in the relevant binders to enable users to trace the design and implementation requirements from the documentation to the source code. D. A table of all software components affecting software loss costs with the number of lines of code, number of lines of comments, number of lines of combined code and comments, and number of blank lines is included in the Primary Documents Binder. An estimate of the breakdown between explanatory and non-explanatory comment lines is also included. E. Components are commented at the code level at the time of development. Code-level comments include file headers, class headers, function headers, and inline comments to explain non-obvious sections of code. F. Lists of all equations and formulas and cross-referenced lists of implementation source code terms and variable names for all components or data modified by items identified in Standard G- 1, Disclosures 5 are maintained in the appropriate component documentation binders.

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1. Specify the hardware, operating system, other software, and all computer languages required to use the hurricane model. The model runs on computers running the Windows® XP, Windows 7, or Windows Server operating systems. The computer languages used to implement the model are FORTRAN, C++, C#, and T-SQL.

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CI-5 Hurricane Model Verification A. General. For each component, the modeling organization shall maintain procedures for verification, such as code inspections, reviews, calculation crosschecks, and walkthroughs, sufficient to demonstrate code correctness. Verification procedures shall include tests performed by modeling organization personnel other than the original component developers. B. Component Testing 1. The modeling organization shall use testing software to assist in documenting and analyzing all components. 2. Unit tests shall be performed and documented for each component. 3. Regression tests shall be performed and documented on incremental builds. 4. Aggregation tests shall be performed and documented to ensure the correctness of all hurricane model components. Sufficient testing shall be performed to ensure that all components have been executed at least once. C. Data Testing 1. The modeling organization shall use testing software to assist in documenting and analyzing all databases and data files accessed by components. 2. The modeling organization shall perform and document integrity, consistency, and correctness checks on all databases and data files accessed by the components. A. ARA's software verification procedures include: (i) use of logical assertions and error checking throughout the code to ensure that data values are within valid ranges; (ii) reviews of completed code by engineers on the team who were not responsible for developing that code; (iii) walkthroughs of the code to ensure proper flow; (iv) inspections of internal variables to ensure proper input, output, and processing; (v) reviews of outputs to ensure proper trends; and (vi) validations against historical events, experimental data, and/or independently-computed results. Several stand-alone driver programs have been developed to test individual components of the model. B. ARA utilizes testing software written in-house and designed specifically to test, verify, and validate the various components of the models. The testing process has been designed to ensure that all components have been executed at least once. Unit tests are performed for each component as it is written. Regression tests are performed and documented for all incremental builds of the model. Regression testing includes comparisons of annual FCHLPM submissions to the previous year with an investigation and explanation of all associated differences. Verification and validation tests for the software components are documented through extensive comparisons of intermediate and final outputs produced by the code against historical, experimental, and/or independently-computed results. Results of these tests are documented, typically in the form of graphs or tables, in the component documentation binders. C. ARA utilizes testing software written in-house such as bin-to-txt and bin-to-bmp utilities to verify integrity, consistency, and correctness on databases and data files. Additional data testing is performed through spot checks assisted by similar in-house utilities.

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1. State whether any two executions of the hurricane model with no changes in input data, parameters, code, and seeds of random number generators produce the same hurricane loss costs and hurricane probable maximum loss levels. The model produces the same loss costs and probable maximum losses when run more than once with the same input data, analysis options, code, and random number seeds. 2. Provide an overview of the component testing procedures. New components or existing components undergoing any code revision are subject to the testing procedures in place at the time of development or update. Existing components that were developed prior to the FCHLPM standards or under previous FCHLPM standards were tested in accordance with the adopted testing procedures at the time of development. Existing components are subject to new unit-level testing when revisions occur, and all components are subject to ARA’s ongoing system-level and regression testing. ARA’s current software testing procedures include unit-level testing for all newly developed or updated components, system-level testing for the model as a whole and its major sub-systems, and regression testing between versioned builds. Data files undergo specialized testing tailored to the specific dataset and designed to ensure that the data is accurate and complete. 3. Provide a description of verification approaches used for externally acquired data, software, and models. Updated versions of externally acquired geographic data sets, such as ZIP Code polygons and NLCD LULC raster layers, are visually inspected and compared to their preceding versions using GIS software. Updates to externally acquired environmental data sets, such as historical event tracks, sea surface temperature data sets, and wind shear data sets, are inspected for changes in data formats and compared to previous versions using file comparison tools to check for any differences in sections of the data sets that existed in both the previous version of the data and the new version.

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CI-6 Hurricane Model Maintenance and Revision

A. The modeling organization shall maintain a clearly written policy for hurricane model review, maintenance, and revision, including verification and validation of revised components, databases, and data files. B. A revision to any portion of the hurricane model that results in a change in any Florida residential hurricane loss cost or hurricane probable maximum loss level shall result in a new hurricane model version identification. C. The modeling organization shall use tracking software to identify and describe all errors, as well as modifications to code, data, and documentation. D. The modeling organization shall maintain a list of all hurricane model versions since the initial submission for this year. Each hurricane model description shall have a unique version identification, and a list of additions, deletions, and changes that define that version. A. ARA has developed and implemented a clearly written policy for model revision. In addition, procedures specific to a component are documented in the appropriate binder. B. Any revision to the model that results in a change in any Florida residential hurricane loss cost or probably maximum loss level results in a new model version number. C. See Disclosure 1. D. ARA will maintain list of all model versions since the initial submission for this year. Each model version shall have a unique version identification and a list of changes that define that version. 1. Identify procedures used to review and maintain code, data, and documentation. ARA uses Microsoft Visual SourceSafe, Microsoft Team Foundation Server, and GitHub to track all changes to the software and documentation. Only authorized users are allowed to check in changes to the archive. Project check points are used to document the individual revision numbers of the source code files, header files, workspace files, data files, and documentation files in each new release of the model. 2. Describe the rules underlying the hurricane model and code revision identification systems. Any revision to the model that results in a change in any Florida residential hurricane loss cost or probably maximum loss level results in a new model version number. Major changes to the hazard or vulnerability models, database schema, or user interface result in a change to the leading digit of the version number. Data updates (e.g., ZIP Codes and terrain) result in a change to the second digit of the version number. Code corrections or updates made after the initial submission of the model to the FCHLPM result in a third digit being added to the version number.

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CI-7 Hurricane Model Security The modeling organization shall have implemented and fully documented security procedures for: (1) secure access to individual computers where the software components or data can be created or modified, (2) secure operation of the hurricane model by clients, if relevant, to ensure that the correct software operation cannot be compromised, (3) anti-virus software installation for all machines where all components and data are being accessed, and (4) secure access to documentation, software, and data in the event of a catastrophe. ARA’s policy for model revision includes security procedures for accessing code, data, and documentation. These procedures are in accordance with standard industry practices. ARA corporate policy requires all company computers to run ESET NOD32 anti-virus software. Regular backups are performed for all computers on the ARA network and include offsite storage of backup tapes. Clients will only have access to the licensable version the model, which checks imported portfolio data for reasonable input values. It is the responsibility of the client to ensure that the portfolio data are correct. Clients will not have direct access to any of the model data, such as the terrain or wind hazard databases. 1. Describe methods used to ensure the security and integrity of the code, data, and documentation. Modifications to the code, data, and documentation can only be checked into the revision control system by authorized, in-house developers. Baseline tests are always run to ensure the model is functioning properly and reproducing known results.

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Grossi, P. and Kunreuther, H. (2005), Catastrophe Modeling: a New Approach to Managing Risk, Springer. Hebert, P.J., Jarrell, J.D., and Mayfield, B.M. (1996). “The Deadliest, Costliest, and Most Intense United States Hurricanes of This Century (and Other Frequently Requested Hurricane Facts),” NOAA Technical Memorandum NWS-NHC-31, p. 41. Hebert, P.J., Jarrell, J.D., and Mayfield, B.M. (1997). “The Deadliest, Costliest, and Most Intense United States Hurricanes of This Century (and Other Frequently Requested Hurricane Facts),” NOAA Technical Memorandum NWS-TPC-1, pp. 30. Jain, V.K., Davidson, R., and Rosowsky, D. (2005), “Modeling changes in hurricane risk over time,” Natural Hazards Review, Vol.6, No.2, pp.88-96. Marshall & Swift / Boeckh (MS/B), http://www.msbinfo.com Murray, R.A. (2005), “Hurricane Katrina: implications for the construction industry,” McGraw Hill Construction. Munich Re (2006), “The 1906 Earthquake and Hurricane Katrina,” http://www.munichre.com/ . NAPCOLLC (2006), “The impact of changes to the RMS U.S. hurricane catastrophe model,” http://www.napcollc.com/articles/JuneReviewRMSHurricane.pdf National Association of Home Builders (NAHB) (2005), “Impact of hurricane Katrina on Building Materials and Prices,” http://www.nahb.org (9/2/2005) RSMeans Company (2001), RS Means Building Construction Cost Data, Kinston, MA. Westfall, C. (2006), “Insurers Balance Supply and Demand (Surge),” http://www.kpmginsiders.com (03/17/2006). Computer/Information Standards Object Management Group (2013). Business Process Model and Notation, Version 2.0.2, http://www.omg.org/spec/BPMN

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APPENDIX A - FORMS

Form G-1: General Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1) The hurricane model meets the General Standards (G1 – G5); 2) The disclosures and forms related to the General Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3) My review was completed in accordance with the professional standards and code of ethical conduct for my profession; 4) My review involved ensuring the consistency of the content in all sections of the submission; and 5) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion. Francis M. Lavelle Ph.D., P.E., (Engineering) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019

Signature (response to deficiencies, if any)

3/21/2019

Signature (revisions to submission, if any Date

7/12/2019 Signature (final submission) Date An updated signature and form are required following any modification of the hurricane model and any revision of the original submission. If a signatory differs from the original signatory, provide the printed name and professional credentials for any new signatories. Additional signature lines shall be added as necessary with the following format:

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-2: Meteorological Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1) The hurricane model meets the Meteorological Standards (M1 – M6); 2) The disclosures and forms related to the Meteorological Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3) My review was completed in accordance with the professional standards and code of ethical conduct for my profession; and 4) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion.

Peter J. Vickery Ph.D., P.E., (Engineering Sciences) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019 Signature ( response to deficiencies, if any) Date

3/21/2019 Signature (revision to submission, if any) Date

5/29/2019 Signature (final submission) Date An updated signature and form are required following any modification of the hurricane model and any revision of the original submission. If a signatory differs from the original signatory, provide the printed name and professional credentials for any new signatories. Additional signature lines shall be added as necessary with the following format:

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-3: Statistical Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1. The model meets the Statistical Standards (S1 – S6); 2. The disclosures and forms related to the Statistical Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3. My review was completed in accordance with the professional standards and code of ethical conduct for my profession; and 4. In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion.

Marshall B. Hardy M.S. (Statistics) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019 Signature (response to deficiencies, if any) Date

3/21/2019 Date Signature (revision to submission, if any)

5/29/2019 Date Signature (final submission)

An updated signature and form are required following any modification of the hurricane model and any revision of the original submission. If a signatory differs from the original signatory, provide the printed name and professional credentials for any new signatories. Additional signature lines shall be added as necessary with the following format:

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-4: Vulnerability Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1) The hurricane model meets the Vulnerability Standards (V1 – V3); 2) The disclosures and forms related to the Vulnerability Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3) My review was completed in accordance with the professional standards and code of ethical conduct for my profession; and 4) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion. Peter J. Vickery Ph.D., P.E., (Engineering Sciences) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019 Signature (response to deficiencies, if any) Date

3/21/2019 Signature (revisions to submission, if any) Date

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-5: Actuarial Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1) The hurricane model meets the Actuarial Standards (A-1 – A-6); 2) The disclosures and forms related to the Actuarial Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3) My review was completed in accordance with the Actuarial Standards of Practice and Code of Conduct; and 4) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion.

Signature (original submission) Date

1/21/2019 Signature (response to deficiencies, if any) Date

Signature (revisions to submission, if any) Date

Signature (final submission) Date An updated signature and form are required following any modification of the hurricane model and any revision of the original submission. If a signatory differs from the original signatory, provide the printed name and professional credentials for any new signatories. Additional signature lines shall be added as necessary with the following format:

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-6: Computer/Information Standards Expert Certification

I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the 2017 Hurricane Standards adopted by the Florida Commission on Hurricane Loss Projection Methodology and hereby certify that: 1) The hurricane model meets the Computer/Information Standards (CI1 – CI7); 2) The disclosures and forms related to the Computer/Information Standards section are editorially and technically accurate, reliable, unbiased, and complete; 3) My review was completed in accordance with the professional standards and code of ethical conduct for my profession; and 4) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion. Francis M. Lavelle Ph.D., P.E., (Engineering) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019 Signature (revision to submission)

3/22/2019 Signature (response to deficiencies, if any) Date

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form G-7: Editorial Certification I hereby certify that I have reviewed the current submission of HurLoss Version 9.0 (Name of Hurricane Model) for compliance with the “Process for Determining the Acceptability of a Computer Simulation Hurricane Model” adopted by the Florida Commission on Hurricane Loss Projection Methodology in its Hurricane Standards Report of Activities as of November 1, 2017, and hereby certify that: 1) The hurricane model submission is in compliance with the Notification Requirements and General Standard G-5 (Editorial Compliance); 2) The disclosures and forms related to each hurricane standards section are editorially accurate and contain complete information and any changes that have been made to the submission during the review process have been reviewed for completeness, grammatical correctness, and typographical errors; 3) There are no incomplete responses, charts or graphs, inaccurate citations, or extraneous text or references; 4) The current version of the hurricane model submission has been reviewed for grammatical correctness, typographical errors, completeness, the exclusion of extraneous data/ information and is otherwise acceptable for publication; and 5) In expressing my opinion I have not been influenced by any other party in order to bias or prejudice my opinion. Lisa West B.S. (Technical Editing) Name Professional Credentials (area of expertise)

11/5/2018 Signature (original submission) Date

1/21/2019 Signature (response to deficiencies, if any)

3/21/2019 Signature (revisions to submission, if any) Date

Signature (revision to submission) Date NOTE: A facsimile or any properly reproduced signature will be acceptable to meet this requirement.

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Form M-1: Annual Occurrence Rates A. Provide a table of annual occurrence rates for hurricane landfall from the data set defined by marine exposure that the hurricane model generates by hurricane category (defined by maximum windspeed at hurricane landfall in the Saffir-Simpson Hurricane Wind Scale) for the entire state of Florida and additional regions as defined in Figure 31. List the annual occurrence rate per hurricane category. Annual occurrence rates shall be rounded to two decimal places. The historical frequencies below have been derived from the Base Hurricane Storm Set. If modeling organization Base Hurricane Storm Set differs from that defined in Standard M-1. Base Hurricane Storm Set (for example, using a different historical period), the historical rates in the table shall be edited to reflect this difference (see below). As defined, a by-passing hurricane is a hurricane which does not make landfall, but produces minimum damaging windspeeds or greater on land in Florida. For the by- passing hurricanes included in the table only, the hurricane intensity enetered is the maximum windspeed at closest approach to Florida as a hurricane, not the windspeed over Florida. B. Describe hurricane model variations from the historical frequencies. C. Provide vertical bar graphs depicting distributions of hurricane frequencies by category by region of Florida (Figure 31), for the neighboring states of Alabama/Mississippi and Georgia, and for by-passing hurricanes. For the neighboring states, statistics based on the closest coastal segment to the state boundaries used in the hurricane model are adequate. D. If the data are partitioned or modified, provide the historical annual occurrence rates for the applicable partition (and its complement) or modification as well as the modeled annual occurrence rates in additional copies of Form M-1, Annual Occurrence Rates. E. List all hurricanes added, removed, or modified from the previously accepted hurricane model version of the Base Hurricane Storm Set. F. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form M-1, Annual Occurrence Rates, in a submission appendix.

Note: Except where specified, Number of Hurricanes does not include By-Passing Hurricanes. Each time a hurricane goes from water to land (once per region) it is counted as a hurricane landfall in that region. However, each hurricane is counted only once in the Entire State totals. Hurricanes recorded for neighboring states need not have reported damaging winds in Florida.

Form M-1, Annual Occurrence Rates, Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), From A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), and Form S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year, are based on the 117-year period 1900- 2016 (consistent with Standard M-1, Base Hurricane Storm Set). It is intended that the storm set underlying Forms M-1, Annual Occurrence Rates, Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), Form A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), and S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year, will be the same.

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As specified in Standard M-1, Base Hurricane Storm Set, the modeling organization may exclude hurricanes that caused zero modeled damage, or include additional complete hurricane seasons, or may modify data for historical storms based on evidence in current scientific and technical literature. This may result in the modeling organization including additional hurricane landfalls in Florida and neighboring states to those listed in Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), and Form A- 2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data) for Florida or counted in Form M-1, Annual Occurrence Rates, in the case of neighboring states. In this situation, the historical numbers in Form M-1, Annual Occurrence Rates, should be updated to agree with the modeling organization Base Hurricane Storm Set.

Any additional Florida hurricanes should be included in Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), Form A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), as instructed there, and the historical hurricane landfall counts in Form S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year, should be updated.

In some circumstances, the modeling organization windfield reconstruction of a historical storm may indicate that it is a by-passing hurricane (the modeling organization windfield results in damaging winds somewhere in the state). In this situation, the historical numbers in Form M- 1, Annual Occurrence Rates, should be updated to agree with the modeling organization Base Hurricane Storm Set, but no changes are required for Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), Form A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), or Form S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year. A. Annual occurrence rates generated by the model are provided in Form M-1. B. Modeled probabilities of landfalling hurricanes by region are consistent with the limited observed (or historical) data. Figure 32 presents comparisons of modeled and observed landfall counts of hurricanes as a function of Saffir-Simpson category, as defined by windspeed. The agreement between the modeled and historical rates of landfalling storms as a function of intensity and region is reasonable, with the differences between historical and modeled results falling well within the range of uncertainty associated with the limited number of historical observations of landfalling hurricanes. The intensities of historical storms and the landfall region have been obtained directly from the data given in the Form M-1. C. See Figure 32. D. The data are not partitioned or modified. E. The hurricanes that have been added to reflect the May 2018 release of HURDAT2 are Hurricanes Irma and Nate in 2017, as well as Hurricane Hermine from 2016. F. See Form M-1.

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Table 3. Annual Occurrence Rates

Entire State Region A - NW Florida Historical Modeled Historical Modeled CategoryNumber Rate Number Rate Number Rate Number Rate 1 260.22230.19160.14110.09 2 140.12140.124 0.034 0.03 3 150.13120.106 0.052 0.02 4 11 0.09 5 0.05 0 0.00 1 0.00 5 2 0.02 1 0.01 0 0.00 0 0.00

Region B - SW Florida Region C - SE Florida Historical Modeled Historical Modeled CategoryNumber Rate Number Rate Number Rate Number Rate 1 8 0.07 5 0.04 6 0.05 7 0.06 2 3 0.03 4 0.03 6 0.05 6 0.05 3 5 0.04 4 0.04 5 0.04 5 0.04 4 5 0.04 2 0.02 6 0.05 3 0.02 5 0 0.00 1 0.00 2 0.02 1 0.01

Region D - NE Florida Florida By-Passing Hurricanes Historical Modeled Historical Modeled CategoryNumber Rate Number Rate Number Rate Number Rate 1 1 0.01 2 0.02 1 0.01 6 0.05 2 2 0.02 1 0.01 1 0.01 3 0.03 3 0 0.00 0 0.00 3 0.03 3 0.02 400.0000.000010.01 500.0000.000000.00

Region E - Georgia Region F - Alabama/Mississippi Historical Modeled Historical Modeled CategoryNumber Rate Number Rate Number Rate Number Rate 1 1 0.01 2 0.01 7 0.06 6 0.05 2 1 0.01 1 0.01 2 0.02 3 0.03 3 0 0.00 0 0.00 4 0.03 3 0.02 4 0 0.00 0 0.00 1 0.01 1 0.01 5 0 0.00 0 0.00 1 0.01 0 0.00

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(Northeast)

(Northwest) 80.53 W 28.45 N

Note: Lake Okeechobee 26.9714N80.875W Figure 31. State of Florida and Neighboring States By Region

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Region F - Alabama/Mississippi Region A - NW Florida 0.12 0.16 0.10 0.14 Modeled 0.12 Modeled 0.08 Historical 0.10 Historical 0.06 0.08 0.04 0.06 0.04 0.02 0.02 Annual FrequencyAnnual Annual FrequencyAnnual 0.00 0.00 12345 12345 Hurricane Category Hurricane Category

Region B - SW Florida Region C - SE Florida 0.12 0.12 0.10 0.10 Modeled Modeled 0.08 0.08 Historical Historical 0.06 0.06 0.04 0.04 0.02 0.02 Annual FrequencyAnnual Annual Frequency Annual 0.00 0.00 12345 12345 Hurricane Category Hurricane Category

Region D - NE Florida Region E - Georgia 0.12 0.12 0.10 0.10 Modeled Modeled 0.08 0.08 Historical Historical 0.06 0.06 0.04 0.04 0.02 0.02 Annual Frequency Annual Annual Frequency Annual 0.00 0.00 12345 12345 Hurricane Category Hurricane Category

Figure 32. Comparison of Modeled and Observed Landfalling Counts of Hurricanes by Category (defined by windspeed) and Region

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Form M-2: Maps of Maximum Winds A. Provide color-coded contour plots on maps with ZIP Code boundaries of the maximum winds for the modeled version of the Base Hurricane Storm Set for land use set for open terrain and for land use set for actual terrain. Plot the position and values of the maximum windspeeds on each contour map. B. Provide color-coded contour plots on maps with ZIP Code boundaries of the maximum winds for a 100-year and a 250-year return period from the stochastic storm set for land use set for open terrain and for land use set for actual terrain. Plot the position and values of te maximum windspeeds on each contour map. Actual terrain is the roughness distribution used in the standard version of the hurricane model as defined by the modeling organization. Open terrain uses the same roughness length of 0.03 meters at all land points. Maximum winds in these maps are defined as the maximum one-minute sustained winds over the terrain as modeled and recorded at each location. The same color scheme and increments shall be used for all maps. Use the following eight isotach values and interval color coding:

(1) Minimum damaging Blue (2) 50 mph Medium Blue (3) 65 mph Light Blue (4) 80 mph White (5) 95 mph Light Red (6) 110 mph Medium Red (7) 125 mph Red (8) 140 mph Magenta Contouring in addition to these isotach values may be included. C. Include Form M-2, Maps of Maximum Winds, in a submission appendix.

A. Figure 33 shows the maximum windspeeds (one-minute sustained at a height of 10 m in both open and local terrains, at the ZIP-Code centroid) for the historical storm set. If central pressure data is given in HURDAT, the central pressure as a function of time after landfall uses the HURDAT data. If central pressure data is not given in HURDAT, the central pressure after landfall is modeled using the filling models given in Vickery (2005), whereas the central pressure at or before landfall is estimated using the windspeed given in HURDAT. If available, the radius to maximum winds is modeled using information obtained from NWS-38 or the Hurricane Research Division of NOAA. If no radius to maximum wind data is available, then Rmax is modeled using the mean of the regression models used in the stochastic storm modeling. Windspeeds data are given for both and open terrain conditions (upper map) and local (actual) terrain (lower map).

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B. Figure 34 and Figure 35 present the maximum sustained windspeeds for return periods of 100- and 250 years from the stochastic storm set. The upper map in each figure presents results for open terrain conditions and the lower map presents results for actual terrain conditions.

C. The maximum windspeeds plotted in Figure 33 (modeled historical windspeeds) are 155 mph in open terrain and 107 mph in actual terrain. The maximum 100-year return period windspeeds plotted in Figure 34 are 119 mph in open terrain and 93 mph in actual terrain. The maximum 250-year return period windspeeds plotted in Figure 35 are 134 mph in open terrain and 102 mph in actual terrain.

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Figure 33. Maximum One-Minute Sustained Windspeed at a Height of 10 m in Open Terrain (upper map) and Local Terrain (lower map) Derived from the Historical Storm Set

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Figure 34. 100-Year Return Period Sustained Windspeeds at a Height of 10 m Above Ground in Open Terrain (upper plot) and Local Terrain (lower plot)

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Figure 35. 250-Year Return Period Sustained Windspeeds at a Height of 10 m Above Ground in Open Terrain (upper plot) and Local Terrain (lower plot)

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Form M-3: Radius of Maximum Winds and Radii of Standard Wind Thresholds A. For the central pressures in the table below, provide the first quartile (1Q), median (2Q), and third quartile (3Q) values for (1) the radius of maximum winds (Rmax) used by the hurricane model to create the stochastic storm set, and the first quartile (1Q), median (2Q), and third quartile (3Q) values for the outer radii of (2) Category 3 winds (>110 mph), (3) Category 1 winds (>73 mph), and (4) gale force winds (>40 mph). B. Describe the procedure used to complete this form. C. Identify the other variables that influence Rmax. D. Sepcify any truncations applied to Rmax distrubutions in the hurricane model, and if and how these truncations vary with other variables. E. Provide a box plot and histogram of Central Pressure (x-axis) versus Rmax (y-axis) to demonstrate relative populations and continuity of sampled hurricanes in the stochastic storm set. F. Provide this form in Excel using the format given in the file named “2017FormM3.xlsx.” The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form M-3, Radius of Maximum Winds and Radii of Standard Wind Thresholds, in a submission appendix.

A. The ranges provided are the results of simulations performed using the statistical models for Rmax and the Holland pressure profile parameter described earlier. For each central pressure value given in the table (far field pressure = 1013 mbar in all cases), 1000 examples of Florida landfalling storms were extracted from the stochastic storm set. Using the values of B, Rmax, central pressures, and translation speed associated with each of the 1000 example hurricanes, we compute the range (distance from the storm center) to the indicated windspeed. The central pressures associated with the 100 hurricanes are centered on the indicated value, within a range of 5 mb. The range to the indicated windspeed was obtained by computing the maximum windspeed over the full azimuth range of 360 degrees in 10-degree increments. The radii were increased at increments of 0.05 Rmax until the maximum computed windspeed reduced below the target windspeed. From

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each of the 1000 simulations we provide minimum and maximum values resulting from the 1000 simulations. B. The radius to maximum winds is a function of central pressure and latitude. The functional form of the relationship between Rmax and both latitude and central pressures is described in M-2. C. A graphical representation of 5,000 landfalling storm examples is given in Figure 36. Black boxes represent data points more than 1.5 but less than 3 times the inter quartile range higher than the third quartile. Red boxes represent data points more than 3 times the inter quartile range higher than the third quartile. Figure 37 presents histograms showing the relative frequency of pressures and radius to maximum winds for Florida landfalling hurricanes, computed using the model results from a 300,000 year simulation. D. An electronic copy of Form M-3 is given in the file ARA17FormM3.xls. Form M-3 presents radii data from 100 randomly chosen landfalling storms in each of 10 central pressure bins.

Figure 36. Simulated Distribution of Rmax vs. Central Pressure Derived from 5,000 Florida Landfalling Model Hurricanes

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25%

20%

15% Frequency

10% Relative 5%

Central Pressure (mbar)

40%

35%

30%

25%

Frequency 20%

15%

Relative 10%

0% < 10 10‐20 20‐30 30‐40 40‐50 50‐60 60‐70 70‐80 80‐90 >90 Radius to Maximum Winds (miles)

Figure 37. Histograms of Central Pressure (upper plot) and Radius to Maximum Winds (lower plot) for all Model Florida Landfalling Hurricanes

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Form S-1: Probability and Frequency of Florida Landfalling Hurricanes per Year A. Complete the table below showing the probability and modeled frequency of landfalling Florida hurricanes per year. Modeled probability shall be rounded to three decimal places. The historical probabilities and frequencies below have been derived from the Base Hurricane Storm Set for the 117 year period 1900-2016 (as given in Form A-2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Hurricane Exposure Data)). Exclusion of hurricanes that caused zero modeled Florida damage or additional Florida hurricane landfalls included in the modeling organization Base Hurricane Storm Set as identified in their response to Standard M-1, Base Hurricane Storm Set, should be used to adjust the historical probabilities and frequencies provided. B. If the data are partitioned or modified, provide the historical probabilities and frequencies for the applicable partition (and its complement) or modification as well as the modeled probabilities and frequencies in additional copies of Form S-1, Probability and Frequency of Florida Hurricanes per Year). C. Include Form S-1, Probability and Frequency of Florida Landfalling Hurricanes per Year, in a submission appendix. Hurricane Model Results Probability of Florida Landfalling Hurricanes per Year (Historical Data for 1900-2017) Number of Historical Modeled Historical Modeled Hurricanes Per Probability Probability Frequency Frequency Year

0 0.6017 0.6326 71 75 1 0.2458 0.2823 29 33 2 0.1271 0.0695 15 8 3 0.0254 0.0132 3 2 4 0.0000 0.0020 0 0 5 0.0000 0.0003 0 0 6 0.0000 0.0000 0 0 7 0.0000 0.0000 0 0 8 0.0000 0.0000 0 0 9 0.0000 0.0000 0 0 10 or more 0.0000 0.0000 0 0

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Form S-2A: Examples of Hurricane Loss Exceedance Estimates (2012 FHCF Exposure Data) A. Provide estimates of the annual aggregate combined personal and commercial insured hurricane losses for various probability levels using the notional risk data set specified in Form A-1, Zero Deductible Personal Residential Hurricane Loss Costs by ZIP Code, and using the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data provided in the file named “hlpm2012c.exe.” Provide the total average annual hurricane loss for the hurricane loss exceedance distribution. If the modeling methodology does not allow the hurricane model to produce a viable answer, state so and why. B. Include Form S-2A, Examples of Hurricane Loss Exceedance Estimates (2012 FHCF Exposure Data), in a submission appendix. Part A Estimated Personal and Estimated Hurricane Return Period Annual Probability Commercial Residential Loss Notional Risk (years) of Exceedance Hurricane Loss 2012 FHCF Dataset Dataset Top Event N/A 73,519,404 307,959,953,615 10,000 0.01% 42,396,590 204,844,799,790 5,000 0.02% 38,911,627 180,424,260,143 2,000 0.05% 33,635,536 153,436,844,558 1,000 0.10% 29,132,490 131,972,613,651 500 0.20% 25,341,225 112,782,878,416 250 0.40% 21,510,714 93,337,223,070 100 1.00% 16,308,521 69,626,821,554 50 2.00% 12,510,166 51,995,408,800 20 5.00% 7,519,469 30,735,994,214 10 10.00% 4,125,782 16,528,960,600 5 20.00% 1,415,340 5,065,828,116 Part B Mean (Total Average Annual Hurricane Loss) 1,298,304 5,239,249,018 Median 24,006 81,666,655 Standard Deviation 3,275,379 13,964,899,959 Interquartile Range 808,501 2,657,282,959 Sample Size 250,000 years 250,000 years

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Form S-2B: Examples of Hurricane Loss Exceedance Estimates (2017 FHCF Exposure Data) A. Provide estimates of the annual aggregate combined personal and commercial insured hurricane losses for various probability levels using the notional risk data set specified in Form A-1, Zero Deductible Personal Residential Hurricane Loss Costs by ZIP Code, and using the 2017 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data provided in the file named “hlpm2017c.exe.” Provide the total average annual hurricane loss for the hurricane loss exceedance distribution. If the modeling methodology does not allow the hurricane model to produce a viable answer, state so and why. B. Include Form S-2A, Examples of Hurricane Loss Exceedance Estimates (2017 FHCF Exposure Data), in a submission appendix. Part A Estimated Personal and Estimated Hurricane Return Period Annual Probability Commercial Residential Loss Notional Risk (years) of Exceedance Hurricane Loss 2017 FHCF Dataset Dataset Top Event N/A 73,519,404 317,745,808,230 10,000 0.01% 42,396,590 189,550,911,307 5,000 0.02% 38,911,627 171,891,576,018 2,000 0.05% 33,635,536 145,415,421,034 1,000 0.10% 29,132,490 124,978,922,848 500 0.20% 25,341,225 106,432,677,406 250 0.40% 21,510,714 88,873,537,707 100 1.00% 16,308,521 66,575,034,048 50 2.00% 12,510,166 50,155,680,871 20 5.00% 7,519,469 30,017,194,198 10 10.00% 4,125,782 16,237,022,359 5 20.00% 1,415,340 4,988,953,981 Part B Mean (Total Average Annual Hurricane Loss) 1,298,304 5,098,292,548 Median 24,006 82,874,617 Standard Deviation 3,275,379 13,436,993,433 Interquartile Range 808,501 2,599,603,543 Sample Size 250,000 years 250,000 years

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Form S-3: Distributions of Stochastic Hurricane Parameters A. Provide the probability distribution functional form used for each stochastic hurricane parameter in the hurricane model. Provide a summary of the justification for each functional form selected for each general classification. B. Include Form S-3, Distributions of Stochastic Hurricane Parameters, in a submission appendix.

Stochastic Hurricane Year Parameter Functional Form of Justification for Data Source Range (Function or Distribution Functional Form Used Variable) Fits to historical Occurrence Rate(2) Polya HURDAT 1886-2017 data Regression model with HURDAT, Blake et Fits to historical Relative Intensity (1) residuals fit to bi-normal al. (2007 with NHC 1886-2007 data distributions Updates Regression model with Fits to historical Translation Speed(1) residuals fit to bi-normal HURDAT 1886-2007 data distributions Normally distributed Radius to Maximum Flight Level Data, 1977-2001 residual errors in log Best fit to data Winds (1) H*Wind Analyses 1988-2005 space Regression model with Fits to historical Heading(1) residuals fit to bi-normal HURDAT 1886-2007 data distributions Normally distributed 1977-2001 Holland B(1) Flight Level Data Best fit to data errors in linear space 1988-2005 (1) Dates of data used to develop hurricane track and intensity model. (2) Dates of data used to initiate storms in the current model. Figure 38 presents a comparison of the distribution of the historical and modeled basin-wide occurrence rate and the p-values for various statistical tests. Figure 39 presents coastal segments used to compare modeled and historical hurricane parameters. Figure 40 through Figure 44 presents comparisons of modeled and historical translation speeds, headings, occurrence rates, and central pressures along the coastal segments given in Figure 39. P-values associated with various statistical tests for equivalence are presented in the figures. Figure 45 through Figure 49 presents the same information given in Figure 40 through Figure 44, except the comparisons are given for the four Florida landfall regions rather than the coastal segments. Figure 50 presents comparisons of the key hurricane parameters on a statewide basis. Figure 51 presents comparisons of modeled and historical values of B and RMW at landfall along the coast of Florida and adjacent states.

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CDF

Figure 38. Modeled and Historical Basin Wide Storm Frequencies

Figure 39. Locations of Coastal Segments Used to Compare Modeled and Historical Properties of Hurricanes at Landfall

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Figure 40. Comparisons of Modeled and Observed Translation Speed at Landfall for Segments Along the Florida Coast Line

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Figure 41. Comparisons of Modeled and Observed Storm Headings at Landfall for Segments Along the Florida Coast Line

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Figure 42. Comparisons of Modeled and Observed Landfall Rate for Segments Along the Florida Coast Line

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Figure 43. Comparisons of Modeled and Observed Landfall Central Pressures for Segments along the Florida Coast Line

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Figure 44. Comparisons of Modeled and Observed Landfall Central Pressures for Segments along the Florida Coast Line Plotted as a function of Return Period

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Figure 45. Comparisons of Modeled and Observed Translation Speed at Landfall Along the Coasts of the Four Florida Regions

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Figure 46. Comparisons of Modeled and Observed Storm Heading at Landfall Along the Coasts of the Four Florida Regions

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Figure 47. Comparisons of Modeled and Observed Landfall Rates Along the Coasts of the Four Florida Regions

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Figure 48. Comparisons of Modeled and Observed Distributions of Landfall Central Pressure Along the Coasts of the Four Florida Regions

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Figure 49. Comparisons of Modeled and Observed Distributions of Landfall Central Pressure Plotted as a Function of Return Period Along the Coasts of the Four Florida Regions

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Figure 50. Comparisons of Modeled and Observed Distributions of Translation Speed, Heading, Landfall Rates, and Central Pressure Plotted vs. Return Period for the Entire Florida Coastline

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Figure 51. Comparisons of Modeled and Historical Values of B (left) and RMW (right) Along the Coast of Florida and Adjoining States

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Form S-4: Validation Comparisons A. Provide five validation comparisons of actual personal residential exposures and hurricane loss to modeled exposures and hurricane loss. Provide these comparisons by line of insurance, construction type, policy coverage, county or other level of similar detail in addition to total hurricane losses. Include hurricane loss as a percent of total exposure. Total exposure represents the total amount of insured values (all coverages combined) in the area affected by the hurricane. This would include exposures for policies that did not have a hurricane loss. If this is not available, use exposures for only those policies that had a hurricane loss. Specify which was used. Also, specify the name of the hurricane event compared. B. Provide a validation comparison of actual commercial residential exposures and hurricane loss to modeled exposures and hurricane loss. Use and provide a definition of the model’s relevant commercial residential classifications. C. Provide scatter plot(s) of modeled versus historical hurricane losses for each of the required validation comparisons. (Plot the historical hurricane losses on the x-axis and the modeled hurricane losses on the y-axis.) D. Include Form S-4, Validation Comparisons, in a submission appendix. Rather than using a specific published hurricane windfield directly, the winds underlying the modeled hurricane loss cost calculations must be produced by the hurricane model being evaluated and should be the same hurricane parameters as used in completing Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data) and Form A- 2B, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data).

Example Formats for Personal Residential: Hurricane = Exposure = Specify total exposure or hurricane loss only

Company Actual Modeled Hurricane Loss / Construction Hurricane Loss / Difference Exposure Exposure Wood Frame Masonry Other (specify) Total Hurricane = Exposure = Specify total exposure or hurricane loss only

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Company Actual Modeled Hurricane Loss / Coverage Hurricane Loss / Difference Exposure Exposure A B C D Total

Example Format for Commercial Residential:

Hurricane = Exposure = Specify total exposure or hurricane loss only

Company Actual Modeled Hurricane Loss / Construction Hurricane Loss / Difference Exposure Exposure

Total Five validation personal residential comparisons and two commercial residential comparisons are provided on the following pages. In each case, the exposure includes all ZIP Codes with a loss. Scatter plots of the results are shown in Figure 52. The modeled losses in the validation cases do not include demand surge.

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A. Personal Residential Comparisons

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B. Commercial Residential Comparisons

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Total Losses by County ‐ Hurricane Charley Total Losses by Construction Type ‐ Hurricane Andrew 0.12 0.35

0.30 0.10

0.25 0.08 0.20 0.06 Ratio Ratio

0.15

Loss

Loss 0.04 0.10 Model Model 0.02 0.05

0.00 0.00 0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Actual Loss Ratio Actual Loss Ratio

Total Losses by Coverage ‐ Hurricane Andrew Total Losses by Storm and Company 0.25 0.25

0.20 0.20

0.15 0.15 Ratio Ratio

0.10 0.10 Loss Loss

0.05 0.05 Model Model

0.00 0.00 0.00 0.05 0.10 0.15 0.20 0.25 0.00 0.05 0.10 0.15 0.20 0.25 Actual Loss Ratio Actual Loss Ratio

Total Losses Line of Business‐ Hurricane Andrew 0.25

0.20

0.15 Ratio 0.10 Loss

0.05 Model

0.00 0.00 0.05 0.10 0.15 0.20 0.25 Actual Loss Ratio

(Part A: Personal Residential) Figure 52. Validation Comparisons

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Total Losses by Storm 0.020

0.015 Ratio

Loss

0.010 Modeled

0.005

0.000 0.000 0.005 0.010 0.015 0.020 Actual Loss Ratio

Total Losses by Construction ‐ Hurricane Wilma 0.030

0.025

0.020 Ratio

Loss

0.015

Modeled 0.010

0.005

0.000 0.000 0.005 0.010 0.015 0.020 0.025 0.030 Actual Loss Ratio

(Part B: Commercial Residential)

Figure 52. Validation Comparisons (continued)

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Form S-5: Average Annual Zero Deductible Statewide Hurricane Loss Costs – Historical versus Modeled A. Provide the average annual zero deductible statewide personal and commercial residential hurricane loss costs produced using the list of hurricanes in the Base Hurricane Storm Set as defined in Standard M-1, Base Hurricane Storm Set based on the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential exposure data found in the file named “hlpm2012c.exe.” Average Annual Zero Deductible Statewide Personal and Commercial Residential Hurricane Loss Costs (2012 FHCF Exposure Data) Historical Produced by Time Period Hurricanes Hurricane Model Current Submission (9.0) $4.14B $5.24B Previously Accepted Hurricane Model* (8.0.a) $4.78B $6.00B (2015 Standards) Percent Change Current Submission/ -13.4% -12.7% Previously Accepted Hurricane Model* Second Previously Accepted Hurricane Model* $5.22B $5.95B (2013 Standards) Percent change Current Submission/Second -20.7% -11.9% Previously-Accepted Hurricane Model* *NA if no previously accepted model. B. Provide a comparison with the statewide personal and commercial residential hurricane loss costs produced by the hurricane model on an average industry basis. C. Provide the 95% confidence interval on the differences between the mean of the historical and modeled personal and commercial residential hurricane loss costs. The 95% confidence interval on the difference between the mean of the historical loss and the mean of the modeled loss is -$3.05B to +$0.85B. D. Provide the average annual zero deductible statewide personal and commercial residential hurricane loss costs produced using the list of hurricanes in the Base Hurricane Storm Set as defined in Standard M-1, Base Hurricane Storm Set, based on the 2017 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2017c.exe.” Average Annual Zero Deductible Statewide Personal and Commercial Residential Hurricane Loss Costs (2017 FHCF Exposure Data) Time Period Historical Hurricanes Produced by Hurricane Model Current Submission $4.05B $5.10B

E. Provide a comparison with the statewide personal and commercial residential hurricane loss costs produced by the hurricane model on an average industry basis. F. Provide the 95% confidence interval on the differences between the means of the historical and modeled personal and commercial residential hurricane loss costs.

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The 95% confidence interval on the difference between the mean of the historical loss and the mean of the modeled loss is -$2.94B to +$0.83B. G. If the data are partitioned or modified, provide the average annual zero deductible statewide personal and commercial residential hurricane loss costs for the applicable partition (and its complement) or modification as well as the modeled average annual zero deductible statewide personal and commercial residential hurricane loss costs in additional copies of Form S-5, Average Annual Zero Deductible Hurricane Loss Costs – Historical versus Modeled. Not applicable. H. Include Form S-5, Average Annual Zero Deductible Statewide Hurricane Loss Costs – Historical versus Modeled, in a submission appendix.

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Form V-1: One Hypothetical Event A. Windspeeds for 96 ZIP Codes and sample personal and commercial residential exposure data are provided in the file named “FormV1Input15.xlsx.” The windspeeds and ZIP Codes represent a hypothetical hurricane track. Model the sample personal and commercial residential exposure data provided in the file against these windspeeds at the specified ZIP Codes and provide the damage ratios summarized by windspeed (mph) and construction type. The windspeeds provided are one-minute sustained 10-meter windspeeds. The sample personal and commercial residential exposure data provided consists of four structures (one of each construction type – wood frame, masonry, manufactured home, and concrete) individually placed at the population centroid of each of the ZIP Codes provided. Each ZIP Code is subjected to a specific windspeed. For completing Part A, Estimated Damage for each individual windspeed range is the sum of ground up hurricane loss to all structures in the ZIP Codes subjected to that individual windspeed range, excluding demand surge and storm surge. Subject Exposure is all exposures in the ZIP Codes subjected to that individual windspeed range. For completing Part B, Estimated Damage is the sum of the ground up hurricane loss to all structures of a specific type (wood frame, masonry, manufactured home, or concrete) in all of the windspeed ranges, excluding demand surge and storm surge. Subject Exposure is all exposures of that specific type in all of the ZIP Codes. One reference structure for each of the construction types shall be placed at the population centroid of the ZIP Codes. Do not include contents, appurtenant structures, or time element coverages. Reference Frame Structure Reference Masonry Structure  One story  One story  Unbraced gable end roof  Unbraced gable end roof  ASTM D3161 Class D or  ASTM D3161 Class D or  ASTM D7158 Class D shingles  ASTM D7158 Class D shingles  ½” plywood deck  ½” plywood deck  6d nails, deck to roof members  6d nails, deck to roof members  Toe nail truss to wall anchor  Weak truss to wall connection  Wood framed exterior walls  Masonry exterior walls  5/8” diameter anchors at 48” centers for  No vertical wall reinforcing wall/floor/foundation connections  No shutters  No shutters  Standard glass windows  Standard glass windows  No door covers  No door covers  No skylight covers  No skylight covers  Constructed in 1995  Constructed in 1995 Reference Manufactured Home Structure Reference Concrete Structure  Tie downs  Twenty story  Single unit  Eight apartment units per story  Manufactured in 1980  No shutters  Standard glass windows  Constructed in 1980 B. Confirm that the structures used in completing the form are identical to those in the above table for the reference structures. If additional assumptions are necessary to

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complete this form (for example, regarding structural characteristics, duration or surface roughness), provide the reasons why the assumptions were necessary as well as a detailed description of how they were included. The structures used in completing Form V-1 are identical to those in the above table. Windspeeds are assumed to be representative of sustained winds at a height of 10 m in open terrain. No additional assumptions were required. Demand surge is not included in the estimated damages. C. Provide a plot of the Estimated Damage/Subject Exposure (y-axis) versus Windspeed (x- axis) Part A data. Figure 53. D. Include Form V-1, One Hypothetical Event, in a submission appendix. Part A Windspeed (mph, one-minute Estimated sustained 10-meter) Damage/Subject Exposure 41 – 50 0.07% 51 – 60 0.17% 61 – 70 1.22% 71 – 80 2.69% 81 – 90 6.06% 91 – 100 12.81% 101 – 110 19.15% 111 – 120 44.00% 121 – 130 59.83% 131 – 140 71.32% 141 – 150 83.98% 151 – 160 88.82% 161 – 170 91.43% Part B Estimated Construction Type Damage/Subject Exposure Wood Frame 32.27% Masonry 32.24% Manufactured Home 38.80% Concrete 19.67%

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100% 90% 80% 70% 60% 50% 40% 30% 20%

Total Loss / Subject Exposure / Loss Total 10% 0% 41-50 51-60 61-70 71-80 81-90 91-100 101-110 111-120 121-130 131-140 141-150 151-160 161-170 Sustained Wind Speed (mph)

Figure 53. Losses vs. Windspeed for Form V-1, Part A

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Form V-2: Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage A. Provide the change in the zero deductible personal residential reference building damage ratio (not hurricane loss cost) for each individual hurricane mitigation measure and secondary characteristic listed in Form V-2, Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage, as well as for the combination of the four hurricane mitigation measures and secondary characteristics provided for the Mitigated Frame Building and the Mitigated Masonry Building below. B. If additional assumptions are necessary to complete this form (for example, regarding duration or surface roughness), provide the rationale for the assumptions as well as a detailed description of how they are included. C. Provide this form in Excel format without truncation. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form V-2, Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage, in a submission appendix.

Reference Frame Building Reference Masonry Building  One story  One story  Unbraced gable end roof  Unbraced gable end roof  ASTM D3161 Class D or  ASTM D3161 Class D or  ASTM D7158 Class D shingles  ASTM D7158 Class D shingles  ½” plywood deck  ½” plywood deck  6d nails, deck to roof members  6d nails, deck to roof members  Toe nail truss to wall anchor  Weak truss to wall connection  Wood framed exterior walls  Masonry exterior walls  5/8” diameter anchors at 48” centers for  No vertical wall reinforcing wall/floor/foundation connections  No shutters  No shutters  Standard glass windows  Standard glass windows  No door covers  No door covers  No skylight covers  No skylight covers  Constructed in 1995  Constructed in 1995 Mitigated Frame Building Mitigated Masonry Building  ASTM D7158 Class H shingles  ASTM D7158 Class H shingles  8d nails, deck to roof members  8d nails, deck to roof members  Truss straps at roof  Truss straps at roof  Structural wood panel shutters  Structural and wood shutters Place the reference building at the population centroid for ZIP Code 33921. A. The changes in expected ground-up building damage rates for mitigated frame and masonry structures are provided in Form V-2. Winds specified are assumed to be one-minute winds in open terrain. B. The surface roughness assumed is the ZIP Code average surface roughness used by the model for the specified ZIP Code. For opening protection, all glazed openings must be protected to the level indicated, For window, door, and skylight strength, no credit is given for individual

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PERCENTAGE CHANGES IN DAMAGE Individual Hurricane ((REFERENCE DAMAGE RATE - MITIGATED DAMAGE RATIO) / Mitigation Measures and REFERENCE DAMAGE RATIO) * 100 Secondary Characteristics FRAME BUILDING MASONRY BUILDING WINDSPEED (MPH)* WINDSPEED (MPH)* 60 85 110 135 160 60 85 110 135 160 REFERENCE BUILDING ------

BRACED GABLE ENDS 0% 3% 2% 0% 0% 0% 3% 2% 0% 0% ROOF RATION CONFIGU- HIP ROOF 43% 15% 52% 20% 1% 42% 17% 53% 15% 0%

METAL 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% ASTM D7158 CLASS H SHINGLES 79% 48% 8% 3% 0% 78% 47% 9% 3% 0% ROOF

COVERING MEMBRANE 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% NAILING OF DECK 8d 3% 6% 13% 5% 0% 4% 7% 14% 4% 0%

CLIPS 5% 2% 22% 3% 0% 4% 2% 22% 2% 0% STRENGTH ROOF-WALL STRAPS 2% 3% 27% 6% 0% 0% 2% 27% 5% 0% R

TIES OR CLIPS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% STRENGTH

WALL- FLOO STRAPS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

LARGER ANCHORS OR CLOSER 0% 0% 0% 0% 0% ------SPACING WALL-

STRENGTH STRAPS 0% 0% 0% 0% 0% ------FOUNDATION VERTICAL REINFORCING ------0% 0% 0% 0% 0% O

STRUCTURAL WINDOW WOOD PANEL 0% 5% 29% 16% 3% 0% 6% 30% 13% 1% SHUTTERS METAL 0% 5% 29% 16% 3% 0% 6% 30% 13% 1% ENGINEERED 0% 7% 41% 22% 4% 0% 8% 42% 16% 1%

OPENING PROTECTI DOOR AND SKYLIGHT COVERS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

WINDOWS IMPACT RATED 0% 7% 41% 22% 4% 0% 8% 42% 16% 1% MEETS WIND- ENTRY BORNE DEBRIS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS REQUIREMENTS MEETS WIND- GARAGE

STRENGTH BORNE DEBRIS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS REQUIREMENTS

WINDOW, DOOR, SKYLIGHT MEETS WIND- SLIDING GLASS BORNE DEBRIS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS REQUIREMENTS SKYLIGHTIMPACT RATED0%0%0%0%0%0%0%0%0%0% PERCENTAGE CHANGES IN DAMAGE ((REFERENCE DAMAGE RATE - MITIGATED DAMAGE RATIO) / HURRICANE MITIGATION MEASURES AND REFERENCE DAMAGE RATIO) * 100 SEC O N D AR Y C H AR AC T ER IST IC S IN FRAME BUILDING MASONRY BUILDING COMBINATION WINDSPEED (MPH)* WINDSPEED (MPH)* 60 85 110 135 160 60 85 110 135 160

MITIGATED BUILDING 77% 60% 66% 64% 34% 77% 61% 68% 62% 26%

*Windspeeds are one‐minute sustained 10‐meter.

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Form V-4: Differences in Hurricane Mitigation Measures and Secondary Characteristics A. Provide the differences between the values reported in Form V-2, Hurricane Mitigation Measures and Secondary Characteristics, Range of Changes in Damage, relative to the equivalent data compiled from the previously-accepted hurricane model. B. Provide a list and describe any assumptions made to complete this form. C. Provide a summary description of the differences. D. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form V-4, Differences in Hurricane Mitigation Measures and Secondary Characteristics, in a submission appendix.

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DIFFERENCES FROM FORM V-2 Individual Hurricane RELATIVE TO PREVIOUSLY-ACCEPTED HURRICANE MODEL Mitigation Measures and Secondary Characteristics FRAME BUILDING MASONRY BUILDING WINDSPEED (MPH)* WINDSPEED (MPH)* 60 85 110 135 160 60 85 110 135 160 REFERENCE BUILDING ------ROOF ATION BRACED GABLE ENDS 0% 1% 0% 0% 0% 0% 0% 0% 0% 0% CONFIGUR- HIP ROOF 37% -11% -3% -3% -1% 35% -12% -3% -2% 0% G

METAL 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% ASTM D7158 CLASS H SHINGLES 79% 48% 8% 3% 0% 78% 47% 9% 3% 0% MEMBRANE 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

ROOF COVERIN ROOF NAILING OF DECK 8d 3%-9%3%2%0%4%-10%3%2%0%

CLIPS 5% 1% -5% -2% 0% 4% 2% -5% -1% 0% STRENGTH ROOF-WALL STRAPS 2% 2% -4% -3% 0% 0% 2% -4% 0% 0% R

TIES OR CLIPS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% STRENGTH

WALL- FLOO STRAPS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

LARGER ANCHORS OR 0% 0% 0% 0% 0% ------CLOSER SPACING WALL-

STRENGTH STRAPS 0% 0% 0% 0% 0% ------FOUNDATION FOUNDATION VERTICAL REINFORCING ------0% 0% 0% 0% 0%

WINDOW STR. WOOD PANELS 0% -6% -4% -3% -1% 0% -5% -3% -3% -1% SHUTTERS METAL 0% -6% -4% -3% -1% 0% -5% -3% -3% -1% ENGINEERED 0% -7% -6% -5% -2% 0% -7% -5% -7% 0%

OPENING OPENING PROTECTION DOOR AND SKYLIGHT COVERS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%

WINDOWS IMPACT GLASS 0% -7% -6% -5% -2% 0% -7% -5% -7% 0% MEETS WIND- ENTRY BORNE DEBRIS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS REQUIREMENTS MEETS WIND- GARAGE BORNE DEBRIS 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS REQUIREMENTS SLIDING GLASS MEETS WIND- 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% DOORS BORNE DEBRIS WINDOW, DOOR, STRENGTHWINDOW, SKYLIGHT SKYLIGHTIMPACT RATED0%0%0%0%0%0%0%0%0%0% DIFFERENCES FROM FORM V-2 RELATIVE TO PREVIOUSLY-ACCEPTED HURRICANE MODEL MITIGATION MEASURES IN COMBINATION FRAME BUILDING MASONRY BUILDING WINDSPEED (MPH)* WINDSPEED (MPH)* 60 85 110 135 160 60 85 110 135 160

MITIGATED BUILDING 77% 37% 2% 2% 1% 77% 36% 2% 2% 1% BUILDING *Windspeeds are one‐minute sustained 10‐meter.

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Form A-1: Zero Deductible Personal Residential Hurricane Loss Costs by ZIP Code A. Provide three maps, color-coded by ZIP Code (with a minimum of six value ranges), displaying zero deductible personal residential hurricane loss costs per $1,000 of exposure for frame owners, masonry owners, and manufactured homes. B. Create exposure sets for these exhibits by modeling all of the buildings from Notional Set 3 described in the file “Notional Input17.xlsx” geocoded to each ZIP Code centroid in the state, as provided in the hurricane model. Provide the predominant County name and the Federal Information Processing Standards (FIPS) Code associated with each ZIP Code centroid. Refer to the Notional Hurricane Policy Specification below for additional modeling information. Explain any assumptions, deviations, and differences from the prescribed exposure information. C. Provide, in the format given in the file names “2017FormA1.xlsx,” in both Excel and PDF format, the underlying hurricane loss cost data rounded to 3 decimal places used for A. above. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Notional Hurricane Policy Specifications

Policy Type Assumptions Owners Coverage A = Building  Replacement Cost included subject to Coverage A limit  Ordinance or Law not included Coverage B = Appurtenant Structures  Replacement Cost included subject to Coverage B limit  Ordinance or Law not included Coverage C = Contents  Replacement Cost included subject to Coverage C limit Coverage D = Time Element  Time Element = 12 months  Per Diem = $150.00/day per policy, if used Hurricane loss costs per $1,000 shall be related to the Coverage A limit.

Manufactured Homes Coverage A = Building  Replacement Cost included subject to Coverage A limit Coverage B = Appurtenant Structures  Replacement Cost included subject to Coverage B limit Coverage C = Contents  Replacement Cost included subject to Coverage C limit Coverage D = Time Element  Time Element = 12 months  Per Diem = $150.00/day per policy, if used Hurricane loss costs per $1,000 shall be related to the Coverage A limit.

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A. The required maps are shown in Figure 54 through Figure 56. B. The loss costs plotted are the total average annual losses summed across the four coverages per $1,000 of Coverage A. The risks are modeled using ZIP Code level location information. C. The underlying loss cost data, rounded to three decimal places, are provided in ARA17FormA1.xlsx.

Figure 54. Ground-Up Loss Cost Wood Frame Houses

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Figure 55. Ground-Up Loss Cost for Masonry Wall Houses

Figure 56. Ground-Up Loss Cost for Manufactured Home

April 9, 2019 Applied Research Associates, Inc. 195 Appendix A - Forms 4/9/2019 11:00 AM

Form A-2A: Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data) A. Provide the total insured hurricane loss and the dollar contribution to the average annual hurricane loss assuming zero deductible policies for individual historical hurricanes using the Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data provided in the file named “hlpm2012c.exe.” The list of hurricanes in this form should include all Florida and by-passing hurricanes in the modeling organization Base Hurricane Storm Set, as defined in Standard M-1, Base Hurricane Storm Set. The table below contains the minimum number of hurricanes from HURDAT2 to be included in the Base Hurricane Storm Set, based on the 117-year period 1900-2016. As defined, a by-passing hurricane (ByP) is a hurricane which does not make landfall, but produces minimum damaging windspeeds or greater on land in Florida. For the by- passing hurricanes include in the table only, the hurricane intensity entered is a maximum windspeed at closest approach to Florida as a hurricane, not the windspeed over Florida. Each hurricane has been assigned an ID number. As defined in Standard M-1, Base Hurricane Storm Set, the Base Hurricane Storm Set for the modeling organization may exclude hurricanes that had zero modeled impact, or it may include additional hurricanes where there is clear justification for the changes. For hurricanes in the table below resulting in zero hurricane loss, the table entry should be left blank. Additional hurricanes included in the hurricane model Base Hurricane Storm Set shall be added to the table below in order of year and assigned an intermediate ID number as the hurricane falls within the bounding ID numbers. B. If additional assumptions are necessary to complete this form, provide the rationale for the assumptions as well as a detailed description of how they are included. C. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data), in a submission appendix. Note: Total dollar contributions should agree with the total average annual zero deductible statewide hurricane loss costs provided in Form S-5, Average Annual Zero Deductible Statewide

Hurricane Loss Costs – Historical versus Modeled, based on the 2012 FHCF Exposure Data.

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Landfall/ Region as Personal and Closest defined in Commercial ID Year Name Dollar Contribution Approach Figure 3- Residential Insured Date Category Losses ($) 1 9/6/1900 1900 NoName01-1900 ByP-TS 4,243,180 35,959 5 8/15/1901 1901 NoName04-1901 F-1 104,238,893 883,380 10 9/11/1903 1903 NoName03-1903 C-1/A-1 5,833,917,848 49,439,982 15 10/17/1904 1904 NoName04-1904 C-1 647,148,182 5,484,307 20 6/17/1906 1906 NoName02-1906 B-1 1,117,263,039 9,468,331 25 9/27/1906 1906 NoName06-1906 F-2 272,582,921 2,310,025 30 10/18/1906 1906 NoName08-1906 ByP-3/C-3 15,734,173,831 133,340,456 35 10/11/1909 1909 NoName11-1909 B-3 959,110,428 8,128,054 40 10/18/1910 1910 NoName05-1910 B-2 8,864,006,842 75,118,702 45 8/11/1911 1911 NoName02-1911 A-1 207,226,958 1,756,161 50 9/14/1912 1912 NoName04-1912 F-1 102,471,125 868,399 55 8/1/1915 1915 NoName01-1915 D-1 126,526,795 1,072,261 60 9/4/1915 1915 NoName04-1915 A-1 86,354,396 731,817 65 7/5/1916 1916 NoName02-1916 F-3 466,942,172 3,957,137 70 10/18/1916 1916 NoName14-1916 A-2 1,691,298,004 14,333,034 75 9/29/1917 1917 NoName04-1917 A-3 4,985,384,801 42,249,024 80 9/10/1919 1919 NoName02-1919 B-4 435,812,666 3,693,328 85 10/25/1921 1921 TampaBay06-1921 B-3 7,471,626,667 63,318,870 90 9/15/1924 1924 NoName05-1924 A-1 36,070,523 305,682 95 10/21/1924 1924 NoName10-1924 B-1 509,994,341 4,321,986 100 7/28/1926 1926 NoName01-1926 D-2 532,381,304 4,511,706 105 9/18/1926 1926 GreatMiami07-1926 C-4/A-3 73,287,036,241 621,076,578 110 10/21/1926 1926 NoName10-1926 ByP-1 744,059,461 6,305,589 115 8/8/1928 1928 NoName01-1928 C-2 5,430,785,010 46,023,602 120 9/17/1928 1928 LakeOkeechobee04- C-4 54,437,824,954 461,337,500 125 9/28/1929 1929 NoName02-1929 C-3/A-1 5,991,402,465 50,774,597 130 9/1/1932 1932 NoName03-1932 F-1 417,712,089 3,539,933 135 7/30/1933 1933 NoName05-1933 C-1 2,882,769,617 24,430,251 136 9/1/1933 1933 NoName08-1933 Byp-3 4,016,959 34,042 140 9/4/1933 1933 NoName11-1933 C-3 11,061,011,535 93,737,386 141 7/23/1934 1934 NoName03-1934 D-TD 73,594,944 623,686 145 9/3/1935 1935 LaborDay03-1935 C-5/A-2 19,689,415,207 166,859,451 150 11/4/1935 1935 NoName07-1935 C-2 575,253,123 4,875,026 155 7/31/1936 1936 NoName05-1936 A-2 1,246,172,063 10,560,780 160 8/11/1939 1939 NoName02-1939 C-1/A-1 852,047,859 7,220,745 165 10/6/1941 1941 NoName05-1941 C-2/A-1 22,446,754,587 190,226,734 170 10/19/1944 1944 NoName13-1944 B-3 12,897,395,837 109,299,965 175 6/24/1945 1945 NoName01-1945 A-1 2,013,238,718 17,061,345 180 9/15/1945 1945 NoName09-1945 C-4 14,465,034,667 122,585,040 185 10/8/1946 1946 NoName06-1946 B-2 2,661,737,904 22,557,101 190 9/17/1947 1947 NoName04-1947 C-4 41,546,817,874 352,091,677 195 10/12/1947 1947 NoName09-1947 B-1/E-2 1,216,757,646 10,311,505 200 9/22/1948 1948 NoName08-1948 B-4 6,314,157,503 53,509,809 205 10/5/1948 1948 NoName09-1948 B-2 2,350,529,082 19,919,738 210 8/26/1949 1949 NoName02-1949 C-4 23,146,127,118 196,153,620 215 8/31/1950 1950 Baker-1950 F-1 136,033,463 1,152,826 220 9/5/1950 1950 Easy-1950 A-3 736,186,826 6,238,871 225 10/18/1950 1950 King-1950 C-4 9,883,801,881 83,761,033 230 9/26/1953 1953 Florence-1953 A-1 158,186,613 1,340,565

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Landfall/ Region as Personal and Closest defined in Commercial ID Year Name Dollar Contribution Approach Figure 3- Residential Insured Date Category Losses ($) 235 10/9/1953 1953 Hazel-1953 B-1 507,407,003 4,300,059 240 9/25/1956 1956 Flossy-1956 A-1 167,690,969 1,421,110 245 9/10/1960 1960 Donna-1960 B-4 15,882,369,513 134,596,352 250 9/15/1960 1960 Ethel-1960 F-1 - - 255 8/27/1964 1964 Cleo-1964 C-2 6,074,255,865 51,476,745 260 9/10/1964 1964 Dora-1964 D-2 5,848,958,985 49,567,449 261 10/3/1964 1964 Hilda-1964 LA-3 1,384,808 11,736 265 10/14/1964 1964 Isbell-1964 B-3 8,828,961,648 74,821,709 270 9/8/1965 1965 Betsy-1965 C-3 4,345,720,113 36,828,137 275 6/9/1966 1966 Alma-1966 A-1 1,967,355,103 16,672,501 280 10/4/1966 1966 Inez-1966 B-1 282,542,401 2,394,427 285 10/19/1968 1968 Gladys-1968 A-1 807,528,672 6,843,463 290 8/18/1969 1969 Camille-1969 F-5 - - 295 6/19/1972 1972 Agnes-1972 A-1 24,692,436 209,258 300 9/23/1975 1975 Eloise-1975 A-3 667,561,969 5,657,305 305 9/4/1979 1979 David-1979 C-2/E-1 5,254,514,201 44,529,781 310 9/13/1979 1979 Frederic-1979 F-4 197,033,013 1,669,771 315 9/2/1985 1985 Elena-1985 F-3 56,913,806 482,320 316 10/31/1985 1985 Juan-1985 F-TS 49,371,680 418,404 320 11/21/1985 1985 Kate-1985 A-2 285,364,385 2,418,342 325 10/12/1987 1987 Floyd-1987 B-1 12,214,001 103,508 330 8/24/1992 1992 Andrew-1992 C-5 19,575,560,296 165,894,579 335 8/3/1995 1995 Erin-1995 C-1/A-1 1,306,472,996 11,071,805 340 10/4/1995 1995 Opal-1995 A-3 454,137,784 3,848,625 345 7/19/1997 1997 Danny-1997 F-1 70,200,379 594,918 350 9/3/1998 1998 Earl-1998 A-1 59,515,939 504,372 355 9/25/1998 1998 Georges-1998 B-2/F-2 303,284,958 2,570,212 356 9/14/1999 1999 Floyd-1999 ByP-3 37,272,983 315,873 360 10/15/1999 1999 Irene-1999 B-1 350,141,078 2,967,297 365 8/13/2004 2004 Charley-2004 B-4 7,127,652,081 60,403,831 370 9/5/2004 2004 Frances-2004 C-2 6,934,129,357 58,763,808 375 9/16/2004 2004 Ivan-2004 F-3 1,216,563,706 10,309,862 380 9/26/2004 2004 Jeanne-2004 C-3 7,041,367,469 59,672,606 385 0710/2005 2005 Dennis-2005 A-3 637,757,187 5,404,722 390 8/25/2005 2005 Katrina-2005 C-1/F-3 1,008,116,803 8,543,363 395 9/20/2005 2005 Rita-2005 ByP-2 8,485,596 71,912 400 10/24/2005 2005 Wilma-2005 B-3 11,378,275,041 96,426,060 401 8/27/2012 2012 Isaac-2012 ByP-TS 6,825,175 57,840 405 9/2/2016 2016 Hermine-2016 A-1 12,626,148 107,001 410 10/7/2016 2016 Matthew-2016 ByP-3 2,173,296,190 18,417,764 411 9/10/2017 2017 Irma-2017 B-4 10,270,787,947 87,040,576 412 10/8/2017 2017 Nate-2017 F-1 - - Total 488,088,945,846 4,136,346,999

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Form A-2B: Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data) A. Provide the total insured hurricane loss and the dollar contribution to the average annual hurricane loss assuming zero deductible policies for individual historical hurricanes using the Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data provided in the file named “hlpm2017c.exe.” The list of hurricanes in this form should include all Florida and by-passing hurricanes in the modeling organization Base Hurricane Storm Set, as defined in Standard M-1, Base Hurricane Storm Set. The table below contains the minimum number of hurricanes from HURDAT2 to be included in the Base Hurricane Storm Set, based on the 117-year period 1900-2016. As defined, a by-passing hurricane (ByP) is a hurricane which does not make landfall, but produces minimum damaging windspeeds or greater on land in Florida. For the by- passing hurricanes include in the table only, the hurricane intensity entered is a maximum windspeed at closest approach to Florida as a hurricane, not the windspeed over Florida. Each hurricane has been assigned an ID number. As defined in Standard M-1, Base Hurricane Storm Set, the Base Hurricane Storm Set for the modeling organization may exclude hurricanes that had zero modeled impact, or it may include additional hurricanes where there is clear justification for the changes. For hurricanes in the table below resulting in zero hurricane loss, the table entry should be left blank. Additional hurricanes included in the hurricane model Base Hurricane Storm Set shall be added to the table below in order of year and assigned an intermediate ID number as the hurricane falls within the bounding ID numbers. B. If additional assumptions are necessary to complete this form, provide the rationale for the assumptions as well as a detailed description of how they are included. C. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data), in a submission appendix. Note: Total dollar contributions should agree with the total average annual zero deductible statewide hurricane loss costs provided in Form S-5, Average Annual Zero Deductible Statewide

Hurricane Loss Costs – Historical versus Modeled, based on the 2017 FHCF Exposure Data.

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30 10/18/1906 1906 NoName08-1906 ByP-3/C-3 14,111,247,117 119,586,840 35 10/11/1909 1909 NoName11-1909 B-3 782,103,005 6,627,992 40 10/18/1910 1910 NoName05-1910 B-2 9,294,528,573 78,767,191 45 8/11/1911 1911 NoName02-1911 A-1 224,002,297 1,898,325 50 9/14/1912 1912 NoName04-1912 F-1 108,573,308 920,113 55 8/1/1915 1915 NoName01-1915 D-1 130,802,195 1,108,493 60 9/4/1915 1915 NoName04-1915 A-1 89,076,709 754,887 65 7/5/1916 1916 NoName02-1916 F-3 491,786,000 4,167,678 70 10/18/1916 1916 NoName14-1916 A-2 1,807,315,687 15,316,235 75 9/29/1917 1917 NoName04-1917 A-3 5,195,424,363 44,029,020 80 9/10/1919 1919 NoName02-1919 B-4 304,517,917 2,580,660 85 10/25/1921 1921 TampaBay06-1921 B-3 7,437,522,312 63,029,850 90 9/15/1924 1924 NoName05-1924 A-1 37,471,464 317,555 95 10/21/1924 1924 NoName10-1924 B-1 486,393,915 4,121,982 100 7/28/1926 1926 NoName01-1926 D-2 549,838,785 4,659,651 105 9/18/1926 1926 GreatMiami07-1926 C-4/A-3 68,311,887,360 578,914,300 110 10/21/1926 1926 NoName10-1926 ByP-1 648,117,835 5,492,524 115 8/8/1928 1928 NoName01-1928 C-2 5,526,217,921 46,832,355 120 9/17/1928 1928 LakeOkeechobee04- C-4 54,448,890,863 461,431,279 125 9/28/1929 1929 NoName02-1929 C-3/A-1 5,770,988,532 48,906,682 130 9/1/1932 1932 NoName03-1932 F-1 405,793,913 3,438,931 135 7/30/1933 1933 NoName05-1933 C-1 2,916,596,082 24,716,916 136 9/1/1933 1933 NoName08-1933 ByP-3 3,094,148 26,222 140 9/4/1933 1933 NoName11-1933 C-3 11,193,671,274 94,861,621 141 7/23/1934 1934 NoName03-1934 D-TD 80,872,428 685,360 145 9/3/1935 1935 LaborDay03-1935 C-5/A-2 19,288,145,648 163,458,861 150 11/4/1935 1935 NoName07-1935 C-2 534,697,562 4,531,335 155 7/31/1936 1936 NoName05-1936 A-2 1,311,706,519 11,116,157 160 8/11/1939 1939 NoName02-1939 C-1/A-1 897,073,839 7,602,321 165 10/6/1941 1941 NoName05-1941 C-2/A-1 21,932,801,685 185,871,201 170 10/19/1944 1944 NoName13-1944 B-3 13,317,303,705 112,858,506 175 6/24/1945 1945 NoName01-1945 A-1 2,081,104,380 17,636,478 180 9/15/1945 1945 NoName09-1945 C-4 13,942,036,675 118,152,853 185 10/8/1946 1946 NoName06-1946 B-2 2,806,631,279 23,785,011 190 9/17/1947 1947 NoName04-1947 C-4 40,170,190,396 340,425,342 195 10/12/1947 1947 NoName09-1947 B-1/E-2 1,099,031,654 9,313,828 200 9/22/1948 1948 NoName08-1948 B-4 6,131,759,033 51,964,060 205 10/5/1948 1948 NoName09-1948 B-2 2,093,140,525 17,738,479 210 8/26/1949 1949 NoName02-1949 C-4 23,258,999,895 197,110,169 215 8/31/1950 1950 Baker-1950 F-1 145,896,994 1,236,415 220 9/5/1950 1950 Easy-1950 A-3 743,285,774 6,299,032 225 10/18/1950 1950 King-1950 C-4 9,258,354,223 78,460,629 230 9/26/1953 1953 Florence-1953 A-1 169,781,297 1,438,825

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Landfall/ Region as Personal and Closest defined in Commercial ID Year Name Dollar Contribution Approach Figure 3- Residential Insured Date Category Losses ($) 235 10/9/1953 1953 Hazel-1953 B-1 515,075,898 4,365,050 240 9/25/1956 1956 Flossy-1956 A-1 180,048,896 1,525,838 245 9/10/1960 1960 Donna-1960 B-4 16,451,873,666 139,422,658 250 9/15/1960 1960 Ethel-1960 F-1 - - 255 8/27/1964 1964 Cleo-1964 C-2 5,615,414,789 47,588,261 260 9/10/1964 1964 Dora-1964 D-2 6,213,558,464 52,657,275 261 10/3/1964 1964 Hilda-1964 LA-3 1,389,814 11,778 265 10/14/1964 1964 Isbell-1964 B-3 8,564,717,509 72,582,352 270 9/8/1965 1965 Betsy-1965 C-3 3,975,961,310 33,694,587 275 6/9/1966 1966 Alma-1966 A-1 1,864,231,745 15,798,574 280 10/4/1966 1966 Inez-1966 B-1 251,092,542 2,127,903 285 10/19/1968 1968 Gladys-1968 A-1 844,483,594 7,156,641 290 8/18/1969 1969 Camille-1969 F-5 - - 295 6/19/1972 1972 Agnes-1972 A-1 26,431,066 223,992 300 9/23/1975 1975 Eloise-1975 A-3 729,952,604 6,186,039 305 9/4/1979 1979 David-1979 C-2/E-1 5,255,561,709 44,538,659 310 9/13/1979 1979 Frederic-1979 F-4 209,617,594 1,776,420 315 9/2/1985 1985 Elena-1985 F-3 61,011,575 517,047 316 10/31/1985 1985 Juan-1985 F-TS 53,300,127 451,696 320 11/21/1985 1985 Kate-1985 A-2 304,297,667 2,578,794 325 10/12/1987 1987 Floyd-1987 B-1 9,572,879 81,126 330 8/24/1992 1992 Andrew-1992 C-5 18,316,454,055 155,224,187 335 8/3/1995 1995 Erin-1995 C-1/A-1 1,406,923,193 11,923,078 340 10/4/1995 1995 Opal-1995 A-3 483,008,746 4,093,294 345 7/19/1997 1997 Danny-1997 F-1 75,015,836 635,727 350 9/3/1998 1998 Earl-1998 A-1 64,249,921 544,491 355 9/25/1998 1998 Georges-1998 B-2/F-2 281,289,838 2,383,812 356 9/14/1999 1999 Floyd-1999 ByP-3 39,228,047 332,441 360 10/15/1999 1999 Irene-1999 B-1 333,438,966 2,825,754 365 8/13/2004 2004 Charley-2004 B-4 7,320,119,391 62,034,910 370 9/5/2004 2004 Frances-2004 C-2 7,059,669,987 59,827,712 375 9/16/2004 2004 Ivan-2004 F-3 1,287,386,921 10,910,059 380 9/26/2004 2004 Jeanne-2004 C-3 7,209,036,153 61,093,527 385 0710/2005 2005 Dennis-2005 A-3 703,551,903 5,962,304 390 8/25/2005 2005 Katrina-2005 C-1/F-3 942,219,701 7,984,913 395 9/20/2005 2005 Rita-2005 ByP-2 6,119,705 51,862 400 10/24/2005 2005 Wilma-2005 B-3 10,741,362,642 91,028,497 401 8/27/2012 2012 Isaac-2012 ByP-TS 5,432,746 46,040 405 9/2/2016 2016 Hermine-2016 A-1 13,566,199 114,968 410 10/7/2016 2016 Matthew-2016 ByP-3 2,218,256,655 18,798,785 411 9/10/2017 2017 Irma-2017 B-4 10,424,969,561 88,347,200 412 10/8/2017 2017 Nate-2017 F-1 - - Total 477,356,711,289 4,045,395,858

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Form A-3A: 2004 Hurricane Season Losses (2012 FHCF Exposure Data) A. Provide the percentage of residential zero deductible hurricane losses, rounded to four decimal places, and the monetary contribution from Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) for each affected ZIP Code, individually and in total. Include all ZIP Codes where hurricane losses are equal to or greater than $500,000. Use the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential zero exposure exposure data provided in the file named “hlpm2012c.exe.” Rather than using directly a specified published windfield, the winds underlying the hurricane loss cost calculations must be produced by the hurricane model being evaluated and should be the same hurricane parameters as used in completing Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2012 FHCF Exposure Data). B. Provide maps color-coded by ZIP Code depicting the percentage of total residential hurricane losses from each hurricane, Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004), and for the cumulative hurricane losses using the following interval coding:

Red Over 5% Light Red 2% to 5% Pink 1% to 2% Light Pink 0.5% to 1% Light Blue 0.2% to 0.5% Medium Blue 0.1% to 0.2% Blue Below 0.1% Plot the relevant storm track on each map. C. Provide this form in Excel format. The file name should include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-3A, 2004 Hurricane Season Losses (2012 FHCF Exposure Data), in a submission appendix.

The monetary contributions from each 2004 hurricane to each affected ZIP Code with modeled losses of at least $500,000 are given below for the 2012 FHCF exposure data. The data are also provided in the file named ARA17FormA3A.xlsx.

April 9, 2019 Applied Research Associates, Inc. 202 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32003 - 0.0000% 2,540,520 0.0366% - 0.0000% 1,843,243 0.0262% 4,383,763 0.0196% 32008 - 0.0000% 527,884 0.0076% - 0.0000% 189,180 0.0027% 717,064 0.0032% 32009 - 0.0000% 120,236 0.0017% - 0.0000% 97,668 0.0014% 217,904 0.0010% 32011 - 0.0000% 406,125 0.0059% - 0.0000% 316,322 0.0045% 722,447 0.0032% 32013 - 0.0000% 2,457 0.0000% - 0.0000% 1,043 0.0000% 3,500 0.0000% 32024 - 0.0000% 1,737,254 0.0251% - 0.0000% 987,695 0.0140% 2,724,949 0.0122% 32025 - 0.0000% 1,205,550 0.0174% - 0.0000% 864,869 0.0123% 2,070,419 0.0093% 32033 - 0.0000% 390,441 0.0056% - 0.0000% 213,030 0.0030% 603,471 0.0027% 32034 - 0.0000% 1,958,656 0.0282% - 0.0000% - 0.0000% 1,958,656 0.0088% 32038 - 0.0000% 1,060,255 0.0153% - 0.0000% 396,974 0.0056% 1,457,229 0.0065% 32040 - 0.0000% 270,879 0.0039% - 0.0000% 212,974 0.0030% 483,853 0.0022% 32043 - 0.0000% 1,743,293 0.0251% - 0.0000% 1,226,022 0.0174% 2,969,315 0.0133% 32044 - 0.0000% 124,566 0.0018% - 0.0000% 78,122 0.0011% 202,688 0.0009% 32046 - 0.0000% 216,941 0.0031% - 0.0000% 179,127 0.0025% 396,068 0.0018% 32052 - 0.0000% 179,129 0.0026% - 0.0000% 168,448 0.0024% 347,576 0.0016% 32053 - 0.0000% 106,909 0.0015% - 0.0000% 82,346 0.0012% 189,255 0.0008% 32054 - 0.0000% 630,227 0.0091% - 0.0000% 395,990 0.0056% 1,026,218 0.0046% 32055 - 0.0000% 837,114 0.0121% - 0.0000% 675,081 0.0096% 1,512,196 0.0068% 32058 - 0.0000% 142,533 0.0021% - 0.0000% 100,091 0.0014% 242,624 0.0011% 32059 - 0.0000% 96,923 0.0014% - 0.0000% 57,088 0.0008% 154,011 0.0007% 32060 - 0.0000% 1,030,655 0.0149% - 0.0000% 545,500 0.0077% 1,576,155 0.0071% 32061 - 0.0000% 19,268 0.0003% - 0.0000% 12,121 0.0002% 31,389 0.0001% 32062 - 0.0000% 196,404 0.0028% - 0.0000% 78,766 0.0011% 275,170 0.0012% 32063 - 0.0000% 549,611 0.0079% - 0.0000% 432,972 0.0061% 982,584 0.0044% 32064 - 0.0000% 221,498 0.0032% - 0.0000% 160,021 0.0023% 381,518 0.0017% 32065 - 0.0000% 1,989,937 0.0287% - 0.0000% 1,546,380 0.0220% 3,536,316 0.0158% 32066 - 0.0000% 307,076 0.0044% - 0.0000% 121,753 0.0017% 428,830 0.0019% 32068 - 0.0000% 2,995,935 0.0432% - 0.0000% 2,225,881 0.0316% 5,221,815 0.0234% 32071 - 0.0000% 369,472 0.0053% - 0.0000% 113,381 0.0016% 482,852 0.0022% 32073 - 0.0000% 2,409,672 0.0348% - 0.0000% 1,812,433 0.0257% 4,222,106 0.0189% 32080 - 0.0000% 3,526,926 0.0509% - 0.0000% 1,599,193 0.0227% 5,126,119 0.0230% 32081 - 0.0000% 457,776 0.0066% - 0.0000% 343,296 0.0049% 801,072 0.0036% 32082 - 0.0000% 4,191,768 0.0605% - 0.0000% 2,918,701 0.0415% 7,110,469 0.0319% 32083 - 0.0000% 37,273 0.0005% - 0.0000% 24,861 0.0004% 62,135 0.0003% 32084 - 0.0000% 1,751,816 0.0253% - 0.0000% 1,103,160 0.0157% 2,854,975 0.0128% 32086 - 0.0000% 2,056,251 0.0297% - 0.0000% 1,199,934 0.0170% 3,256,185 0.0146% 32087 - 0.0000% 98,111 0.0014% - 0.0000% 78,183 0.0011% 176,294 0.0008% 32091 - 0.0000% 850,319 0.0123% - 0.0000% 571,922 0.0081% 1,422,242 0.0064% 32092 - 0.0000% 2,534,265 0.0365% - 0.0000% 1,803,867 0.0256% 4,338,132 0.0194% 32094 - 0.0000% 178,974 0.0026% - 0.0000% 110,680 0.0016% 289,654 0.0013% 32095 - 0.0000% 628,186 0.0091% - 0.0000% 444,207 0.0063% 1,072,393 0.0048% 32096 - 0.0000% 92,547 0.0013% - 0.0000% 88,119 0.0013% 180,666 0.0008% 32097 - 0.0000% 518,431 0.0075% - 0.0000% - 0.0000% 518,431 0.0023% 32102 - 0.0000% 577,687 0.0083% - 0.0000% 196,005 0.0028% 773,693 0.0035% 32110 - 0.0000% 508,836 0.0073% - 0.0000% 189,791 0.0027% 698,627 0.0031% 32112 - 0.0000% 816,752 0.0118% - 0.0000% 317,708 0.0045% 1,134,461 0.0051% 32113 - 0.0000% 983,890 0.0142% - 0.0000% 461,213 0.0066% 1,445,103 0.0065% 32114 3,460,332 0.0485% 1,855,022 0.0268% - 0.0000% 660,789 0.0094% 5,976,143 0.0268% 32117 2,978,222 0.0418% 2,159,211 0.0311% - 0.0000% 765,001 0.0109% 5,902,434 0.0264% 32118 11,303,268 0.1586% 4,295,580 0.0619% - 0.0000% 1,298,733 0.0184% 16,897,580 0.0757% 32119 8,570,384 0.1202% 3,189,512 0.0460% - 0.0000% 1,154,684 0.0164% 12,914,580 0.0579% 32124 510,927 0.0072% 649,334 0.0094% - 0.0000% 309,571 0.0044% 1,469,832 0.0066% 32127 29,589,807 0.4151% 6,028,110 0.0869% - 0.0000% 2,394,844 0.0340% 38,012,761 0.1703% 32128 12,514,356 0.1756% 4,458,027 0.0643% - 0.0000% 1,929,026 0.0274% 18,901,409 0.0847% 32129 8,795,230 0.1234% 2,917,182 0.0421% - 0.0000% 1,099,462 0.0156% 12,811,874 0.0574% 32130 156,929 0.0022% 857,835 0.0124% - 0.0000% 313,021 0.0044% 1,327,784 0.0059% 32131 - 0.0000% 392,222 0.0057% - 0.0000% 191,075 0.0027% 583,297 0.0026% 32132 8,163,263 0.1145% 1,323,472 0.0191% - 0.0000% 717,970 0.0102% 10,204,704 0.0457% 32134 - 0.0000% 1,121,256 0.0162% - 0.0000% 503,533 0.0072% 1,624,789 0.0073% 32136 584,321 0.0082% 1,375,065 0.0198% - 0.0000% 552,408 0.0078% 2,511,794 0.0113% 32137 - 0.0000% 6,030,545 0.0870% - 0.0000% 3,217,336 0.0457% 9,247,881 0.0414% 32139 - 0.0000% 232,532 0.0034% - 0.0000% 72,072 0.0010% 304,604 0.0014%

April 9, 2019 Applied Research Associates, Inc. 203 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32140 - 0.0000% 121,859 0.0018% - 0.0000% 72,705 0.0010% 194,563 0.0009% 32141 14,545,756 0.2041% 3,067,836 0.0442% - 0.0000% 1,823,257 0.0259% 19,436,850 0.0871% 32145 - 0.0000% 214,803 0.0031% - 0.0000% 101,866 0.0014% 316,670 0.0014% 32148 - 0.0000% 918,951 0.0133% - 0.0000% 425,525 0.0060% 1,344,476 0.0060% 32159 - 0.0000% 15,698,807 0.2264% - 0.0000% 9,765,034 0.1387% 25,463,842 0.1141% 32162 - 0.0000% 23,972,705 0.3457% - 0.0000% 16,904,457 0.2401% 40,877,162 0.1831% 32163 - 0.0000% 670,897 0.0097% - 0.0000% 517,152 0.0073% 1,188,049 0.0053% 32164 - 0.0000% 4,937,754 0.0712% - 0.0000% 2,536,452 0.0360% 7,474,206 0.0335% 32168 27,160,393 0.3811% 4,489,986 0.0648% - 0.0000% 2,195,088 0.0312% 33,845,468 0.1516% 32169 44,101,530 0.6187% 6,010,250 0.0867% - 0.0000% 2,862,964 0.0407% 52,974,743 0.2373% 32174 6,961,948 0.0977% 8,554,859 0.1234% - 0.0000% 3,447,371 0.0490% 18,964,177 0.0850% 32176 6,903,192 0.0969% 5,701,701 0.0822% - 0.0000% 1,498,864 0.0213% 14,103,757 0.0632% 32177 - 0.0000% 1,872,703 0.0270% - 0.0000% 974,041 0.0138% 2,846,744 0.0128% 32179 - 0.0000% 1,615,704 0.0233% - 0.0000% 784,396 0.0111% 2,400,100 0.0108% 32180 - 0.0000% 443,096 0.0064% - 0.0000% 163,128 0.0023% 606,223 0.0027% 32181 - 0.0000% 264,433 0.0038% - 0.0000% 104,648 0.0015% 369,081 0.0017% 32187 - 0.0000% 176,307 0.0025% - 0.0000% 79,052 0.0011% 255,359 0.0011% 32189 - 0.0000% 473,695 0.0068% - 0.0000% 180,958 0.0026% 654,653 0.0029% 32190 - 0.0000% 102,232 0.0015% - 0.0000% 37,879 0.0005% 140,110 0.0006% 32195 - 0.0000% 1,139,608 0.0164% - 0.0000% 672,423 0.0095% 1,812,031 0.0081% 32202 - 0.0000% 35,862 0.0005% - 0.0000% 28,315 0.0004% 64,177 0.0003% 32204 - 0.0000% 247,444 0.0036% - 0.0000% 186,030 0.0026% 433,473 0.0019% 32205 - 0.0000% 1,364,957 0.0197% - 0.0000% 1,062,461 0.0151% 2,427,418 0.0109% 32206 - 0.0000% 371,540 0.0054% - 0.0000% 282,012 0.0040% 653,551 0.0029% 32207 - 0.0000% 1,531,459 0.0221% - 0.0000% 1,159,016 0.0165% 2,690,475 0.0121% 32208 - 0.0000% 830,995 0.0120% - 0.0000% 634,806 0.0090% 1,465,801 0.0066% 32209 - 0.0000% 616,367 0.0089% - 0.0000% 471,632 0.0067% 1,087,999 0.0049% 32210 - 0.0000% 2,655,525 0.0383% - 0.0000% 1,994,253 0.0283% 4,649,778 0.0208% 32211 - 0.0000% 852,313 0.0123% - 0.0000% 640,788 0.0091% 1,493,102 0.0067% 32212 - 0.0000% 1,310 0.0000% - 0.0000% 583 0.0000% 1,893 0.0000% 32216 - 0.0000% 1,280,627 0.0185% - 0.0000% 954,331 0.0136% 2,234,959 0.0100% 32217 - 0.0000% 991,417 0.0143% - 0.0000% 737,437 0.0105% 1,728,854 0.0077% 32218 - 0.0000% 1,919,437 0.0277% - 0.0000% 1,555,461 0.0221% 3,474,897 0.0156% 32219 - 0.0000% 408,466 0.0059% - 0.0000% 327,524 0.0047% 735,991 0.0033% 32220 - 0.0000% 514,104 0.0074% - 0.0000% 406,147 0.0058% 920,251 0.0041% 32221 - 0.0000% 1,352,101 0.0195% - 0.0000% 1,055,543 0.0150% 2,407,644 0.0108% 32222 - 0.0000% 478,361 0.0069% - 0.0000% 377,166 0.0054% 855,527 0.0038% 32223 - 0.0000% 1,890,197 0.0273% - 0.0000% 1,403,050 0.0199% 3,293,247 0.0148% 32224 - 0.0000% 1,905,367 0.0275% - 0.0000% 1,400,764 0.0199% 3,306,132 0.0148% 32225 - 0.0000% 2,619,071 0.0378% - 0.0000% 1,913,680 0.0272% 4,532,751 0.0203% 32226 - 0.0000% 783,546 0.0113% - 0.0000% 562,860 0.0080% 1,346,406 0.0060% 32227 - 0.0000% 1,582 0.0000% - 0.0000% 916 0.0000% 2,498 0.0000% 32233 - 0.0000% 939,745 0.0136% - 0.0000% 678,539 0.0096% 1,618,283 0.0073% 32234 - 0.0000% 249,736 0.0036% - 0.0000% 190,947 0.0027% 440,683 0.0020% 32244 - 0.0000% 2,360,833 0.0340% - 0.0000% 1,839,411 0.0261% 4,200,244 0.0188% 32246 - 0.0000% 1,640,127 0.0237% - 0.0000% 1,222,023 0.0174% 2,862,150 0.0128% 32250 - 0.0000% 1,375,579 0.0198% - 0.0000% 987,924 0.0140% 2,363,503 0.0106% 32254 - 0.0000% 256,264 0.0037% - 0.0000% 199,515 0.0028% 455,779 0.0020% 32256 - 0.0000% 1,912,899 0.0276% - 0.0000% 1,449,016 0.0206% 3,361,915 0.0151% 32257 - 0.0000% 1,864,566 0.0269% - 0.0000% 1,409,453 0.0200% 3,274,019 0.0147% 32258 - 0.0000% 1,877,669 0.0271% - 0.0000% 1,447,847 0.0206% 3,325,516 0.0149% 32259 - 0.0000% 3,559,340 0.0513% - 0.0000% 2,689,108 0.0382% 6,248,448 0.0280% 32266 - 0.0000% 435,361 0.0063% - 0.0000% 321,487 0.0046% 756,848 0.0034% 32277 - 0.0000% 1,132,134 0.0163% - 0.0000% 721,183 0.0102% 1,853,318 0.0083% 32301 - 0.0000% 771,241 0.0111% - 0.0000% - 0.0000% 771,241 0.0035% 32303 - 0.0000% 1,748,399 0.0252% - 0.0000% - 0.0000% 1,748,399 0.0078% 32304 - 0.0000% 419,815 0.0061% - 0.0000% - 0.0000% 419,815 0.0019% 32305 - 0.0000% 390,318 0.0056% - 0.0000% - 0.0000% 390,318 0.0017% 32308 - 0.0000% 1,220,743 0.0176% - 0.0000% - 0.0000% 1,220,743 0.0055% 32309 - 0.0000% 2,040,461 0.0294% - 0.0000% - 0.0000% 2,040,461 0.0091% 32310 - 0.0000% 305,585 0.0044% - 0.0000% - 0.0000% 305,585 0.0014% 32311 - 0.0000% 982,674 0.0142% - 0.0000% - 0.0000% 982,674 0.0044%

April 9, 2019 Applied Research Associates, Inc. 204 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32312 - 0.0000% 2,658,019 0.0383% - 0.0000% - 0.0000% 2,658,019 0.0119% 32317 - 0.0000% 870,908 0.0126% - 0.0000% - 0.0000% 870,908 0.0039% 32320 - 0.0000% 89,899 0.0013% 91,012 0.0075% - 0.0000% 180,910 0.0008% 32321 - 0.0000% 68,205 0.0010% 59,291 0.0049% - 0.0000% 127,496 0.0006% 32322 - 0.0000% 115,088 0.0017% - 0.0000% - 0.0000% 115,088 0.0005% 32324 - 0.0000% 62,796 0.0009% - 0.0000% - 0.0000% 62,796 0.0003% 32327 - 0.0000% 911,431 0.0131% - 0.0000% - 0.0000% 911,431 0.0041% 32328 - 0.0000% 297,788 0.0043% 244,979 0.0201% - 0.0000% 542,767 0.0024% 32331 - 0.0000% 113,548 0.0016% - 0.0000% 61,027 0.0009% 174,574 0.0008% 32332 - 0.0000% 10,950 0.0002% - 0.0000% - 0.0000% 10,950 0.0000% 32333 - 0.0000% 465,299 0.0067% - 0.0000% - 0.0000% 465,299 0.0021% 32334 - 0.0000% 28,712 0.0004% - 0.0000% - 0.0000% 28,712 0.0001% 32336 - 0.0000% 41,840 0.0006% - 0.0000% - 0.0000% 41,840 0.0002% 32340 - 0.0000% 353,133 0.0051% - 0.0000% 225,654 0.0032% 578,787 0.0026% 32344 - 0.0000% 491,456 0.0071% - 0.0000% - 0.0000% 491,456 0.0022% 32346 - 0.0000% 166,668 0.0024% - 0.0000% - 0.0000% 166,668 0.0007% 32347 - 0.0000% 356,193 0.0051% - 0.0000% 119,620 0.0017% 475,813 0.0021% 32348 - 0.0000% 359,200 0.0052% - 0.0000% - 0.0000% 359,200 0.0016% 32350 - 0.0000% 50,535 0.0007% - 0.0000% 36,205 0.0005% 86,740 0.0004% 32351 - 0.0000% 336,269 0.0048% - 0.0000% - 0.0000% 336,269 0.0015% 32352 - 0.0000% 108,274 0.0016% - 0.0000% - 0.0000% 108,274 0.0005% 32356 - 0.0000% 6,269 0.0001% - 0.0000% 1,748 0.0000% 8,018 0.0000% 32358 - 0.0000% 88,574 0.0013% - 0.0000% - 0.0000% 88,574 0.0004% 32359 - 0.0000% 206,760 0.0030% - 0.0000% 56,405 0.0008% 263,165 0.0012% 32401 - 0.0000% - 0.0000% 845,953 0.0695% - 0.0000% 845,953 0.0038% 32403 - 0.0000% - 0.0000% 53,494 0.0044% - 0.0000% 53,494 0.0002% 32404 - 0.0000% - 0.0000% 1,458,386 0.1199% - 0.0000% 1,458,386 0.0065% 32405 - 0.0000% - 0.0000% 1,346,943 0.1107% - 0.0000% 1,346,943 0.0060% 32407 - 0.0000% - 0.0000% 721,278 0.0593% - 0.0000% 721,278 0.0032% 32408 - 0.0000% - 0.0000% 1,799,743 0.1479% - 0.0000% 1,799,743 0.0081% 32409 - 0.0000% - 0.0000% 358,781 0.0295% - 0.0000% 358,781 0.0016% 32413 - 0.0000% - 0.0000% 2,568,124 0.2111% - 0.0000% 2,568,124 0.0115% 32420 - 0.0000% - 0.0000% 72,082 0.0059% - 0.0000% 72,082 0.0003% 32421 - 0.0000% - 0.0000% 64,911 0.0053% - 0.0000% 64,911 0.0003% 32423 - 0.0000% - 0.0000% 21,297 0.0018% - 0.0000% 21,297 0.0001% 32424 - 0.0000% - 0.0000% 104,046 0.0086% - 0.0000% 104,046 0.0005% 32425 - 0.0000% - 0.0000% 336,998 0.0277% - 0.0000% 336,998 0.0015% 32426 - 0.0000% - 0.0000% 17,103 0.0014% - 0.0000% 17,103 0.0001% 32427 - 0.0000% - 0.0000% 29,434 0.0024% - 0.0000% 29,434 0.0001% 32428 - 0.0000% - 0.0000% 500,991 0.0412% - 0.0000% 500,991 0.0022% 32430 - 0.0000% - 0.0000% 20,746 0.0017% - 0.0000% 20,746 0.0001% 32431 - 0.0000% - 0.0000% 91,403 0.0075% - 0.0000% 91,403 0.0004% 32433 - 0.0000% - 0.0000% 1,055,385 0.0868% - 0.0000% 1,055,385 0.0047% 32435 - 0.0000% - 0.0000% 419,820 0.0345% - 0.0000% 419,820 0.0019% 32437 - 0.0000% - 0.0000% 11,224 0.0009% - 0.0000% 11,224 0.0001% 32438 - 0.0000% - 0.0000% 41,852 0.0034% - 0.0000% 41,852 0.0002% 32439 - 0.0000% - 0.0000% 837,818 0.0689% - 0.0000% 837,818 0.0038% 32440 - 0.0000% - 0.0000% 136,693 0.0112% - 0.0000% 136,693 0.0006% 32442 - 0.0000% - 0.0000% 52,790 0.0043% - 0.0000% 52,790 0.0002% 32443 - 0.0000% - 0.0000% 46,809 0.0038% - 0.0000% 46,809 0.0002% 32444 - 0.0000% - 0.0000% 1,224,081 0.1006% - 0.0000% 1,224,081 0.0055% 32445 - 0.0000% - 0.0000% 21,349 0.0018% - 0.0000% 21,349 0.0001% 32446 - 0.0000% - 0.0000% 286,578 0.0236% - 0.0000% 286,578 0.0013% 32448 - 0.0000% - 0.0000% 143,219 0.0118% - 0.0000% 143,219 0.0006% 32449 - 0.0000% - 0.0000% 7,528 0.0006% - 0.0000% 7,528 0.0000% 32455 - 0.0000% - 0.0000% 143,692 0.0118% - 0.0000% 143,692 0.0006% 32456 - 0.0000% - 0.0000% 484,134 0.0398% - 0.0000% 484,134 0.0022% 32459 - 0.0000% - 0.0000% 6,871,836 0.5649% - 0.0000% 6,871,836 0.0308% 32460 - 0.0000% 59,885 0.0009% - 0.0000% - 0.0000% 59,885 0.0003% 32462 - 0.0000% - 0.0000% 93,296 0.0077% - 0.0000% 93,296 0.0004% 32464 - 0.0000% - 0.0000% 127,870 0.0105% - 0.0000% 127,870 0.0006% 32465 - 0.0000% - 0.0000% 104,495 0.0086% - 0.0000% 104,495 0.0005%

April 9, 2019 Applied Research Associates, Inc. 205 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32466 - 0.0000% - 0.0000% 152,685 0.0126% - 0.0000% 152,685 0.0007% 32501 - 0.0000% - 0.0000% 23,696,975 1.9479% - 0.0000% 23,696,975 0.1062% 32502 - 0.0000% - 0.0000% 9,013,185 0.7409% - 0.0000% 9,013,185 0.0404% 32503 - 0.0000% - 0.0000% 76,221,979 6.2654% - 0.0000% 76,221,979 0.3415% 32504 - 0.0000% - 0.0000% 61,335,768 5.0417% - 0.0000% 61,335,768 0.2748% 32505 - 0.0000% - 0.0000% 39,359,315 3.2353% - 0.0000% 39,359,315 0.1763% 32506 - 0.0000% - 0.0000% 74,963,846 6.1619% - 0.0000% 74,963,846 0.3359% 32507 - 0.0000% - 0.0000% 166,399,435 13.6778 - 0.0000% 166,399,435 0.7455% % 32508 - 0.0000% - 0.0000% 331,399 0.0272% - 0.0000% 331,399 0.0015% 32509 - 0.0000% - 0.0000% 38 0.0000% - 0.0000% 38 0.0000% 32511 - 0.0000% - 0.0000% 50,168 0.0041% - 0.0000% 50,168 0.0002% 32514 - 0.0000% - 0.0000% 78,265,547 6.4333% - 0.0000% 78,265,547 0.3507% 32526 - 0.0000% - 0.0000% 84,918,104 6.9802% - 0.0000% 84,918,104 0.3805% 32531 - 0.0000% - 0.0000% 1,961,971 0.1613% - 0.0000% 1,961,971 0.0088% 32533 - 0.0000% - 0.0000% 65,590,000 5.3914% - 0.0000% 65,590,000 0.2939% 32534 - 0.0000% - 0.0000% 26,522,088 2.1801% - 0.0000% 26,522,088 0.1188% 32535 - 0.0000% - 0.0000% 4,139,570 0.3403% - 0.0000% 4,139,570 0.0185% 32536 - 0.0000% - 0.0000% 6,517,093 0.5357% - 0.0000% 6,517,093 0.0292% 32539 - 0.0000% - 0.0000% 6,033,398 0.4959% - 0.0000% 6,033,398 0.0270% 32541 - 0.0000% - 0.0000% 17,577,131 1.4448% - 0.0000% 17,577,131 0.0788% 32542 - 0.0000% - 0.0000% 17,946 0.0015% - 0.0000% 17,946 0.0001% 32544 - 0.0000% - 0.0000% 14,231 0.0012% - 0.0000% 14,231 0.0001% 32547 - 0.0000% - 0.0000% 15,344,092 1.2613% - 0.0000% 15,344,092 0.0687% 32548 - 0.0000% - 0.0000% 18,917,848 1.5550% - 0.0000% 18,917,848 0.0848% 32550 - 0.0000% - 0.0000% 7,987,124 0.6565% - 0.0000% 7,987,124 0.0358% 32561 - 0.0000% - 0.0000% 93,808,572 7.7109% - 0.0000% 93,808,572 0.4203% 32563 - 0.0000% - 0.0000% 75,225,994 6.1835% - 0.0000% 75,225,994 0.3370% 32564 - 0.0000% - 0.0000% 863,748 0.0710% - 0.0000% 863,748 0.0039% 32565 - 0.0000% - 0.0000% 6,503,960 0.5346% - 0.0000% 6,503,960 0.0291% 32566 - 0.0000% - 0.0000% 54,176,829 4.4533% - 0.0000% 54,176,829 0.2427% 32567 - 0.0000% - 0.0000% 507,157 0.0417% - 0.0000% 507,157 0.0023% 32568 - 0.0000% - 0.0000% 3,936,235 0.3236% - 0.0000% 3,936,235 0.0176% 32569 - 0.0000% - 0.0000% 13,223,832 1.0870% - 0.0000% 13,223,832 0.0592% 32570 - 0.0000% - 0.0000% 32,828,530 2.6985% - 0.0000% 32,828,530 0.1471% 32571 - 0.0000% - 0.0000% 54,806,647 4.5050% - 0.0000% 54,806,647 0.2456% 32577 - 0.0000% - 0.0000% 10,029,236 0.8244% - 0.0000% 10,029,236 0.0449% 32578 - 0.0000% - 0.0000% 11,154,647 0.9169% - 0.0000% 11,154,647 0.0500% 32579 - 0.0000% - 0.0000% 7,716,641 0.6343% - 0.0000% 7,716,641 0.0346% 32580 - 0.0000% - 0.0000% 1,476,078 0.1213% - 0.0000% 1,476,078 0.0066% 32583 - 0.0000% - 0.0000% 42,057,201 3.4570% - 0.0000% 42,057,201 0.1884% 32601 - 0.0000% 1,232,424 0.0178% - 0.0000% 680,778 0.0097% 1,913,202 0.0086% 32603 - 0.0000% 326,258 0.0047% - 0.0000% 173,838 0.0025% 500,096 0.0022% 32605 - 0.0000% 4,123,613 0.0595% - 0.0000% 2,297,006 0.0326% 6,420,619 0.0288% 32606 - 0.0000% 3,534,887 0.0510% - 0.0000% 1,777,170 0.0252% 5,312,057 0.0238% 32607 - 0.0000% 3,014,003 0.0435% - 0.0000% 1,562,237 0.0222% 4,576,241 0.0205% 32608 - 0.0000% 5,818,568 0.0839% - 0.0000% 2,619,249 0.0372% 8,437,817 0.0378% 32609 - 0.0000% 1,271,147 0.0183% - 0.0000% 707,829 0.0101% 1,978,976 0.0089% 32615 - 0.0000% 2,582,271 0.0372% - 0.0000% 1,199,039 0.0170% 3,781,310 0.0169% 32617 - 0.0000% 1,052,463 0.0152% - 0.0000% 453,665 0.0064% 1,506,128 0.0067% 32618 - 0.0000% 1,210,945 0.0175% - 0.0000% 360,674 0.0051% 1,571,619 0.0070% 32619 - 0.0000% 549,721 0.0079% - 0.0000% 140,418 0.0020% 690,139 0.0031% 32621 - 0.0000% 579,731 0.0084% - 0.0000% 138,456 0.0020% 718,186 0.0032% 32622 - 0.0000% 131,595 0.0019% - 0.0000% 82,428 0.0012% 214,023 0.0010% 32625 - 0.0000% 285,199 0.0041% - 0.0000% 82,834 0.0012% 368,034 0.0016% 32626 - 0.0000% 993,504 0.0143% - 0.0000% 246,812 0.0035% 1,240,315 0.0056% 32628 - 0.0000% 220,170 0.0032% - 0.0000% 69,814 0.0010% 289,984 0.0013% 32631 - 0.0000% 98,817 0.0014% - 0.0000% 63,157 0.0009% 161,974 0.0007% 32640 - 0.0000% 1,365,830 0.0197% - 0.0000% 719,194 0.0102% 2,085,025 0.0093% 32641 - 0.0000% 945,514 0.0136% - 0.0000% 527,206 0.0075% 1,472,721 0.0066% 32643 - 0.0000% 1,673,953 0.0241% - 0.0000% 686,860 0.0098% 2,360,813 0.0106% 32648 - 0.0000% 45,284 0.0007% - 0.0000% 13,901 0.0002% 59,184 0.0003%

April 9, 2019 Applied Research Associates, Inc. 206 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32653 - 0.0000% 2,590,541 0.0374% - 0.0000% 1,450,569 0.0206% 4,041,110 0.0181% 32656 - 0.0000% 1,294,337 0.0187% - 0.0000% 795,750 0.0113% 2,090,087 0.0094% 32666 - 0.0000% 828,716 0.0120% - 0.0000% 489,075 0.0069% 1,317,790 0.0059% 32667 - 0.0000% 865,347 0.0125% - 0.0000% 411,975 0.0059% 1,277,323 0.0057% 32668 - 0.0000% 1,641,885 0.0237% - 0.0000% 499,715 0.0071% 2,141,599 0.0096% 32669 - 0.0000% 2,781,321 0.0401% - 0.0000% 930,240 0.0132% 3,711,561 0.0166% 32680 - 0.0000% 736,736 0.0106% - 0.0000% 174,434 0.0025% 911,171 0.0041% 32686 - 0.0000% 1,294,036 0.0187% - 0.0000% 542,382 0.0077% 1,836,418 0.0082% 32693 - 0.0000% 1,373,439 0.0198% - 0.0000% 321,718 0.0046% 1,695,157 0.0076% 32694 - 0.0000% 144,530 0.0021% - 0.0000% 90,043 0.0013% 234,573 0.0011% 32696 - 0.0000% 2,073,537 0.0299% - 0.0000% 616,337 0.0088% 2,689,874 0.0121% 32701 5,616,149 0.0788% 4,374,118 0.0631% - 0.0000% 3,255,690 0.0462% 13,245,957 0.0593% 32702 - 0.0000% 495,919 0.0072% - 0.0000% 204,270 0.0029% 700,189 0.0031% 32703 5,451,579 0.0765% 13,844,847 0.1997% - 0.0000% 11,046,233 0.1569% 30,342,659 0.1359% 32707 22,225,351 0.3118% 9,195,817 0.1326% - 0.0000% 7,167,768 0.1018% 38,588,936 0.1729% 32708 39,242,187 0.5506% 14,133,337 0.2038% - 0.0000% 11,240,616 0.1596% 64,616,139 0.2895% 32709 765,739 0.0107% 476,286 0.0069% - 0.0000% 605,351 0.0086% 1,847,376 0.0083% 32712 3,238,566 0.0454% 13,196,324 0.1903% - 0.0000% 9,868,552 0.1402% 26,303,442 0.1178% 32713 3,420,233 0.0480% 6,333,820 0.0913% - 0.0000% 2,890,561 0.0411% 12,644,614 0.0567% 32714 6,632,565 0.0931% 7,527,398 0.1086% - 0.0000% 5,583,407 0.0793% 19,743,370 0.0885% 32720 1,576,412 0.0221% 5,627,812 0.0812% - 0.0000% 2,310,759 0.0328% 9,514,982 0.0426% 32724 2,729,737 0.0383% 6,580,056 0.0949% - 0.0000% 2,581,032 0.0367% 11,890,825 0.0533% 32725 12,910,046 0.1811% 11,933,690 0.1721% - 0.0000% 5,206,766 0.0739% 30,050,502 0.1346% 32726 - 0.0000% 6,418,725 0.0926% - 0.0000% 3,904,808 0.0555% 10,323,533 0.0463% 32730 2,534,758 0.0356% 1,301,350 0.0188% - 0.0000% 1,003,413 0.0143% 4,839,520 0.0217% 32732 13,315,279 0.1868% 1,938,203 0.0280% - 0.0000% 1,226,004 0.0174% 16,479,485 0.0738% 32735 - 0.0000% 2,562,300 0.0370% - 0.0000% 1,554,963 0.0221% 4,117,263 0.0184% 32736 - 0.0000% 3,499,749 0.0505% - 0.0000% 1,704,590 0.0242% 5,204,340 0.0233% 32738 16,256,723 0.2281% 8,910,927 0.1285% - 0.0000% 4,065,760 0.0577% 29,233,411 0.1310% 32744 549,929 0.0077% 643,191 0.0093% - 0.0000% 273,770 0.0039% 1,466,890 0.0066% 32746 14,696,797 0.2062% 16,268,751 0.2346% - 0.0000% 9,660,173 0.1372% 40,625,720 0.1820% 32750 7,953,978 0.1116% 8,125,420 0.1172% - 0.0000% 5,610,793 0.0797% 21,690,190 0.0972% 32751 18,384,322 0.2579% 9,143,015 0.1319% - 0.0000% 7,552,029 0.1073% 35,079,366 0.1572% 32754 2,649,826 0.0372% 1,910,057 0.0275% - 0.0000% 1,910,057 0.0271% 6,469,940 0.0290% 32757 - 0.0000% 14,607,138 0.2107% - 0.0000% 9,415,484 0.1337% 24,022,622 0.1076% 32759 1,254,049 0.0176% 510,344 0.0074% - 0.0000% 324,916 0.0046% 2,089,309 0.0094% 32763 1,654,742 0.0232% 3,506,993 0.0506% - 0.0000% 1,543,508 0.0219% 6,705,243 0.0300% 32764 2,289,322 0.0321% 645,994 0.0093% - 0.0000% 338,136 0.0048% 3,273,452 0.0147% 32765 99,611,944 1.3975% 16,309,375 0.2352% - 0.0000% 13,713,602 0.1948% 129,634,921 0.5808% 32766 36,318,078 0.5095% 5,017,030 0.0724% - 0.0000% 4,302,867 0.0611% 45,637,976 0.2045% 32767 - 0.0000% 424,469 0.0061% - 0.0000% 161,359 0.0023% 585,828 0.0026% 32771 13,191,150 0.1851% 12,155,248 0.1753% - 0.0000% 7,001,924 0.0994% 32,348,322 0.1449% 32773 11,606,995 0.1628% 6,318,061 0.0911% - 0.0000% 3,574,602 0.0508% 21,499,658 0.0963% 32776 519,884 0.0073% 3,503,606 0.0505% - 0.0000% 2,088,631 0.0297% 6,112,121 0.0274% 32778 - 0.0000% 9,385,176 0.1353% - 0.0000% 6,755,799 0.0959% 16,140,975 0.0723% 32779 9,228,265 0.1295% 15,101,442 0.2178% - 0.0000% 10,997,728 0.1562% 35,327,435 0.1583% 32780 4,293,165 0.0602% 10,504,075 0.1515% - 0.0000% 13,355,615 0.1897% 28,152,855 0.1261% 32784 - 0.0000% 2,991,576 0.0431% - 0.0000% 1,507,474 0.0214% 4,499,050 0.0202% 32789 41,389,197 0.5807% 16,311,198 0.2352% - 0.0000% 14,929,820 0.2120% 72,630,214 0.3254% 32792 35,758,181 0.5017% 11,066,293 0.1596% - 0.0000% 10,212,466 0.1450% 57,036,940 0.2555% 32796 2,657,279 0.0373% 3,836,593 0.0553% - 0.0000% 4,679,795 0.0665% 11,173,667 0.0501% 32798 79,845 0.0011% 1,528,285 0.0220% - 0.0000% 1,122,450 0.0159% 2,730,580 0.0122% 32801 6,429,732 0.0902% 2,207,828 0.0318% - 0.0000% 2,420,217 0.0344% 11,057,777 0.0495% 32803 24,836,246 0.3484% 7,786,656 0.1123% - 0.0000% 8,550,468 0.1214% 41,173,370 0.1845% 32804 15,318,924 0.2149% 8,331,514 0.1202% - 0.0000% 8,422,023 0.1196% 32,072,461 0.1437% 32805 7,022,675 0.0985% 3,082,710 0.0445% - 0.0000% 3,698,859 0.0525% 13,804,244 0.0618% 32806 39,691,133 0.5569% 10,200,081 0.1471% - 0.0000% 12,070,108 0.1714% 61,961,322 0.2776% 32807 28,050,483 0.3935% 5,782,602 0.0834% - 0.0000% 6,415,973 0.0911% 40,249,058 0.1803% 32808 7,970,979 0.1118% 7,158,596 0.1032% - 0.0000% 7,483,357 0.1063% 22,612,932 0.1013% 32809 23,898,543 0.3353% 5,713,403 0.0824% - 0.0000% 7,962,451 0.1131% 37,574,397 0.1683% 32810 6,514,896 0.0914% 6,587,185 0.0950% - 0.0000% 5,720,778 0.0812% 18,822,859 0.0843% 32811 4,571,889 0.0641% 2,839,072 0.0409% - 0.0000% 3,413,208 0.0485% 10,824,168 0.0485%

April 9, 2019 Applied Research Associates, Inc. 207 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 32812 52,216,291 0.7326% 9,819,301 0.1416% - 0.0000% 12,613,769 0.1791% 74,649,360 0.3345% 32814 6,770,699 0.0950% 2,011,465 0.0290% - 0.0000% 2,011,465 0.0286% 10,793,629 0.0484% 32815 559 0.0000% 1,058 0.0000% - 0.0000% 1,304 0.0000% 2,921 0.0000% 32817 42,203,748 0.5921% 8,019,217 0.1156% - 0.0000% 7,655,999 0.1087% 57,878,964 0.2593% 32818 7,262,739 0.1019% 9,885,693 0.1426% - 0.0000% 10,337,272 0.1468% 27,485,704 0.1231% 32819 22,734,466 0.3190% 12,814,122 0.1848% - 0.0000% 18,039,712 0.2562% 53,588,300 0.2401% 32820 11,272,107 0.1581% 1,982,931 0.0286% - 0.0000% 2,239,270 0.0318% 15,494,308 0.0694% 32821 9,878,539 0.1386% 3,637,622 0.0525% - 0.0000% 6,116,212 0.0869% 19,632,373 0.0880% 32822 44,898,523 0.6299% 7,522,338 0.1085% - 0.0000% 9,623,001 0.1367% 62,043,862 0.2780% 32824 64,252,131 0.9014% 9,521,413 0.1373% - 0.0000% 16,584,476 0.2355% 90,358,020 0.4048% 32825 92,028,200 1.2911% 12,924,897 0.1864% - 0.0000% 14,579,308 0.2071% 119,532,405 0.5355% 32826 36,520,409 0.5124% 4,216,070 0.0608% - 0.0000% 4,216,070 0.0599% 44,952,550 0.2014% 32827 38,027,922 0.5335% 3,550,120 0.0512% - 0.0000% 5,458,295 0.0775% 47,036,337 0.2107% 32828 114,575,776 1.6075% 14,317,823 0.2065% - 0.0000% 16,805,086 0.2387% 145,698,685 0.6528% 32829 39,113,683 0.5488% 4,109,936 0.0593% - 0.0000% 5,428,581 0.0771% 48,652,200 0.2180% 32830 8,768 0.0001% 7,891 0.0001% - 0.0000% 12,593 0.0002% 29,252 0.0001% 32831 37,615 0.0005% 10,744 0.0002% - 0.0000% 14,426 0.0002% 62,784 0.0003% 32832 30,342,461 0.4257% 4,997,523 0.0721% - 0.0000% 7,872,024 0.1118% 43,212,007 0.1936% 32833 7,465,361 0.1047% 2,574,023 0.0371% - 0.0000% 3,263,146 0.0463% 13,302,530 0.0596% 32834 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 32835 12,295,651 0.1725% 9,867,277 0.1423% - 0.0000% 12,179,841 0.1730% 34,342,769 0.1539% 32836 18,527,428 0.2599% 10,036,858 0.1447% - 0.0000% 16,051,837 0.2280% 44,616,123 0.1999% 32837 60,835,154 0.8535% 13,948,160 0.2012% - 0.0000% 24,858,569 0.3530% 99,641,883 0.4464% 32839 15,040,269 0.2110% 4,493,179 0.0648% - 0.0000% 6,225,735 0.0884% 25,759,183 0.1154% 32901 436,342 0.0061% 16,307,135 0.2352% - 0.0000% 31,129,320 0.4421% 47,872,797 0.2145% 32903 575,604 0.0081% 32,933,050 0.4749% - 0.0000% 54,508,122 0.7741% 88,016,776 0.3943% 32904 1,028,140 0.0144% 25,036,622 0.3611% - 0.0000% 47,236,805 0.6708% 73,301,567 0.3284% 32905 413,027 0.0058% 20,196,649 0.2913% - 0.0000% 35,759,913 0.5079% 56,369,589 0.2526% 32907 1,365,342 0.0192% 43,175,227 0.6226% - 0.0000% 84,011,294 1.1931% 128,551,863 0.5760% 32908 378,616 0.0053% 13,453,886 0.1940% - 0.0000% 26,172,957 0.3717% 40,005,459 0.1792% 32909 987,343 0.0139% 31,260,645 0.4508% - 0.0000% 55,444,855 0.7874% 87,692,843 0.3929% 32920 391,543 0.0055% 6,237,207 0.0899% - 0.0000% 9,462,387 0.1344% 16,091,137 0.0721% 32922 357,861 0.0050% 3,218,784 0.0464% - 0.0000% 5,436,378 0.0772% 9,013,023 0.0404% 32925 270 0.0000% 11,884 0.0002% - 0.0000% 19,898 0.0003% 32,052 0.0001% 32926 1,316,152 0.0185% 8,003,344 0.1154% - 0.0000% 12,672,708 0.1800% 21,992,204 0.0985% 32927 1,875,055 0.0263% 7,947,091 0.1146% - 0.0000% 11,422,339 0.1622% 21,244,484 0.0952% 32931 698,513 0.0098% 16,114,178 0.2324% - 0.0000% 25,464,492 0.3616% 42,277,182 0.1894% 32934 868,685 0.0122% 16,946,323 0.2444% - 0.0000% 32,207,675 0.4574% 50,022,683 0.2241% 32935 1,069,633 0.0150% 37,004,927 0.5337% - 0.0000% 64,729,718 0.9193% 102,804,278 0.4606% 32937 1,121,729 0.0157% 36,566,915 0.5273% - 0.0000% 62,335,408 0.8853% 100,024,052 0.4481% 32940 2,315,591 0.0325% 31,687,531 0.4570% - 0.0000% 59,106,364 0.8394% 93,109,486 0.4172% 32948 - 0.0000% 5,597,915 0.0807% - 0.0000% 8,227,393 0.1168% 13,825,308 0.0619% 32949 - 0.0000% 4,563,229 0.0658% - 0.0000% 7,087,085 0.1006% 11,650,315 0.0522% 32950 - 0.0000% 6,805,306 0.0981% - 0.0000% 11,133,555 0.1581% 17,938,861 0.0804% 32951 392,267 0.0055% 37,775,876 0.5448% - 0.0000% 59,181,175 0.8405% 97,349,318 0.4362% 32952 1,640,102 0.0230% 27,128,159 0.3912% - 0.0000% 44,156,667 0.6271% 72,924,928 0.3267% 32953 1,385,209 0.0194% 12,200,367 0.1759% - 0.0000% 19,713,354 0.2800% 33,298,930 0.1492% 32955 2,161,571 0.0303% 28,494,331 0.4109% - 0.0000% 50,774,252 0.7211% 81,430,154 0.3648% 32958 - 0.0000% 63,102,032 0.9100% - 0.0000% 89,265,409 1.2677% 152,367,440 0.6827% 32960 - 0.0000% 36,060,929 0.5200% - 0.0000% 55,482,560 0.7880% 91,543,489 0.4101% 32962 - 0.0000% 43,749,611 0.6309% - 0.0000% 65,577,902 0.9313% 109,327,513 0.4898% 32963 - 0.0000% 168,190,048 2.4255% - 0.0000% 251,011,748 3.5648% 419,201,796 1.8782% 32966 - 0.0000% 49,008,820 0.7068% - 0.0000% 70,045,063 0.9948% 119,053,883 0.5334% 32967 - 0.0000% 60,007,386 0.8654% - 0.0000% 85,996,369 1.2213% 146,003,755 0.6541% 32968 - 0.0000% 48,866,959 0.7047% - 0.0000% 67,866,490 0.9638% 116,733,449 0.5230% 32976 - 0.0000% 19,808,980 0.2857% - 0.0000% 28,647,568 0.4068% 48,456,549 0.2171% 33001 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33004 - 0.0000% 2,455,955 0.0354% - 0.0000% 635,432 0.0090% 3,091,387 0.0139% 33009 - 0.0000% 3,797,952 0.0548% - 0.0000% 1,032,099 0.0147% 4,830,051 0.0216% 33010 - 0.0000% 1,111,340 0.0160% - 0.0000% 484,986 0.0069% 1,596,326 0.0072% 33012 - 0.0000% 2,410,355 0.0348% - 0.0000% 989,964 0.0141% 3,400,319 0.0152% 33013 - 0.0000% 1,446,246 0.0209% - 0.0000% 602,825 0.0086% 2,049,071 0.0092%

April 9, 2019 Applied Research Associates, Inc. 208 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33014 - 0.0000% 2,403,052 0.0347% - 0.0000% 920,470 0.0131% 3,323,522 0.0149% 33015 - 0.0000% 4,551,498 0.0656% - 0.0000% 1,640,443 0.0233% 6,191,941 0.0277% 33016 - 0.0000% 1,734,114 0.0250% - 0.0000% 767,424 0.0109% 2,501,537 0.0112% 33018 - 0.0000% 2,795,093 0.0403% - 0.0000% 1,150,607 0.0163% 3,945,700 0.0177% 33019 - 0.0000% 4,365,436 0.0630% - 0.0000% 1,195,206 0.0170% 5,560,642 0.0249% 33020 - 0.0000% 4,633,288 0.0668% - 0.0000% 1,269,886 0.0180% 5,903,174 0.0264% 33021 - 0.0000% 9,472,265 0.1366% - 0.0000% 2,673,963 0.0380% 12,146,228 0.0544% 33023 - 0.0000% 8,483,354 0.1223% - 0.0000% 2,531,148 0.0359% 11,014,502 0.0493% 33024 - 0.0000% 11,018,976 0.1589% - 0.0000% 3,319,578 0.0471% 14,338,554 0.0642% 33025 - 0.0000% 6,042,514 0.0871% - 0.0000% 1,985,667 0.0282% 8,028,181 0.0360% 33026 - 0.0000% 6,469,261 0.0933% - 0.0000% 2,072,638 0.0294% 8,541,899 0.0383% 33027 - 0.0000% 9,170,110 0.1322% - 0.0000% 3,627,367 0.0515% 12,797,477 0.0573% 33028 - 0.0000% 5,862,681 0.0845% - 0.0000% 2,090,730 0.0297% 7,953,410 0.0356% 33029 - 0.0000% 12,495,078 0.1802% - 0.0000% 4,114,556 0.0584% 16,609,634 0.0744% 33030 - 0.0000% 536,168 0.0077% - 0.0000% - 0.0000% 536,168 0.0024% 33031 - 0.0000% 337,259 0.0049% - 0.0000% - 0.0000% 337,259 0.0015% 33032 - 0.0000% 899,452 0.0130% - 0.0000% - 0.0000% 899,452 0.0040% 33033 - 0.0000% 991,744 0.0143% - 0.0000% - 0.0000% 991,744 0.0044% 33034 - 0.0000% 173,727 0.0025% - 0.0000% - 0.0000% 173,727 0.0008% 33035 - 0.0000% 257,840 0.0037% - 0.0000% - 0.0000% 257,840 0.0012% 33036 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33037 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33039 - 0.0000% 1,967 0.0000% - 0.0000% - 0.0000% 1,967 0.0000% 33040 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33042 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33043 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33050 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33051 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33054 - 0.0000% 1,364,730 0.0197% - 0.0000% 472,897 0.0067% 1,837,628 0.0082% 33055 - 0.0000% 3,633,808 0.0524% - 0.0000% 1,177,020 0.0167% 4,810,828 0.0216% 33056 - 0.0000% 3,053,115 0.0440% - 0.0000% 990,060 0.0141% 4,043,175 0.0181% 33060 - 0.0000% 12,319,698 0.1777% - 0.0000% 3,681,431 0.0523% 16,001,129 0.0717% 33062 - 0.0000% 17,081,772 0.2463% - 0.0000% 4,529,404 0.0643% 21,611,176 0.0968% 33063 - 0.0000% 23,284,178 0.3358% - 0.0000% 7,418,616 0.1054% 30,702,794 0.1376% 33064 - 0.0000% 32,682,193 0.4713% - 0.0000% 10,793,153 0.1533% 43,475,346 0.1948% 33065 - 0.0000% 24,074,639 0.3472% - 0.0000% 8,245,675 0.1171% 32,320,314 0.1448% 33066 - 0.0000% 7,395,301 0.1067% - 0.0000% 2,327,245 0.0331% 9,722,546 0.0436% 33067 - 0.0000% 32,221,790 0.4647% - 0.0000% 11,247,302 0.1597% 43,469,092 0.1948% 33068 - 0.0000% 14,731,867 0.2125% - 0.0000% 4,811,181 0.0683% 19,543,047 0.0876% 33069 - 0.0000% 6,112,357 0.0881% - 0.0000% 1,734,115 0.0246% 7,846,471 0.0352% 33070 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33071 - 0.0000% 27,193,972 0.3922% - 0.0000% 8,993,376 0.1277% 36,187,349 0.1621% 33073 - 0.0000% 20,194,313 0.2912% - 0.0000% 6,881,084 0.0977% 27,075,397 0.1213% 33076 - 0.0000% 41,403,731 0.5971% - 0.0000% 13,793,806 0.1959% 55,197,537 0.2473% 33109 - 0.0000% 387,588 0.0056% - 0.0000% 136,490 0.0019% 524,078 0.0023% 33122 - 0.0000% 2,826 0.0000% - 0.0000% 1,124 0.0000% 3,951 0.0000% 33125 - 0.0000% 1,033,754 0.0149% - 0.0000% 491,440 0.0070% 1,525,194 0.0068% 33126 - 0.0000% 771,684 0.0111% - 0.0000% 390,779 0.0055% 1,162,462 0.0052% 33127 - 0.0000% 715,083 0.0103% - 0.0000% 307,163 0.0044% 1,022,246 0.0046% 33128 - 0.0000% 48,855 0.0007% - 0.0000% 23,213 0.0003% 72,068 0.0003% 33129 - 0.0000% 604,928 0.0087% - 0.0000% 339,502 0.0048% 944,430 0.0042% 33130 - 0.0000% 230,364 0.0033% - 0.0000% 133,354 0.0019% 363,719 0.0016% 33131 - 0.0000% 306,891 0.0044% - 0.0000% 258,287 0.0037% 565,178 0.0025% 33132 - 0.0000% 164,155 0.0024% - 0.0000% 119,154 0.0017% 283,309 0.0013% 33133 - 0.0000% 2,345,894 0.0338% - 0.0000% 1,238,143 0.0176% 3,584,037 0.0161% 33134 - 0.0000% 2,314,000 0.0334% - 0.0000% 1,231,861 0.0175% 3,545,861 0.0159% 33135 - 0.0000% 627,637 0.0091% - 0.0000% 305,591 0.0043% 933,228 0.0042% 33136 - 0.0000% 118,292 0.0017% - 0.0000% 57,205 0.0008% 175,497 0.0008% 33137 - 0.0000% 968,589 0.0140% - 0.0000% 369,110 0.0052% 1,337,699 0.0060% 33138 - 0.0000% 2,163,222 0.0312% - 0.0000% 814,925 0.0116% 2,978,147 0.0133% 33139 - 0.0000% 2,870,378 0.0414% - 0.0000% 920,510 0.0131% 3,790,888 0.0170% 33140 - 0.0000% 5,135,956 0.0741% - 0.0000% 1,378,602 0.0196% 6,514,557 0.0292%

April 9, 2019 Applied Research Associates, Inc. 209 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33141 - 0.0000% 3,593,245 0.0518% - 0.0000% 896,558 0.0127% 4,489,804 0.0201% 33142 - 0.0000% 1,258,413 0.0181% - 0.0000% 541,413 0.0077% 1,799,826 0.0081% 33143 - 0.0000% 2,649,274 0.0382% - 0.0000% 1,521,496 0.0216% 4,170,770 0.0187% 33144 - 0.0000% 861,825 0.0124% - 0.0000% 449,623 0.0064% 1,311,448 0.0059% 33145 - 0.0000% 1,090,527 0.0157% - 0.0000% 558,848 0.0079% 1,649,374 0.0074% 33146 - 0.0000% 1,200,915 0.0173% - 0.0000% 684,953 0.0097% 1,885,869 0.0084% 33147 - 0.0000% 1,644,406 0.0237% - 0.0000% 667,597 0.0095% 2,312,002 0.0104% 33149 - 0.0000% 1,215,173 0.0175% - 0.0000% 647,539 0.0092% 1,862,711 0.0083% 33150 - 0.0000% 946,757 0.0137% - 0.0000% 376,614 0.0053% 1,323,372 0.0059% 33154 - 0.0000% 3,663,521 0.0528% - 0.0000% 994,943 0.0141% 4,658,464 0.0209% 33155 - 0.0000% 2,030,475 0.0293% - 0.0000% 1,085,589 0.0154% 3,116,065 0.0140% 33156 - 0.0000% 4,142,798 0.0597% - 0.0000% 2,582,543 0.0367% 6,725,341 0.0301% 33157 - 0.0000% 2,804,550 0.0404% - 0.0000% 1,603,851 0.0228% 4,408,401 0.0198% 33158 - 0.0000% 646,480 0.0093% - 0.0000% 398,990 0.0057% 1,045,470 0.0047% 33160 - 0.0000% 3,651,975 0.0527% - 0.0000% 1,103,494 0.0157% 4,755,469 0.0213% 33161 - 0.0000% 2,617,332 0.0377% - 0.0000% 937,933 0.0133% 3,555,265 0.0159% 33162 - 0.0000% 3,109,628 0.0448% - 0.0000% 997,193 0.0142% 4,106,822 0.0184% 33165 - 0.0000% 2,341,051 0.0338% - 0.0000% 1,271,355 0.0181% 3,612,405 0.0162% 33166 - 0.0000% 1,062,898 0.0153% - 0.0000% 486,355 0.0069% 1,549,253 0.0069% 33167 - 0.0000% 1,011,095 0.0146% - 0.0000% 374,168 0.0053% 1,385,264 0.0062% 33168 - 0.0000% 1,540,019 0.0222% - 0.0000% 555,806 0.0079% 2,095,825 0.0094% 33169 - 0.0000% 3,347,287 0.0483% - 0.0000% 1,090,010 0.0155% 4,437,297 0.0199% 33170 - 0.0000% 350,089 0.0050% - 0.0000% - 0.0000% 350,089 0.0016% 33172 - 0.0000% 473,955 0.0068% - 0.0000% 246,558 0.0035% 720,514 0.0032% 33173 - 0.0000% 1,451,781 0.0209% - 0.0000% 844,262 0.0120% 2,296,043 0.0103% 33174 - 0.0000% 905,080 0.0131% - 0.0000% 468,249 0.0066% 1,373,329 0.0062% 33175 - 0.0000% 2,386,235 0.0344% - 0.0000% 1,331,515 0.0189% 3,717,750 0.0167% 33176 - 0.0000% 2,714,052 0.0391% - 0.0000% 1,633,995 0.0232% 4,348,047 0.0195% 33177 - 0.0000% 1,644,388 0.0237% - 0.0000% 935,765 0.0133% 2,580,154 0.0116% 33178 - 0.0000% 2,460,691 0.0355% - 0.0000% 1,205,771 0.0171% 3,666,462 0.0164% 33179 - 0.0000% 4,180,676 0.0603% - 0.0000% 1,286,945 0.0183% 5,467,621 0.0245% 33180 - 0.0000% 3,084,302 0.0445% - 0.0000% 954,167 0.0136% 4,038,468 0.0181% 33181 - 0.0000% 1,328,363 0.0192% - 0.0000% 433,912 0.0062% 1,762,275 0.0079% 33182 - 0.0000% 893,354 0.0129% - 0.0000% 449,016 0.0064% 1,342,369 0.0060% 33183 - 0.0000% 1,141,885 0.0165% - 0.0000% 666,105 0.0095% 1,807,991 0.0081% 33184 - 0.0000% 852,141 0.0123% - 0.0000% 466,121 0.0066% 1,318,262 0.0059% 33185 - 0.0000% 1,522,579 0.0220% - 0.0000% 870,225 0.0124% 2,392,803 0.0107% 33186 - 0.0000% 2,702,673 0.0390% - 0.0000% 1,604,397 0.0228% 4,307,070 0.0193% 33187 - 0.0000% 778,655 0.0112% - 0.0000% 409,097 0.0058% 1,187,751 0.0053% 33189 - 0.0000% 790,929 0.0114% - 0.0000% - 0.0000% 790,929 0.0035% 33190 - 0.0000% 310,635 0.0045% - 0.0000% - 0.0000% 310,635 0.0014% 33191 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33193 - 0.0000% 1,494,271 0.0215% - 0.0000% 861,458 0.0122% 2,355,729 0.0106% 33194 - 0.0000% 302,366 0.0044% - 0.0000% 166,464 0.0024% 468,830 0.0021% 33196 - 0.0000% 1,907,775 0.0275% - 0.0000% 1,076,193 0.0153% 2,983,968 0.0134% 33199 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33301 - 0.0000% 9,437,785 0.1361% - 0.0000% 2,370,620 0.0337% 11,808,405 0.0529% 33304 - 0.0000% 6,485,595 0.0935% - 0.0000% 1,619,413 0.0230% 8,105,008 0.0363% 33305 - 0.0000% 6,535,280 0.0942% - 0.0000% 1,732,742 0.0246% 8,268,021 0.0370% 33306 - 0.0000% 2,153,736 0.0311% - 0.0000% 607,033 0.0086% 2,760,769 0.0124% 33308 - 0.0000% 18,005,627 0.2597% - 0.0000% 5,045,277 0.0717% 23,050,904 0.1033% 33309 - 0.0000% 10,994,072 0.1586% - 0.0000% 3,278,917 0.0466% 14,272,988 0.0639% 33311 - 0.0000% 11,279,730 0.1627% - 0.0000% 3,024,087 0.0429% 14,303,817 0.0641% 33312 - 0.0000% 12,371,245 0.1784% - 0.0000% 3,349,084 0.0476% 15,720,329 0.0704% 33313 - 0.0000% 9,092,658 0.1311% - 0.0000% 2,554,231 0.0363% 11,646,889 0.0522% 33314 - 0.0000% 3,105,452 0.0448% - 0.0000% 880,409 0.0125% 3,985,861 0.0179% 33315 - 0.0000% 3,705,165 0.0534% - 0.0000% 978,626 0.0139% 4,683,791 0.0210% 33316 - 0.0000% 7,424,772 0.1071% - 0.0000% 1,782,492 0.0253% 9,207,264 0.0413% 33317 - 0.0000% 12,424,702 0.1792% - 0.0000% 3,592,477 0.0510% 16,017,178 0.0718% 33319 - 0.0000% 13,103,874 0.1890% - 0.0000% 3,922,202 0.0557% 17,026,076 0.0763% 33321 - 0.0000% 19,834,691 0.2860% - 0.0000% 6,510,550 0.0925% 26,345,241 0.1180% 33322 - 0.0000% 14,058,495 0.2027% - 0.0000% 4,122,752 0.0586% 18,181,247 0.0815%

April 9, 2019 Applied Research Associates, Inc. 210 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33323 - 0.0000% 9,499,884 0.1370% - 0.0000% 2,820,234 0.0401% 12,320,118 0.0552% 33324 - 0.0000% 12,253,905 0.1767% - 0.0000% 3,773,967 0.0536% 16,027,872 0.0718% 33325 - 0.0000% 9,137,381 0.1318% - 0.0000% 2,863,786 0.0407% 12,001,167 0.0538% 33326 - 0.0000% 10,749,431 0.1550% - 0.0000% 3,365,394 0.0478% 14,114,825 0.0632% 33327 - 0.0000% 13,689,503 0.1974% - 0.0000% 3,885,796 0.0552% 17,575,300 0.0787% 33328 - 0.0000% 9,491,849 0.1369% - 0.0000% 2,923,879 0.0415% 12,415,728 0.0556% 33330 - 0.0000% 5,837,200 0.0842% - 0.0000% 2,084,709 0.0296% 7,921,909 0.0355% 33331 - 0.0000% 7,169,461 0.1034% - 0.0000% 2,675,722 0.0380% 9,845,183 0.0441% 33332 - 0.0000% 4,261,710 0.0615% - 0.0000% 1,464,202 0.0208% 5,725,912 0.0257% 33334 - 0.0000% 10,030,297 0.1447% - 0.0000% 2,991,238 0.0425% 13,021,535 0.0583% 33351 - 0.0000% 9,719,523 0.1402% - 0.0000% 2,968,792 0.0422% 12,688,314 0.0568% 33388 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33401 - 0.0000% 21,943,913 0.3165% - 0.0000% 20,752,147 0.2947% 42,696,060 0.1913% 33403 - 0.0000% 8,745,950 0.1261% - 0.0000% 9,494,956 0.1348% 18,240,906 0.0817% 33404 - 0.0000% 27,312,416 0.3939% - 0.0000% 29,040,639 0.4124% 56,353,055 0.2525% 33405 - 0.0000% 21,337,371 0.3077% - 0.0000% 19,610,143 0.2785% 40,947,514 0.1835% 33406 - 0.0000% 21,140,171 0.3049% - 0.0000% 17,668,526 0.2509% 38,808,697 0.1739% 33407 - 0.0000% 21,356,448 0.3080% - 0.0000% 21,185,495 0.3009% 42,541,943 0.1906% 33408 - 0.0000% 48,238,586 0.6957% - 0.0000% 56,162,013 0.7976% 104,400,599 0.4678% 33409 - 0.0000% 20,531,900 0.2961% - 0.0000% 18,528,518 0.2631% 39,060,417 0.1750% 33410 - 0.0000% 75,203,674 1.0845% - 0.0000% 82,387,731 1.1701% 157,591,405 0.7061% 33411 - 0.0000% 111,322,513 1.6054% - 0.0000% 90,867,991 1.2905% 202,190,504 0.9059% 33412 - 0.0000% 48,732,092 0.7028% - 0.0000% 44,127,472 0.6267% 92,859,564 0.4160% 33413 - 0.0000% 18,359,303 0.2648% - 0.0000% 14,841,448 0.2108% 33,200,751 0.1488% 33414 - 0.0000% 125,201,846 1.8056% - 0.0000% 94,409,140 1.3408% 219,610,986 0.9839% 33415 - 0.0000% 26,189,075 0.3777% - 0.0000% 20,744,924 0.2946% 46,933,999 0.2103% 33417 - 0.0000% 21,834,901 0.3149% - 0.0000% 18,503,054 0.2628% 40,337,955 0.1807% 33418 - 0.0000% 128,014,799 1.8462% - 0.0000% 130,532,307 1.8538% 258,547,106 1.1584% 33426 - 0.0000% 20,365,407 0.2937% - 0.0000% 13,477,321 0.1914% 33,842,728 0.1516% 33428 - 0.0000% 40,304,685 0.5813% - 0.0000% 15,496,803 0.2201% 55,801,488 0.2500% 33430 - 0.0000% 7,304,259 0.1053% - 0.0000% 5,164,519 0.0733% 12,468,778 0.0559% 33431 - 0.0000% 21,910,259 0.3160% - 0.0000% 9,118,434 0.1295% 31,028,693 0.1390% 33432 - 0.0000% 32,326,395 0.4662% - 0.0000% 11,457,580 0.1627% 43,783,975 0.1962% 33433 - 0.0000% 44,752,357 0.6454% - 0.0000% 17,317,266 0.2459% 62,069,624 0.2781% 33434 - 0.0000% 31,266,015 0.4509% - 0.0000% 12,918,061 0.1835% 44,184,075 0.1980% 33435 - 0.0000% 30,411,133 0.4386% - 0.0000% 19,941,090 0.2832% 50,352,223 0.2256% 33436 - 0.0000% 53,889,998 0.7772% - 0.0000% 35,638,182 0.5061% 89,528,180 0.4011% 33437 - 0.0000% 81,555,851 1.1762% - 0.0000% 49,313,341 0.7003% 130,869,192 0.5863% 33438 - 0.0000% 653,412 0.0094% - 0.0000% 549,001 0.0078% 1,202,413 0.0054% 33440 - 0.0000% 8,553,324 0.1234% - 0.0000% 6,960,886 0.0989% 15,514,210 0.0695% 33441 - 0.0000% 14,139,645 0.2039% - 0.0000% 4,993,097 0.0709% 19,132,743 0.0857% 33442 - 0.0000% 18,310,038 0.2641% - 0.0000% 6,485,683 0.0921% 24,795,721 0.1111% 33444 - 0.0000% 16,582,723 0.2391% - 0.0000% 9,051,254 0.1285% 25,633,977 0.1148% 33445 - 0.0000% 35,230,242 0.5081% - 0.0000% 18,687,819 0.2654% 53,918,061 0.2416% 33446 - 0.0000% 64,505,893 0.9303% - 0.0000% 31,458,849 0.4468% 95,964,743 0.4300% 33449 - 0.0000% 23,706,160 0.3419% - 0.0000% 16,604,231 0.2358% 40,310,390 0.1806% 33455 - 0.0000% 76,155,627 1.0983% - 0.0000% 95,158,524 1.3514% 171,314,152 0.7675% 33458 - 0.0000% 104,647,462 1.5092% - 0.0000% 114,900,076 1.6318% 219,547,538 0.9836% 33460 - 0.0000% 22,787,886 0.3286% - 0.0000% 18,577,690 0.2638% 41,365,576 0.1853% 33461 - 0.0000% 22,378,388 0.3227% - 0.0000% 17,223,382 0.2446% 39,601,769 0.1774% 33462 - 0.0000% 39,436,761 0.5687% - 0.0000% 28,842,904 0.4096% 68,279,664 0.3059% 33463 - 0.0000% 50,609,042 0.7299% - 0.0000% 37,122,714 0.5272% 87,731,756 0.3931% 33467 - 0.0000% 95,517,578 1.3775% - 0.0000% 68,377,649 0.9711% 163,895,227 0.7343% 33469 - 0.0000% 50,575,696 0.7294% - 0.0000% 62,189,791 0.8832% 112,765,488 0.5052% 33470 - 0.0000% 65,938,366 0.9509% - 0.0000% 56,313,522 0.7998% 122,251,888 0.5477% 33471 94,165 0.0013% 3,673,239 0.0530% - 0.0000% 3,858,351 0.0548% 7,625,756 0.0342% 33472 - 0.0000% 33,575,087 0.4842% - 0.0000% 22,469,163 0.3191% 56,044,250 0.2511% 33473 - 0.0000% 16,758,962 0.2417% - 0.0000% 9,972,375 0.1416% 26,731,336 0.1198% 33476 - 0.0000% 3,384,556 0.0488% - 0.0000% 2,761,447 0.0392% 6,146,003 0.0275% 33477 - 0.0000% 62,908,622 0.9072% - 0.0000% 76,168,321 1.0817% 139,076,943 0.6231% 33478 - 0.0000% 31,215,485 0.4502% - 0.0000% 31,951,525 0.4538% 63,167,010 0.2830% 33480 - 0.0000% 135,229,852 1.9502% - 0.0000% 128,583,506 1.8261% 263,813,358 1.1820%

April 9, 2019 Applied Research Associates, Inc. 211 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33483 - 0.0000% 31,822,663 0.4589% - 0.0000% 16,565,334 0.2353% 48,387,997 0.2168% 33484 - 0.0000% 32,593,862 0.4700% - 0.0000% 16,642,610 0.2364% 49,236,472 0.2206% 33486 - 0.0000% 24,242,622 0.3496% - 0.0000% 9,615,207 0.1366% 33,857,829 0.1517% 33487 - 0.0000% 31,836,380 0.4591% - 0.0000% 14,055,128 0.1996% 45,891,508 0.2056% 33493 - 0.0000% 1,272,611 0.0184% - 0.0000% 864,414 0.0123% 2,137,025 0.0096% 33496 - 0.0000% 68,655,522 0.9901% - 0.0000% 30,195,622 0.4288% 98,851,145 0.4429% 33498 - 0.0000% 30,243,429 0.4362% - 0.0000% 13,252,803 0.1882% 43,496,232 0.1949% 33510 - 0.0000% 3,191,505 0.0460% - 0.0000% 4,428,139 0.0629% 7,619,644 0.0341% 33511 - 0.0000% 5,696,390 0.0822% - 0.0000% 7,993,355 0.1135% 13,689,745 0.0613% 33513 - 0.0000% 1,665,396 0.0240% - 0.0000% 1,377,762 0.0196% 3,043,158 0.0136% 33514 - 0.0000% 262,526 0.0038% - 0.0000% 241,117 0.0034% 503,643 0.0023% 33523 - 0.0000% 2,846,655 0.0411% - 0.0000% 3,109,988 0.0442% 5,956,643 0.0267% 33525 - 0.0000% 4,297,196 0.0620% - 0.0000% 5,161,243 0.0733% 9,458,438 0.0424% 33527 - 0.0000% 1,827,975 0.0264% - 0.0000% 2,657,991 0.0377% 4,485,966 0.0201% 33534 - 0.0000% 821,262 0.0118% - 0.0000% 1,039,668 0.0148% 1,860,931 0.0083% 33538 - 0.0000% 790,327 0.0114% - 0.0000% 556,617 0.0079% 1,346,944 0.0060% 33540 - 0.0000% 1,514,686 0.0218% - 0.0000% 2,246,898 0.0319% 3,761,584 0.0169% 33541 - 0.0000% 4,120,818 0.0594% - 0.0000% 5,510,919 0.0783% 9,631,737 0.0432% 33542 - 0.0000% 3,495,813 0.0504% - 0.0000% 4,986,146 0.0708% 8,481,959 0.0380% 33543 - 0.0000% 4,703,312 0.0678% - 0.0000% 5,253,228 0.0746% 9,956,539 0.0446% 33544 - 0.0000% 3,733,617 0.0538% - 0.0000% 3,763,390 0.0534% 7,497,008 0.0336% 33545 - 0.0000% 2,256,419 0.0325% - 0.0000% 2,509,594 0.0356% 4,766,013 0.0214% 33547 - 0.0000% 4,127,607 0.0595% - 0.0000% 6,298,712 0.0895% 10,426,319 0.0467% 33548 - 0.0000% 1,462,592 0.0211% - 0.0000% 1,312,943 0.0186% 2,775,535 0.0124% 33549 - 0.0000% 3,020,857 0.0436% - 0.0000% 2,885,739 0.0410% 5,906,596 0.0265% 33556 - 0.0000% 5,778,839 0.0833% - 0.0000% 4,564,306 0.0648% 10,343,145 0.0463% 33558 - 0.0000% 3,838,416 0.0554% - 0.0000% 3,211,141 0.0456% 7,049,557 0.0316% 33559 - 0.0000% 1,820,217 0.0263% - 0.0000% 1,873,713 0.0266% 3,693,929 0.0166% 33563 - 0.0000% 2,433,744 0.0351% - 0.0000% 4,044,941 0.0574% 6,478,685 0.0290% 33565 - 0.0000% 2,777,519 0.0401% - 0.0000% 4,316,393 0.0613% 7,093,912 0.0318% 33566 - 0.0000% 3,560,882 0.0514% - 0.0000% 6,079,990 0.0863% 9,640,872 0.0432% 33567 - 0.0000% 1,488,277 0.0215% - 0.0000% 2,522,726 0.0358% 4,011,003 0.0180% 33569 - 0.0000% 4,212,840 0.0608% - 0.0000% 5,859,509 0.0832% 10,072,350 0.0451% 33570 - 0.0000% 1,772,114 0.0256% - 0.0000% 2,108,854 0.0299% 3,880,968 0.0174% 33572 - 0.0000% 3,174,256 0.0458% - 0.0000% 3,993,468 0.0567% 7,167,725 0.0321% 33573 - 0.0000% 2,895,290 0.0418% - 0.0000% 3,627,790 0.0515% 6,523,081 0.0292% 33576 - 0.0000% 1,121,828 0.0162% - 0.0000% 1,215,960 0.0173% 2,337,788 0.0105% 33578 - 0.0000% 3,005,832 0.0433% - 0.0000% 3,998,680 0.0568% 7,004,513 0.0314% 33579 - 0.0000% 2,417,808 0.0349% - 0.0000% 3,327,605 0.0473% 5,745,413 0.0257% 33584 - 0.0000% 3,355,558 0.0484% - 0.0000% 4,666,069 0.0663% 8,021,627 0.0359% 33585 - 0.0000% 292,448 0.0042% - 0.0000% 234,203 0.0033% 526,651 0.0024% 33592 - 0.0000% 1,102,870 0.0159% - 0.0000% 1,387,282 0.0197% 2,490,153 0.0112% 33594 - 0.0000% 6,021,851 0.0868% - 0.0000% 8,599,233 0.1221% 14,621,084 0.0655% 33596 - 0.0000% 4,928,436 0.0711% - 0.0000% 7,148,693 0.1015% 12,077,129 0.0541% 33597 - 0.0000% 926,050 0.0134% - 0.0000% 902,501 0.0128% 1,828,551 0.0082% 33598 - 0.0000% 930,688 0.0134% - 0.0000% 1,271,938 0.0181% 2,202,626 0.0099% 33602 - 0.0000% 1,217,317 0.0176% - 0.0000% 1,255,082 0.0178% 2,472,399 0.0111% 33603 - 0.0000% 1,571,809 0.0227% - 0.0000% 1,609,286 0.0229% 3,181,095 0.0143% 33604 - 0.0000% 2,653,456 0.0383% - 0.0000% 2,673,862 0.0380% 5,327,318 0.0239% 33605 - 0.0000% 894,845 0.0129% - 0.0000% 997,782 0.0142% 1,892,627 0.0085% 33606 - 0.0000% 3,076,999 0.0444% - 0.0000% 3,160,118 0.0449% 6,237,117 0.0279% 33607 - 0.0000% 1,371,913 0.0198% - 0.0000% 1,336,557 0.0190% 2,708,471 0.0121% 33609 - 0.0000% 2,766,325 0.0399% - 0.0000% 2,701,022 0.0384% 5,467,347 0.0245% 33610 - 0.0000% 2,012,317 0.0290% - 0.0000% 2,365,817 0.0336% 4,378,133 0.0196% 33611 - 0.0000% 3,811,652 0.0550% - 0.0000% 3,775,502 0.0536% 7,587,154 0.0340% 33612 - 0.0000% 2,725,324 0.0393% - 0.0000% 2,725,324 0.0387% 5,450,648 0.0244% 33613 - 0.0000% 2,660,692 0.0384% - 0.0000% 2,628,390 0.0373% 5,289,082 0.0237% 33614 - 0.0000% 2,481,325 0.0358% - 0.0000% 2,383,407 0.0338% 4,864,731 0.0218% 33615 - 0.0000% 3,797,181 0.0548% - 0.0000% 3,157,867 0.0448% 6,955,049 0.0312% 33616 - 0.0000% 1,119,654 0.0161% - 0.0000% 1,003,662 0.0143% 2,123,316 0.0095% 33617 - 0.0000% 3,476,114 0.0501% - 0.0000% 3,975,790 0.0565% 7,451,904 0.0334% 33618 - 0.0000% 4,023,870 0.0580% - 0.0000% 3,650,945 0.0518% 7,674,815 0.0344%

April 9, 2019 Applied Research Associates, Inc. 212 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33619 - 0.0000% 1,836,733 0.0265% - 0.0000% 2,399,767 0.0341% 4,236,501 0.0190% 33620 - 0.0000% 1,160 0.0000% - 0.0000% 1,268 0.0000% 2,428 0.0000% 33621 - 0.0000% 5,156 0.0001% - 0.0000% 5,542 0.0001% 10,699 0.0000% 33624 - 0.0000% 5,222,479 0.0753% - 0.0000% 4,601,558 0.0654% 9,824,037 0.0440% 33625 - 0.0000% 2,673,658 0.0386% - 0.0000% 2,306,917 0.0328% 4,980,575 0.0223% 33626 - 0.0000% 4,345,224 0.0627% - 0.0000% 3,419,661 0.0486% 7,764,885 0.0348% 33629 - 0.0000% 5,395,257 0.0778% - 0.0000% 5,302,631 0.0753% 10,697,888 0.0479% 33634 - 0.0000% 1,773,874 0.0256% - 0.0000% 1,514,325 0.0215% 3,288,200 0.0147% 33635 - 0.0000% 1,378,695 0.0199% - 0.0000% 1,091,709 0.0155% 2,470,404 0.0111% 33637 - 0.0000% 978,579 0.0141% - 0.0000% 1,197,046 0.0170% 2,175,625 0.0097% 33647 - 0.0000% 9,104,052 0.1313% - 0.0000% 9,849,499 0.1399% 18,953,551 0.0849% 33701 - 0.0000% 869,003 0.0125% - 0.0000% 723,568 0.0103% 1,592,571 0.0071% 33702 - 0.0000% 2,545,655 0.0367% - 0.0000% 2,009,855 0.0285% 4,555,510 0.0204% 33703 - 0.0000% 3,228,296 0.0466% - 0.0000% 2,580,355 0.0366% 5,808,651 0.0260% 33704 - 0.0000% 2,456,227 0.0354% - 0.0000% 1,935,811 0.0275% 4,392,038 0.0197% 33705 - 0.0000% 1,705,631 0.0246% - 0.0000% 1,417,796 0.0201% 3,123,427 0.0140% 33706 - 0.0000% 3,927,994 0.0566% - 0.0000% 2,545,704 0.0362% 6,473,698 0.0290% 33707 - 0.0000% 2,577,217 0.0372% - 0.0000% 1,773,092 0.0252% 4,350,309 0.0195% 33708 - 0.0000% 2,577,810 0.0372% - 0.0000% 1,457,461 0.0207% 4,035,271 0.0181% 33709 - 0.0000% 1,589,733 0.0229% - 0.0000% 1,103,062 0.0157% 2,692,795 0.0121% 33710 - 0.0000% 3,094,970 0.0446% - 0.0000% 2,166,705 0.0308% 5,261,676 0.0236% 33711 - 0.0000% 1,087,288 0.0157% - 0.0000% 842,826 0.0120% 1,930,114 0.0086% 33712 - 0.0000% 1,249,140 0.0180% - 0.0000% 1,016,629 0.0144% 2,265,769 0.0102% 33713 - 0.0000% 2,173,333 0.0313% - 0.0000% 1,625,732 0.0231% 3,799,065 0.0170% 33714 - 0.0000% 950,063 0.0137% - 0.0000% 699,804 0.0099% 1,649,867 0.0074% 33715 - 0.0000% 2,457,585 0.0354% - 0.0000% 1,630,258 0.0232% 4,087,843 0.0183% 33716 - 0.0000% 333,831 0.0048% - 0.0000% 276,234 0.0039% 610,066 0.0027% 33755 - 0.0000% 2,319,395 0.0334% - 0.0000% 1,318,651 0.0187% 3,638,046 0.0163% 33756 - 0.0000% 3,492,802 0.0504% - 0.0000% 2,048,910 0.0291% 5,541,712 0.0248% 33759 - 0.0000% 1,543,094 0.0223% - 0.0000% 1,000,179 0.0142% 2,543,273 0.0114% 33760 - 0.0000% 892,806 0.0129% - 0.0000% 596,432 0.0085% 1,489,238 0.0067% 33761 - 0.0000% 2,446,860 0.0353% - 0.0000% 1,535,848 0.0218% 3,982,708 0.0178% 33762 - 0.0000% 881,691 0.0127% - 0.0000% 633,442 0.0090% 1,515,133 0.0068% 33763 - 0.0000% 1,520,792 0.0219% - 0.0000% 925,666 0.0131% 2,446,459 0.0110% 33764 - 0.0000% 2,603,181 0.0375% - 0.0000% 1,668,492 0.0237% 4,271,674 0.0191% 33765 - 0.0000% 1,028,019 0.0148% - 0.0000% 625,298 0.0089% 1,653,317 0.0074% 33767 - 0.0000% 2,558,380 0.0369% - 0.0000% 1,200,955 0.0171% 3,759,335 0.0168% 33770 - 0.0000% 2,690,164 0.0388% - 0.0000% 1,539,345 0.0219% 4,229,509 0.0189% 33771 - 0.0000% 1,722,745 0.0248% - 0.0000% 1,013,510 0.0144% 2,736,255 0.0123% 33772 - 0.0000% 2,511,454 0.0362% - 0.0000% 1,495,542 0.0212% 4,006,996 0.0180% 33773 - 0.0000% 1,611,397 0.0232% - 0.0000% 1,026,934 0.0146% 2,638,331 0.0118% 33774 - 0.0000% 2,274,874 0.0328% - 0.0000% 1,281,549 0.0182% 3,556,422 0.0159% 33776 - 0.0000% 2,024,446 0.0292% - 0.0000% 1,173,654 0.0167% 3,198,100 0.0143% 33777 - 0.0000% 1,993,537 0.0287% - 0.0000% 1,282,928 0.0182% 3,276,464 0.0147% 33778 - 0.0000% 1,394,598 0.0201% - 0.0000% 819,557 0.0116% 2,214,156 0.0099% 33781 - 0.0000% 1,581,596 0.0228% - 0.0000% 1,116,942 0.0159% 2,698,538 0.0121% 33782 - 0.0000% 1,941,966 0.0280% - 0.0000% 1,351,851 0.0192% 3,293,818 0.0148% 33785 - 0.0000% 1,518,897 0.0219% - 0.0000% 755,982 0.0107% 2,274,879 0.0102% 33786 - 0.0000% 2,018,405 0.0291% - 0.0000% 976,197 0.0139% 2,994,602 0.0134% 33801 1,266,095 0.0178% 5,371,566 0.0775% - 0.0000% 10,758,637 0.1528% 17,396,298 0.0779% 33803 1,785,011 0.0250% 7,143,533 0.1030% - 0.0000% 14,619,074 0.2076% 23,547,618 0.1055% 33805 507,398 0.0071% 3,149,896 0.0454% - 0.0000% 6,247,312 0.0887% 9,904,605 0.0444% 33809 929,011 0.0130% 6,105,519 0.0881% - 0.0000% 11,289,773 0.1603% 18,324,303 0.0821% 33810 1,067,334 0.0150% 9,439,832 0.1361% - 0.0000% 16,871,863 0.2396% 27,379,028 0.1227% 33811 1,103,427 0.0155% 4,626,838 0.0667% - 0.0000% 9,063,861 0.1287% 14,794,126 0.0663% 33812 3,833,676 0.0538% 4,543,773 0.0655% - 0.0000% 9,999,264 0.1420% 18,376,713 0.0823% 33813 4,276,580 0.0600% 11,358,010 0.1638% - 0.0000% 23,518,398 0.3340% 39,152,988 0.1754% 33815 185,420 0.0026% 1,209,658 0.0174% - 0.0000% 2,340,413 0.0332% 3,735,491 0.0167% 33823 8,387,190 0.1177% 8,292,986 0.1196% - 0.0000% 17,862,161 0.2537% 34,542,337 0.1548% 33825 30,406,182 0.4266% 8,270,931 0.1193% - 0.0000% 21,929,771 0.3114% 60,606,884 0.2715% 33827 27,814,094 0.3902% 2,257,959 0.0326% - 0.0000% 6,255,955 0.0888% 36,328,007 0.1628% 33830 35,865,563 0.5032% 8,489,811 0.1224% - 0.0000% 19,892,244 0.2825% 64,247,618 0.2879%

April 9, 2019 Applied Research Associates, Inc. 213 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33834 13,131,294 0.1842% 852,152 0.0123% - 0.0000% 2,052,219 0.0291% 16,035,665 0.0718% 33837 20,198,223 0.2834% 7,086,639 0.1022% - 0.0000% 15,507,620 0.2202% 42,792,482 0.1917% 33838 7,276,326 0.1021% 1,326,930 0.0191% - 0.0000% 3,320,388 0.0472% 11,923,644 0.0534% 33839 3,957,061 0.0555% 1,073,827 0.0155% - 0.0000% 2,573,259 0.0365% 7,604,147 0.0341% 33841 27,576,306 0.3869% 2,230,404 0.0322% - 0.0000% 5,572,540 0.0791% 35,379,251 0.1585% 33843 21,110,021 0.2962% 3,575,984 0.0516% - 0.0000% 9,493,680 0.1348% 34,179,686 0.1531% 33844 55,831,442 0.7833% 10,604,690 0.1529% - 0.0000% 25,878,727 0.3675% 92,314,859 0.4136% 33849 - 0.0000% 130,578 0.0019% - 0.0000% 214,545 0.0030% 345,124 0.0015% 33850 5,428,262 0.0762% 2,919,481 0.0421% - 0.0000% 6,343,329 0.0901% 14,691,072 0.0658% 33852 5,791,911 0.0813% 20,071,048 0.2895% - 0.0000% 39,285,550 0.5579% 65,148,510 0.2919% 33853 57,547,595 0.8074% 4,864,661 0.0702% - 0.0000% 13,047,976 0.1853% 75,460,231 0.3381% 33857 146,087 0.0020% 1,851,394 0.0267% - 0.0000% 3,257,137 0.0463% 5,254,618 0.0235% 33859 50,167,677 0.7038% 4,000,157 0.0577% - 0.0000% 10,074,910 0.1431% 64,242,744 0.2878% 33860 1,259,068 0.0177% 4,955,538 0.0715% - 0.0000% 9,927,887 0.1410% 16,142,493 0.0723% 33865 1,694,076 0.0238% 114,638 0.0017% - 0.0000% 235,821 0.0033% 2,044,535 0.0092% 33868 494,636 0.0069% 2,234,991 0.0322% - 0.0000% 4,227,982 0.0600% 6,957,609 0.0312% 33870 14,379,283 0.2017% 10,109,876 0.1458% - 0.0000% 23,754,193 0.3374% 48,243,352 0.2161% 33872 16,275,386 0.2283% 6,445,348 0.0930% - 0.0000% 15,483,471 0.2199% 38,204,205 0.1712% 33873 86,627,370 1.2154% 2,470,672 0.0356% - 0.0000% 6,270,460 0.0891% 95,368,502 0.4273% 33875 6,804,595 0.0955% 4,367,679 0.0630% - 0.0000% 10,450,508 0.1484% 21,622,782 0.0969% 33876 2,199,285 0.0309% 4,520,360 0.0652% - 0.0000% 9,543,534 0.1355% 16,263,180 0.0729% 33880 29,482,098 0.4136% 9,710,601 0.1400% - 0.0000% 22,987,407 0.3265% 62,180,105 0.2786% 33881 26,765,822 0.3755% 10,976,258 0.1583% - 0.0000% 25,118,035 0.3567% 62,860,115 0.2816% 33884 90,300,262 1.2669% 14,440,176 0.2082% - 0.0000% 36,374,731 0.5166% 141,115,168 0.6322% 33890 64,155,771 0.9001% 947,700 0.0137% - 0.0000% 2,324,439 0.0330% 67,427,910 0.3021% 33896 5,462,752 0.0766% 2,710,522 0.0391% - 0.0000% 5,683,862 0.0807% 13,857,136 0.0621% 33897 4,302,488 0.0604% 5,452,523 0.0786% - 0.0000% 10,134,495 0.1439% 19,889,506 0.0891% 33898 104,686,143 1.4687% 8,870,271 0.1279% - 0.0000% 24,151,540 0.3430% 137,707,953 0.6170% 33901 13,616,177 0.1910% 932,756 0.0135% - 0.0000% 1,174,852 0.0167% 15,723,785 0.0704% 33903 31,340,142 0.4397% 972,877 0.0140% - 0.0000% 1,313,460 0.0187% 33,626,480 0.1507% 33904 108,169,288 1.5176% 2,480,807 0.0358% - 0.0000% 2,716,651 0.0386% 113,366,747 0.5079% 33905 7,717,191 0.1083% 1,737,308 0.0251% - 0.0000% 2,096,640 0.0298% 11,551,139 0.0518% 33907 6,885,512 0.0966% 700,580 0.0101% - 0.0000% 795,309 0.0113% 8,381,401 0.0376% 33908 35,836,884 0.5028% 2,736,222 0.0395% - 0.0000% 2,780,203 0.0395% 41,353,308 0.1853% 33909 66,931,647 0.9390% 1,323,235 0.0191% - 0.0000% 1,636,035 0.0232% 69,890,918 0.3131% 33912 8,002,271 0.1123% 1,733,419 0.0250% - 0.0000% 1,880,566 0.0267% 11,616,256 0.0520% 33913 4,681,043 0.0657% 2,049,168 0.0296% - 0.0000% 2,273,502 0.0323% 9,003,713 0.0403% 33914 163,276,397 2.2907% 2,885,382 0.0416% - 0.0000% 3,017,163 0.0428% 169,178,941 0.7580% 33916 3,576,473 0.0502% 394,648 0.0057% - 0.0000% 467,509 0.0066% 4,438,630 0.0199% 33917 28,713,112 0.4028% 1,516,929 0.0219% - 0.0000% 1,944,178 0.0276% 32,174,219 0.1442% 33919 26,149,773 0.3669% 1,850,868 0.0267% - 0.0000% 2,038,949 0.0290% 30,039,590 0.1346% 33920 738,648 0.0104% 610,434 0.0088% - 0.0000% 764,088 0.0109% 2,113,169 0.0095% 33922 90,614,355 1.2713% 256,838 0.0037% - 0.0000% 241,039 0.0034% 91,112,232 0.4082% 33924 210,603,960 2.9547% 1,666,592 0.0240% - 0.0000% 1,340,176 0.0190% 213,610,728 0.9570% 33928 4,955,755 0.0695% 2,078,993 0.0300% - 0.0000% 2,016,340 0.0286% 9,051,087 0.0406% 33931 11,302,275 0.1586% 676,605 0.0098% - 0.0000% 663,309 0.0094% 12,642,189 0.0566% 33935 563,575 0.0079% 3,266,531 0.0471% - 0.0000% 4,319,540 0.0613% 8,149,646 0.0365% 33936 1,579,919 0.0222% 1,421,786 0.0205% - 0.0000% 1,702,139 0.0242% 4,703,844 0.0211% 33946 30,156,704 0.4231% 512,061 0.0074% - 0.0000% 449,005 0.0064% 31,117,771 0.1394% 33947 46,019,958 0.6457% 926,216 0.0134% - 0.0000% 955,357 0.0136% 47,901,532 0.2146% 33948 106,065,105 1.4881% 1,304,788 0.0188% - 0.0000% 1,571,583 0.0223% 108,941,477 0.4881% 33950 615,004,202 8.6284% 2,684,795 0.0387% - 0.0000% 3,558,650 0.0505% 621,247,647 2.7834% 33952 234,021,652 3.2833% 2,091,937 0.0302% - 0.0000% 2,637,524 0.0375% 238,751,113 1.0697% 33953 27,283,522 0.3828% 589,473 0.0085% - 0.0000% 677,332 0.0096% 28,550,326 0.1279% 33954 66,364,463 0.9311% 816,137 0.0118% - 0.0000% 1,033,339 0.0147% 68,213,939 0.3056% 33955 172,383,276 2.4185% 958,394 0.0138% - 0.0000% 1,177,933 0.0167% 174,519,603 0.7819% 33956 31,818,699 0.4464% 247,168 0.0036% - 0.0000% 211,933 0.0030% 32,277,800 0.1446% 33957 215,718,517 3.0265% 1,268,654 0.0183% - 0.0000% 1,077,319 0.0153% 218,064,489 0.9770% 33960 72,622 0.0010% 370,660 0.0053% - 0.0000% 614,805 0.0087% 1,058,087 0.0047% 33966 3,118,875 0.0438% 631,189 0.0091% - 0.0000% 708,568 0.0101% 4,458,631 0.0200% 33967 3,432,552 0.0482% 1,191,709 0.0172% - 0.0000% 1,198,199 0.0170% 5,822,461 0.0261% 33971 2,208,157 0.0310% 1,396,556 0.0201% - 0.0000% 1,613,878 0.0229% 5,218,591 0.0234%

April 9, 2019 Applied Research Associates, Inc. 214 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 33972 754,218 0.0106% 956,192 0.0138% - 0.0000% 1,096,641 0.0156% 2,807,051 0.0126% 33973 707,951 0.0099% 363,646 0.0052% - 0.0000% 408,191 0.0058% 1,479,788 0.0066% 33974 637,995 0.0090% 829,608 0.0120% - 0.0000% 945,724 0.0134% 2,413,326 0.0108% 33976 908,974 0.0128% 696,154 0.0100% - 0.0000% 802,307 0.0114% 2,407,435 0.0108% 33980 177,222,023 2.4864% 908,511 0.0131% - 0.0000% 1,329,032 0.0189% 179,459,566 0.8040% 33981 66,806,225 0.9373% 805,101 0.0116% - 0.0000% 921,070 0.0131% 68,532,396 0.3070% 33982 241,651,667 3.3903% 986,732 0.0142% - 0.0000% 1,623,409 0.0231% 244,261,808 1.0944% 33983 151,358,636 2.1235% 1,479,702 0.0213% - 0.0000% 2,097,856 0.0298% 154,936,194 0.6942% 33990 71,918,811 1.0090% 1,676,098 0.0242% - 0.0000% 1,948,026 0.0277% 75,542,935 0.3385% 33991 102,490,213 1.4379% 1,261,744 0.0182% - 0.0000% 1,317,599 0.0187% 105,069,555 0.4707% 33993 163,641,973 2.2959% 1,472,517 0.0212% - 0.0000% 1,692,188 0.0240% 166,806,677 0.7474% 34102 3,244,237 0.0455% 1,667,262 0.0240% - 0.0000% 1,519,945 0.0216% 6,431,445 0.0288% 34103 1,878,124 0.0263% 1,000,263 0.0144% - 0.0000% 925,286 0.0131% 3,803,673 0.0170% 34104 1,535,602 0.0215% 995,330 0.0144% - 0.0000% 901,864 0.0128% 3,432,797 0.0154% 34105 2,563,710 0.0360% 1,624,909 0.0234% - 0.0000% 1,487,186 0.0211% 5,675,806 0.0254% 34108 3,967,025 0.0557% 1,908,583 0.0275% - 0.0000% 1,784,373 0.0253% 7,659,980 0.0343% 34109 2,867,444 0.0402% 1,724,172 0.0249% - 0.0000% 1,582,598 0.0225% 6,174,214 0.0277% 34110 4,318,130 0.0606% 2,361,454 0.0341% - 0.0000% 2,207,600 0.0314% 8,887,185 0.0398% 34112 1,799,712 0.0252% 1,089,830 0.0157% - 0.0000% 974,027 0.0138% 3,863,570 0.0173% 34113 1,403,356 0.0197% 1,020,072 0.0147% - 0.0000% 899,477 0.0128% 3,322,905 0.0149% 34114 1,046,675 0.0147% 855,825 0.0123% - 0.0000% 733,223 0.0104% 2,635,722 0.0118% 34116 973,247 0.0137% 778,459 0.0112% - 0.0000% 701,425 0.0100% 2,453,132 0.0110% 34117 696,833 0.0098% 812,704 0.0117% - 0.0000% 723,673 0.0103% 2,233,210 0.0100% 34119 3,836,100 0.0538% 2,892,279 0.0417% - 0.0000% 2,641,572 0.0375% 9,369,951 0.0420% 34120 1,800,963 0.0253% 2,148,750 0.0310% - 0.0000% 1,939,818 0.0275% 5,889,531 0.0264% 34134 5,166,362 0.0725% 2,229,226 0.0321% - 0.0000% 2,123,984 0.0302% 9,519,572 0.0427% 34135 5,320,234 0.0746% 3,074,866 0.0443% - 0.0000% 2,875,892 0.0408% 11,270,992 0.0505% 34138 - 0.0000% 6,678 0.0001% - 0.0000% 4,380 0.0001% 11,058 0.0000% 34139 - 0.0000% 19,024 0.0003% - 0.0000% 14,922 0.0002% 33,946 0.0002% 34141 - 0.0000% 8,964 0.0001% - 0.0000% 6,797 0.0001% 15,761 0.0001% 34142 156,101 0.0022% 419,408 0.0060% - 0.0000% 391,581 0.0056% 967,090 0.0043% 34145 2,161,684 0.0303% 1,551,626 0.0224% - 0.0000% 1,181,359 0.0168% 4,894,669 0.0219% 34201 - 0.0000% 840,664 0.0121% - 0.0000% 918,800 0.0130% 1,759,464 0.0079% 34202 - 0.0000% 3,462,845 0.0499% - 0.0000% 4,007,649 0.0569% 7,470,495 0.0335% 34203 - 0.0000% 2,373,998 0.0342% - 0.0000% 2,481,158 0.0352% 4,855,156 0.0218% 34205 - 0.0000% 1,535,320 0.0221% - 0.0000% 1,476,047 0.0210% 3,011,367 0.0135% 34207 - 0.0000% 1,145,509 0.0165% - 0.0000% 1,071,279 0.0152% 2,216,788 0.0099% 34208 - 0.0000% 1,725,926 0.0249% - 0.0000% 1,797,142 0.0255% 3,523,068 0.0158% 34209 - 0.0000% 3,281,305 0.0473% - 0.0000% 2,887,413 0.0410% 6,168,719 0.0276% 34210 - 0.0000% 1,094,943 0.0158% - 0.0000% 965,501 0.0137% 2,060,443 0.0092% 34211 - 0.0000% 513,422 0.0074% - 0.0000% 632,968 0.0090% 1,146,390 0.0051% 34212 - 0.0000% 2,041,161 0.0294% - 0.0000% 2,448,050 0.0348% 4,489,211 0.0201% 34215 - 0.0000% 134,956 0.0019% - 0.0000% 111,809 0.0016% 246,765 0.0011% 34216 - 0.0000% 508,607 0.0073% - 0.0000% 364,873 0.0052% 873,480 0.0039% 34217 - 0.0000% 1,513,472 0.0218% - 0.0000% 1,102,439 0.0157% 2,615,911 0.0117% 34219 - 0.0000% 2,542,992 0.0367% - 0.0000% 3,246,263 0.0461% 5,789,255 0.0259% 34221 - 0.0000% 3,014,195 0.0435% - 0.0000% 3,014,195 0.0428% 6,028,390 0.0270% 34222 - 0.0000% 852,691 0.0123% - 0.0000% 944,633 0.0134% 1,797,324 0.0081% 34223 7,394,353 0.1037% 1,570,816 0.0227% - 0.0000% 1,439,881 0.0204% 10,405,049 0.0466% 34224 34,167,927 0.4794% 1,024,762 0.0148% - 0.0000% 1,014,637 0.0144% 36,207,326 0.1622% 34228 - 0.0000% 2,590,870 0.0374% - 0.0000% 2,157,377 0.0306% 4,748,247 0.0213% 34229 - 0.0000% 1,196,020 0.0172% - 0.0000% 1,170,194 0.0166% 2,366,214 0.0106% 34231 - 0.0000% 2,367,420 0.0341% - 0.0000% 2,349,642 0.0334% 4,717,062 0.0211% 34232 - 0.0000% 2,040,594 0.0294% - 0.0000% 2,207,921 0.0314% 4,248,514 0.0190% 34233 - 0.0000% 1,303,175 0.0188% - 0.0000% 1,370,446 0.0195% 2,673,621 0.0120% 34234 - 0.0000% 799,807 0.0115% - 0.0000% 768,309 0.0109% 1,568,116 0.0070% 34235 - 0.0000% 1,057,442 0.0152% - 0.0000% 1,148,522 0.0163% 2,205,964 0.0099% 34236 - 0.0000% 1,611,719 0.0232% - 0.0000% 1,518,669 0.0216% 3,130,387 0.0140% 34237 - 0.0000% 497,734 0.0072% - 0.0000% 497,734 0.0071% 995,469 0.0045% 34238 - 0.0000% 2,142,772 0.0309% - 0.0000% 2,224,988 0.0316% 4,367,760 0.0196% 34239 - 0.0000% 1,297,949 0.0187% - 0.0000% 1,288,577 0.0183% 2,586,525 0.0116% 34240 - 0.0000% 1,707,621 0.0246% - 0.0000% 1,960,292 0.0278% 3,667,914 0.0164%

April 9, 2019 Applied Research Associates, Inc. 215 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 34241 - 0.0000% 1,650,703 0.0238% - 0.0000% 1,852,605 0.0263% 3,503,308 0.0157% 34242 - 0.0000% 1,790,139 0.0258% - 0.0000% 1,688,018 0.0240% 3,478,157 0.0156% 34243 - 0.0000% 2,488,905 0.0359% - 0.0000% 2,564,809 0.0364% 5,053,714 0.0226% 34250 - 0.0000% 93,466 0.0013% - 0.0000% 88,966 0.0013% 182,432 0.0008% 34251 1,435,176 0.0201% 853,313 0.0123% - 0.0000% 1,302,922 0.0185% 3,591,412 0.0161% 34266 402,906,183 5.6527% 3,451,695 0.0498% - 0.0000% 7,459,629 0.1059% 413,817,508 1.8540% 34269 62,319,372 0.8743% 425,951 0.0061% - 0.0000% 684,990 0.0097% 63,430,313 0.2842% 34275 - 0.0000% 1,796,325 0.0259% - 0.0000% 1,738,653 0.0247% 3,534,978 0.0158% 34285 736,976 0.0103% 1,409,305 0.0203% - 0.0000% 1,310,998 0.0186% 3,457,279 0.0155% 34286 53,346,170 0.7484% 1,511,992 0.0218% - 0.0000% 1,767,018 0.0251% 56,625,180 0.2537% 34287 35,935,637 0.5042% 1,524,593 0.0220% - 0.0000% 1,833,419 0.0260% 39,293,650 0.1760% 34288 38,510,385 0.5403% 950,267 0.0137% - 0.0000% 1,166,985 0.0166% 40,627,637 0.1820% 34289 10,114,911 0.1419% 162,579 0.0023% - 0.0000% 208,083 0.0030% 10,485,573 0.0470% 34291 3,936,254 0.0552% 412,087 0.0059% - 0.0000% 474,618 0.0067% 4,822,960 0.0216% 34292 1,333,126 0.0187% 1,484,798 0.0214% - 0.0000% 1,548,970 0.0220% 4,366,895 0.0196% 34293 2,844,735 0.0399% 2,619,208 0.0378% - 0.0000% 2,639,734 0.0375% 8,103,676 0.0363% 34420 - 0.0000% 3,537,579 0.0510% - 0.0000% 1,893,105 0.0269% 5,430,684 0.0243% 34428 - 0.0000% 1,500,076 0.0216% - 0.0000% 715,905 0.0102% 2,215,980 0.0099% 34429 - 0.0000% 1,991,870 0.0287% - 0.0000% 959,151 0.0136% 2,951,021 0.0132% 34431 - 0.0000% 1,860,300 0.0268% - 0.0000% 829,576 0.0118% 2,689,876 0.0121% 34432 - 0.0000% 3,235,995 0.0467% - 0.0000% 1,607,021 0.0228% 4,843,016 0.0217% 34433 - 0.0000% 1,351,660 0.0195% - 0.0000% 645,952 0.0092% 1,997,612 0.0089% 34434 - 0.0000% 1,567,997 0.0226% - 0.0000% 915,448 0.0130% 2,483,445 0.0111% 34436 - 0.0000% 1,371,576 0.0198% - 0.0000% 930,068 0.0132% 2,301,645 0.0103% 34442 - 0.0000% 3,850,020 0.0555% - 0.0000% 2,257,668 0.0321% 6,107,688 0.0274% 34446 - 0.0000% 4,025,307 0.0581% - 0.0000% 2,273,392 0.0323% 6,298,699 0.0282% 34448 - 0.0000% 1,720,141 0.0248% - 0.0000% 875,454 0.0124% 2,595,595 0.0116% 34449 - 0.0000% 413,325 0.0060% - 0.0000% 160,739 0.0023% 574,064 0.0026% 34450 - 0.0000% 2,078,980 0.0300% - 0.0000% 1,364,335 0.0194% 3,443,314 0.0154% 34452 - 0.0000% 1,909,436 0.0275% - 0.0000% 1,258,648 0.0179% 3,168,085 0.0142% 34453 - 0.0000% 1,904,148 0.0275% - 0.0000% 1,149,932 0.0163% 3,054,080 0.0137% 34461 - 0.0000% 2,369,868 0.0342% - 0.0000% 1,345,511 0.0191% 3,715,379 0.0166% 34465 - 0.0000% 3,916,041 0.0565% - 0.0000% 2,238,856 0.0318% 6,154,897 0.0276% 34470 - 0.0000% 3,116,827 0.0449% - 0.0000% 1,515,409 0.0215% 4,632,236 0.0208% 34471 - 0.0000% 6,493,899 0.0937% - 0.0000% 3,212,370 0.0456% 9,706,269 0.0435% 34472 - 0.0000% 5,031,777 0.0726% - 0.0000% 2,663,216 0.0378% 7,694,993 0.0345% 34473 - 0.0000% 3,582,039 0.0517% - 0.0000% 2,166,310 0.0308% 5,748,349 0.0258% 34474 - 0.0000% 2,762,635 0.0398% - 0.0000% 1,333,026 0.0189% 4,095,661 0.0183% 34475 - 0.0000% 1,222,534 0.0176% - 0.0000% 572,917 0.0081% 1,795,451 0.0080% 34476 - 0.0000% 7,308,038 0.1054% - 0.0000% 3,704,192 0.0526% 11,012,229 0.0493% 34479 - 0.0000% 2,631,489 0.0379% - 0.0000% 1,205,748 0.0171% 3,837,238 0.0172% 34480 - 0.0000% 4,918,306 0.0709% - 0.0000% 2,539,659 0.0361% 7,457,965 0.0334% 34481 - 0.0000% 4,983,538 0.0719% - 0.0000% 2,402,498 0.0341% 7,386,036 0.0331% 34482 - 0.0000% 5,245,303 0.0756% - 0.0000% 2,237,407 0.0318% 7,482,710 0.0335% 34484 - 0.0000% 1,151,755 0.0166% - 0.0000% 753,233 0.0107% 1,904,988 0.0085% 34488 - 0.0000% 1,356,206 0.0196% - 0.0000% 618,303 0.0088% 1,974,509 0.0088% 34491 - 0.0000% 8,892,850 0.1282% - 0.0000% 5,455,637 0.0775% 14,348,487 0.0643% 34498 - 0.0000% 152,160 0.0022% - 0.0000% 56,915 0.0008% 209,076 0.0009% 34601 - 0.0000% 3,120,202 0.0450% - 0.0000% 2,216,264 0.0315% 5,336,466 0.0239% 34602 - 0.0000% 1,510,881 0.0218% - 0.0000% 1,336,154 0.0190% 2,847,035 0.0128% 34604 - 0.0000% 1,567,489 0.0226% - 0.0000% 1,137,575 0.0162% 2,705,065 0.0121% 34606 - 0.0000% 5,608,039 0.0809% - 0.0000% 3,191,630 0.0453% 8,799,670 0.0394% 34607 - 0.0000% 2,081,037 0.0300% - 0.0000% 1,115,467 0.0158% 3,196,504 0.0143% 34608 - 0.0000% 6,418,548 0.0926% - 0.0000% 3,922,734 0.0557% 10,341,282 0.0463% 34609 - 0.0000% 8,545,464 0.1232% - 0.0000% 5,669,723 0.0805% 14,215,187 0.0637% 34610 - 0.0000% 1,912,381 0.0276% - 0.0000% 1,247,855 0.0177% 3,160,236 0.0142% 34613 - 0.0000% 4,090,915 0.0590% - 0.0000% 2,356,750 0.0335% 6,447,665 0.0289% 34614 - 0.0000% 1,104,495 0.0159% - 0.0000% 679,749 0.0097% 1,784,244 0.0080% 34637 - 0.0000% 1,121,544 0.0162% - 0.0000% 955,971 0.0136% 2,077,515 0.0093% 34638 - 0.0000% 3,465,459 0.0500% - 0.0000% 2,908,750 0.0413% 6,374,209 0.0286% 34639 - 0.0000% 4,760,252 0.0686% - 0.0000% 4,448,323 0.0632% 9,208,575 0.0413% 34652 - 0.0000% 3,243,491 0.0468% - 0.0000% 1,785,854 0.0254% 5,029,345 0.0225%

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Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total ZIP Code Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Commercial Percent Residential of Residential of Residential of Residential of Residential of Monetary Losses Monetary Losses Monetary Losses Monetary Losses Monetary Losses Contribution (%) Contribution (%) Contribution (%) Contribution (%) Contribution (%) ($) ($) ($) ($) ($) 34653 - 0.0000% 3,342,051 0.0482% - 0.0000% 1,947,896 0.0277% 5,289,947 0.0237% 34654 - 0.0000% 3,078,051 0.0444% - 0.0000% 2,072,629 0.0294% 5,150,679 0.0231% 34655 - 0.0000% 6,976,735 0.1006% - 0.0000% 4,659,699 0.0662% 11,636,434 0.0521% 34667 - 0.0000% 5,771,738 0.0832% - 0.0000% 3,033,710 0.0431% 8,805,448 0.0395% 34668 - 0.0000% 5,685,929 0.0820% - 0.0000% 3,018,930 0.0429% 8,704,859 0.0390% 34669 - 0.0000% 1,754,500 0.0253% - 0.0000% 1,081,916 0.0154% 2,836,417 0.0127% 34677 - 0.0000% 2,949,753 0.0425% - 0.0000% 2,041,337 0.0290% 4,991,091 0.0224% 34683 - 0.0000% 5,826,083 0.0840% - 0.0000% 3,485,681 0.0495% 9,311,763 0.0417% 34684 - 0.0000% 3,504,048 0.0505% - 0.0000% 2,109,639 0.0300% 5,613,686 0.0252% 34685 - 0.0000% 3,126,078 0.0451% - 0.0000% 2,143,622 0.0304% 5,269,700 0.0236% 34688 - 0.0000% 1,887,035 0.0272% - 0.0000% 1,273,850 0.0181% 3,160,885 0.0142% 34689 - 0.0000% 3,911,054 0.0564% - 0.0000% 2,142,221 0.0304% 6,053,276 0.0271% 34690 - 0.0000% 1,370,175 0.0198% - 0.0000% 788,124 0.0112% 2,158,298 0.0097% 34691 - 0.0000% 2,477,550 0.0357% - 0.0000% 1,309,541 0.0186% 3,787,091 0.0170% 34695 - 0.0000% 2,890,716 0.0417% - 0.0000% 1,860,385 0.0264% 4,751,102 0.0213% 34698 - 0.0000% 5,081,446 0.0733% - 0.0000% 2,920,711 0.0415% 8,002,156 0.0359% 34705 - 0.0000% 937,689 0.0135% - 0.0000% 827,585 0.0118% 1,765,274 0.0079% 34711 2,163,328 0.0304% 27,464,295 0.3961% - 0.0000% 36,053,232 0.5120% 65,680,856 0.2943% 34714 1,013,909 0.0142% 3,526,701 0.0509% - 0.0000% 5,723,697 0.0813% 10,264,307 0.0460% 34715 - 0.0000% 6,595,473 0.0951% - 0.0000% 7,211,756 0.1024% 13,807,229 0.0619% 34731 - 0.0000% 3,534,684 0.0510% - 0.0000% 2,504,697 0.0356% 6,039,381 0.0271% 34734 1,091,554 0.0153% 1,653,960 0.0239% - 0.0000% 2,010,283 0.0285% 4,755,797 0.0213% 34736 - 0.0000% 3,352,562 0.0483% - 0.0000% 3,646,840 0.0518% 6,999,403 0.0314% 34737 - 0.0000% 2,151,270 0.0310% - 0.0000% 1,785,384 0.0254% 3,936,653 0.0176% 34739 86,980 0.0012% 1,042,487 0.0150% - 0.0000% 2,164,839 0.0307% 3,294,306 0.0148% 34741 33,882,205 0.4754% 6,041,266 0.0871% - 0.0000% 12,001,360 0.1704% 51,924,831 0.2326% 34743 98,559,429 1.3828% 9,667,424 0.1394% - 0.0000% 18,742,465 0.2662% 126,969,317 0.5689% 34744 186,652,351 2.6187% 17,469,151 0.2519% - 0.0000% 35,485,878 0.5040% 239,607,379 1.0735% 34746 76,745,051 1.0767% 12,317,810 0.1776% - 0.0000% 28,125,233 0.3994% 117,188,094 0.5250% 34747 21,234,610 0.2979% 8,971,295 0.1294% - 0.0000% 17,417,813 0.2474% 47,623,717 0.2134% 34748 - 0.0000% 16,632,430 0.2399% - 0.0000% 14,047,550 0.1995% 30,679,980 0.1375% 34753 - 0.0000% 1,075,873 0.0155% - 0.0000% 1,250,594 0.0178% 2,326,467 0.0104% 34756 186,777 0.0026% 2,468,825 0.0356% - 0.0000% 2,639,349 0.0375% 5,294,951 0.0237% 34758 43,531,891 0.6107% 7,051,860 0.1017% - 0.0000% 17,060,379 0.2423% 67,644,130 0.3031% 34759 103,309,745 1.4494% 8,305,925 0.1198% - 0.0000% 20,146,983 0.2861% 131,762,652 0.5903% 34761 4,513,184 0.0633% 10,730,953 0.1548% - 0.0000% 11,590,948 0.1646% 26,835,085 0.1202% 34762 - 0.0000% 202,262 0.0029% - 0.0000% 154,561 0.0022% 356,823 0.0016% 34769 45,612,392 0.6399% 10,996,380 0.1586% - 0.0000% 23,487,767 0.3336% 80,096,540 0.3589% 34771 16,935,427 0.2376% 6,693,935 0.0965% - 0.0000% 14,955,365 0.2124% 38,584,727 0.1729% 34772 35,896,319 0.5036% 9,206,713 0.1328% - 0.0000% 23,393,533 0.3322% 68,496,565 0.3069% 34773 277,697 0.0039% 1,171,072 0.0169% - 0.0000% 2,750,143 0.0391% 4,198,912 0.0188% 34785 - 0.0000% 2,404,457 0.0347% - 0.0000% 1,677,923 0.0238% 4,082,380 0.0183% 34786 15,543,935 0.2181% 21,674,607 0.3126% - 0.0000% 29,911,812 0.4248% 67,130,353 0.3008% 34787 4,722,674 0.0663% 17,075,891 0.2463% - 0.0000% 21,991,508 0.3123% 43,790,073 0.1962% 34788 - 0.0000% 7,267,507 0.1048% - 0.0000% 4,777,241 0.0678% 12,044,748 0.0540% 34797 - 0.0000% 1,324,370 0.0191% - 0.0000% 978,225 0.0139% 2,302,595 0.0103% 34945 - 0.0000% 14,428,622 0.2081% - 0.0000% 18,761,147 0.2664% 33,189,769 0.1487% 34946 - 0.0000% 7,613,005 0.1098% - 0.0000% 10,654,651 0.1513% 18,267,656 0.0818% 34947 - 0.0000% 9,402,234 0.1356% - 0.0000% 13,033,336 0.1851% 22,435,570 0.1005% 34949 - 0.0000% 30,147,197 0.4348% - 0.0000% 48,543,775 0.6894% 78,690,972 0.3526% 34950 - 0.0000% 14,694,379 0.2119% - 0.0000% 20,732,386 0.2944% 35,426,765 0.1587% 34951 - 0.0000% 41,914,452 0.6045% - 0.0000% 58,704,639 0.8337% 100,619,092 0.4508% 34952 - 0.0000% 79,222,788 1.1425% - 0.0000% 103,123,877 1.4645% 182,346,665 0.8170% 34953 - 0.0000% 138,968,002 2.0041% - 0.0000% 173,824,258 2.4686% 312,792,259 1.4014% 34956 - 0.0000% 7,995,910 0.1153% - 0.0000% 8,285,884 0.1177% 16,281,794 0.0729% 34957 - 0.0000% 62,854,996 0.9065% - 0.0000% 86,361,241 1.2265% 149,216,238 0.6685% 34972 247,736 0.0035% 22,022,941 0.3176% - 0.0000% 26,246,849 0.3728% 48,517,525 0.2174% 34974 439,651 0.0062% 47,209,933 0.6808% - 0.0000% 49,729,541 0.7062% 97,379,124 0.4363% 34981 - 0.0000% 5,821,036 0.0839% - 0.0000% 7,761,029 0.1102% 13,582,065 0.0609% 34982 - 0.0000% 40,305,009 0.5813% - 0.0000% 55,696,973 0.7910% 96,001,983 0.4301% 34983 - 0.0000% 77,486,724 1.1175% - 0.0000% 101,714,028 1.4445% 179,200,752 0.8029% 34984 - 0.0000% 37,110,562 0.5352% - 0.0000% 47,556,897 0.6754% 84,667,459 0.3793%

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April 9, 2019 Applied Research Associates, Inc. 218 Appendix A - Forms 4/9/2019 11:00 AM

Figure 57. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Charley

Figure 58. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Frances

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Figure 59. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Ivan

Figure 60. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Jeanne

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Figure 61. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for All Four of the 2004 Hurricanes

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Form A-3B: 2004 Hurricane Season Losses (2017 FHCF Exposure Data) A. Provide the percentage of residential zero deductible hurricane losses, rounded to four decimal places, and the monetary contribution from Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) for each affected ZIP Code, individually and in total. Include all ZIP Codes where hurricane losses are equal to or greater than $500,000. Use the 2017 Florida Hurricane Catastrophe Fund personal and commercial residential zero exposure exposure data provided in the file named “hlpm2017c.exe.” Rather than using directly a specified published windfield, the winds underlying the hurricane loss cost calculations must be produced by the hurricane model being evaluated and should be the same hurricane parameters as used in completing Form A-2A, Base Hurricane Storm Set Statewide Hurricane Losses (2017 FHCF Exposure Data). B. Provide maps color-coded by ZIP Code depicting the percentage of total residential hurricane losses from each hurricane, Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004), and for the cumulative hurricane losses using the following interval coding:

Red Over 5% Light Red 2% to 5% Pink 1% to 2% Light Pink 0.5% to 1% Light Blue 0.2% to 0.5% Medium Blue 0.1% to 0.2% Blue Below 0.1% Plot the relevant storm track on each map. C. Provide this form in Excel format. The file name should include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-3B, 2004 Hurricane Season Losses (2017 FHCF Exposure Data), in a submission appendix.

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Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32003 - 0.0000% 2,704,844 0.0383% - 0.0000% 1,954,667 0.0271% 4,659,511 0.0204% 32008 - 0.0000% 537,119 0.0076% - 0.0000% 194,014 0.0027% 731,133 0.0032% 32009 - 0.0000% 127,153 0.0018% - 0.0000% 103,353 0.0014% 230,506 0.0010% 32011 - 0.0000% 484,375 0.0069% - 0.0000% 377,621 0.0052% 861,996 0.0038% 32013 - 0.0000% 690 0.0000% - 0.0000% 284 0.0000% 975 0.0000% 32024 - 0.0000% 1,889,010 0.0268% - 0.0000% 1,082,019 0.0150% 2,971,029 0.0130% 32025 - 0.0000% 1,246,394 0.0177% - 0.0000% 892,077 0.0124% 2,138,471 0.0093% 32033 - 0.0000% 421,863 0.0060% - 0.0000% 234,395 0.0033% 656,258 0.0029% 32034 - 0.0000% 2,208,826 0.0313% - 0.0000% - 0.0000% 2,208,826 0.0097% 32038 - 0.0000% 1,120,935 0.0159% - 0.0000% 423,932 0.0059% 1,544,867 0.0068% 32040 - 0.0000% 303,722 0.0043% - 0.0000% 239,589 0.0033% 543,311 0.0024% 32043 - 0.0000% 1,981,359 0.0281% - 0.0000% 1,397,706 0.0194% 3,379,066 0.0148% 32044 - 0.0000% 126,467 0.0018% - 0.0000% 80,857 0.0011% 207,324 0.0009% 32046 - 0.0000% 232,870 0.0033% - 0.0000% 191,735 0.0027% 424,604 0.0019% 32052 - 0.0000% 193,673 0.0027% - 0.0000% 181,943 0.0025% 375,616 0.0016% 32053 - 0.0000% 114,426 0.0016% - 0.0000% 88,080 0.0012% 202,506 0.0009% 32054 - 0.0000% 674,266 0.0096% - 0.0000% 424,086 0.0059% 1,098,352 0.0048% 32055 - 0.0000% 832,726 0.0118% - 0.0000% 672,967 0.0093% 1,505,693 0.0066% 32058 - 0.0000% 148,800 0.0021% - 0.0000% 104,616 0.0015% 253,416 0.0011% 32059 - 0.0000% 104,876 0.0015% - 0.0000% 61,213 0.0008% 166,089 0.0007% 32060 - 0.0000% 1,073,889 0.0152% - 0.0000% 567,608 0.0079% 1,641,497 0.0072% 32061 - 0.0000% 21,161 0.0003% - 0.0000% 13,096 0.0002% 34,256 0.0001% 32062 - 0.0000% 198,079 0.0028% - 0.0000% 79,477 0.0011% 277,556 0.0012% 32063 - 0.0000% 588,160 0.0083% - 0.0000% 463,528 0.0064% 1,051,689 0.0046% 32064 - 0.0000% 240,330 0.0034% - 0.0000% 172,295 0.0024% 412,625 0.0018% 32065 - 0.0000% 2,364,184 0.0335% - 0.0000% 1,843,781 0.0256% 4,207,965 0.0184% 32066 - 0.0000% 320,727 0.0045% - 0.0000% 128,462 0.0018% 449,189 0.0020% 32068 - 0.0000% 3,328,042 0.0471% - 0.0000% 2,483,690 0.0345% 5,811,731 0.0254% 32071 - 0.0000% 385,316 0.0055% - 0.0000% 118,044 0.0016% 503,360 0.0022% 32073 - 0.0000% 2,462,713 0.0349% - 0.0000% 1,847,161 0.0256% 4,309,874 0.0188% 32080 - 0.0000% 3,592,097 0.0509% - 0.0000% 1,626,204 0.0226% 5,218,302 0.0228% 32081 - 0.0000% 1,717,489 0.0243% - 0.0000% 1,287,420 0.0179% 3,004,909 0.0131% 32082 - 0.0000% 4,451,894 0.0631% - 0.0000% 3,118,358 0.0433% 7,570,252 0.0331% 32083 - 0.0000% 39,652 0.0006% - 0.0000% 26,471 0.0004% 66,123 0.0003% 32084 - 0.0000% 1,951,547 0.0276% - 0.0000% 1,235,404 0.0171% 3,186,952 0.0139% 32086 - 0.0000% 2,324,418 0.0329% - 0.0000% 1,378,227 0.0191% 3,702,645 0.0162% 32087 - 0.0000% 107,072 0.0015% - 0.0000% 85,494 0.0012% 192,566 0.0008% 32091 - 0.0000% 897,425 0.0127% - 0.0000% 604,989 0.0084% 1,502,414 0.0066% 32092 - 0.0000% 3,108,867 0.0440% - 0.0000% 2,216,968 0.0308% 5,325,836 0.0233% 32094 - 0.0000% 179,893 0.0025% - 0.0000% 110,801 0.0015% 290,694 0.0013% 32095 - 0.0000% 1,023,269 0.0145% - 0.0000% 734,180 0.0102% 1,757,449 0.0077% 32096 - 0.0000% 100,049 0.0014% - 0.0000% 95,314 0.0013% 195,363 0.0009% 32097 - 0.0000% 693,490 0.0098% - 0.0000% - 0.0000% 693,490 0.0030% 32102 - 0.0000% 533,829 0.0076% - 0.0000% 184,035 0.0026% 717,865 0.0031% 32110 - 0.0000% 502,206 0.0071% - 0.0000% 191,514 0.0027% 693,720 0.0030% 32112 - 0.0000% 821,646 0.0116% - 0.0000% 323,236 0.0045% 1,144,882 0.0050% 32113 - 0.0000% 943,353 0.0134% - 0.0000% 449,297 0.0062% 1,392,650 0.0061% 32114 3,111,197 0.0425% 1,690,131 0.0239% - 0.0000% 603,246 0.0084% 5,404,574 0.0236% 32117 2,928,306 0.0400% 2,151,690 0.0305% - 0.0000% 774,292 0.0107% 5,854,288 0.0256% 32118 9,290,104 0.1269% 3,616,905 0.0512% - 0.0000% 1,114,517 0.0155% 14,021,525 0.0613% 32119 8,230,236 0.1124% 3,086,590 0.0437% - 0.0000% 1,127,707 0.0156% 12,444,533 0.0544% 32124 632,516 0.0086% 799,257 0.0113% - 0.0000% 387,601 0.0054% 1,819,375 0.0080% 32127 28,877,052 0.3945% 5,887,667 0.0834% - 0.0000% 2,356,224 0.0327% 37,120,943 0.1623% 32128 13,458,019 0.1838% 4,806,052 0.0681% - 0.0000% 2,110,639 0.0293% 20,374,710 0.0891% 32129 8,734,232 0.1193% 2,906,747 0.0412% - 0.0000% 1,120,400 0.0155% 12,761,379 0.0558% 32130 163,123 0.0022% 870,586 0.0123% - 0.0000% 322,827 0.0045% 1,356,536 0.0059% 32131 - 0.0000% 398,109 0.0056% - 0.0000% 194,711 0.0027% 592,820 0.0026% 32132 8,338,403 0.1139% 1,372,641 0.0194% - 0.0000% 750,930 0.0104% 10,461,975 0.0457% 32134 - 0.0000% 1,078,073 0.0153% - 0.0000% 491,412 0.0068% 1,569,485 0.0069% 32136 622,505 0.0085% 1,458,574 0.0207% - 0.0000% 588,797 0.0082% 2,669,876 0.0117% 32137 - 0.0000% 6,499,611 0.0921% - 0.0000% 3,496,096 0.0485% 9,995,707 0.0437% 32139 - 0.0000% 192,805 0.0027% - 0.0000% 59,493 0.0008% 252,298 0.0011%

April 9, 2019 Applied Research Associates, Inc. 223 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32140 - 0.0000% 120,722 0.0017% - 0.0000% 73,036 0.0010% 193,757 0.0008% 32141 14,679,272 0.2005% 3,083,233 0.0437% - 0.0000% 1,851,396 0.0257% 19,613,902 0.0857% 32145 - 0.0000% 216,234 0.0031% - 0.0000% 104,298 0.0014% 320,531 0.0014% 32148 - 0.0000% 800,014 0.0113% - 0.0000% 375,107 0.0052% 1,175,122 0.0051% 32159 - 0.0000% 15,751,282 0.2231% - 0.0000% 9,804,839 0.1360% 25,556,122 0.1117% 32162 - 0.0000% 27,610,154 0.3911% - 0.0000% 19,316,550 0.2679% 46,926,704 0.2051% 32163 - 0.0000% 12,117,424 0.1716% - 0.0000% 9,341,605 0.1296% 21,459,029 0.0938% 32164 - 0.0000% 5,367,449 0.0760% - 0.0000% 2,761,874 0.0383% 8,129,323 0.0355% 32168 29,248,521 0.3996% 5,011,664 0.0710% - 0.0000% 2,517,643 0.0349% 36,777,828 0.1608% 32169 38,728,831 0.5291% 5,439,571 0.0771% - 0.0000% 2,596,709 0.0360% 46,765,111 0.2044% 32174 7,529,257 0.1029% 9,228,497 0.1307% - 0.0000% 3,766,995 0.0523% 20,524,749 0.0897% 32176 6,637,088 0.0907% 5,507,667 0.0780% - 0.0000% 1,471,658 0.0204% 13,616,413 0.0595% 32177 - 0.0000% 1,897,101 0.0269% - 0.0000% 985,371 0.0137% 2,882,473 0.0126% 32179 - 0.0000% 1,531,304 0.0217% - 0.0000% 757,732 0.0105% 2,289,036 0.0100% 32180 - 0.0000% 439,934 0.0062% - 0.0000% 163,971 0.0023% 603,906 0.0026% 32181 - 0.0000% 272,413 0.0039% - 0.0000% 108,866 0.0015% 381,279 0.0017% 32187 - 0.0000% 165,832 0.0023% - 0.0000% 76,383 0.0011% 242,214 0.0011% 32189 - 0.0000% 453,811 0.0064% - 0.0000% 178,337 0.0025% 632,149 0.0028% 32190 - 0.0000% 99,300 0.0014% - 0.0000% 37,116 0.0005% 136,416 0.0006% 32195 - 0.0000% 1,176,153 0.0167% - 0.0000% 694,552 0.0096% 1,870,705 0.0082% 32202 - 0.0000% 38,794 0.0005% - 0.0000% 34,958 0.0005% 73,752 0.0003% 32204 - 0.0000% 244,139 0.0035% - 0.0000% 180,732 0.0025% 424,871 0.0019% 32205 - 0.0000% 1,458,949 0.0207% - 0.0000% 1,121,265 0.0156% 2,580,214 0.0113% 32206 - 0.0000% 356,729 0.0051% - 0.0000% 265,372 0.0037% 622,101 0.0027% 32207 - 0.0000% 1,575,597 0.0223% - 0.0000% 1,184,353 0.0164% 2,759,950 0.0121% 32208 - 0.0000% 782,043 0.0111% - 0.0000% 590,067 0.0082% 1,372,110 0.0060% 32209 - 0.0000% 551,038 0.0078% - 0.0000% 416,937 0.0058% 967,975 0.0042% 32210 - 0.0000% 2,779,292 0.0394% - 0.0000% 2,060,510 0.0286% 4,839,802 0.0212% 32211 - 0.0000% 885,669 0.0125% - 0.0000% 657,954 0.0091% 1,543,623 0.0067% 32212 - 0.0000% 789 0.0000% - 0.0000% 209 0.0000% 998 0.0000% 32216 - 0.0000% 1,252,390 0.0177% - 0.0000% 933,021 0.0129% 2,185,411 0.0096% 32217 - 0.0000% 1,021,786 0.0145% - 0.0000% 755,207 0.0105% 1,776,993 0.0078% 32218 - 0.0000% 2,221,653 0.0315% - 0.0000% 1,803,391 0.0250% 4,025,044 0.0176% 32219 - 0.0000% 463,787 0.0066% - 0.0000% 372,922 0.0052% 836,709 0.0037% 32220 - 0.0000% 523,966 0.0074% - 0.0000% 414,526 0.0058% 938,492 0.0041% 32221 - 0.0000% 1,439,083 0.0204% - 0.0000% 1,122,705 0.0156% 2,561,789 0.0112% 32222 - 0.0000% 573,405 0.0081% - 0.0000% 451,955 0.0063% 1,025,360 0.0045% 32223 - 0.0000% 2,053,666 0.0291% - 0.0000% 1,526,757 0.0212% 3,580,423 0.0157% 32224 - 0.0000% 2,137,957 0.0303% - 0.0000% 1,582,990 0.0220% 3,720,947 0.0163% 32225 - 0.0000% 2,697,413 0.0382% - 0.0000% 1,974,971 0.0274% 4,672,383 0.0204% 32226 - 0.0000% 866,054 0.0123% - 0.0000% 620,513 0.0086% 1,486,567 0.0065% 32227 - 0.0000% 182 0.0000% - 0.0000% 126 0.0000% 308 0.0000% 32233 - 0.0000% 1,018,963 0.0144% - 0.0000% 738,984 0.0103% 1,757,947 0.0077% 32234 - 0.0000% 302,549 0.0043% - 0.0000% 233,648 0.0032% 536,197 0.0023% 32244 - 0.0000% 2,361,615 0.0335% - 0.0000% 1,840,229 0.0255% 4,201,844 0.0184% 32246 - 0.0000% 1,735,964 0.0246% - 0.0000% 1,294,337 0.0180% 3,030,302 0.0132% 32250 - 0.0000% 1,462,293 0.0207% - 0.0000% 1,057,589 0.0147% 2,519,883 0.0110% 32254 - 0.0000% 243,619 0.0035% - 0.0000% 188,495 0.0026% 432,114 0.0019% 32256 - 0.0000% 1,830,563 0.0259% - 0.0000% 1,396,324 0.0194% 3,226,887 0.0141% 32257 - 0.0000% 1,973,032 0.0279% - 0.0000% 1,499,712 0.0208% 3,472,744 0.0152% 32258 - 0.0000% 2,116,698 0.0300% - 0.0000% 1,634,685 0.0227% 3,751,383 0.0164% 32259 - 0.0000% 4,605,800 0.0652% - 0.0000% 3,492,251 0.0484% 8,098,051 0.0354% 32266 - 0.0000% 460,789 0.0065% - 0.0000% 338,778 0.0047% 799,567 0.0035% 32277 - 0.0000% 1,157,839 0.0164% - 0.0000% 737,259 0.0102% 1,895,098 0.0083% 32301 - 0.0000% 781,650 0.0111% - 0.0000% - 0.0000% 781,650 0.0034% 32303 - 0.0000% 1,851,774 0.0262% - 0.0000% - 0.0000% 1,851,774 0.0081% 32304 - 0.0000% 413,666 0.0059% - 0.0000% - 0.0000% 413,666 0.0018% 32305 - 0.0000% 423,959 0.0060% - 0.0000% - 0.0000% 423,959 0.0019% 32308 - 0.0000% 1,274,227 0.0180% - 0.0000% - 0.0000% 1,274,227 0.0056% 32309 - 0.0000% 2,321,511 0.0329% - 0.0000% - 0.0000% 2,321,511 0.0101% 32310 - 0.0000% 311,029 0.0044% - 0.0000% - 0.0000% 311,029 0.0014% 32311 - 0.0000% 1,103,133 0.0156% - 0.0000% - 0.0000% 1,103,133 0.0048%

April 9, 2019 Applied Research Associates, Inc. 224 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32312 - 0.0000% 2,985,167 0.0423% - 0.0000% - 0.0000% 2,985,167 0.0130% 32317 - 0.0000% 989,351 0.0140% - 0.0000% - 0.0000% 989,351 0.0043% 32320 - 0.0000% 83,157 0.0012% 84,191 0.0065% - 0.0000% 167,348 0.0007% 32321 - 0.0000% 73,656 0.0010% 64,192 0.0050% - 0.0000% 137,847 0.0006% 32322 - 0.0000% 105,731 0.0015% - 0.0000% - 0.0000% 105,731 0.0005% 32324 - 0.0000% 61,121 0.0009% - 0.0000% - 0.0000% 61,121 0.0003% 32327 - 0.0000% 1,008,638 0.0143% - 0.0000% - 0.0000% 1,008,638 0.0044% 32328 - 0.0000% 263,963 0.0037% 217,541 0.0169% - 0.0000% 481,504 0.0021% 32331 - 0.0000% 121,160 0.0017% - 0.0000% 64,528 0.0009% 185,688 0.0008% 32332 - 0.0000% 10,349 0.0001% - 0.0000% - 0.0000% 10,349 0.0000% 32333 - 0.0000% 501,140 0.0071% - 0.0000% - 0.0000% 501,140 0.0022% 32334 - 0.0000% 29,973 0.0004% - 0.0000% - 0.0000% 29,973 0.0001% 32336 - 0.0000% 45,655 0.0006% - 0.0000% - 0.0000% 45,655 0.0002% 32340 - 0.0000% 372,214 0.0053% - 0.0000% 236,052 0.0033% 608,266 0.0027% 32344 - 0.0000% 547,916 0.0078% - 0.0000% - 0.0000% 547,916 0.0024% 32346 - 0.0000% 159,252 0.0023% - 0.0000% - 0.0000% 159,252 0.0007% 32347 - 0.0000% 378,446 0.0054% - 0.0000% 125,880 0.0017% 504,326 0.0022% 32348 - 0.0000% 389,925 0.0055% - 0.0000% - 0.0000% 389,925 0.0017% 32350 - 0.0000% 55,774 0.0008% - 0.0000% 39,941 0.0006% 95,715 0.0004% 32351 - 0.0000% 347,968 0.0049% - 0.0000% - 0.0000% 347,968 0.0015% 32352 - 0.0000% 117,501 0.0017% - 0.0000% - 0.0000% 117,501 0.0005% 32356 - 0.0000% 3,975 0.0001% - 0.0000% 1,149 0.0000% 5,124 0.0000% 32358 - 0.0000% 100,846 0.0014% - 0.0000% - 0.0000% 100,846 0.0004% 32359 - 0.0000% 216,050 0.0031% - 0.0000% 60,204 0.0008% 276,254 0.0012% 32401 - 0.0000% - 0.0000% 831,788 0.0646% - 0.0000% 831,788 0.0036% 32403 - 0.0000% - 0.0000% 21,608 0.0017% - 0.0000% 21,608 0.0001% 32404 - 0.0000% - 0.0000% 1,598,017 0.1241% - 0.0000% 1,598,017 0.0070% 32405 - 0.0000% - 0.0000% 1,401,722 0.1089% - 0.0000% 1,401,722 0.0061% 32407 - 0.0000% - 0.0000% 740,287 0.0575% - 0.0000% 740,287 0.0032% 32408 - 0.0000% - 0.0000% 1,836,545 0.1427% - 0.0000% 1,836,545 0.0080% 32409 - 0.0000% - 0.0000% 425,312 0.0330% - 0.0000% 425,312 0.0019% 32413 - 0.0000% - 0.0000% 3,180,685 0.2471% - 0.0000% 3,180,685 0.0139% 32420 - 0.0000% - 0.0000% 75,746 0.0059% - 0.0000% 75,746 0.0003% 32421 - 0.0000% - 0.0000% 70,630 0.0055% - 0.0000% 70,630 0.0003% 32423 - 0.0000% - 0.0000% 21,634 0.0017% - 0.0000% 21,634 0.0001% 32424 - 0.0000% - 0.0000% 107,967 0.0084% - 0.0000% 107,967 0.0005% 32425 - 0.0000% - 0.0000% 344,611 0.0268% - 0.0000% 344,611 0.0015% 32426 - 0.0000% - 0.0000% 18,169 0.0014% - 0.0000% 18,169 0.0001% 32427 - 0.0000% - 0.0000% 28,216 0.0022% - 0.0000% 28,216 0.0001% 32428 - 0.0000% - 0.0000% 521,307 0.0405% - 0.0000% 521,307 0.0023% 32430 - 0.0000% - 0.0000% 22,418 0.0017% - 0.0000% 22,418 0.0001% 32431 - 0.0000% - 0.0000% 95,776 0.0074% - 0.0000% 95,776 0.0004% 32433 - 0.0000% - 0.0000% 1,038,939 0.0807% - 0.0000% 1,038,939 0.0045% 32435 - 0.0000% - 0.0000% 425,282 0.0330% - 0.0000% 425,282 0.0019% 32437 - 0.0000% - 0.0000% 11,417 0.0009% - 0.0000% 11,417 0.0000% 32438 - 0.0000% - 0.0000% 38,897 0.0030% - 0.0000% 38,897 0.0002% 32439 - 0.0000% - 0.0000% 1,096,453 0.0852% - 0.0000% 1,096,453 0.0048% 32440 - 0.0000% - 0.0000% 146,208 0.0114% - 0.0000% 146,208 0.0006% 32442 - 0.0000% - 0.0000% 54,944 0.0043% - 0.0000% 54,944 0.0002% 32443 - 0.0000% - 0.0000% 50,578 0.0039% - 0.0000% 50,578 0.0002% 32444 - 0.0000% - 0.0000% 1,288,113 0.1001% - 0.0000% 1,288,113 0.0056% 32445 - 0.0000% - 0.0000% 21,654 0.0017% - 0.0000% 21,654 0.0001% 32446 - 0.0000% - 0.0000% 304,750 0.0237% - 0.0000% 304,750 0.0013% 32448 - 0.0000% - 0.0000% 148,725 0.0116% - 0.0000% 148,725 0.0007% 32449 - 0.0000% - 0.0000% 8,098 0.0006% - 0.0000% 8,098 0.0000% 32455 - 0.0000% - 0.0000% 146,441 0.0114% - 0.0000% 146,441 0.0006% 32456 - 0.0000% - 0.0000% 587,314 0.0456% - 0.0000% 587,314 0.0026% 32459 - 0.0000% - 0.0000% 8,432,139 0.6550% - 0.0000% 8,432,139 0.0369% 32460 - 0.0000% 65,244 0.0009% - 0.0000% - 0.0000% 65,244 0.0003% 32462 - 0.0000% - 0.0000% 94,095 0.0073% - 0.0000% 94,095 0.0004% 32464 - 0.0000% - 0.0000% 133,208 0.0103% - 0.0000% 133,208 0.0006% 32465 - 0.0000% - 0.0000% 105,795 0.0082% - 0.0000% 105,795 0.0005%

April 9, 2019 Applied Research Associates, Inc. 225 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32466 - 0.0000% - 0.0000% 147,947 0.0115% - 0.0000% 147,947 0.0006% 32501 - 0.0000% - 0.0000% 22,171,664 1.7222% - 0.0000% 22,171,664 0.0969% 32502 - 0.0000% - 0.0000% 11,755,200 0.9131% - 0.0000% 11,755,200 0.0514% 32503 - 0.0000% - 0.0000% 79,058,233 6.1410% - 0.0000% 79,058,233 0.3456% 32504 - 0.0000% - 0.0000% 62,228,377 4.8337% - 0.0000% 62,228,377 0.2720% 32505 - 0.0000% - 0.0000% 35,404,038 2.7501% - 0.0000% 35,404,038 0.1548% 32506 - 0.0000% - 0.0000% 76,727,816 5.9600% - 0.0000% 76,727,816 0.3354% 32507 - 0.0000% - 0.0000% 151,924,117 11.8010% - 0.0000% 151,924,117 0.6641% 32508 - 0.0000% - 0.0000% 84,877 0.0066% - 0.0000% 84,877 0.0004% 32509 - 0.0000% - 0.0000% 55 0.0000% - 0.0000% 55 0.0000% 32511 - 0.0000% - 0.0000% 39,489 0.0031% - 0.0000% 39,489 0.0002% 32514 - 0.0000% - 0.0000% 82,449,283 6.4044% - 0.0000% 82,449,283 0.3604% 32526 - 0.0000% - 0.0000% 98,791,540 7.6738% - 0.0000% 98,791,540 0.4319% 32531 - 0.0000% - 0.0000% 2,190,015 0.1701% - 0.0000% 2,190,015 0.0096% 32533 - 0.0000% - 0.0000% 75,856,851 5.8923% - 0.0000% 75,856,851 0.3316% 32534 - 0.0000% - 0.0000% 29,280,959 2.2744% - 0.0000% 29,280,959 0.1280% 32535 - 0.0000% - 0.0000% 4,417,263 0.3431% - 0.0000% 4,417,263 0.0193% 32536 - 0.0000% - 0.0000% 7,206,403 0.5598% - 0.0000% 7,206,403 0.0315% 32539 - 0.0000% - 0.0000% 6,724,090 0.5223% - 0.0000% 6,724,090 0.0294% 32541 - 0.0000% - 0.0000% 17,374,779 1.3496% - 0.0000% 17,374,779 0.0760% 32542 - 0.0000% - 0.0000% 13,904 0.0011% - 0.0000% 13,904 0.0001% 32544 - 0.0000% - 0.0000% 13,167 0.0010% - 0.0000% 13,167 0.0001% 32547 - 0.0000% - 0.0000% 16,186,396 1.2573% - 0.0000% 16,186,396 0.0708% 32548 - 0.0000% - 0.0000% 18,207,206 1.4143% - 0.0000% 18,207,206 0.0796% 32550 - 0.0000% - 0.0000% 8,242,206 0.6402% - 0.0000% 8,242,206 0.0360% 32561 - 0.0000% - 0.0000% 89,055,957 6.9176% - 0.0000% 89,055,957 0.3893% 32563 - 0.0000% - 0.0000% 91,302,623 7.0921% - 0.0000% 91,302,623 0.3991% 32564 - 0.0000% - 0.0000% 919,601 0.0714% - 0.0000% 919,601 0.0040% 32565 - 0.0000% - 0.0000% 7,282,919 0.5657% - 0.0000% 7,282,919 0.0318% 32566 - 0.0000% - 0.0000% 62,009,545 4.8167% - 0.0000% 62,009,545 0.2711% 32567 - 0.0000% - 0.0000% 579,507 0.0450% - 0.0000% 579,507 0.0025% 32568 - 0.0000% - 0.0000% 4,041,954 0.3140% - 0.0000% 4,041,954 0.0177% 32569 - 0.0000% - 0.0000% 13,726,548 1.0662% - 0.0000% 13,726,548 0.0600% 32570 - 0.0000% - 0.0000% 37,505,766 2.9133% - 0.0000% 37,505,766 0.1640% 32571 - 0.0000% - 0.0000% 68,952,564 5.3560% - 0.0000% 68,952,564 0.3014% 32577 - 0.0000% - 0.0000% 10,934,985 0.8494% - 0.0000% 10,934,985 0.0478% 32578 - 0.0000% - 0.0000% 12,278,398 0.9537% - 0.0000% 12,278,398 0.0537% 32579 - 0.0000% - 0.0000% 7,997,892 0.6213% - 0.0000% 7,997,892 0.0350% 32580 - 0.0000% - 0.0000% 1,559,967 0.1212% - 0.0000% 1,559,967 0.0068% 32583 - 0.0000% - 0.0000% 46,901,407 3.6431% - 0.0000% 46,901,407 0.2050% 32601 - 0.0000% 1,271,139 0.0180% - 0.0000% 706,566 0.0098% 1,977,705 0.0086% 32603 - 0.0000% 347,613 0.0049% - 0.0000% 185,300 0.0026% 532,912 0.0023% 32605 - 0.0000% 4,297,285 0.0609% - 0.0000% 2,391,637 0.0332% 6,688,921 0.0292% 32606 - 0.0000% 3,789,510 0.0537% - 0.0000% 1,913,523 0.0265% 5,703,034 0.0249% 32607 - 0.0000% 3,065,455 0.0434% - 0.0000% 1,584,898 0.0220% 4,650,353 0.0203% 32608 - 0.0000% 6,318,935 0.0895% - 0.0000% 2,854,133 0.0396% 9,173,068 0.0401% 32609 - 0.0000% 1,354,788 0.0192% - 0.0000% 767,403 0.0106% 2,122,191 0.0093% 32615 - 0.0000% 2,821,941 0.0400% - 0.0000% 1,319,893 0.0183% 4,141,834 0.0181% 32617 - 0.0000% 1,109,495 0.0157% - 0.0000% 477,376 0.0066% 1,586,871 0.0069% 32618 - 0.0000% 1,261,881 0.0179% - 0.0000% 380,249 0.0053% 1,642,130 0.0072% 32619 - 0.0000% 560,923 0.0079% - 0.0000% 146,183 0.0020% 707,106 0.0031% 32621 - 0.0000% 580,555 0.0082% - 0.0000% 143,820 0.0020% 724,375 0.0032% 32622 - 0.0000% 135,208 0.0019% - 0.0000% 85,820 0.0012% 221,028 0.0010% 32625 - 0.0000% 275,675 0.0039% - 0.0000% 78,504 0.0011% 354,179 0.0015% 32626 - 0.0000% 978,668 0.0139% - 0.0000% 252,975 0.0035% 1,231,643 0.0054% 32628 - 0.0000% 212,881 0.0030% - 0.0000% 67,796 0.0009% 280,677 0.0012% 32631 - 0.0000% 85,967 0.0012% - 0.0000% 54,847 0.0008% 140,815 0.0006% 32640 - 0.0000% 1,379,290 0.0195% - 0.0000% 731,539 0.0101% 2,110,830 0.0092% 32641 - 0.0000% 985,036 0.0140% - 0.0000% 551,468 0.0076% 1,536,505 0.0067% 32643 - 0.0000% 1,848,291 0.0262% - 0.0000% 770,894 0.0107% 2,619,185 0.0114% 32648 - 0.0000% 49,829 0.0007% - 0.0000% 14,702 0.0002% 64,531 0.0003% 32653 - 0.0000% 2,766,926 0.0392% - 0.0000% 1,556,517 0.0216% 4,323,442 0.0189%

April 9, 2019 Applied Research Associates, Inc. 226 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32656 - 0.0000% 1,309,392 0.0185% - 0.0000% 810,095 0.0112% 2,119,486 0.0093% 32666 - 0.0000% 858,784 0.0122% - 0.0000% 511,129 0.0071% 1,369,913 0.0060% 32667 - 0.0000% 921,950 0.0131% - 0.0000% 439,465 0.0061% 1,361,415 0.0060% 32668 - 0.0000% 1,629,602 0.0231% - 0.0000% 501,420 0.0070% 2,131,021 0.0093% 32669 - 0.0000% 3,294,707 0.0467% - 0.0000% 1,123,370 0.0156% 4,418,078 0.0193% 32680 - 0.0000% 719,288 0.0102% - 0.0000% 175,526 0.0024% 894,815 0.0039% 32686 - 0.0000% 1,297,797 0.0184% - 0.0000% 549,529 0.0076% 1,847,327 0.0081% 32693 - 0.0000% 1,427,158 0.0202% - 0.0000% 346,814 0.0048% 1,773,972 0.0078% 32694 - 0.0000% 162,818 0.0023% - 0.0000% 103,368 0.0014% 266,186 0.0012% 32696 - 0.0000% 2,180,649 0.0309% - 0.0000% 656,507 0.0091% 2,837,156 0.0124% 32701 5,387,727 0.0736% 4,197,133 0.0595% - 0.0000% 3,125,688 0.0434% 12,710,549 0.0556% 32702 - 0.0000% 466,413 0.0066% - 0.0000% 196,387 0.0027% 662,800 0.0029% 32703 5,753,023 0.0786% 14,420,773 0.2043% - 0.0000% 11,535,535 0.1600% 31,709,332 0.1386% 32707 22,386,314 0.3058% 9,276,591 0.1314% - 0.0000% 7,238,493 0.1004% 38,901,398 0.1701% 32708 41,172,426 0.5625% 14,821,450 0.2099% - 0.0000% 11,801,243 0.1637% 67,795,118 0.2964% 32709 740,512 0.0101% 461,128 0.0065% - 0.0000% 585,472 0.0081% 1,787,113 0.0078% 32712 3,472,197 0.0474% 13,914,639 0.1971% - 0.0000% 10,427,926 0.1447% 27,814,762 0.1216% 32713 3,559,982 0.0486% 6,574,928 0.0931% - 0.0000% 3,011,628 0.0418% 13,146,538 0.0575% 32714 6,410,220 0.0876% 7,277,141 0.1031% - 0.0000% 5,394,113 0.0748% 19,081,474 0.0834% 32720 1,691,402 0.0231% 5,895,004 0.0835% - 0.0000% 2,462,597 0.0342% 10,049,003 0.0439% 32724 3,124,103 0.0427% 7,293,581 0.1033% - 0.0000% 2,960,633 0.0411% 13,378,317 0.0585% 32725 12,993,777 0.1775% 12,005,520 0.1701% - 0.0000% 5,238,201 0.0727% 30,237,497 0.1322% 32726 - 0.0000% 6,465,048 0.0916% - 0.0000% 3,956,371 0.0549% 10,421,420 0.0456% 32730 2,508,013 0.0343% 1,291,356 0.0183% - 0.0000% 997,290 0.0138% 4,796,659 0.0210% 32732 14,002,482 0.1913% 2,017,885 0.0286% - 0.0000% 1,278,136 0.0177% 17,298,503 0.0756% 32735 - 0.0000% 2,755,605 0.0390% - 0.0000% 1,673,093 0.0232% 4,428,698 0.0194% 32736 - 0.0000% 3,750,406 0.0531% - 0.0000% 1,847,278 0.0256% 5,597,683 0.0245% 32738 16,610,438 0.2269% 9,036,552 0.1280% - 0.0000% 4,105,136 0.0569% 29,752,126 0.1301% 32744 581,569 0.0079% 679,692 0.0096% - 0.0000% 291,118 0.0040% 1,552,378 0.0068% 32746 15,710,523 0.2146% 17,393,613 0.2464% - 0.0000% 10,330,357 0.1433% 43,434,493 0.1899% 32750 8,159,563 0.1115% 8,334,994 0.1181% - 0.0000% 5,761,566 0.0799% 22,256,124 0.0973% 32751 19,175,085 0.2620% 9,579,961 0.1357% - 0.0000% 7,929,555 0.1100% 36,684,601 0.1604% 32754 2,579,450 0.0352% 1,866,562 0.0264% - 0.0000% 1,866,562 0.0259% 6,312,575 0.0276% 32757 - 0.0000% 16,209,487 0.2296% - 0.0000% 10,515,508 0.1459% 26,724,995 0.1168% 32759 1,234,213 0.0169% 504,296 0.0071% - 0.0000% 323,497 0.0045% 2,062,006 0.0090% 32763 1,662,883 0.0227% 3,500,950 0.0496% - 0.0000% 1,552,138 0.0215% 6,715,971 0.0294% 32764 2,295,412 0.0314% 642,673 0.0091% - 0.0000% 339,286 0.0047% 3,277,371 0.0143% 32765 106,098,150 1.4494% 17,286,939 0.2449% - 0.0000% 14,554,035 0.2019% 137,939,124 0.6030% 32766 39,613,549 0.5412% 5,397,362 0.0765% - 0.0000% 4,617,366 0.0640% 49,628,277 0.2169% 32767 - 0.0000% 397,012 0.0056% - 0.0000% 153,271 0.0021% 550,283 0.0024% 32771 13,998,266 0.1912% 12,913,572 0.1829% - 0.0000% 7,495,564 0.1040% 34,407,403 0.1504% 32773 11,623,022 0.1588% 6,360,181 0.0901% - 0.0000% 3,623,445 0.0503% 21,606,648 0.0945% 32776 603,395 0.0082% 3,898,255 0.0552% - 0.0000% 2,338,554 0.0324% 6,840,204 0.0299% 32778 - 0.0000% 9,824,471 0.1392% - 0.0000% 7,082,896 0.0983% 16,907,366 0.0739% 32779 9,490,221 0.1296% 15,530,889 0.2200% - 0.0000% 11,307,184 0.1568% 36,328,294 0.1588% 32780 4,354,736 0.0595% 10,520,692 0.1490% - 0.0000% 13,333,680 0.1850% 28,209,109 0.1233% 32784 - 0.0000% 3,024,483 0.0428% - 0.0000% 1,535,535 0.0213% 4,560,018 0.0199% 32789 46,537,225 0.6357% 18,603,135 0.2635% - 0.0000% 17,064,168 0.2367% 82,204,528 0.3593% 32792 36,121,759 0.4935% 11,308,494 0.1602% - 0.0000% 10,448,975 0.1449% 57,879,228 0.2530% 32796 2,590,219 0.0354% 3,728,236 0.0528% - 0.0000% 4,531,701 0.0629% 10,850,156 0.0474% 32798 70,873 0.0010% 1,382,096 0.0196% - 0.0000% 1,016,596 0.0141% 2,469,565 0.0108% 32801 5,051,125 0.0690% 1,758,387 0.0249% - 0.0000% 1,925,894 0.0267% 8,735,406 0.0382% 32803 24,250,936 0.3313% 7,945,998 0.1126% - 0.0000% 8,687,752 0.1205% 40,884,686 0.1787% 32804 15,859,315 0.2167% 8,794,985 0.1246% - 0.0000% 8,886,886 0.1233% 33,541,186 0.1466% 32805 6,128,510 0.0837% 2,773,419 0.0393% - 0.0000% 3,304,466 0.0458% 12,206,395 0.0534% 32806 39,625,463 0.5413% 10,536,754 0.1493% - 0.0000% 12,405,976 0.1721% 62,568,193 0.2735% 32807 27,167,288 0.3711% 5,767,369 0.0817% - 0.0000% 6,384,084 0.0886% 39,318,741 0.1719% 32808 7,589,786 0.1037% 6,828,193 0.0967% - 0.0000% 7,132,594 0.0989% 21,550,574 0.0942% 32809 23,339,144 0.3188% 5,709,384 0.0809% - 0.0000% 7,908,787 0.1097% 36,957,316 0.1616% 32810 6,382,377 0.0872% 6,452,428 0.0914% - 0.0000% 5,613,070 0.0779% 18,447,875 0.0806% 32811 4,341,626 0.0593% 2,729,413 0.0387% - 0.0000% 3,262,800 0.0453% 10,333,839 0.0452% 32812 52,071,531 0.7113% 9,862,910 0.1397% - 0.0000% 12,640,603 0.1753% 74,575,044 0.3260%

April 9, 2019 Applied Research Associates, Inc. 227 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 32814 6,869,623 0.0938% 2,064,186 0.0292% - 0.0000% 2,064,186 0.0286% 10,997,996 0.0481% 32815 647 0.0000% 1,225 0.0000% - 0.0000% 1,510 0.0000% 3,382 0.0000% 32817 42,738,853 0.5839% 8,132,086 0.1152% - 0.0000% 7,764,046 0.1077% 58,634,985 0.2563% 32818 7,207,152 0.0985% 9,810,879 0.1390% - 0.0000% 10,259,026 0.1423% 27,277,057 0.1192% 32819 23,284,560 0.3181% 13,105,980 0.1856% - 0.0000% 18,455,892 0.2560% 54,846,432 0.2398% 32820 14,147,898 0.1933% 2,419,860 0.0343% - 0.0000% 2,738,379 0.0380% 19,306,137 0.0844% 32821 9,405,304 0.1285% 3,477,992 0.0493% - 0.0000% 5,846,875 0.0811% 18,730,172 0.0819% 32822 42,970,742 0.5870% 7,157,858 0.1014% - 0.0000% 9,155,497 0.1270% 59,284,097 0.2592% 32824 76,644,568 1.0470% 11,398,071 0.1615% - 0.0000% 19,670,857 0.2729% 107,713,496 0.4709% 32825 97,853,565 1.3368% 13,665,611 0.1936% - 0.0000% 15,421,474 0.2139% 126,940,650 0.5549% 32826 36,146,172 0.4938% 4,197,911 0.0595% - 0.0000% 4,197,911 0.0582% 44,541,993 0.1947% 32827 67,764,145 0.9257% 6,200,825 0.0878% - 0.0000% 9,398,547 0.1304% 83,363,517 0.3644% 32828 120,043,651 1.6399% 14,840,869 0.2102% - 0.0000% 17,455,194 0.2421% 152,339,715 0.6659% 32829 40,401,340 0.5519% 4,286,160 0.0607% - 0.0000% 5,693,319 0.0790% 50,380,819 0.2202% 32830 52,325 0.0007% 47,507 0.0007% - 0.0000% 73,139 0.0010% 172,971 0.0008% 32831 16,716 0.0002% 4,645 0.0001% - 0.0000% 6,268 0.0001% 27,628 0.0001% 32832 43,136,361 0.5893% 6,971,180 0.0987% - 0.0000% 10,973,515 0.1522% 61,081,056 0.2670% 32833 8,051,296 0.1100% 2,747,593 0.0389% - 0.0000% 3,485,804 0.0484% 14,284,692 0.0624% 32834 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 32835 12,078,983 0.1650% 9,680,177 0.1371% - 0.0000% 11,964,572 0.1660% 33,723,732 0.1474% 32836 22,264,941 0.3042% 12,150,867 0.1721% - 0.0000% 19,307,371 0.2678% 53,723,179 0.2348% 32837 62,873,024 0.8589% 14,349,969 0.2033% - 0.0000% 25,658,319 0.3559% 102,881,312 0.4497% 32839 14,452,448 0.1974% 4,360,887 0.0618% - 0.0000% 6,014,186 0.0834% 24,827,520 0.1085% 32901 439,904 0.0060% 15,429,378 0.2186% - 0.0000% 29,139,471 0.4042% 45,008,752 0.1967% 32903 624,981 0.0085% 32,825,259 0.4650% - 0.0000% 53,859,014 0.7471% 87,309,253 0.3817% 32904 1,190,485 0.0163% 27,680,757 0.3921% - 0.0000% 52,218,871 0.7244% 81,090,113 0.3545% 32905 393,126 0.0054% 18,596,479 0.2634% - 0.0000% 32,973,017 0.4574% 51,962,622 0.2271% 32907 1,443,036 0.0197% 45,309,604 0.6418% - 0.0000% 88,243,535 1.2241% 134,996,175 0.5901% 32908 409,148 0.0056% 14,391,731 0.2039% - 0.0000% 27,958,774 0.3878% 42,759,653 0.1869% 32909 1,080,944 0.0148% 34,091,512 0.4829% - 0.0000% 60,506,417 0.8393% 95,678,873 0.4182% 32920 271,758 0.0037% 4,142,887 0.0587% - 0.0000% 6,357,502 0.0882% 10,772,147 0.0471% 32922 296,265 0.0040% 2,417,184 0.0342% - 0.0000% 3,992,255 0.0554% 6,705,704 0.0293% 32925 279 0.0000% 12,878 0.0002% - 0.0000% 22,223 0.0003% 35,380 0.0002% 32926 1,357,400 0.0185% 8,026,310 0.1137% - 0.0000% 12,726,707 0.1765% 22,110,417 0.0967% 32927 1,875,736 0.0256% 7,943,537 0.1125% - 0.0000% 11,443,635 0.1587% 21,262,908 0.0929% 32931 571,341 0.0078% 11,630,217 0.1647% - 0.0000% 18,270,499 0.2534% 30,472,057 0.1332% 32934 942,814 0.0129% 18,115,966 0.2566% - 0.0000% 34,505,332 0.4786% 53,564,112 0.2341% 32935 1,072,965 0.0147% 33,934,192 0.4807% - 0.0000% 58,778,754 0.8153% 93,785,912 0.4100% 32937 1,159,082 0.0158% 35,172,567 0.4982% - 0.0000% 59,176,866 0.8209% 95,508,515 0.4175% 32940 2,742,082 0.0375% 36,922,298 0.5230% - 0.0000% 68,974,842 0.9568% 108,639,223 0.4749% 32948 - 0.0000% 5,730,765 0.0812% - 0.0000% 8,401,537 0.1165% 14,132,303 0.0618% 32949 - 0.0000% 5,239,292 0.0742% - 0.0000% 8,133,802 0.1128% 13,373,094 0.0585% 32950 - 0.0000% 7,286,170 0.1032% - 0.0000% 11,921,777 0.1654% 19,207,946 0.0840% 32951 480,663 0.0066% 42,467,494 0.6016% - 0.0000% 65,766,362 0.9123% 108,714,519 0.4752% 32952 1,673,127 0.0229% 26,490,772 0.3752% - 0.0000% 43,052,321 0.5972% 71,216,219 0.3113% 32953 1,398,460 0.0191% 11,943,053 0.1692% - 0.0000% 19,280,710 0.2675% 32,622,223 0.1426% 32955 2,297,438 0.0314% 29,608,763 0.4194% - 0.0000% 52,730,318 0.7314% 84,636,519 0.3700% 32958 - 0.0000% 68,739,820 0.9737% - 0.0000% 97,353,700 1.3504% 166,093,520 0.7261% 32960 - 0.0000% 30,153,699 0.4271% - 0.0000% 46,004,815 0.6382% 76,158,514 0.3329% 32962 - 0.0000% 41,984,716 0.5947% - 0.0000% 62,919,311 0.8728% 104,904,027 0.4586% 32963 - 0.0000% 166,770,626 2.3623% - 0.0000% 245,549,874 3.4061% 412,320,500 1.8024% 32966 - 0.0000% 48,543,546 0.6876% - 0.0000% 69,627,172 0.9658% 118,170,718 0.5166% 32967 - 0.0000% 68,374,710 0.9685% - 0.0000% 98,630,200 1.3681% 167,004,910 0.7300% 32968 - 0.0000% 54,280,342 0.7689% - 0.0000% 75,259,654 1.0440% 129,539,995 0.5663% 32976 - 0.0000% 13,744,107 0.1947% - 0.0000% 19,939,143 0.2766% 33,683,250 0.1472% 33001 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33004 - 0.0000% 2,070,276 0.0293% - 0.0000% 539,743 0.0075% 2,610,019 0.0114% 33009 - 0.0000% 2,536,660 0.0359% - 0.0000% 686,563 0.0095% 3,223,224 0.0141% 33010 - 0.0000% 853,209 0.0121% - 0.0000% 373,902 0.0052% 1,227,111 0.0054% 33012 - 0.0000% 1,899,971 0.0269% - 0.0000% 788,473 0.0109% 2,688,444 0.0118% 33013 - 0.0000% 1,106,987 0.0157% - 0.0000% 461,607 0.0064% 1,568,594 0.0069% 33014 - 0.0000% 2,079,815 0.0295% - 0.0000% 793,323 0.0110% 2,873,138 0.0126%

April 9, 2019 Applied Research Associates, Inc. 228 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33015 - 0.0000% 4,236,282 0.0600% - 0.0000% 1,523,277 0.0211% 5,759,560 0.0252% 33016 - 0.0000% 1,573,633 0.0223% - 0.0000% 700,395 0.0097% 2,274,028 0.0099% 33018 - 0.0000% 3,060,056 0.0433% - 0.0000% 1,282,028 0.0178% 4,342,084 0.0190% 33019 - 0.0000% 3,573,341 0.0506% - 0.0000% 980,591 0.0136% 4,553,931 0.0199% 33020 - 0.0000% 3,561,374 0.0504% - 0.0000% 998,489 0.0139% 4,559,863 0.0199% 33021 - 0.0000% 7,872,034 0.1115% - 0.0000% 2,262,812 0.0314% 10,134,846 0.0443% 33023 - 0.0000% 7,290,778 0.1033% - 0.0000% 2,232,123 0.0310% 9,522,902 0.0416% 33024 - 0.0000% 10,730,708 0.1520% - 0.0000% 3,260,914 0.0452% 13,991,623 0.0612% 33025 - 0.0000% 6,445,662 0.0913% - 0.0000% 2,124,655 0.0295% 8,570,317 0.0375% 33026 - 0.0000% 6,340,136 0.0898% - 0.0000% 2,015,789 0.0280% 8,355,925 0.0365% 33027 - 0.0000% 8,996,534 0.1274% - 0.0000% 3,570,968 0.0495% 12,567,502 0.0549% 33028 - 0.0000% 6,051,346 0.0857% - 0.0000% 2,152,746 0.0299% 8,204,092 0.0359% 33029 - 0.0000% 12,448,487 0.1763% - 0.0000% 4,091,910 0.0568% 16,540,397 0.0723% 33030 - 0.0000% 512,852 0.0073% - 0.0000% - 0.0000% 512,852 0.0022% 33031 - 0.0000% 301,712 0.0043% - 0.0000% - 0.0000% 301,712 0.0013% 33032 - 0.0000% 1,087,781 0.0154% - 0.0000% - 0.0000% 1,087,781 0.0048% 33033 - 0.0000% 1,091,965 0.0155% - 0.0000% - 0.0000% 1,091,965 0.0048% 33034 - 0.0000% 139,073 0.0020% - 0.0000% - 0.0000% 139,073 0.0006% 33035 - 0.0000% 257,077 0.0036% - 0.0000% - 0.0000% 257,077 0.0011% 33036 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33037 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33039 - 0.0000% 272 0.0000% - 0.0000% - 0.0000% 272 0.0000% 33040 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33042 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33043 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33050 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33051 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33054 - 0.0000% 1,080,545 0.0153% - 0.0000% 381,385 0.0053% 1,461,930 0.0064% 33055 - 0.0000% 3,100,757 0.0439% - 0.0000% 1,015,137 0.0141% 4,115,894 0.0180% 33056 - 0.0000% 2,647,055 0.0375% - 0.0000% 868,618 0.0120% 3,515,673 0.0154% 33060 - 0.0000% 11,095,647 0.1572% - 0.0000% 3,352,686 0.0465% 14,448,333 0.0632% 33062 - 0.0000% 13,876,204 0.1966% - 0.0000% 3,701,914 0.0514% 17,578,117 0.0768% 33063 - 0.0000% 21,666,641 0.3069% - 0.0000% 6,847,145 0.0950% 28,513,786 0.1246% 33064 - 0.0000% 29,131,105 0.4126% - 0.0000% 9,571,650 0.1328% 38,702,755 0.1692% 33065 - 0.0000% 22,702,717 0.3216% - 0.0000% 7,757,381 0.1076% 30,460,098 0.1332% 33066 - 0.0000% 5,532,877 0.0784% - 0.0000% 1,658,512 0.0230% 7,191,388 0.0314% 33067 - 0.0000% 31,860,958 0.4513% - 0.0000% 11,060,169 0.1534% 42,921,127 0.1876% 33068 - 0.0000% 13,617,018 0.1929% - 0.0000% 4,446,828 0.0617% 18,063,845 0.0790% 33069 - 0.0000% 4,462,240 0.0632% - 0.0000% 1,200,672 0.0167% 5,662,911 0.0248% 33070 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33071 - 0.0000% 26,446,399 0.3746% - 0.0000% 8,758,419 0.1215% 35,204,818 0.1539% 33073 - 0.0000% 20,423,366 0.2893% - 0.0000% 6,901,015 0.0957% 27,324,381 0.1194% 33076 - 0.0000% 52,095,707 0.7379% - 0.0000% 17,198,173 0.2386% 69,293,880 0.3029% 33109 - 0.0000% 131,710 0.0019% - 0.0000% 50,574 0.0007% 182,284 0.0008% 33122 - 0.0000% 33,524 0.0005% - 0.0000% 16,905 0.0002% 50,429 0.0002% 33125 - 0.0000% 774,981 0.0110% - 0.0000% 372,492 0.0052% 1,147,473 0.0050% 33126 - 0.0000% 598,026 0.0085% - 0.0000% 306,602 0.0043% 904,627 0.0040% 33127 - 0.0000% 463,671 0.0066% - 0.0000% 200,064 0.0028% 663,735 0.0029% 33128 - 0.0000% 28,246 0.0004% - 0.0000% 13,550 0.0002% 41,795 0.0002% 33129 - 0.0000% 451,969 0.0064% - 0.0000% 247,036 0.0034% 699,005 0.0031% 33130 - 0.0000% 177,276 0.0025% - 0.0000% 116,323 0.0016% 293,599 0.0013% 33131 - 0.0000% 235,527 0.0033% - 0.0000% 220,557 0.0031% 456,084 0.0020% 33132 - 0.0000% 125,962 0.0018% - 0.0000% 98,647 0.0014% 224,609 0.0010% 33133 - 0.0000% 1,878,161 0.0266% - 0.0000% 1,005,939 0.0140% 2,884,100 0.0126% 33134 - 0.0000% 1,880,516 0.0266% - 0.0000% 1,009,231 0.0140% 2,889,746 0.0126% 33135 - 0.0000% 452,350 0.0064% - 0.0000% 220,877 0.0031% 673,227 0.0029% 33136 - 0.0000% 97,409 0.0014% - 0.0000% 48,549 0.0007% 145,958 0.0006% 33137 - 0.0000% 714,911 0.0101% - 0.0000% 284,186 0.0039% 999,097 0.0044% 33138 - 0.0000% 1,760,049 0.0249% - 0.0000% 662,102 0.0092% 2,422,151 0.0106% 33139 - 0.0000% 2,155,194 0.0305% - 0.0000% 686,396 0.0095% 2,841,590 0.0124% 33140 - 0.0000% 4,562,922 0.0646% - 0.0000% 1,240,511 0.0172% 5,803,433 0.0254% 33141 - 0.0000% 3,101,803 0.0439% - 0.0000% 786,801 0.0109% 3,888,604 0.0170%

April 9, 2019 Applied Research Associates, Inc. 229 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33142 - 0.0000% 921,670 0.0131% - 0.0000% 400,732 0.0056% 1,322,403 0.0058% 33143 - 0.0000% 2,468,243 0.0350% - 0.0000% 1,432,502 0.0199% 3,900,745 0.0171% 33144 - 0.0000% 712,830 0.0101% - 0.0000% 373,718 0.0052% 1,086,548 0.0047% 33145 - 0.0000% 874,465 0.0124% - 0.0000% 450,842 0.0063% 1,325,307 0.0058% 33146 - 0.0000% 1,099,735 0.0156% - 0.0000% 634,697 0.0088% 1,734,432 0.0076% 33147 - 0.0000% 1,246,985 0.0177% - 0.0000% 511,849 0.0071% 1,758,835 0.0077% 33149 - 0.0000% 1,192,322 0.0169% - 0.0000% 658,066 0.0091% 1,850,388 0.0081% 33150 - 0.0000% 703,982 0.0100% - 0.0000% 282,694 0.0039% 986,676 0.0043% 33154 - 0.0000% 3,640,481 0.0516% - 0.0000% 972,186 0.0135% 4,612,667 0.0202% 33155 - 0.0000% 1,744,260 0.0247% - 0.0000% 945,093 0.0131% 2,689,353 0.0118% 33156 - 0.0000% 3,843,085 0.0544% - 0.0000% 2,406,652 0.0334% 6,249,738 0.0273% 33157 - 0.0000% 2,490,575 0.0353% - 0.0000% 1,424,530 0.0198% 3,915,105 0.0171% 33158 - 0.0000% 555,418 0.0079% - 0.0000% 342,633 0.0048% 898,052 0.0039% 33160 - 0.0000% 2,695,039 0.0382% - 0.0000% 810,111 0.0112% 3,505,151 0.0153% 33161 - 0.0000% 2,093,283 0.0297% - 0.0000% 747,733 0.0104% 2,841,016 0.0124% 33162 - 0.0000% 2,421,363 0.0343% - 0.0000% 787,417 0.0109% 3,208,780 0.0140% 33165 - 0.0000% 1,982,080 0.0281% - 0.0000% 1,094,648 0.0152% 3,076,727 0.0134% 33166 - 0.0000% 948,068 0.0134% - 0.0000% 440,938 0.0061% 1,389,006 0.0061% 33167 - 0.0000% 770,955 0.0109% - 0.0000% 286,828 0.0040% 1,057,783 0.0046% 33168 - 0.0000% 1,209,163 0.0171% - 0.0000% 438,568 0.0061% 1,647,731 0.0072% 33169 - 0.0000% 2,816,968 0.0399% - 0.0000% 941,497 0.0131% 3,758,464 0.0164% 33170 - 0.0000% 353,739 0.0050% - 0.0000% - 0.0000% 353,739 0.0015% 33172 - 0.0000% 466,657 0.0066% - 0.0000% 250,601 0.0035% 717,259 0.0031% 33173 - 0.0000% 1,322,538 0.0187% - 0.0000% 772,199 0.0107% 2,094,737 0.0092% 33174 - 0.0000% 792,153 0.0112% - 0.0000% 411,661 0.0057% 1,203,814 0.0053% 33175 - 0.0000% 2,157,061 0.0306% - 0.0000% 1,211,679 0.0168% 3,368,740 0.0147% 33176 - 0.0000% 2,494,738 0.0353% - 0.0000% 1,506,397 0.0209% 4,001,135 0.0175% 33177 - 0.0000% 1,545,228 0.0219% - 0.0000% 884,557 0.0123% 2,429,784 0.0106% 33178 - 0.0000% 2,872,637 0.0407% - 0.0000% 1,412,148 0.0196% 4,284,785 0.0187% 33179 - 0.0000% 3,758,860 0.0532% - 0.0000% 1,174,006 0.0163% 4,932,866 0.0216% 33180 - 0.0000% 2,158,603 0.0306% - 0.0000% 667,924 0.0093% 2,826,527 0.0124% 33181 - 0.0000% 975,323 0.0138% - 0.0000% 319,414 0.0044% 1,294,737 0.0057% 33182 - 0.0000% 845,569 0.0120% - 0.0000% 426,171 0.0059% 1,271,740 0.0056% 33183 - 0.0000% 1,070,255 0.0152% - 0.0000% 624,220 0.0087% 1,694,474 0.0074% 33184 - 0.0000% 774,864 0.0110% - 0.0000% 424,486 0.0059% 1,199,350 0.0052% 33185 - 0.0000% 1,540,808 0.0218% - 0.0000% 884,985 0.0123% 2,425,793 0.0106% 33186 - 0.0000% 2,519,860 0.0357% - 0.0000% 1,503,691 0.0209% 4,023,551 0.0176% 33187 - 0.0000% 802,943 0.0114% - 0.0000% 428,428 0.0059% 1,231,371 0.0054% 33189 - 0.0000% 728,591 0.0103% - 0.0000% - 0.0000% 728,591 0.0032% 33190 - 0.0000% 363,004 0.0051% - 0.0000% - 0.0000% 363,004 0.0016% 33191 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33193 - 0.0000% 1,444,847 0.0205% - 0.0000% 833,722 0.0116% 2,278,570 0.0100% 33194 - 0.0000% 310,849 0.0044% - 0.0000% 171,071 0.0024% 481,919 0.0021% 33196 - 0.0000% 2,041,073 0.0289% - 0.0000% 1,153,129 0.0160% 3,194,202 0.0140% 33199 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33301 - 0.0000% 8,991,371 0.1274% - 0.0000% 2,257,253 0.0313% 11,248,623 0.0492% 33304 - 0.0000% 5,539,618 0.0785% - 0.0000% 1,393,448 0.0193% 6,933,066 0.0303% 33305 - 0.0000% 5,544,460 0.0785% - 0.0000% 1,498,129 0.0208% 7,042,589 0.0308% 33306 - 0.0000% 1,869,303 0.0265% - 0.0000% 538,753 0.0075% 2,408,055 0.0105% 33308 - 0.0000% 13,992,222 0.1982% - 0.0000% 3,971,859 0.0551% 17,964,082 0.0785% 33309 - 0.0000% 9,932,473 0.1407% - 0.0000% 2,976,324 0.0413% 12,908,797 0.0564% 33311 - 0.0000% 9,068,936 0.1285% - 0.0000% 2,477,174 0.0344% 11,546,110 0.0505% 33312 - 0.0000% 10,320,763 0.1462% - 0.0000% 2,870,624 0.0398% 13,191,387 0.0577% 33313 - 0.0000% 7,929,412 0.1123% - 0.0000% 2,231,703 0.0310% 10,161,115 0.0444% 33314 - 0.0000% 2,971,880 0.0421% - 0.0000% 856,173 0.0119% 3,828,052 0.0167% 33315 - 0.0000% 3,400,796 0.0482% - 0.0000% 914,152 0.0127% 4,314,948 0.0189% 33316 - 0.0000% 6,267,277 0.0888% - 0.0000% 1,496,978 0.0208% 7,764,255 0.0339% 33317 - 0.0000% 11,614,645 0.1645% - 0.0000% 3,400,210 0.0472% 15,014,854 0.0656% 33319 - 0.0000% 12,116,684 0.1716% - 0.0000% 3,597,139 0.0499% 15,713,823 0.0687% 33321 - 0.0000% 17,754,288 0.2515% - 0.0000% 5,797,953 0.0804% 23,552,241 0.1030% 33322 - 0.0000% 12,729,346 0.1803% - 0.0000% 3,704,317 0.0514% 16,433,663 0.0718% 33323 - 0.0000% 9,451,796 0.1339% - 0.0000% 2,803,270 0.0389% 12,255,067 0.0536%

April 9, 2019 Applied Research Associates, Inc. 230 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33324 - 0.0000% 11,499,576 0.1629% - 0.0000% 3,530,316 0.0490% 15,029,892 0.0657% 33325 - 0.0000% 9,359,368 0.1326% - 0.0000% 2,935,416 0.0407% 12,294,783 0.0537% 33326 - 0.0000% 10,533,585 0.1492% - 0.0000% 3,286,496 0.0456% 13,820,081 0.0604% 33327 - 0.0000% 13,943,733 0.1975% - 0.0000% 3,937,496 0.0546% 17,881,229 0.0782% 33328 - 0.0000% 9,668,865 0.1370% - 0.0000% 2,974,289 0.0413% 12,643,154 0.0553% 33330 - 0.0000% 5,942,903 0.0842% - 0.0000% 2,136,991 0.0296% 8,079,894 0.0353% 33331 - 0.0000% 7,413,006 0.1050% - 0.0000% 2,770,356 0.0384% 10,183,362 0.0445% 33332 - 0.0000% 4,303,060 0.0610% - 0.0000% 1,473,943 0.0204% 5,777,003 0.0253% 33334 - 0.0000% 9,168,320 0.1299% - 0.0000% 2,783,512 0.0386% 11,951,832 0.0522% 33351 - 0.0000% 9,588,091 0.1358% - 0.0000% 2,915,933 0.0404% 12,504,024 0.0547% 33388 - 0.0000% - 0.0000% - 0.0000% - 0.0000% - 0.0000% 33401 - 0.0000% 15,499,852 0.2196% - 0.0000% 14,662,401 0.2034% 30,162,254 0.1318% 33403 - 0.0000% 6,898,012 0.0977% - 0.0000% 7,454,947 0.1034% 14,352,959 0.0627% 33404 - 0.0000% 21,408,016 0.3032% - 0.0000% 22,744,176 0.3155% 44,152,192 0.1930% 33405 - 0.0000% 17,961,606 0.2544% - 0.0000% 16,468,401 0.2284% 34,430,008 0.1505% 33406 - 0.0000% 19,906,896 0.2820% - 0.0000% 16,569,521 0.2298% 36,476,417 0.1595% 33407 - 0.0000% 18,025,433 0.2553% - 0.0000% 17,881,837 0.2480% 35,907,270 0.1570% 33408 - 0.0000% 48,744,348 0.6905% - 0.0000% 56,578,522 0.7848% 105,322,871 0.4604% 33409 - 0.0000% 18,978,357 0.2688% - 0.0000% 17,151,227 0.2379% 36,129,584 0.1579% 33410 - 0.0000% 73,700,492 1.0440% - 0.0000% 80,749,567 1.1201% 154,450,060 0.6752% 33411 - 0.0000% 115,787,874 1.6401% - 0.0000% 94,333,067 1.3085% 210,120,941 0.9185% 33412 - 0.0000% 53,941,630 0.7641% - 0.0000% 48,822,069 0.6772% 102,763,699 0.4492% 33413 - 0.0000% 18,615,815 0.2637% - 0.0000% 15,013,833 0.2083% 33,629,648 0.1470% 33414 - 0.0000% 132,794,759 1.8810% - 0.0000% 99,896,003 1.3857% 232,690,762 1.0172% 33415 - 0.0000% 24,452,005 0.3464% - 0.0000% 19,225,641 0.2667% 43,677,647 0.1909% 33417 - 0.0000% 20,066,354 0.2842% - 0.0000% 16,769,451 0.2326% 36,835,805 0.1610% 33418 - 0.0000% 147,904,115 2.0951% - 0.0000% 150,840,499 2.0924% 298,744,614 1.3059% 33426 - 0.0000% 20,480,286 0.2901% - 0.0000% 13,506,511 0.1874% 33,986,797 0.1486% 33428 - 0.0000% 39,084,352 0.5536% - 0.0000% 14,926,364 0.2071% 54,010,716 0.2361% 33430 - 0.0000% 5,809,779 0.0823% - 0.0000% 4,089,759 0.0567% 9,899,538 0.0433% 33431 - 0.0000% 20,506,331 0.2905% - 0.0000% 8,583,921 0.1191% 29,090,252 0.1272% 33432 - 0.0000% 31,726,634 0.4494% - 0.0000% 11,029,683 0.1530% 42,756,316 0.1869% 33433 - 0.0000% 42,665,631 0.6044% - 0.0000% 16,329,609 0.2265% 58,995,239 0.2579% 33434 - 0.0000% 28,157,849 0.3989% - 0.0000% 11,513,903 0.1597% 39,671,751 0.1734% 33435 - 0.0000% 25,199,293 0.3569% - 0.0000% 16,362,842 0.2270% 41,562,135 0.1817% 33436 - 0.0000% 51,404,694 0.7281% - 0.0000% 33,716,257 0.4677% 85,120,952 0.3721% 33437 - 0.0000% 76,837,669 1.0884% - 0.0000% 46,301,165 0.6423% 123,138,833 0.5383% 33438 - 0.0000% 471,788 0.0067% - 0.0000% 404,850 0.0056% 876,638 0.0038% 33440 - 0.0000% 7,529,553 0.1067% - 0.0000% 6,133,924 0.0851% 13,663,477 0.0597% 33441 - 0.0000% 12,689,466 0.1797% - 0.0000% 4,462,236 0.0619% 17,151,703 0.0750% 33442 - 0.0000% 15,738,996 0.2229% - 0.0000% 5,459,943 0.0757% 21,198,940 0.0927% 33444 - 0.0000% 15,606,306 0.2211% - 0.0000% 8,523,700 0.1182% 24,130,006 0.1055% 33445 - 0.0000% 33,935,846 0.4807% - 0.0000% 17,983,333 0.2495% 51,919,179 0.2270% 33446 - 0.0000% 81,715,018 1.1575% - 0.0000% 39,644,006 0.5499% 121,359,024 0.5305% 33449 - 0.0000% 28,062,256 0.3975% - 0.0000% 19,600,379 0.2719% 47,662,636 0.2084% 33455 - 0.0000% 84,955,892 1.2034% - 0.0000% 105,873,103 1.4686% 190,828,995 0.8342% 33458 - 0.0000% 117,932,882 1.6705% - 0.0000% 129,417,840 1.7952% 247,350,722 1.0813% 33460 - 0.0000% 19,128,967 0.2710% - 0.0000% 15,525,625 0.2154% 34,654,592 0.1515% 33461 - 0.0000% 19,188,243 0.2718% - 0.0000% 14,693,272 0.2038% 33,881,515 0.1481% 33462 - 0.0000% 39,957,440 0.5660% - 0.0000% 29,170,945 0.4046% 69,128,384 0.3022% 33463 - 0.0000% 53,627,496 0.7596% - 0.0000% 39,171,710 0.5434% 92,799,206 0.4057% 33467 - 0.0000% 93,311,213 1.3218% - 0.0000% 66,734,854 0.9257% 160,046,068 0.6996% 33469 - 0.0000% 49,705,127 0.7041% - 0.0000% 60,939,508 0.8453% 110,644,635 0.4837% 33470 - 0.0000% 68,928,348 0.9764% - 0.0000% 58,859,775 0.8165% 127,788,123 0.5586% 33471 88,908 0.0012% 3,416,058 0.0484% - 0.0000% 3,588,105 0.0498% 7,093,071 0.0310% 33472 - 0.0000% 38,770,724 0.5492% - 0.0000% 25,847,660 0.3585% 64,618,384 0.2825% 33473 - 0.0000% 35,884,450 0.5083% - 0.0000% 21,342,543 0.2961% 57,226,994 0.2502% 33476 - 0.0000% 2,621,941 0.0371% - 0.0000% 2,139,605 0.0297% 4,761,546 0.0208% 33477 - 0.0000% 60,381,717 0.8553% - 0.0000% 72,590,416 1.0069% 132,972,133 0.5813% 33478 - 0.0000% 38,861,370 0.5505% - 0.0000% 39,783,930 0.5519% 78,645,300 0.3438% 33480 - 0.0000% 145,476,558 2.0607% - 0.0000% 138,476,253 1.9209% 283,952,811 1.2413% 33483 - 0.0000% 30,698,930 0.4348% - 0.0000% 15,902,790 0.2206% 46,601,720 0.2037%

April 9, 2019 Applied Research Associates, Inc. 231 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33484 - 0.0000% 27,984,004 0.3964% - 0.0000% 13,936,569 0.1933% 41,920,573 0.1832% 33486 - 0.0000% 23,624,790 0.3346% - 0.0000% 9,424,540 0.1307% 33,049,330 0.1445% 33487 - 0.0000% 28,123,000 0.3984% - 0.0000% 12,597,585 0.1747% 40,720,585 0.1780% 33493 - 0.0000% 1,015,786 0.0144% - 0.0000% 690,493 0.0096% 1,706,278 0.0075% 33496 - 0.0000% 73,859,372 1.0462% - 0.0000% 32,167,673 0.4462% 106,027,045 0.4635% 33498 - 0.0000% 29,956,401 0.4243% - 0.0000% 13,141,180 0.1823% 43,097,581 0.1884% 33510 - 0.0000% 3,281,318 0.0465% - 0.0000% 4,545,312 0.0631% 7,826,629 0.0342% 33511 - 0.0000% 5,817,393 0.0824% - 0.0000% 8,124,913 0.1127% 13,942,306 0.0609% 33513 - 0.0000% 1,650,468 0.0234% - 0.0000% 1,367,199 0.0190% 3,017,668 0.0132% 33514 - 0.0000% 262,774 0.0037% - 0.0000% 241,525 0.0034% 504,299 0.0022% 33523 - 0.0000% 2,772,199 0.0393% - 0.0000% 3,027,036 0.0420% 5,799,235 0.0254% 33525 - 0.0000% 4,309,709 0.0610% - 0.0000% 5,172,217 0.0717% 9,481,926 0.0414% 33527 - 0.0000% 1,929,169 0.0273% - 0.0000% 2,790,428 0.0387% 4,719,597 0.0206% 33534 - 0.0000% 954,198 0.0135% - 0.0000% 1,203,414 0.0167% 2,157,612 0.0094% 33538 - 0.0000% 722,705 0.0102% - 0.0000% 512,220 0.0071% 1,234,925 0.0054% 33540 - 0.0000% 1,415,409 0.0200% - 0.0000% 2,098,074 0.0291% 3,513,483 0.0154% 33541 - 0.0000% 3,587,581 0.0508% - 0.0000% 4,788,198 0.0664% 8,375,780 0.0366% 33542 - 0.0000% 3,542,236 0.0502% - 0.0000% 5,043,652 0.0700% 8,585,888 0.0375% 33543 - 0.0000% 5,322,223 0.0754% - 0.0000% 5,930,389 0.0823% 11,252,612 0.0492% 33544 - 0.0000% 4,111,175 0.0582% - 0.0000% 4,143,963 0.0575% 8,255,138 0.0361% 33545 - 0.0000% 2,842,610 0.0403% - 0.0000% 3,157,246 0.0438% 5,999,856 0.0262% 33547 - 0.0000% 5,157,758 0.0731% - 0.0000% 7,846,389 0.1088% 13,004,148 0.0568% 33548 - 0.0000% 1,712,890 0.0243% - 0.0000% 1,544,527 0.0214% 3,257,417 0.0142% 33549 - 0.0000% 3,053,256 0.0432% - 0.0000% 2,916,801 0.0405% 5,970,057 0.0261% 33556 - 0.0000% 6,405,770 0.0907% - 0.0000% 5,062,830 0.0702% 11,468,600 0.0501% 33558 - 0.0000% 4,358,774 0.0617% - 0.0000% 3,642,487 0.0505% 8,001,262 0.0350% 33559 - 0.0000% 1,975,721 0.0280% - 0.0000% 2,033,295 0.0282% 4,009,016 0.0175% 33563 - 0.0000% 2,466,695 0.0349% - 0.0000% 4,067,527 0.0564% 6,534,222 0.0286% 33565 - 0.0000% 2,723,145 0.0386% - 0.0000% 4,217,306 0.0585% 6,940,450 0.0303% 33566 - 0.0000% 3,661,047 0.0519% - 0.0000% 6,221,912 0.0863% 9,882,960 0.0432% 33567 - 0.0000% 1,498,724 0.0212% - 0.0000% 2,511,930 0.0348% 4,010,654 0.0175% 33569 - 0.0000% 3,798,258 0.0538% - 0.0000% 5,282,025 0.0733% 9,080,283 0.0397% 33570 - 0.0000% 2,245,086 0.0318% - 0.0000% 2,652,992 0.0368% 4,898,078 0.0214% 33572 - 0.0000% 3,823,965 0.0542% - 0.0000% 4,816,536 0.0668% 8,640,500 0.0378% 33573 - 0.0000% 3,009,584 0.0426% - 0.0000% 3,760,080 0.0522% 6,769,664 0.0296% 33576 - 0.0000% 1,314,317 0.0186% - 0.0000% 1,422,936 0.0197% 2,737,254 0.0120% 33578 - 0.0000% 4,085,708 0.0579% - 0.0000% 5,451,456 0.0756% 9,537,165 0.0417% 33579 - 0.0000% 3,451,755 0.0489% - 0.0000% 4,774,753 0.0662% 8,226,507 0.0360% 33584 - 0.0000% 3,395,032 0.0481% - 0.0000% 4,710,214 0.0653% 8,105,246 0.0354% 33585 - 0.0000% 266,622 0.0038% - 0.0000% 214,283 0.0030% 480,905 0.0021% 33592 - 0.0000% 1,225,497 0.0174% - 0.0000% 1,521,913 0.0211% 2,747,409 0.0120% 33594 - 0.0000% 5,411,272 0.0767% - 0.0000% 7,725,812 0.1072% 13,137,084 0.0574% 33596 - 0.0000% 5,249,022 0.0744% - 0.0000% 7,631,848 0.1059% 12,880,870 0.0563% 33597 - 0.0000% 898,500 0.0127% - 0.0000% 875,927 0.0122% 1,774,426 0.0078% 33598 - 0.0000% 1,692,611 0.0240% - 0.0000% 2,293,740 0.0318% 3,986,352 0.0174% 33602 - 0.0000% 967,927 0.0137% - 0.0000% 999,311 0.0139% 1,967,238 0.0086% 33603 - 0.0000% 1,658,982 0.0235% - 0.0000% 1,698,408 0.0236% 3,357,390 0.0147% 33604 - 0.0000% 2,613,954 0.0370% - 0.0000% 2,634,067 0.0365% 5,248,022 0.0229% 33605 - 0.0000% 761,903 0.0108% - 0.0000% 847,733 0.0118% 1,609,637 0.0070% 33606 - 0.0000% 3,285,927 0.0465% - 0.0000% 3,372,725 0.0468% 6,658,652 0.0291% 33607 - 0.0000% 1,273,507 0.0180% - 0.0000% 1,241,132 0.0172% 2,514,639 0.0110% 33609 - 0.0000% 2,944,927 0.0417% - 0.0000% 2,875,715 0.0399% 5,820,642 0.0254% 33610 - 0.0000% 1,886,076 0.0267% - 0.0000% 2,206,711 0.0306% 4,092,787 0.0179% 33611 - 0.0000% 3,943,326 0.0559% - 0.0000% 3,906,634 0.0542% 7,849,960 0.0343% 33612 - 0.0000% 2,630,753 0.0373% - 0.0000% 2,630,753 0.0365% 5,261,505 0.0230% 33613 - 0.0000% 2,701,825 0.0383% - 0.0000% 2,669,486 0.0370% 5,371,311 0.0235% 33614 - 0.0000% 2,368,033 0.0335% - 0.0000% 2,273,671 0.0315% 4,641,704 0.0203% 33615 - 0.0000% 3,647,623 0.0517% - 0.0000% 3,032,593 0.0421% 6,680,217 0.0292% 33616 - 0.0000% 1,258,544 0.0178% - 0.0000% 1,130,736 0.0157% 2,389,280 0.0104% 33617 - 0.0000% 3,337,606 0.0473% - 0.0000% 3,812,370 0.0529% 7,149,975 0.0313% 33618 - 0.0000% 4,212,790 0.0597% - 0.0000% 3,824,774 0.0531% 8,037,564 0.0351% 33619 - 0.0000% 1,800,179 0.0255% - 0.0000% 2,332,388 0.0324% 4,132,567 0.0181%

April 9, 2019 Applied Research Associates, Inc. 232 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33620 - 0.0000% 158 0.0000% - 0.0000% 166 0.0000% 324 0.0000% 33621 - 0.0000% 3,406 0.0000% - 0.0000% 3,618 0.0001% 7,024 0.0000% 33624 - 0.0000% 5,228,049 0.0741% - 0.0000% 4,605,305 0.0639% 9,833,354 0.0430% 33625 - 0.0000% 2,797,673 0.0396% - 0.0000% 2,415,940 0.0335% 5,213,613 0.0228% 33626 - 0.0000% 4,688,427 0.0664% - 0.0000% 3,689,649 0.0512% 8,378,076 0.0366% 33629 - 0.0000% 5,911,286 0.0837% - 0.0000% 5,811,269 0.0806% 11,722,555 0.0512% 33634 - 0.0000% 1,719,844 0.0244% - 0.0000% 1,467,677 0.0204% 3,187,522 0.0139% 33635 - 0.0000% 1,458,454 0.0207% - 0.0000% 1,157,024 0.0160% 2,615,478 0.0114% 33637 - 0.0000% 951,111 0.0135% - 0.0000% 1,160,808 0.0161% 2,111,920 0.0092% 33647 - 0.0000% 9,579,804 0.1357% - 0.0000% 10,359,827 0.1437% 19,939,632 0.0872% 33701 - 0.0000% 745,708 0.0106% - 0.0000% 621,185 0.0086% 1,366,893 0.0060% 33702 - 0.0000% 2,421,964 0.0343% - 0.0000% 1,903,890 0.0264% 4,325,854 0.0189% 33703 - 0.0000% 3,229,583 0.0457% - 0.0000% 2,588,381 0.0359% 5,817,964 0.0254% 33704 - 0.0000% 2,559,380 0.0363% - 0.0000% 2,033,379 0.0282% 4,592,758 0.0201% 33705 - 0.0000% 1,581,214 0.0224% - 0.0000% 1,316,683 0.0183% 2,897,897 0.0127% 33706 - 0.0000% 3,331,221 0.0472% - 0.0000% 2,174,604 0.0302% 5,505,825 0.0241% 33707 - 0.0000% 2,400,848 0.0340% - 0.0000% 1,651,724 0.0229% 4,052,572 0.0177% 33708 - 0.0000% 2,295,021 0.0325% - 0.0000% 1,299,657 0.0180% 3,594,678 0.0157% 33709 - 0.0000% 1,444,600 0.0205% - 0.0000% 1,007,743 0.0140% 2,452,343 0.0107% 33710 - 0.0000% 3,032,203 0.0430% - 0.0000% 2,126,934 0.0295% 5,159,137 0.0226% 33711 - 0.0000% 968,984 0.0137% - 0.0000% 752,148 0.0104% 1,721,132 0.0075% 33712 - 0.0000% 1,166,867 0.0165% - 0.0000% 949,790 0.0132% 2,116,657 0.0093% 33713 - 0.0000% 2,145,366 0.0304% - 0.0000% 1,604,215 0.0223% 3,749,580 0.0164% 33714 - 0.0000% 845,657 0.0120% - 0.0000% 620,052 0.0086% 1,465,709 0.0064% 33715 - 0.0000% 1,863,344 0.0264% - 0.0000% 1,241,528 0.0172% 3,104,873 0.0136% 33716 - 0.0000% 316,439 0.0045% - 0.0000% 261,660 0.0036% 578,099 0.0025% 33755 - 0.0000% 2,187,255 0.0310% - 0.0000% 1,251,351 0.0174% 3,438,606 0.0150% 33756 - 0.0000% 3,327,866 0.0471% - 0.0000% 1,961,423 0.0272% 5,289,289 0.0231% 33759 - 0.0000% 1,542,174 0.0218% - 0.0000% 999,912 0.0139% 2,542,086 0.0111% 33760 - 0.0000% 819,569 0.0116% - 0.0000% 550,362 0.0076% 1,369,931 0.0060% 33761 - 0.0000% 2,279,044 0.0323% - 0.0000% 1,427,205 0.0198% 3,706,249 0.0162% 33762 - 0.0000% 851,585 0.0121% - 0.0000% 609,963 0.0085% 1,461,548 0.0064% 33763 - 0.0000% 1,286,255 0.0182% - 0.0000% 780,997 0.0108% 2,067,252 0.0090% 33764 - 0.0000% 2,459,194 0.0348% - 0.0000% 1,573,868 0.0218% 4,033,062 0.0176% 33765 - 0.0000% 985,756 0.0140% - 0.0000% 596,397 0.0083% 1,582,153 0.0069% 33767 - 0.0000% 2,067,566 0.0293% - 0.0000% 978,163 0.0136% 3,045,729 0.0133% 33770 - 0.0000% 2,671,394 0.0378% - 0.0000% 1,537,182 0.0213% 4,208,576 0.0184% 33771 - 0.0000% 1,480,119 0.0210% - 0.0000% 874,869 0.0121% 2,354,988 0.0103% 33772 - 0.0000% 2,501,946 0.0354% - 0.0000% 1,491,469 0.0207% 3,993,414 0.0175% 33773 - 0.0000% 1,570,043 0.0222% - 0.0000% 1,001,890 0.0139% 2,571,933 0.0112% 33774 - 0.0000% 2,145,796 0.0304% - 0.0000% 1,205,893 0.0167% 3,351,689 0.0147% 33776 - 0.0000% 2,018,730 0.0286% - 0.0000% 1,162,428 0.0161% 3,181,159 0.0139% 33777 - 0.0000% 1,895,171 0.0268% - 0.0000% 1,218,318 0.0169% 3,113,490 0.0136% 33778 - 0.0000% 1,345,505 0.0191% - 0.0000% 797,054 0.0111% 2,142,559 0.0094% 33781 - 0.0000% 1,548,024 0.0219% - 0.0000% 1,096,386 0.0152% 2,644,409 0.0116% 33782 - 0.0000% 1,897,216 0.0269% - 0.0000% 1,320,707 0.0183% 3,217,923 0.0141% 33785 - 0.0000% 1,249,480 0.0177% - 0.0000% 621,148 0.0086% 1,870,628 0.0082% 33786 - 0.0000% 1,732,735 0.0245% - 0.0000% 845,510 0.0117% 2,578,245 0.0113% 33801 1,155,558 0.0158% 4,798,502 0.0680% - 0.0000% 9,496,289 0.1317% 15,450,349 0.0675% 33803 1,825,133 0.0249% 7,106,423 0.1007% - 0.0000% 14,351,701 0.1991% 23,283,258 0.1018% 33805 525,889 0.0072% 3,041,055 0.0431% - 0.0000% 5,940,609 0.0824% 9,507,554 0.0416% 33809 918,197 0.0125% 5,930,561 0.0840% - 0.0000% 10,990,323 0.1525% 17,839,082 0.0780% 33810 1,154,160 0.0158% 9,753,233 0.1382% - 0.0000% 17,394,047 0.2413% 28,301,441 0.1237% 33811 1,160,068 0.0158% 4,820,099 0.0683% - 0.0000% 9,477,889 0.1315% 15,458,057 0.0676% 33812 4,102,011 0.0560% 4,867,005 0.0689% - 0.0000% 10,776,954 0.1495% 19,745,970 0.0863% 33813 4,479,242 0.0612% 11,765,480 0.1667% - 0.0000% 24,369,283 0.3380% 40,614,006 0.1775% 33815 163,623 0.0022% 1,016,968 0.0144% - 0.0000% 1,953,579 0.0271% 3,134,171 0.0137% 33823 8,577,629 0.1172% 8,482,608 0.1202% - 0.0000% 18,196,301 0.2524% 35,256,538 0.1541% 33825 28,556,603 0.3901% 7,752,774 0.1098% - 0.0000% 20,608,309 0.2859% 56,917,686 0.2488% 33827 26,761,741 0.3656% 2,192,934 0.0311% - 0.0000% 6,020,158 0.0835% 34,974,832 0.1529% 33830 34,259,663 0.4680% 8,244,803 0.1168% - 0.0000% 19,075,026 0.2646% 61,579,492 0.2692% 33834 11,793,914 0.1611% 777,893 0.0110% - 0.0000% 1,858,796 0.0258% 14,430,603 0.0631%

April 9, 2019 Applied Research Associates, Inc. 233 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33837 24,571,657 0.3357% 8,675,393 0.1229% - 0.0000% 18,820,870 0.2611% 52,067,920 0.2276% 33838 8,110,515 0.1108% 1,467,774 0.0208% - 0.0000% 3,675,828 0.0510% 13,254,118 0.0579% 33839 3,947,953 0.0539% 1,074,673 0.0152% - 0.0000% 2,562,373 0.0355% 7,584,999 0.0332% 33841 25,381,661 0.3467% 2,093,233 0.0297% - 0.0000% 5,178,314 0.0718% 32,653,207 0.1427% 33843 20,038,844 0.2738% 3,447,064 0.0488% - 0.0000% 9,092,660 0.1261% 32,578,568 0.1424% 33844 58,280,534 0.7962% 10,952,509 0.1551% - 0.0000% 26,773,683 0.3714% 96,006,727 0.4197% 33849 - 0.0000% 110,764 0.0016% - 0.0000% 180,870 0.0025% 291,634 0.0013% 33850 5,458,806 0.0746% 2,946,524 0.0417% - 0.0000% 6,377,844 0.0885% 14,783,174 0.0646% 33852 5,581,409 0.0762% 19,404,881 0.2749% - 0.0000% 38,109,315 0.5286% 63,095,604 0.2758% 33853 49,100,954 0.6708% 4,276,516 0.0606% - 0.0000% 11,361,086 0.1576% 64,738,556 0.2830% 33857 137,038 0.0019% 1,722,098 0.0244% - 0.0000% 3,033,895 0.0421% 4,893,032 0.0214% 33859 50,167,757 0.6853% 4,060,436 0.0575% - 0.0000% 10,282,414 0.1426% 64,510,607 0.2820% 33860 1,285,041 0.0176% 4,917,353 0.0697% - 0.0000% 9,807,858 0.1360% 16,010,253 0.0700% 33865 1,755,770 0.0240% 120,801 0.0017% - 0.0000% 246,336 0.0034% 2,122,907 0.0093% 33868 536,903 0.0073% 2,279,960 0.0323% - 0.0000% 4,299,388 0.0596% 7,116,251 0.0311% 33870 13,418,289 0.1833% 9,449,522 0.1339% - 0.0000% 22,158,502 0.3074% 45,026,312 0.1968% 33872 15,283,908 0.2088% 6,005,803 0.0851% - 0.0000% 14,533,886 0.2016% 35,823,596 0.1566% 33873 79,976,332 1.0926% 2,304,357 0.0326% - 0.0000% 5,787,754 0.0803% 88,068,444 0.3850% 33875 6,892,606 0.0942% 4,409,647 0.0625% - 0.0000% 10,636,172 0.1475% 21,938,425 0.0959% 33876 2,037,548 0.0278% 4,237,433 0.0600% - 0.0000% 9,084,669 0.1260% 15,359,650 0.0671% 33880 28,764,910 0.3930% 9,552,036 0.1353% - 0.0000% 22,410,759 0.3109% 60,727,705 0.2655% 33881 26,291,887 0.3592% 10,895,731 0.1543% - 0.0000% 24,669,526 0.3422% 61,857,144 0.2704% 33884 94,382,604 1.2894% 14,988,730 0.2123% - 0.0000% 37,884,861 0.5255% 147,256,195 0.6437% 33890 61,589,609 0.8414% 898,829 0.0127% - 0.0000% 2,201,033 0.0305% 64,689,471 0.2828% 33896 7,363,590 0.1006% 3,692,445 0.0523% - 0.0000% 7,659,085 0.1062% 18,715,120 0.0818% 33897 4,738,993 0.0647% 6,030,294 0.0854% - 0.0000% 11,337,878 0.1573% 22,107,165 0.0966% 33898 109,424,926 1.4949% 9,052,616 0.1282% - 0.0000% 24,830,074 0.3444% 143,307,615 0.6264% 33901 11,451,450 0.1564% 885,060 0.0125% - 0.0000% 1,095,824 0.0152% 13,432,334 0.0587% 33903 26,251,918 0.3586% 894,850 0.0127% - 0.0000% 1,161,978 0.0161% 28,308,747 0.1237% 33904 109,577,122 1.4969% 2,549,882 0.0361% - 0.0000% 2,786,862 0.0387% 114,913,865 0.5023% 33905 8,241,708 0.1126% 1,911,516 0.0271% - 0.0000% 2,292,471 0.0318% 12,445,694 0.0544% 33907 5,851,572 0.0799% 588,064 0.0083% - 0.0000% 668,016 0.0093% 7,107,653 0.0311% 33908 33,711,848 0.4605% 2,642,754 0.0374% - 0.0000% 2,681,231 0.0372% 39,035,833 0.1706% 33909 72,892,582 0.9958% 1,446,925 0.0205% - 0.0000% 1,780,920 0.0247% 76,120,427 0.3327% 33912 8,038,380 0.1098% 1,764,463 0.0250% - 0.0000% 1,914,634 0.0266% 11,717,477 0.0512% 33913 6,277,719 0.0858% 2,771,488 0.0393% - 0.0000% 3,066,478 0.0425% 12,115,685 0.0530% 33914 188,899,276 2.5805% 3,363,388 0.0476% - 0.0000% 3,514,191 0.0487% 195,776,855 0.8558% 33916 3,397,614 0.0464% 396,563 0.0056% - 0.0000% 466,670 0.0065% 4,260,846 0.0186% 33917 29,139,724 0.3981% 1,551,773 0.0220% - 0.0000% 1,981,758 0.0275% 32,673,255 0.1428% 33919 23,275,365 0.3180% 1,663,496 0.0236% - 0.0000% 1,826,403 0.0253% 26,765,264 0.1170% 33920 828,657 0.0113% 686,681 0.0097% - 0.0000% 856,801 0.0119% 2,372,140 0.0104% 33922 87,560,522 1.1962% 261,172 0.0037% - 0.0000% 245,528 0.0034% 88,067,222 0.3850% 33924 160,868,317 2.1976% 1,238,163 0.0175% - 0.0000% 1,000,662 0.0139% 163,107,142 0.7130% 33928 5,529,893 0.0755% 2,364,714 0.0335% - 0.0000% 2,298,091 0.0319% 10,192,698 0.0446% 33931 9,392,606 0.1283% 592,005 0.0084% - 0.0000% 580,830 0.0081% 10,565,441 0.0462% 33935 542,062 0.0074% 3,085,738 0.0437% - 0.0000% 4,082,837 0.0566% 7,710,637 0.0337% 33936 1,456,479 0.0199% 1,311,824 0.0186% - 0.0000% 1,568,258 0.0218% 4,336,561 0.0190% 33946 28,806,866 0.3935% 487,079 0.0069% - 0.0000% 427,435 0.0059% 29,721,379 0.1299% 33947 50,080,756 0.6842% 1,007,219 0.0143% - 0.0000% 1,038,754 0.0144% 52,126,729 0.2279% 33948 108,699,470 1.4849% 1,329,720 0.0188% - 0.0000% 1,602,531 0.0222% 111,631,721 0.4880% 33950 685,326,426 9.3622% 2,889,818 0.0409% - 0.0000% 3,817,640 0.0530% 692,033,884 3.0251% 33952 228,734,359 3.1247% 2,076,835 0.0294% - 0.0000% 2,616,362 0.0363% 233,427,555 1.0204% 33953 29,044,804 0.3968% 630,844 0.0089% - 0.0000% 723,612 0.0100% 30,399,260 0.1329% 33954 69,410,855 0.9482% 850,237 0.0120% - 0.0000% 1,075,753 0.0149% 71,336,845 0.3118% 33955 171,302,749 2.3402% 944,475 0.0134% - 0.0000% 1,156,763 0.0160% 173,403,987 0.7580% 33956 29,920,583 0.4087% 249,287 0.0035% - 0.0000% 215,562 0.0030% 30,385,432 0.1328% 33957 161,179,056 2.2019% 990,802 0.0140% - 0.0000% 849,787 0.0118% 163,019,645 0.7126% 33960 69,604 0.0010% 352,018 0.0050% - 0.0000% 588,136 0.0082% 1,009,758 0.0044% 33966 3,404,384 0.0465% 681,555 0.0097% - 0.0000% 765,576 0.0106% 4,851,515 0.0212% 33967 3,782,294 0.0517% 1,320,582 0.0187% - 0.0000% 1,327,662 0.0184% 6,430,538 0.0281% 33971 2,190,154 0.0299% 1,386,052 0.0196% - 0.0000% 1,601,278 0.0222% 5,177,484 0.0226% 33972 797,040 0.0109% 1,007,736 0.0143% - 0.0000% 1,154,139 0.0160% 2,958,915 0.0129%

April 9, 2019 Applied Research Associates, Inc. 234 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 33973 780,582 0.0107% 402,056 0.0057% - 0.0000% 451,160 0.0063% 1,633,798 0.0071% 33974 750,889 0.0103% 971,911 0.0138% - 0.0000% 1,106,377 0.0153% 2,829,177 0.0124% 33976 1,028,405 0.0140% 791,558 0.0112% - 0.0000% 909,636 0.0126% 2,729,599 0.0119% 33980 178,806,874 2.4427% 914,890 0.0130% - 0.0000% 1,331,607 0.0185% 181,053,371 0.7914% 33981 80,242,115 1.0962% 987,924 0.0140% - 0.0000% 1,124,459 0.0156% 82,354,497 0.3600% 33982 246,739,915 3.3707% 1,016,464 0.0144% - 0.0000% 1,664,341 0.0231% 249,420,720 1.0903% 33983 158,669,572 2.1676% 1,506,196 0.0213% - 0.0000% 2,139,517 0.0297% 162,315,285 0.7095% 33990 77,397,906 1.0573% 1,784,761 0.0253% - 0.0000% 2,073,109 0.0288% 81,255,775 0.3552% 33991 121,472,594 1.6594% 1,526,027 0.0216% - 0.0000% 1,591,591 0.0221% 124,590,212 0.5446% 33993 188,055,252 2.5690% 1,717,255 0.0243% - 0.0000% 1,969,137 0.0273% 191,741,644 0.8382% 34102 4,428,551 0.0605% 2,369,705 0.0336% - 0.0000% 2,165,091 0.0300% 8,963,348 0.0392% 34103 1,697,256 0.0232% 927,965 0.0131% - 0.0000% 861,790 0.0120% 3,487,011 0.0152% 34104 1,338,208 0.0183% 888,324 0.0126% - 0.0000% 804,093 0.0112% 3,030,625 0.0132% 34105 2,769,926 0.0378% 1,783,624 0.0253% - 0.0000% 1,636,713 0.0227% 6,190,263 0.0271% 34108 3,786,935 0.0517% 1,847,475 0.0262% - 0.0000% 1,733,358 0.0240% 7,367,768 0.0322% 34109 2,860,956 0.0391% 1,747,961 0.0248% - 0.0000% 1,613,170 0.0224% 6,222,086 0.0272% 34110 4,783,268 0.0653% 2,675,910 0.0379% - 0.0000% 2,516,779 0.0349% 9,975,957 0.0436% 34112 1,497,402 0.0205% 936,658 0.0133% - 0.0000% 834,320 0.0116% 3,268,380 0.0143% 34113 1,936,945 0.0265% 1,446,445 0.0205% - 0.0000% 1,280,115 0.0178% 4,663,505 0.0204% 34114 1,350,158 0.0184% 1,123,708 0.0159% - 0.0000% 966,717 0.0134% 3,440,583 0.0150% 34116 993,872 0.0136% 798,047 0.0113% - 0.0000% 720,535 0.0100% 2,512,454 0.0110% 34117 738,829 0.0101% 860,325 0.0122% - 0.0000% 766,970 0.0106% 2,366,124 0.0103% 34119 4,908,878 0.0671% 3,732,608 0.0529% - 0.0000% 3,420,536 0.0474% 12,062,022 0.0527% 34120 2,307,263 0.0315% 2,733,605 0.0387% - 0.0000% 2,477,586 0.0344% 7,518,454 0.0329% 34134 4,923,611 0.0673% 2,147,994 0.0304% - 0.0000% 2,046,410 0.0284% 9,118,015 0.0399% 34135 5,780,869 0.0790% 3,417,336 0.0484% - 0.0000% 3,211,361 0.0445% 12,409,566 0.0542% 34138 - 0.0000% 7,372 0.0001% - 0.0000% 4,968 0.0001% 12,340 0.0001% 34139 - 0.0000% 20,364 0.0003% - 0.0000% 16,128 0.0002% 36,492 0.0002% 34141 - 0.0000% 4,857 0.0001% - 0.0000% 3,676 0.0001% 8,534 0.0000% 34142 303,567 0.0041% 772,070 0.0109% - 0.0000% 723,791 0.0100% 1,799,428 0.0079% 34145 1,945,232 0.0266% 1,398,009 0.0198% - 0.0000% 1,069,433 0.0148% 4,412,674 0.0193% 34201 - 0.0000% 909,002 0.0129% - 0.0000% 993,499 0.0138% 1,902,501 0.0083% 34202 - 0.0000% 4,148,729 0.0588% - 0.0000% 4,794,691 0.0665% 8,943,420 0.0391% 34203 - 0.0000% 2,423,064 0.0343% - 0.0000% 2,528,477 0.0351% 4,951,541 0.0216% 34205 - 0.0000% 1,385,058 0.0196% - 0.0000% 1,331,905 0.0185% 2,716,963 0.0119% 34207 - 0.0000% 939,229 0.0133% - 0.0000% 880,734 0.0122% 1,819,963 0.0080% 34208 - 0.0000% 1,882,921 0.0267% - 0.0000% 1,957,684 0.0272% 3,840,604 0.0168% 34209 - 0.0000% 3,174,894 0.0450% - 0.0000% 2,796,117 0.0388% 5,971,011 0.0261% 34210 - 0.0000% 831,982 0.0118% - 0.0000% 735,924 0.0102% 1,567,906 0.0069% 34211 - 0.0000% 1,340,335 0.0190% - 0.0000% 1,631,141 0.0226% 2,971,475 0.0130% 34212 - 0.0000% 2,622,694 0.0372% - 0.0000% 3,133,122 0.0435% 5,755,816 0.0252% 34215 - 0.0000% 109,748 0.0016% - 0.0000% 91,956 0.0013% 201,704 0.0009% 34216 - 0.0000% 564,040 0.0080% - 0.0000% 408,419 0.0057% 972,459 0.0043% 34217 - 0.0000% 1,253,789 0.0178% - 0.0000% 917,909 0.0127% 2,171,698 0.0095% 34219 - 0.0000% 3,282,486 0.0465% - 0.0000% 4,165,956 0.0578% 7,448,443 0.0326% 34221 - 0.0000% 3,077,870 0.0436% - 0.0000% 3,077,870 0.0427% 6,155,740 0.0269% 34222 - 0.0000% 869,269 0.0123% - 0.0000% 956,903 0.0133% 1,826,173 0.0080% 34223 7,261,800 0.0992% 1,615,815 0.0229% - 0.0000% 1,488,385 0.0206% 10,365,999 0.0453% 34224 31,970,371 0.4367% 976,080 0.0138% - 0.0000% 967,106 0.0134% 33,913,556 0.1482% 34228 - 0.0000% 1,497,964 0.0212% - 0.0000% 1,251,833 0.0174% 2,749,797 0.0120% 34229 - 0.0000% 1,241,314 0.0176% - 0.0000% 1,214,483 0.0168% 2,455,796 0.0107% 34231 - 0.0000% 2,250,892 0.0319% - 0.0000% 2,234,223 0.0310% 4,485,115 0.0196% 34232 - 0.0000% 2,067,002 0.0293% - 0.0000% 2,235,116 0.0310% 4,302,118 0.0188% 34233 - 0.0000% 1,282,253 0.0182% - 0.0000% 1,347,876 0.0187% 2,630,128 0.0115% 34234 - 0.0000% 744,613 0.0105% - 0.0000% 716,454 0.0099% 1,461,066 0.0064% 34235 - 0.0000% 906,015 0.0128% - 0.0000% 984,522 0.0137% 1,890,537 0.0083% 34236 - 0.0000% 1,320,394 0.0187% - 0.0000% 1,246,406 0.0173% 2,566,799 0.0112% 34237 - 0.0000% 462,645 0.0066% - 0.0000% 462,645 0.0064% 925,291 0.0040% 34238 - 0.0000% 2,333,412 0.0331% - 0.0000% 2,420,519 0.0336% 4,753,932 0.0208% 34239 - 0.0000% 1,460,495 0.0207% - 0.0000% 1,450,236 0.0201% 2,910,731 0.0127% 34240 - 0.0000% 1,908,696 0.0270% - 0.0000% 2,186,782 0.0303% 4,095,478 0.0179% 34241 - 0.0000% 1,710,616 0.0242% - 0.0000% 1,916,584 0.0266% 3,627,201 0.0159%

April 9, 2019 Applied Research Associates, Inc. 235 Appendix A - Forms 4/9/2019 11:00 AM

Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 34242 - 0.0000% 1,315,866 0.0186% - 0.0000% 1,243,011 0.0172% 2,558,876 0.0112% 34243 - 0.0000% 2,604,124 0.0369% - 0.0000% 2,681,956 0.0372% 5,286,081 0.0231% 34250 - 0.0000% 110,054 0.0016% - 0.0000% 104,841 0.0015% 214,895 0.0009% 34251 1,533,064 0.0209% 912,484 0.0129% - 0.0000% 1,391,052 0.0193% 3,836,601 0.0168% 34266 362,339,023 4.9499% 3,092,067 0.0438% - 0.0000% 6,642,991 0.0921% 372,074,081 1.6265% 34269 67,297,724 0.9194% 439,044 0.0062% - 0.0000% 707,275 0.0098% 68,444,043 0.2992% 34275 - 0.0000% 1,988,595 0.0282% - 0.0000% 1,928,005 0.0267% 3,916,600 0.0171% 34285 693,807 0.0095% 1,288,562 0.0183% - 0.0000% 1,201,711 0.0167% 3,184,080 0.0139% 34286 56,311,344 0.7693% 1,569,460 0.0222% - 0.0000% 1,832,395 0.0254% 59,713,199 0.2610% 34287 35,356,157 0.4830% 1,523,737 0.0216% - 0.0000% 1,816,232 0.0252% 38,696,126 0.1692% 34288 42,962,480 0.5869% 1,056,448 0.0150% - 0.0000% 1,294,621 0.0180% 45,313,549 0.1981% 34289 13,807,228 0.1886% 221,490 0.0031% - 0.0000% 282,767 0.0039% 14,311,485 0.0626% 34291 5,011,224 0.0685% 530,052 0.0075% - 0.0000% 609,489 0.0085% 6,150,765 0.0269% 34292 1,428,225 0.0195% 1,588,562 0.0225% - 0.0000% 1,656,651 0.0230% 4,673,438 0.0204% 34293 3,494,529 0.0477% 3,226,076 0.0457% - 0.0000% 3,250,485 0.0451% 9,971,090 0.0436% 34420 - 0.0000% 3,557,350 0.0504% - 0.0000% 1,908,579 0.0265% 5,465,928 0.0239% 34428 - 0.0000% 1,462,838 0.0207% - 0.0000% 706,550 0.0098% 2,169,388 0.0095% 34429 - 0.0000% 1,956,992 0.0277% - 0.0000% 949,590 0.0132% 2,906,581 0.0127% 34431 - 0.0000% 1,873,573 0.0265% - 0.0000% 840,785 0.0117% 2,714,358 0.0119% 34432 - 0.0000% 3,245,878 0.0460% - 0.0000% 1,619,754 0.0225% 4,865,632 0.0213% 34433 - 0.0000% 1,379,935 0.0195% - 0.0000% 668,346 0.0093% 2,048,281 0.0090% 34434 - 0.0000% 1,607,132 0.0228% - 0.0000% 939,262 0.0130% 2,546,394 0.0111% 34436 - 0.0000% 1,331,090 0.0189% - 0.0000% 907,117 0.0126% 2,238,207 0.0098% 34442 - 0.0000% 4,148,544 0.0588% - 0.0000% 2,451,802 0.0340% 6,600,346 0.0289% 34446 - 0.0000% 4,066,037 0.0576% - 0.0000% 2,306,858 0.0320% 6,372,894 0.0279% 34448 - 0.0000% 1,643,048 0.0233% - 0.0000% 849,893 0.0118% 2,492,941 0.0109% 34449 - 0.0000% 394,243 0.0056% - 0.0000% 156,662 0.0022% 550,905 0.0024% 34450 - 0.0000% 2,078,404 0.0294% - 0.0000% 1,368,919 0.0190% 3,447,323 0.0151% 34452 - 0.0000% 1,947,582 0.0276% - 0.0000% 1,287,511 0.0179% 3,235,093 0.0141% 34453 - 0.0000% 1,920,235 0.0272% - 0.0000% 1,162,997 0.0161% 3,083,232 0.0135% 34461 - 0.0000% 2,385,173 0.0338% - 0.0000% 1,363,044 0.0189% 3,748,218 0.0164% 34465 - 0.0000% 4,068,929 0.0576% - 0.0000% 2,325,412 0.0323% 6,394,341 0.0280% 34470 - 0.0000% 3,052,812 0.0432% - 0.0000% 1,493,597 0.0207% 4,546,409 0.0199% 34471 - 0.0000% 6,761,452 0.0958% - 0.0000% 3,348,743 0.0465% 10,110,195 0.0442% 34472 - 0.0000% 5,035,502 0.0713% - 0.0000% 2,667,242 0.0370% 7,702,745 0.0337% 34473 - 0.0000% 3,699,581 0.0524% - 0.0000% 2,242,014 0.0311% 5,941,596 0.0260% 34474 - 0.0000% 2,577,367 0.0365% - 0.0000% 1,254,187 0.0174% 3,831,554 0.0167% 34475 - 0.0000% 1,228,473 0.0174% - 0.0000% 573,225 0.0080% 1,801,698 0.0079% 34476 - 0.0000% 7,805,092 0.1106% - 0.0000% 3,951,533 0.0548% 11,756,625 0.0514% 34479 - 0.0000% 2,639,319 0.0374% - 0.0000% 1,211,693 0.0168% 3,851,013 0.0168% 34480 - 0.0000% 5,406,592 0.0766% - 0.0000% 2,800,996 0.0389% 8,207,588 0.0359% 34481 - 0.0000% 5,209,589 0.0738% - 0.0000% 2,540,556 0.0352% 7,750,144 0.0339% 34482 - 0.0000% 5,499,627 0.0779% - 0.0000% 2,357,377 0.0327% 7,857,004 0.0343% 34484 - 0.0000% 1,466,083 0.0208% - 0.0000% 970,666 0.0135% 2,436,749 0.0107% 34488 - 0.0000% 1,239,630 0.0176% - 0.0000% 575,253 0.0080% 1,814,883 0.0079% 34491 - 0.0000% 9,270,219 0.1313% - 0.0000% 5,676,682 0.0787% 14,946,901 0.0653% 34498 - 0.0000% 155,097 0.0022% - 0.0000% 57,947 0.0008% 213,043 0.0009% 34601 - 0.0000% 3,030,788 0.0429% - 0.0000% 2,166,872 0.0301% 5,197,661 0.0227% 34602 - 0.0000% 1,546,248 0.0219% - 0.0000% 1,370,683 0.0190% 2,916,931 0.0128% 34604 - 0.0000% 1,662,956 0.0236% - 0.0000% 1,217,817 0.0169% 2,880,773 0.0126% 34606 - 0.0000% 5,239,088 0.0742% - 0.0000% 2,974,930 0.0413% 8,214,018 0.0359% 34607 - 0.0000% 1,987,269 0.0281% - 0.0000% 1,063,966 0.0148% 3,051,235 0.0133% 34608 - 0.0000% 6,192,130 0.0877% - 0.0000% 3,774,770 0.0524% 9,966,900 0.0436% 34609 - 0.0000% 8,552,068 0.1211% - 0.0000% 5,669,128 0.0786% 14,221,196 0.0622% 34610 - 0.0000% 1,913,348 0.0271% - 0.0000% 1,272,064 0.0176% 3,185,412 0.0139% 34613 - 0.0000% 3,841,303 0.0544% - 0.0000% 2,226,389 0.0309% 6,067,693 0.0265% 34614 - 0.0000% 1,136,383 0.0161% - 0.0000% 706,949 0.0098% 1,843,332 0.0081% 34637 - 0.0000% 1,357,989 0.0192% - 0.0000% 1,156,093 0.0160% 2,514,082 0.0110% 34638 - 0.0000% 3,998,809 0.0566% - 0.0000% 3,363,355 0.0467% 7,362,164 0.0322% 34639 - 0.0000% 5,036,287 0.0713% - 0.0000% 4,703,741 0.0652% 9,740,028 0.0426% 34652 - 0.0000% 3,026,908 0.0429% - 0.0000% 1,663,497 0.0231% 4,690,404 0.0205% 34653 - 0.0000% 3,114,554 0.0441% - 0.0000% 1,814,750 0.0252% 4,929,304 0.0215%

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Hurricane Charley Hurricane Frances Hurricane Ivan Hurricane Jeanne Total Personal & Personal & Personal & Personal & Personal & Commercial Percent Commercial Percent Commercial Percent Commercial Percent Percent ZIP Commercial Residential of Residential of Residential of Residential of of Code Residential Monetary Losses Monetary Losses Monetary Losses Monetary Losses Losses Monetary Contribution (%) Contribution (%) Contribution (%) Contribution (%) (%) Contribution ($) ($) ($) ($) ($) 34654 - 0.0000% 3,029,259 0.0429% - 0.0000% 2,042,767 0.0283% 5,072,026 0.0222% 34655 - 0.0000% 7,394,635 0.1047% - 0.0000% 4,935,959 0.0685% 12,330,594 0.0539% 34667 - 0.0000% 5,483,722 0.0777% - 0.0000% 2,896,632 0.0402% 8,380,354 0.0366% 34668 - 0.0000% 5,126,197 0.0726% - 0.0000% 2,713,070 0.0376% 7,839,267 0.0343% 34669 - 0.0000% 1,776,651 0.0252% - 0.0000% 1,116,847 0.0155% 2,893,498 0.0126% 34677 - 0.0000% 2,983,262 0.0423% - 0.0000% 2,065,533 0.0287% 5,048,795 0.0221% 34683 - 0.0000% 5,992,736 0.0849% - 0.0000% 3,586,661 0.0498% 9,579,397 0.0419% 34684 - 0.0000% 3,463,731 0.0491% - 0.0000% 2,090,924 0.0290% 5,554,655 0.0243% 34685 - 0.0000% 3,125,955 0.0443% - 0.0000% 2,139,370 0.0297% 5,265,326 0.0230% 34688 - 0.0000% 1,977,834 0.0280% - 0.0000% 1,334,466 0.0185% 3,312,300 0.0145% 34689 - 0.0000% 3,762,834 0.0533% - 0.0000% 2,069,546 0.0287% 5,832,380 0.0255% 34690 - 0.0000% 1,201,033 0.0170% - 0.0000% 691,598 0.0096% 1,892,631 0.0083% 34691 - 0.0000% 2,214,921 0.0314% - 0.0000% 1,173,366 0.0163% 3,388,288 0.0148% 34695 - 0.0000% 2,904,075 0.0411% - 0.0000% 1,875,909 0.0260% 4,779,984 0.0209% 34698 - 0.0000% 4,919,019 0.0697% - 0.0000% 2,833,060 0.0393% 7,752,079 0.0339% 34705 - 0.0000% 887,053 0.0126% - 0.0000% 782,443 0.0109% 1,669,495 0.0073% 34711 2,414,039 0.0330% 30,187,145 0.4276% - 0.0000% 39,650,892 0.5500% 72,252,076 0.3158% 34714 1,247,121 0.0170% 4,243,259 0.0601% - 0.0000% 6,852,927 0.0951% 12,343,307 0.0540% 34715 - 0.0000% 7,936,623 0.1124% - 0.0000% 8,675,310 0.1203% 16,611,933 0.0726% 34731 - 0.0000% 3,496,718 0.0495% - 0.0000% 2,483,414 0.0344% 5,980,132 0.0261% 34734 1,167,089 0.0159% 1,763,207 0.0250% - 0.0000% 2,141,064 0.0297% 5,071,360 0.0222% 34736 - 0.0000% 4,348,811 0.0616% - 0.0000% 4,717,282 0.0654% 9,066,093 0.0396% 34737 - 0.0000% 2,136,740 0.0303% - 0.0000% 1,774,385 0.0246% 3,911,125 0.0171% 34739 81,568 0.0011% 970,966 0.0138% - 0.0000% 2,027,070 0.0281% 3,079,603 0.0135% 34741 34,062,943 0.4653% 6,043,609 0.0856% - 0.0000% 11,947,531 0.1657% 52,054,083 0.2275% 34743 107,342,830 1.4664% 10,455,273 0.1481% - 0.0000% 20,292,046 0.2815% 138,090,148 0.6036% 34744 203,550,338 2.7807% 18,895,182 0.2676% - 0.0000% 38,398,945 0.5327% 260,844,465 1.1402% 34746 85,243,163 1.1645% 13,588,199 0.1925% - 0.0000% 30,961,175 0.4295% 129,792,537 0.5674% 34747 23,424,182 0.3200% 9,911,958 0.1404% - 0.0000% 19,230,672 0.2668% 52,566,812 0.2298% 34748 - 0.0000% 17,333,919 0.2455% - 0.0000% 14,654,597 0.2033% 31,988,517 0.1398% 34753 - 0.0000% 1,096,278 0.0155% - 0.0000% 1,275,223 0.0177% 2,371,501 0.0104% 34756 228,242 0.0031% 2,853,505 0.0404% - 0.0000% 3,050,623 0.0423% 6,132,370 0.0268% 34758 49,335,563 0.6740% 7,875,287 0.1116% - 0.0000% 19,166,288 0.2659% 76,377,139 0.3339% 34759 116,464,918 1.5910% 9,279,712 0.1314% - 0.0000% 22,673,789 0.3145% 148,418,419 0.6488% 34761 4,817,249 0.0658% 11,358,501 0.1609% - 0.0000% 12,260,740 0.1701% 28,436,489 0.1243% 34762 - 0.0000% 205,527 0.0029% - 0.0000% 157,453 0.0022% 362,980 0.0016% 34769 47,415,924 0.6477% 11,408,157 0.1616% - 0.0000% 24,386,694 0.3383% 83,210,775 0.3637% 34771 20,721,858 0.2831% 8,149,811 0.1154% - 0.0000% 18,260,656 0.2533% 47,132,325 0.2060% 34772 42,252,734 0.5772% 10,769,130 0.1525% - 0.0000% 27,449,809 0.3808% 80,471,673 0.3518% 34773 393,472 0.0054% 1,679,587 0.0238% - 0.0000% 4,188,538 0.0581% 6,261,596 0.0274% 34785 - 0.0000% 2,331,087 0.0330% - 0.0000% 1,633,582 0.0227% 3,964,669 0.0173% 34786 19,266,087 0.2632% 26,870,666 0.3806% - 0.0000% 37,104,027 0.5147% 83,240,780 0.3639% 34787 6,807,941 0.0930% 23,556,538 0.3337% - 0.0000% 30,197,209 0.4189% 60,561,688 0.2647% 34788 - 0.0000% 7,090,531 0.1004% - 0.0000% 4,658,867 0.0646% 11,749,398 0.0514% 34797 - 0.0000% 1,346,944 0.0191% - 0.0000% 994,700 0.0138% 2,341,644 0.0102% 34945 - 0.0000% 13,015,296 0.1844% - 0.0000% 16,881,726 0.2342% 29,897,023 0.1307% 34946 - 0.0000% 6,531,070 0.0925% - 0.0000% 9,136,214 0.1267% 15,667,285 0.0685% 34947 - 0.0000% 7,715,218 0.1093% - 0.0000% 10,668,690 0.1480% 18,383,908 0.0804% 34949 - 0.0000% 26,847,588 0.3803% - 0.0000% 43,016,412 0.5967% 69,864,000 0.3054% 34950 - 0.0000% 9,151,199 0.1296% - 0.0000% 13,180,534 0.1828% 22,331,734 0.0976% 34951 - 0.0000% 37,744,520 0.5346% - 0.0000% 52,738,493 0.7316% 90,483,012 0.3955% 34952 - 0.0000% 76,915,316 1.0895% - 0.0000% 100,384,750 1.3925% 177,300,066 0.7750% 34953 - 0.0000% 148,351,139 2.1014% - 0.0000% 185,417,806 2.5720% 333,768,945 1.4590% 34956 - 0.0000% 6,698,685 0.0949% - 0.0000% 6,940,108 0.0963% 13,638,792 0.0596% 34957 - 0.0000% 65,805,947 0.9321% - 0.0000% 89,001,467 1.2346% 154,807,414 0.6767% 34972 252,545 0.0035% 21,660,237 0.3068% - 0.0000% 25,809,648 0.3580% 47,722,430 0.2086% 34974 436,353 0.0060% 45,885,871 0.6500% - 0.0000% 48,338,034 0.6705% 94,660,258 0.4138% 34981 - 0.0000% 5,838,356 0.0827% - 0.0000% 7,785,438 0.1080% 13,623,795 0.0596% 34982 - 0.0000% 35,236,371 0.4991% - 0.0000% 48,701,231 0.6756% 83,937,602 0.3669% 34983 - 0.0000% 79,958,373 1.1326% - 0.0000% 104,839,250 1.4543% 184,797,623 0.8078% 34984 - 0.0000% 39,864,286 0.5647% - 0.0000% 51,082,284 0.7086% 90,946,570 0.3976% 34986 - 0.0000% 97,420,127 1.3800% - 0.0000% 126,101,779 1.7492% 223,521,906 0.9771%

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April 9, 2019 Applied Research Associates, Inc. 238 Appendix A - Forms 4/9/2019 11:00 AM

Figure 62. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Charley

Figure 63. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Frances

April 9, 2019 Applied Research Associates, Inc. 239 Appendix A - Forms 4/9/2019 11:00 AM

Figure 64. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Ivan

Figure 65. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for Hurricane Jeanne

April 9, 2019 Applied Research Associates, Inc. 240 Appendix A - Forms 4/9/2019 11:00 AM

Figure 66. Percentage of Total Personal and Commercial Residential Modeled Losses by ZIP Code for All Four of the 2004 Hurricanes

April 9, 2019 Applied Research Associates, Inc. 241 Appendix A - Forms 4/9/2019 11:00 AM

Form A-4A: Hurricane Output Ranges (2012 FHCF Exposure Data) A. Provide personal and commercial residential hurricane output ranges in the format shown in the file named “2017FormA4A.xlsx” by using an automated program or script. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-4A, Hurricane Output Ranges (2012 FHCF Exposure Data), in a submission appendix. B. Provide hurricane loss costs rounded to three decimal places, by county. Within each county, hurricane loss costs shall be shown separately per $1,000 of exposure for frame owners, masonry owners, frame renters, masonry renters, frame condo unit owners, masonry condo unit owners, manufactured home, and commercial residential. For each of these categories using ZIP Code centroids, the hurricane output range shall show the highest hurricane loss cost, the lowest hurricane loss cost, and the weighted average hurricane loss cost. The aggregate residential exposure data for this form shall be developed from the information in the file named “hlpm2012c.exe,” except for insured value and deductibles information. Insured values shall be based on the hurricane output range specifications below. Deductible amounts of 0% and as specified in the hurricane output range specifications will be assumed to be uniformly applied to all risks. When calculating the weighted average hurricane loss costs, weight the hurricane loss costs by the total insured value calculated above. Include the statewide range of hurricane loss costs (i.e., low, high, and weighted average). C. If a modeling organization has hurricane loss costs for a ZIP Code for which there is no exposure, give the hurricane loss costs zero weight (i.e., assume the exposure in that ZIP Code is zero). Provide a list in the submission document of those ZIP Codes where this occurs. D. If a modeling organization does not have hurricane loss costs for a ZIP Code for which there is some exposure, do not assume such hurricane loss costs are zero, but use only the exposures for which there are hurricane loss costs in calculating the weighted average hurricane loss costs. Provide a list in the submission document of the ZIP Codes where this occurs. E. NA shall be used in cells to signify no exposure. F. All hurricane loss costs that are not consistent with the requirements of Standard A-6 , Hurricane Loss Outputs and Logical Relationships to Risk, and have been explained in Disclosure A-6.17 shall be shaded. G. Indicate if per diem is used in producing hurricane loss costs for Coverage D (Time Element) in the personal residential hurricane output ranges. If a per diem rate is used, a rate of $150.00 per day per policy shall be used. Loss costs are provided in the file named ARA17FormA4A.xlsx. Per diem is not used in producing loss costs for Coverage D (ALE). The model does not produce hurricane loss costs for any ZIP Codes for which there is no exposure, and it does produce loss costs for every ZIP Code for which there is exposure in the FHCF exposure data.

April 9, 2019 Applied Research Associates, Inc. 242 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Alachua LOW 0.409 0.415 1.504 0.044 0.038 0.102 0.106 0.310 AVG. 0.658 0.642 2.091 0.090 0.089 0.167 0.163 0.405 HIGH 1.081 1.059 2.601 0.122 0.116 0.201 0.194 0.660

Baker LOW 0.267 0.265 0.875 0.045 0.045 NA NA NA AVG. 0.432 0.430 1.150 0.060 0.063 NA NA NA HIGH 0.597 0.589 1.279 0.068 0.066 NA NA NA

Bay LOW 0.683 0.720 2.833 0.088 0.082 0.207 0.178 0.598 AVG. 1.459 1.346 3.939 0.172 0.170 0.411 0.380 1.132 HIGH 2.814 2.758 7.152 0.336 0.316 0.564 0.544 1.874

Bradford LOW 0.396 0.391 1.425 0.054 0.054 NA NA NA AVG. 0.577 0.580 1.632 0.080 0.076 NA NA NA HIGH 0.829 0.815 1.825 0.094 0.079 NA NA NA

Brevard LOW 1.898 1.872 6.532 0.175 0.129 0.441 0.349 0.976 AVG. 4.391 4.385 11.013 0.843 0.821 1.203 1.546 3.299 HIGH 8.200 8.069 19.672 1.982 1.925 2.646 2.580 5.028

Broward LOW 5.790 5.600 21.723 0.448 0.378 1.019 0.923 2.639 AVG. 7.923 7.495 24.714 1.316 1.321 2.059 2.029 5.659 HIGH 10.863 10.493 31.512 2.344 2.211 3.235 3.075 7.870

Calhoun LOW 0.370 0.367 1.281 0.063 0.072 NA NA NA AVG. 0.570 0.564 1.666 0.078 0.076 NA NA NA HIGH 0.916 0.903 2.032 0.101 0.078 NA NA NA

Charlotte LOW 2.621 2.583 9.780 0.224 0.184 0.525 0.429 1.547 AVG. 4.471 4.097 13.100 0.726 0.656 1.227 0.977 2.787 HIGH 5.765 5.655 14.982 1.178 1.131 1.666 1.611 3.618

Citrus LOW 0.828 0.816 3.245 0.112 0.095 0.224 0.204 0.814 AVG. 1.326 1.257 4.002 0.219 0.201 0.366 0.369 1.047 HIGH 1.885 1.848 4.518 0.286 0.272 0.430 0.414 1.180

Clay LOW 0.434 0.430 1.677 0.056 0.057 0.112 0.109 0.345 AVG. 0.702 0.686 1.875 0.103 0.103 0.164 0.157 0.434 HIGH 1.122 1.101 2.606 0.140 0.134 0.232 0.225 0.517

Collier LOW 3.041 2.980 11.852 0.347 0.312 0.662 0.525 2.202 AVG. 5.908 5.550 16.648 1.329 1.254 1.937 1.822 4.444 HIGH 12.898 10.913 34.156 2.970 2.884 3.787 3.688 8.502

Columbia LOW 0.241 0.241 0.822 0.023 0.021 0.096 0.096 0.216 AVG. 0.423 0.416 1.295 0.050 0.048 0.100 0.098 0.221 HIGH 0.645 0.634 1.481 0.061 0.057 0.107 0.100 0.242

DeSoto LOW 2.551 2.496 10.899 0.378 0.266 0.663 0.518 2.450 AVG. 4.768 4.440 12.757 0.716 0.632 0.968 0.813 2.540 HIGH 5.163 5.085 13.128 0.757 0.724 1.200 1.160 2.819

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County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Dixie LOW 0.289 0.293 0.903 0.047 0.056 0.080 0.081 0.171 AVG. 0.420 0.399 1.191 0.062 0.059 0.088 0.091 0.186 HIGH 0.559 0.550 1.218 0.071 0.068 0.098 0.120 0.275

Duval LOW 0.368 0.384 1.396 0.049 0.040 0.116 0.111 0.249 AVG. 0.833 0.818 2.053 0.139 0.135 0.210 0.211 0.561 HIGH 1.582 1.660 4.265 0.298 0.287 0.385 0.373 1.032

Escambia LOW 1.698 1.670 7.202 0.169 0.158 0.643 0.571 1.999 AVG. 3.888 3.852 10.732 0.868 0.876 1.495 1.564 3.776 HIGH 7.017 6.466 18.343 1.845 1.783 2.323 2.272 5.407

Flagler LOW 0.867 0.856 3.375 0.101 0.092 0.212 0.210 0.517 AVG. 1.273 1.209 4.032 0.188 0.167 0.360 0.293 0.807 HIGH 2.024 1.985 4.659 0.312 0.301 0.463 0.449 1.224

Franklin LOW 0.260 0.266 0.801 0.038 0.038 0.080 0.081 0.149 AVG. 0.399 0.400 1.052 0.055 0.051 0.089 0.098 0.152 HIGH 0.757 0.745 1.811 0.063 0.060 0.124 0.105 0.152

Gadsden LOW 0.180 0.182 0.581 0.032 0.032 NA 0.078 0.088 AVG. 0.269 0.276 0.705 0.040 0.040 NA 0.078 0.122 HIGH 0.426 0.421 0.897 0.048 0.050 NA 0.078 0.124

Gilchrist LOW 0.375 0.348 1.412 0.039 0.046 NA 0.111 NA AVG. 0.581 0.574 1.746 0.080 0.073 NA 0.111 NA HIGH 0.805 0.789 1.916 0.085 0.079 NA 0.111 NA

Glades LOW 3.635 3.052 11.709 0.908 0.442 NA NA NA AVG. 6.235 5.689 17.153 0.908 0.802 NA NA NA HIGH 6.691 6.600 17.366 0.908 0.865 NA NA NA

Gulf LOW 0.420 0.418 1.581 0.068 0.068 0.138 0.136 0.191 AVG. 0.581 0.578 1.586 0.090 0.087 0.145 0.140 0.282 HIGH 0.765 0.755 1.589 0.100 0.098 0.171 0.163 0.313

Hamilton LOW 0.185 0.184 0.644 0.026 0.032 NA NA NA AVG. 0.263 0.262 0.724 0.034 0.033 NA NA NA HIGH 0.399 0.394 0.839 0.044 0.042 NA NA NA

Hardee LOW 2.158 2.083 8.997 0.240 0.160 NA 0.855 1.450 AVG. 3.916 3.741 9.753 0.498 0.464 NA 0.855 1.646 HIGH 4.352 4.291 10.657 0.570 0.545 NA 0.855 1.841

Hendry LOW 3.428 3.365 16.960 0.330 0.291 0.930 0.495 2.785 AVG. 5.972 5.481 17.072 0.825 0.737 1.305 1.109 3.204 HIGH 6.469 6.366 17.192 0.978 0.937 1.515 1.467 3.456

Hernando LOW 1.130 1.040 4.277 0.150 0.109 0.410 0.293 0.971 AVG. 2.188 2.135 4.950 0.290 0.286 0.558 0.554 1.229 HIGH 2.759 2.710 6.130 0.415 0.396 0.634 0.633 1.506

Highlands LOW 1.624 1.493 6.281 0.130 0.120 0.387 0.305 1.214 AVG. 3.574 3.380 8.981 0.366 0.329 0.699 0.688 1.758 HIGH 4.933 4.868 12.644 0.559 0.531 0.989 0.957 2.402

Hills- LOW 1.154 1.144 4.637 0.126 0.102 0.292 0.291 1.018 borough AVG. 2.721 2.606 6.785 0.363 0.354 0.621 0.631 1.657 HIGH 4.548 4.461 9.004 0.758 0.762 1.144 1.164 3.010

April 9, 2019 Applied Research Associates, Inc. 244 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential

Holmes LOW 0.637 0.632 2.569 0.080 0.111 0.210 NA 0.503 AVG. 0.970 0.943 2.788 0.138 0.123 0.210 NA 0.503 HIGH 1.556 1.532 3.321 0.186 0.179 0.210 NA 0.503

Indian LOW 3.752 3.680 13.384 0.291 0.281 0.870 0.625 2.619 River AVG. 6.153 5.542 16.759 1.327 1.307 1.897 1.992 4.731 HIGH 9.319 9.146 21.341 2.427 2.354 3.173 3.088 5.851

Jackson LOW 0.328 0.328 1.246 0.035 0.038 NA 0.095 0.234 AVG. 0.576 0.579 1.726 0.061 0.059 NA 0.118 0.341 HIGH 1.020 1.005 2.240 0.094 0.075 NA 0.141 0.381

Jefferson LOW 0.146 0.148 0.455 0.022 0.023 0.057 NA NA AVG. 0.194 0.191 0.495 0.026 0.026 0.057 NA NA HIGH 0.250 0.248 0.500 0.032 0.032 0.057 NA NA

Lafayette LOW 0.203 0.219 0.692 0.031 0.038 0.078 NA NA AVG. 0.284 0.279 0.756 0.039 0.038 0.078 NA NA HIGH 0.362 0.357 0.756 0.040 0.038 0.078 NA NA

Lake LOW 0.786 0.736 2.922 0.076 0.063 0.222 0.215 0.843 AVG. 2.200 2.130 5.412 0.213 0.202 0.524 0.498 1.248 HIGH 3.401 3.361 8.129 0.406 0.388 0.639 0.620 1.700

Lee LOW 2.745 2.689 12.575 0.246 0.216 0.563 0.464 1.829 AVG. 5.973 5.060 14.020 1.109 0.947 1.683 1.472 3.776 HIGH 10.345 10.137 25.425 2.932 2.844 3.751 3.648 6.942

Leon LOW 0.169 0.168 0.548 0.026 0.026 0.058 0.060 0.053 AVG. 0.236 0.235 0.576 0.032 0.032 0.066 0.067 0.089 HIGH 0.317 0.313 0.623 0.042 0.041 0.075 0.077 0.095

Levy LOW 0.449 0.443 1.805 0.058 0.060 0.139 0.148 0.449 AVG. 0.924 0.959 3.077 0.144 0.146 0.190 0.187 0.561 HIGH 1.812 1.776 4.905 0.279 0.266 0.213 0.207 0.800

Liberty LOW 0.265 0.263 0.849 0.056 0.068 NA NA NA AVG. 0.384 0.385 0.949 0.067 0.068 NA NA NA HIGH 0.526 0.520 1.007 0.069 0.068 NA NA NA

Madison LOW 0.151 0.150 0.481 0.017 0.020 NA NA NA AVG. 0.214 0.212 0.583 0.026 0.026 NA NA NA HIGH 0.324 0.319 0.722 0.027 0.027 NA NA NA

Manatee LOW 2.437 2.402 9.010 0.178 0.147 0.417 0.406 1.352 AVG. 4.579 3.926 10.760 0.687 0.599 1.318 1.263 3.258 HIGH 8.278 8.155 21.361 1.948 1.890 2.618 2.552 5.979

Marion LOW 0.624 0.615 2.351 0.076 0.047 0.184 0.166 0.480 AVG. 1.308 1.214 3.720 0.157 0.146 0.281 0.333 0.793 HIGH 1.989 1.946 5.093 0.272 0.256 0.424 0.408 1.080

Martin LOW 5.035 4.931 19.640 0.436 0.424 0.959 0.878 3.328 AVG. 8.251 7.563 22.604 1.994 1.905 2.747 2.955 6.038 HIGH 11.550 11.347 26.507 3.233 3.144 4.145 4.041 7.493

April 9, 2019 Applied Research Associates, Inc. 245 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Miami- LOW 4.400 5.066 16.570 0.543 0.434 0.990 0.881 2.584 Dade AVG. 9.261 8.596 34.625 1.871 1.883 2.683 2.644 7.005 HIGH 15.620 15.378 43.429 4.583 4.413 5.747 5.621 12.618

Monroe LOW 6.753 6.454 33.899 2.385 0.950 1.677 1.547 4.194 AVG. 13.093 12.766 37.600 5.591 5.263 5.114 5.432 10.216 HIGH 20.994 20.721 48.884 8.330 8.198 7.712 9.813 14.383

Nassau LOW 0.326 0.336 1.192 0.054 0.046 0.142 0.131 0.273 AVG. 0.932 0.801 1.879 0.165 0.153 0.288 0.293 0.748 HIGH 1.418 1.391 3.581 0.235 0.225 0.334 0.324 0.925

Okaloosa LOW 1.038 1.025 3.976 0.170 0.182 0.356 0.409 1.085 AVG. 2.637 2.708 6.079 0.480 0.518 0.867 0.950 2.543 HIGH 5.352 5.242 14.559 1.070 1.031 1.434 1.390 4.194

Okeecho- LOW 3.176 3.120 14.238 0.408 0.269 0.633 0.564 2.623 bee AVG. 5.488 5.091 14.860 0.737 0.663 0.919 1.178 2.960 HIGH 6.059 5.961 15.002 0.787 0.747 1.310 1.263 3.245

Orange LOW 0.998 0.988 3.985 0.066 0.064 0.212 0.204 0.614 AVG. 2.142 2.174 5.551 0.233 0.220 0.421 0.414 1.086 HIGH 2.926 2.888 6.632 0.388 0.400 0.573 0.565 1.336

Osceola LOW 1.024 1.017 4.075 0.099 0.093 0.236 0.232 0.535 AVG. 2.316 2.331 6.795 0.237 0.222 0.406 0.373 1.079 HIGH 4.837 4.765 10.996 0.680 0.567 0.807 0.782 1.915

Palm LOW 5.287 5.107 19.842 0.431 0.390 0.980 0.868 3.225 Beach AVG. 7.945 7.348 24.972 1.493 1.394 2.263 2.115 5.745 HIGH 13.252 12.888 34.349 3.538 3.396 4.588 4.421 10.314

Pasco LOW 1.148 1.136 4.639 0.125 0.116 0.270 0.270 0.983 AVG. 2.256 2.344 6.096 0.278 0.296 0.536 0.613 1.537 HIGH 3.248 3.192 7.247 0.481 0.460 0.747 0.722 1.860

Pinellas LOW 1.683 1.663 6.579 0.131 0.125 0.342 0.323 1.095 AVG. 4.055 3.797 8.988 0.602 0.619 1.072 1.087 2.594 HIGH 8.030 7.909 16.335 1.874 1.816 2.525 2.460 5.815

Polk LOW 1.088 1.078 4.437 0.075 0.067 0.230 0.227 0.840 AVG. 2.569 2.433 6.622 0.252 0.259 0.428 0.487 1.265 HIGH 4.454 4.401 10.534 0.536 0.514 0.924 0.898 1.827

Putnam LOW 0.543 0.537 2.005 0.065 0.056 0.178 0.135 0.550 AVG. 0.911 0.909 2.675 0.137 0.131 0.253 0.205 0.595 HIGH 1.484 1.459 3.369 0.169 0.160 0.282 0.265 0.651

St. Johns LOW 0.577 0.569 2.316 0.055 0.053 0.136 0.147 0.354 AVG. 1.089 1.280 3.277 0.191 0.197 0.366 0.433 0.971 HIGH 2.528 2.485 6.621 0.462 0.447 0.633 0.617 1.696

St. Lucie LOW 4.489 4.064 14.843 0.612 0.331 0.833 0.764 3.279 AVG. 6.986 6.076 18.409 1.563 1.231 2.164 2.035 4.908 HIGH 10.400 10.194 24.624 2.751 2.665 3.580 3.479 6.660

April 9, 2019 Applied Research Associates, Inc. 246 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Santa LOW 1.619 1.729 6.880 0.184 0.238 0.507 0.437 1.208 Rosa AVG. 3.386 3.520 9.706 0.753 0.718 2.009 1.776 3.948 HIGH 7.951 7.784 21.356 2.248 2.190 2.795 2.729 6.671

Sarasota LOW 2.432 2.400 9.439 0.199 0.190 0.451 0.438 1.535 AVG. 4.108 3.736 11.678 0.644 0.596 1.135 1.078 2.712 HIGH 6.627 6.503 15.483 1.313 1.260 1.864 1.803 4.104

Seminole LOW 0.921 0.914 4.398 0.124 0.105 0.233 0.229 0.574 AVG. 2.048 2.044 5.094 0.240 0.231 0.422 0.417 0.976 HIGH 2.863 2.817 6.224 0.376 0.360 0.587 0.560 1.517

Sumter LOW 0.941 0.880 3.482 0.084 0.053 0.239 0.197 0.799 AVG. 1.464 1.411 3.976 0.138 0.143 0.336 0.267 0.941 HIGH 2.279 2.247 5.135 0.248 0.301 0.377 0.373 1.216

Suwannee LOW 0.229 0.226 0.882 0.019 0.024 0.076 0.075 0.162 AVG. 0.342 0.339 1.030 0.033 0.033 0.076 0.075 0.233 HIGH 0.589 0.580 1.453 0.052 0.049 0.076 0.075 0.273

Taylor LOW 0.152 0.159 0.481 0.026 0.027 0.052 0.065 0.125 AVG. 0.222 0.216 0.594 0.029 0.029 0.068 0.071 0.125 HIGH 0.337 0.333 0.695 0.041 0.040 0.079 0.078 0.125

Union LOW 0.359 0.354 1.256 0.048 0.041 0.101 0.100 0.281 AVG. 0.485 0.482 1.352 0.068 0.063 0.101 0.100 0.281 HIGH 0.629 0.620 1.365 0.074 0.072 0.101 0.100 0.281

Volusia LOW 0.803 0.783 3.029 0.107 0.093 0.246 0.239 0.484 AVG. 2.282 2.165 4.930 0.289 0.295 0.721 0.850 1.587 HIGH 4.885 4.822 11.294 0.942 0.913 1.350 1.317 3.015

Wakulla LOW 0.177 0.176 0.581 0.025 0.030 0.065 0.064 0.088 AVG. 0.243 0.245 0.607 0.035 0.034 0.076 0.078 0.156 HIGH 0.483 0.476 1.107 0.043 0.041 0.089 0.081 0.181

Walton LOW 1.013 1.003 3.976 0.130 0.129 0.302 0.261 0.876 AVG. 2.139 1.963 4.986 0.280 0.273 0.671 0.602 2.008 HIGH 3.912 3.824 9.842 0.567 0.536 0.855 0.821 2.786

Washing- LOW 0.699 0.693 2.591 0.077 0.076 0.256 NA 0.529 ton AVG. 1.003 0.998 2.990 0.125 0.116 0.256 NA 0.571 HIGH 1.576 1.430 3.296 0.207 0.200 0.256 NA 0.656

Statewide LOW 0.146 0.148 0.455 0.017 0.020 0.052 0.060 0.053 AVG. 2.628 4.370 8.037 0.430 0.730 0.861 1.610 4.116 HIGH 20.994 20.721 48.884 8.330 8.198 7.712 9.813 14.383

April 9, 2019 Applied Research Associates, Inc. 247 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Alachua LOW 0.134 0.148 1.014 0.002 0.002 0.006 0.007 0.209 AVG. 0.334 0.318 1.517 0.025 0.023 0.038 0.035 0.291 HIGH 0.668 0.647 1.984 0.064 0.060 0.085 0.080 0.533

Baker LOW 0.072 0.070 0.539 0.001 0.002 NA NA NA AVG. 0.185 0.183 0.749 0.010 0.013 NA NA NA HIGH 0.298 0.290 0.847 0.016 0.015 NA NA NA

Bay LOW 0.270 0.265 1.995 0.004 0.005 0.014 0.013 0.343 AVG. 0.817 0.732 2.916 0.057 0.059 0.138 0.120 0.843 HIGH 1.864 1.810 5.731 0.203 0.189 0.267 0.248 1.538

Bradford LOW 0.142 0.138 0.949 0.006 0.006 NA NA NA AVG. 0.275 0.276 1.118 0.023 0.020 NA NA NA HIGH 0.444 0.432 1.264 0.029 0.023 NA NA NA

Brevard LOW 1.090 1.066 5.164 0.052 0.044 0.117 0.056 0.620 AVG. 3.190 3.170 9.274 0.608 0.593 0.744 1.027 2.713 HIGH 6.573 6.442 17.388 1.618 1.570 1.978 1.916 4.282

Broward LOW 4.141 3.953 19.331 0.132 0.104 0.351 0.245 1.785 AVG. 6.150 5.730 22.227 0.886 0.883 1.270 1.234 4.724 HIGH 8.897 8.531 28.804 1.825 1.704 2.344 2.189 6.511

Calhoun LOW 0.093 0.091 0.764 0.001 0.003 NA NA NA AVG. 0.230 0.224 1.064 0.007 0.005 NA NA NA HIGH 0.469 0.457 1.355 0.015 0.013 NA NA NA

Charlotte LOW 1.638 1.601 8.190 0.062 0.032 0.123 0.109 1.056 AVG. 3.276 2.934 11.308 0.462 0.408 0.714 0.507 2.250 HIGH 4.455 4.346 13.036 0.840 0.803 1.082 1.033 3.017

Citrus LOW 0.401 0.348 2.427 0.018 0.004 0.045 0.040 0.610 AVG. 0.805 0.744 3.149 0.097 0.084 0.153 0.156 0.822 HIGH 1.254 1.213 3.650 0.175 0.164 0.225 0.210 0.945

Clay LOW 0.154 0.150 1.143 0.003 0.005 0.008 0.012 0.236 AVG. 0.359 0.347 1.302 0.041 0.041 0.047 0.041 0.312 HIGH 0.669 0.650 1.922 0.080 0.076 0.101 0.095 0.403

Collier LOW 1.911 1.850 10.053 0.094 0.042 0.158 0.113 1.567 AVG. 4.520 4.182 14.703 0.960 0.902 1.299 1.191 3.718 HIGH 10.884 8.915 31.448 2.494 2.421 3.004 2.911 7.393

Columbia LOW 0.061 0.060 0.509 0.001 0.000 0.008 0.007 0.143 AVG. 0.198 0.192 0.892 0.009 0.010 0.017 0.012 0.147 HIGH 0.354 0.344 1.043 0.023 0.020 0.031 0.020 0.169

DeSoto LOW 1.624 1.570 9.173 0.206 0.128 0.246 0.192 1.917 AVG. 3.460 3.179 10.813 0.480 0.415 0.514 0.387 2.030 HIGH 3.792 3.715 11.140 0.511 0.485 0.694 0.659 2.280

April 9, 2019 Applied Research Associates, Inc. 248 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Dixie LOW 0.103 0.105 0.592 0.004 0.012 0.005 0.006 0.113 AVG. 0.197 0.181 0.824 0.015 0.014 0.009 0.009 0.125 HIGH 0.294 0.286 0.846 0.020 0.019 0.012 0.026 0.199

Duval LOW 0.121 0.135 0.931 0.004 0.005 0.008 0.010 0.142 AVG. 0.473 0.463 1.488 0.072 0.072 0.077 0.084 0.423 HIGH 1.055 1.106 3.405 0.225 0.218 0.247 0.237 0.861

Escambia LOW 0.915 0.917 5.751 0.048 0.039 0.253 0.203 1.384 AVG. 2.779 2.745 9.033 0.595 0.610 1.007 1.057 3.115 HIGH 5.478 4.972 16.170 1.512 1.467 1.782 1.727 4.697

Flagler LOW 0.387 0.377 2.478 0.009 0.008 0.023 0.021 0.332 AVG. 0.712 0.653 3.029 0.080 0.062 0.144 0.091 0.597 HIGH 1.284 1.247 3.575 0.194 0.186 0.239 0.227 0.995

Franklin LOW 0.066 0.069 0.465 0.001 0.002 0.001 0.001 0.088 AVG. 0.152 0.155 0.651 0.010 0.007 0.004 0.005 0.093 HIGH 0.389 0.378 1.230 0.020 0.018 0.029 0.012 0.093

Gadsden LOW 0.027 0.030 0.303 0.000 0.000 NA 0.003 0.048 AVG. 0.079 0.083 0.384 0.002 0.002 NA 0.003 0.069 HIGH 0.176 0.172 0.518 0.003 0.002 NA 0.003 0.071

Gilchrist LOW 0.166 0.142 0.999 0.010 0.015 NA 0.031 NA AVG. 0.318 0.310 1.279 0.039 0.034 NA 0.031 NA HIGH 0.478 0.464 1.421 0.043 0.039 NA 0.031 NA

Glades LOW 2.355 1.949 9.621 0.582 0.240 NA NA NA AVG. 4.552 4.082 14.675 0.582 0.504 NA NA NA HIGH 4.943 4.854 14.873 0.582 0.551 NA NA NA

Gulf LOW 0.107 0.106 0.995 0.001 0.002 0.002 0.003 0.097 AVG. 0.226 0.225 0.997 0.007 0.006 0.007 0.005 0.178 HIGH 0.351 0.343 0.999 0.009 0.008 0.016 0.013 0.220

Hamilton LOW 0.054 0.052 0.392 0.002 0.004 NA NA NA AVG. 0.102 0.100 0.449 0.005 0.005 NA NA NA HIGH 0.185 0.180 0.531 0.007 0.006 NA NA NA

Hardee LOW 1.255 1.199 7.323 0.126 0.064 NA 0.418 0.973 AVG. 2.704 2.551 7.952 0.301 0.277 NA 0.418 1.174 HIGH 3.072 3.012 8.817 0.355 0.338 NA 0.418 1.375

Hendry LOW 2.242 2.180 14.646 0.160 0.130 0.371 0.121 2.085 AVG. 4.379 3.937 14.693 0.536 0.465 0.680 0.545 2.501 HIGH 4.744 4.644 14.743 0.678 0.646 0.908 0.864 2.750

Hernando LOW 0.583 0.502 3.308 0.036 0.010 0.142 0.080 0.711 AVG. 1.461 1.422 3.945 0.137 0.144 0.258 0.255 0.960 HIGH 1.947 1.900 5.011 0.248 0.234 0.322 0.323 1.206

Highlands LOW 0.800 0.687 4.708 0.027 0.008 0.117 0.040 0.879 AVG. 2.348 2.182 7.137 0.185 0.157 0.279 0.270 1.331 HIGH 3.449 3.386 10.461 0.324 0.303 0.471 0.443 1.873

Hills- LOW borough 0.527 0.517 3.526 0.012 0.012 0.019 0.025 0.658 AVG. 1.826 1.718 5.446 0.172 0.168 0.263 0.266 1.288 HIGH 3.420 3.334 7.530 0.527 0.524 0.703 0.699 2.554

April 9, 2019 Applied Research Associates, Inc. 249 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential

Holmes LOW 0.225 0.221 1.739 0.008 0.019 0.033 NA 0.343 AVG. 0.459 0.440 1.910 0.025 0.021 0.033 NA 0.343 HIGH 0.853 0.831 2.337 0.036 0.032 0.033 NA 0.343

Indian LOW River 2.562 2.490 11.491 0.091 0.086 0.372 0.180 1.874 AVG. 4.713 4.143 14.664 1.003 0.999 1.284 1.360 3.987 HIGH 7.611 7.440 18.994 2.018 1.955 2.446 2.367 5.024

Jackson LOW 0.097 0.097 0.759 0.002 0.004 NA 0.011 0.141 AVG. 0.243 0.243 1.113 0.009 0.008 NA 0.015 0.221 HIGH 0.526 0.512 1.502 0.018 0.013 NA 0.021 0.254

Jefferson LOW 0.022 0.026 0.238 0.000 0.000 0.003 NA NA AVG. 0.057 0.054 0.266 0.001 0.001 0.003 NA NA HIGH 0.092 0.090 0.270 0.002 0.001 0.003 NA NA

Lafayette LOW 0.065 0.066 0.427 0.003 0.006 0.010 NA NA AVG. 0.113 0.109 0.476 0.006 0.006 0.010 NA NA HIGH 0.166 0.162 0.476 0.006 0.006 0.010 NA NA

Lake LOW 0.302 0.261 2.012 0.006 0.012 0.029 0.026 0.616 AVG. 1.389 1.319 4.179 0.103 0.095 0.221 0.204 0.941 HIGH 2.337 2.298 6.577 0.238 0.227 0.296 0.281 1.385

Lee LOW 1.709 1.654 10.660 0.063 0.051 0.145 0.113 1.268 AVG. 4.600 3.763 12.175 0.800 0.662 1.098 0.911 3.126 HIGH 8.710 8.505 23.231 2.447 2.370 2.965 2.868 6.050

Leon LOW 0.029 0.029 0.288 0.000 0.000 0.000 0.000 0.020 AVG. 0.071 0.070 0.306 0.002 0.002 0.002 0.002 0.049 HIGH 0.119 0.117 0.342 0.002 0.002 0.004 0.003 0.059

Levy LOW 0.204 0.198 1.333 0.017 0.022 0.026 0.033 0.327 AVG. 0.559 0.582 2.411 0.083 0.087 0.066 0.063 0.428 HIGH 1.236 1.201 4.007 0.197 0.188 0.083 0.077 0.630

Liberty LOW 0.049 0.048 0.464 0.000 0.002 NA NA NA AVG. 0.122 0.121 0.530 0.002 0.002 NA NA NA HIGH 0.212 0.207 0.569 0.002 0.002 NA NA NA

Madison LOW 0.030 0.029 0.262 0.000 0.001 NA NA NA AVG. 0.075 0.073 0.342 0.003 0.003 NA NA NA HIGH 0.148 0.144 0.449 0.006 0.006 NA NA NA

Manatee LOW 1.518 1.485 7.516 0.033 0.036 0.099 0.071 0.910 AVG. 3.399 2.819 9.157 0.452 0.375 0.820 0.767 2.688 HIGH 6.706 6.584 19.204 1.550 1.505 1.930 1.869 5.246

Marion LOW 0.232 0.203 1.594 0.007 0.002 0.024 0.020 0.322 AVG. 0.778 0.701 2.827 0.068 0.061 0.091 0.155 0.592 HIGH 1.339 1.298 4.112 0.180 0.169 0.230 0.216 0.863

Martin LOW 3.612 3.509 17.458 0.146 0.138 0.337 0.282 2.445 AVG. 6.582 5.925 20.285 1.554 1.488 1.969 2.178 5.152 HIGH 9.683 9.482 24.038 2.730 2.655 3.290 3.194 6.503

April 9, 2019 Applied Research Associates, Inc. 250 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Miami- LOW Dade 3.003 3.620 14.420 0.214 0.166 0.361 0.288 1.727 AVG. 7.422 6.776 31.974 1.395 1.395 1.828 1.784 5.926 HIGH 13.425 13.122 40.607 3.911 3.757 4.676 4.543 10.870

Monroe LOW 5.476 5.180 31.420 1.857 0.535 1.101 0.814 3.236 AVG. 11.284 10.895 35.053 4.983 4.660 4.224 4.432 9.003 HIGH 18.864 18.592 46.120 7.570 7.453 6.700 8.675 12.986

Nassau LOW 0.097 0.107 0.776 0.002 0.006 0.034 0.019 0.193 AVG. 0.566 0.465 1.371 0.108 0.097 0.161 0.166 0.582 HIGH 0.939 0.913 2.840 0.173 0.166 0.209 0.200 0.769

Okaloosa LOW 0.468 0.457 2.892 0.019 0.016 0.062 0.096 0.678 AVG. 1.708 1.773 4.748 0.268 0.308 0.475 0.545 2.032 HIGH 3.964 3.858 12.526 0.821 0.792 0.994 0.956 3.593

Okeecho- LOW bee 2.015 1.960 12.017 0.216 0.124 0.243 0.192 1.966 AVG. 3.949 3.603 12.571 0.459 0.404 0.436 0.595 2.301 HIGH 4.429 4.333 12.698 0.490 0.460 0.695 0.653 2.585

Orange LOW 0.417 0.408 2.797 0.008 0.007 0.025 0.013 0.350 AVG. 1.286 1.303 4.214 0.092 0.082 0.130 0.124 0.793 HIGH 1.911 1.874 5.163 0.201 0.194 0.225 0.219 1.058

Osceola LOW 0.372 0.366 2.831 0.008 0.006 0.017 0.012 0.289 AVG. 1.403 1.405 5.260 0.093 0.086 0.108 0.090 0.773 HIGH 3.462 3.392 9.071 0.441 0.368 0.398 0.376 1.459

Palm LOW Beach 3.787 3.611 17.609 0.161 0.141 0.334 0.254 2.342 AVG. 6.231 5.637 22.496 1.069 0.977 1.495 1.350 4.828 HIGH 11.174 10.824 31.556 2.966 2.838 3.632 3.469 8.789

Pasco LOW 0.539 0.527 3.546 0.016 0.013 0.034 0.030 0.648 AVG. 1.474 1.549 4.865 0.125 0.136 0.219 0.278 1.216 HIGH 2.278 2.224 5.891 0.278 0.263 0.380 0.359 1.544

Pinellas LOW 0.960 0.942 5.377 0.032 0.012 0.061 0.036 0.723 AVG. 2.986 2.753 7.570 0.375 0.393 0.631 0.639 2.124 HIGH 6.492 6.373 14.491 1.486 1.442 1.855 1.795 5.099

Polk LOW 0.448 0.439 3.185 0.010 0.005 0.019 0.012 0.494 AVG. 1.608 1.493 5.117 0.101 0.111 0.132 0.166 0.935 HIGH 3.095 3.045 8.575 0.317 0.303 0.451 0.428 1.418

Putnam LOW 0.213 0.208 1.379 0.011 0.008 0.021 0.019 0.398 AVG. 0.470 0.465 1.898 0.049 0.043 0.080 0.048 0.432 HIGH 0.873 0.848 2.498 0.090 0.084 0.116 0.108 0.473

St. Johns LOW 0.251 0.244 1.672 0.006 0.006 0.014 0.014 0.216 AVG. 0.642 0.776 2.463 0.117 0.120 0.201 0.247 0.758 HIGH 1.743 1.702 5.390 0.355 0.346 0.423 0.410 1.429

St. Lucie LOW 3.145 2.769 12.840 0.349 0.110 0.273 0.229 2.409 AVG. 5.433 4.583 16.228 1.178 0.893 1.479 1.367 4.104 HIGH 8.606 8.403 22.132 2.291 2.216 2.784 2.689 5.742

April 9, 2019 Applied Research Associates, Inc. 251 Appendix A - Forms 4/9/2019 11:00 AM

County Loss Frame Masonry Manu- Frame Masonry Frame Masrony Comm. Costs Owners Owners factured Renters Renters Condo Condo Resi- Homes Unit Unit dential Santa LOW Rosa 0.870 0.935 5.457 0.044 0.051 0.122 0.066 0.787 AVG. 2.327 2.446 8.065 0.494 0.467 1.470 1.233 3.280 HIGH 6.292 6.129 18.988 1.888 1.844 2.207 2.149 5.853

Sarasota LOW 1.487 1.455 7.918 0.046 0.039 0.091 0.078 1.029 AVG. 2.978 2.638 10.018 0.387 0.353 0.648 0.598 2.196 HIGH 5.230 5.107 13.596 0.997 0.953 1.283 1.226 3.449

Seminole LOW 0.345 0.338 3.211 0.004 0.003 0.022 0.016 0.328 AVG. 1.221 1.212 3.830 0.088 0.082 0.124 0.121 0.712 HIGH 1.886 1.843 4.830 0.195 0.185 0.260 0.244 1.219

Sumter LOW 0.397 0.344 2.503 0.014 0.008 0.058 0.026 0.592 AVG. 0.859 0.809 2.973 0.056 0.053 0.109 0.083 0.694 HIGH 1.491 1.460 3.995 0.134 0.172 0.124 0.137 0.976

Suwannee LOW 0.079 0.077 0.573 0.003 0.003 0.014 0.010 0.110 AVG. 0.157 0.154 0.692 0.009 0.008 0.014 0.010 0.166 HIGH 0.327 0.319 1.035 0.022 0.016 0.014 0.010 0.199

Taylor LOW 0.032 0.035 0.262 0.001 0.002 0.003 0.003 0.079 AVG. 0.078 0.074 0.352 0.004 0.003 0.005 0.006 0.079 HIGH 0.151 0.147 0.433 0.008 0.007 0.011 0.010 0.079

Union LOW 0.119 0.116 0.819 0.004 0.001 0.011 0.010 0.196 AVG. 0.222 0.219 0.911 0.014 0.014 0.011 0.010 0.196 HIGH 0.324 0.315 0.923 0.016 0.015 0.011 0.010 0.196

Volusia LOW 0.334 0.300 2.132 0.011 0.004 0.025 0.022 0.272 AVG. 1.455 1.358 3.759 0.151 0.157 0.391 0.495 1.258 HIGH 3.639 3.578 9.518 0.712 0.692 0.893 0.864 2.567

Wakulla LOW 0.030 0.029 0.312 0.000 0.000 0.001 0.003 0.047 AVG. 0.073 0.075 0.331 0.002 0.002 0.007 0.010 0.099 HIGH 0.227 0.221 0.705 0.008 0.008 0.014 0.012 0.117

Walton LOW 0.436 0.427 2.892 0.013 0.012 0.034 0.021 0.613 AVG. 1.303 1.162 3.784 0.122 0.116 0.325 0.257 1.568 HIGH 2.724 2.639 8.117 0.378 0.356 0.482 0.452 2.323

Washing- LOW ton 0.248 0.244 1.735 0.012 0.010 0.019 NA 0.351 AVG. 0.497 0.490 2.094 0.029 0.026 0.019 NA 0.397 HIGH 0.852 0.777 2.305 0.034 0.031 0.019 NA 0.495

Statewide LOW 0.022 0.026 0.238 0.000 0.000 0.000 0.000 0.020 AVG. 1.836 3.201 6.695 0.263 0.482 0.494 1.008 3.426 HIGH 18.864 18.592 46.120 7.570 7.453 6.700 8.675 12.986

April 9, 2019 Applied Research Associates, Inc. 252 Appendix A - Forms 4/9/2019 11:00 AM

Form A-4B: Hurricane Output Ranges (2017 FHCF Exposure Data) A. Provide personal and commercial residential hurricane output ranges in the format shown in the file named “2017FormA4B.xlsx” by using an automated program or script. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-4A, Hurricane Output Ranges (2017 FHCF Exposure Data), in a submission appendix. B. Provide hurricane loss costs rounded to three decimal places, by county. Within each county, hurricane loss costs shall be shown separately per $1,000 of exposure for frame owners, masonry owners, frame renters, masonry renters, frame condo unit owners, masonry condo unit owners, manufactured home, and commercial residential. For each of these categories using ZIP Code centroids, the hurricane output range shall show the highest hurricane loss cost, the lowest hurricane loss cost, and the weighted average hurricane loss cost. The aggregate residential exposure data for this form shall be developed from the information in the file named “hlpm2017c.exe,” except for insured value and deductibles information. Insured values shall be based on the hurricane output range specifications below. Deductible amounts of 0% and as specified in the hurricane output range specifications will be assumed to be uniformly applied to all risks. When calculating the weighted average hurricane loss costs, weight the hurricane loss costs by the total insured value calculated above. Include the statewide range of hurricane loss costs (i.e., low, high, and weighted average). C. If a modeling organization has hurricane loss costs for a ZIP Code for which there is no exposure, give the hurricane loss costs zero weight (i.e., assume the exposure in that ZIP Code is zero). Provide a list in the submission document of those ZIP Codes where this occurs. D. If a modeling organization does not have hurricane loss costs for a ZIP Code for which there is some exposure, do not assume such hurricane loss costs are zero, but use only the exposures for which there are hurricane loss costs in calculating the weighted average hurricane loss costs. Provide a list in the submission document of the ZIP Codes where this occurs. E. NA shall be used in cells to signify no exposure. F. All hurricane loss costs that are not consistent with the requirements of Standard A-6 , Hurricane Loss Outputs and Logical Relationships to Risk, and have been explained in Disclosure A-6.17 shall be shaded. G. Indicate if per diem is used in producing hurricane loss costs for Coverage D (Time Element) in the personal residential hurricane output ranges. If a per diem rate is used, a rate of $150.00 per day per policy shall be used. Loss costs are provided in the file named ARA17FormA4B_revised_2019-03-22.xlsx. Per diem is not used in producing loss costs for Coverage D (ALE). The model does not produce hurricane loss costs for any ZIP Codes for which there is no exposure, and it does produce loss costs for every ZIP Code for which there is exposure in the FHCF exposure data.

April 9, 2019 Applied Research Associates, Inc. 253 Appendix A - Forms 4/9/2019 11:00 AM

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Alachua LOW 0.417 0.424 1.504 0.044 0.041 0.102 0.106 0.200 AVERAGE 0.657 0.645 2.098 0.086 0.085 0.167 0.164 0.402 HIGH 1.081 1.059 2.601 0.122 0.116 0.201 0.194 0.595

Baker LOW 0.267 0.265 0.875 0.045 0.044 NA NA 0.275 AVERAGE 0.434 0.436 1.145 0.061 0.059 NA NA 0.275 HIGH 0.597 0.589 1.279 0.068 0.066 NA NA 0.275

Bay LOW 0.726 0.720 2.833 0.088 0.095 0.194 0.205 0.515 AVERAGE 1.448 1.348 3.902 0.178 0.172 0.398 0.383 1.221 HIGH 2.814 2.758 7.152 0.355 0.343 0.564 0.544 2.935

Bradford LOW 0.396 0.391 1.425 0.054 0.056 NA NA NA AVERAGE 0.579 0.583 1.627 0.079 0.075 NA NA NA HIGH 0.829 0.815 1.825 0.094 0.088 NA NA NA

Brevard LOW 1.897 1.872 6.532 0.235 0.129 0.461 0.349 0.827 AVERAGE 4.315 4.188 10.882 0.870 0.832 1.198 1.524 3.177 HIGH 8.200 8.069 19.672 1.982 1.928 2.646 2.580 5.834

Broward LOW 5.782 5.422 21.845 0.418 0.382 0.998 0.932 2.407 AVERAGE 7.824 7.397 24.629 1.350 1.306 2.059 1.997 5.532 HIGH 10.863 10.493 31.512 2.344 2.211 3.235 3.075 8.009

Calhoun LOW 0.370 0.377 1.281 0.052 0.063 NA NA NA AVERAGE 0.574 0.574 1.678 0.073 0.075 NA NA NA HIGH 0.916 0.903 2.032 0.080 0.078 NA NA NA

Charlotte LOW 2.620 2.582 11.419 0.290 0.214 0.523 0.429 1.630 AVERAGE 4.406 4.029 13.102 0.745 0.679 1.180 0.943 2.705 HIGH 5.765 5.655 14.982 1.178 1.131 1.666 1.611 3.618

Citrus LOW 0.828 0.816 3.245 0.112 0.101 0.225 0.217 0.566 AVERAGE 1.321 1.257 4.009 0.212 0.201 0.361 0.365 1.026 HIGH 1.885 1.848 4.518 0.300 0.292 0.441 0.430 1.475

Clay LOW 0.434 0.430 1.677 0.060 0.056 0.117 0.122 0.345 AVERAGE 0.694 0.689 1.870 0.105 0.102 0.163 0.155 0.436 HIGH 1.122 1.101 2.606 0.146 0.142 0.232 0.225 0.723

Collier LOW 3.041 2.980 11.852 0.315 0.241 0.659 0.525 2.014 AVERAGE 5.687 5.318 16.574 1.288 1.228 1.864 1.735 4.142 HIGH 12.898 12.707 34.156 2.976 2.902 3.787 3.688 8.502

Columbia LOW 0.241 0.241 0.822 0.023 0.026 0.098 0.096 0.162 AVERAGE 0.426 0.421 1.305 0.049 0.048 0.100 0.097 0.162 HIGH 0.645 0.634 1.481 0.061 0.057 0.103 0.100 0.162

DeSoto LOW 2.551 2.496 10.899 0.378 0.262 0.663 0.404 1.991 AVERAGE 4.474 4.275 12.686 0.705 0.606 0.944 0.797 2.508 HIGH 5.163 5.085 13.128 0.757 0.724 1.113 1.160 2.819

April 9, 2019 Applied Research Associates, Inc. 254 Appendix A - Forms 4/9/2019 11:00 AM

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Dixie LOW 0.264 0.269 0.903 0.042 0.038 0.080 0.081 0.171 AVERAGE 0.420 0.405 1.192 0.060 0.056 0.089 0.089 0.207 HIGH 0.559 0.550 1.218 0.071 0.058 0.098 0.097 0.275

Duval LOW 0.369 0.384 1.396 0.053 0.050 0.116 0.112 0.273 AVERAGE 0.830 0.830 2.043 0.140 0.139 0.210 0.213 0.546 HIGH 1.582 1.552 4.265 0.304 0.326 0.392 0.384 1.483

Escambia LOW 1.698 1.811 7.202 0.191 0.193 0.605 0.571 2.018 AVERAGE 3.871 3.858 10.669 0.859 0.887 1.463 1.582 3.626 HIGH 7.017 6.858 18.343 2.108 2.072 2.355 2.568 8.817

Flagler LOW 0.832 0.822 3.375 0.104 0.100 0.212 0.210 0.396 AVERAGE 1.242 1.207 4.063 0.185 0.176 0.356 0.292 0.738 HIGH 2.024 1.985 4.659 0.328 0.321 0.463 0.449 1.768

Franklin LOW 0.231 0.230 0.801 0.036 0.038 0.080 0.081 0.152 AVERAGE 0.400 0.398 1.044 0.050 0.050 0.087 0.093 0.155 HIGH 0.757 0.745 1.811 0.063 0.058 0.107 0.105 0.180

Gadsden LOW 0.180 0.180 0.581 0.032 0.032 NA NA 0.085 AVERAGE 0.269 0.279 0.704 0.039 0.039 NA NA 0.117 HIGH 0.426 0.421 0.897 0.048 0.050 NA NA 0.145

Gilchrist LOW 0.375 0.370 1.412 0.039 0.046 NA NA NA AVERAGE 0.576 0.575 1.748 0.075 0.071 NA NA NA HIGH 0.805 0.789 1.916 0.086 0.082 NA NA NA

Glades LOW 3.635 2.818 11.709 0.459 0.464 NA NA 2.511 AVERAGE 5.935 5.553 17.109 0.805 0.798 NA NA 3.128 HIGH 6.691 6.600 17.366 0.908 0.865 NA NA 3.547

Gulf LOW 0.420 0.434 1.581 0.068 0.068 0.138 0.136 0.279 AVERAGE 0.578 0.581 1.586 0.089 0.090 0.146 0.139 0.294 HIGH 0.765 0.755 1.589 0.100 0.098 0.171 0.169 0.393

Hamilton LOW 0.185 0.184 0.644 0.026 0.031 NA NA NA AVERAGE 0.265 0.265 0.723 0.034 0.033 NA NA NA HIGH 0.399 0.394 0.839 0.044 0.040 NA NA NA

Hardee LOW 2.286 2.063 8.997 0.239 0.226 0.892 NA 1.351 AVERAGE 3.728 3.590 9.749 0.478 0.464 0.892 NA 1.351 HIGH 4.352 4.291 10.657 0.574 0.560 0.892 NA 1.351

Hendry LOW 3.428 3.365 16.960 0.450 0.346 0.804 0.495 2.465 AVERAGE 5.747 5.284 17.070 0.810 0.746 1.221 1.090 2.875 HIGH 6.469 6.366 17.192 0.978 0.937 1.515 1.467 4.004

Hernando LOW 1.130 1.040 4.277 0.143 0.133 0.410 0.260 0.870 AVERAGE 2.142 2.121 4.954 0.290 0.296 0.559 0.550 1.203 HIGH 2.759 2.710 6.130 0.416 0.405 0.634 0.633 1.528

Highlands LOW 1.619 1.492 6.281 0.165 0.120 0.460 0.305 0.868 AVERAGE 3.440 3.275 8.918 0.356 0.340 0.695 0.664 1.605 HIGH 4.933 4.868 12.644 0.559 0.531 0.989 0.957 2.402

Hillsborough LOW 1.154 1.144 4.637 0.128 0.108 0.292 0.271 0.723 AVERAGE 2.555 2.566 6.813 0.371 0.352 0.602 0.622 1.632 HIGH 4.548 4.461 8.995 0.798 0.777 1.150 1.122 4.539

April 9, 2019 Applied Research Associates, Inc. 255 Appendix A - Forms 4/9/2019 11:00 AM

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Holmes LOW 0.637 0.670 2.569 0.080 0.080 NA NA 0.503 AVERAGE 0.974 0.940 2.791 0.135 0.131 NA NA 0.503 HIGH 1.556 1.532 3.321 0.186 0.179 NA NA 0.503

Indian River LOW 3.751 3.575 13.384 0.463 0.277 0.805 0.625 2.752 AVERAGE 6.038 5.318 16.680 1.402 1.274 1.851 1.922 4.403 HIGH 9.319 9.146 19.071 2.434 2.370 3.173 3.088 6.693

Jackson LOW 0.328 0.328 1.246 0.035 0.031 NA NA 0.198 AVERAGE 0.580 0.579 1.722 0.060 0.057 NA NA 0.352 HIGH 1.020 1.005 2.240 0.092 0.082 NA NA 0.593

Jefferson LOW 0.149 0.147 0.455 0.022 0.022 NA NA NA AVERAGE 0.195 0.194 0.494 0.026 0.026 NA NA NA HIGH 0.250 0.248 0.500 0.032 0.032 NA NA NA

Lafayette LOW 0.221 0.219 0.692 0.040 0.030 NA NA NA AVERAGE 0.285 0.280 0.756 0.040 0.036 NA NA NA HIGH 0.362 0.357 0.756 0.040 0.038 NA NA NA

Lake LOW 0.786 0.736 2.922 0.075 0.069 0.238 0.209 0.677 AVERAGE 2.117 2.076 5.412 0.205 0.197 0.515 0.474 1.201 HIGH 3.401 3.361 8.129 0.406 0.388 0.639 0.620 2.746

Lee LOW 2.745 2.689 12.575 0.308 0.216 0.560 0.493 1.678 AVERAGE 5.685 4.928 13.939 0.944 0.972 1.582 1.413 3.468 HIGH 10.345 10.137 25.425 2.941 2.862 3.751 3.648 7.892

Leon LOW 0.169 0.168 0.548 0.026 0.026 0.058 0.059 0.053 AVERAGE 0.237 0.238 0.575 0.032 0.032 0.066 0.067 0.090 HIGH 0.317 0.313 0.623 0.042 0.041 0.075 0.075 0.108

Levy LOW 0.480 0.473 1.805 0.058 0.068 0.139 0.148 0.419 AVERAGE 0.929 0.971 3.082 0.146 0.139 0.198 0.189 0.763 HIGH 1.812 1.776 4.905 0.317 0.247 0.213 0.207 1.364

Liberty LOW 0.265 0.267 0.849 0.056 0.065 NA NA NA AVERAGE 0.383 0.388 0.952 0.064 0.067 NA NA NA HIGH 0.526 0.520 1.007 0.069 0.068 NA NA NA

Madison LOW 0.151 0.150 0.481 0.017 0.020 NA NA NA AVERAGE 0.214 0.214 0.583 0.025 0.025 NA NA NA HIGH 0.324 0.319 0.722 0.027 0.027 NA NA NA

Manatee LOW 2.437 2.402 9.573 0.176 0.134 0.415 0.405 1.340 AVERAGE 4.349 3.746 10.741 0.662 0.600 1.215 1.190 2.472 HIGH 8.278 8.155 21.361 2.207 2.167 2.815 2.763 9.074

Marion LOW 0.618 0.615 2.351 0.076 0.070 0.163 0.159 0.480 AVERAGE 1.313 1.220 3.742 0.163 0.149 0.277 0.330 0.822 HIGH 1.989 1.946 5.093 0.297 0.288 0.424 0.408 1.881

Martin LOW 4.981 4.843 19.640 0.436 0.391 0.899 0.872 3.362 AVERAGE 8.138 7.342 22.394 2.303 2.025 2.782 2.878 6.030 HIGH 11.550 11.347 26.507 3.246 3.167 4.145 4.041 8.658

April 9, 2019 Applied Research Associates, Inc. 256 Appendix A - Forms 4/9/2019 11:00 AM

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Miami‐Dade LOW 6.262 6.102 25.944 0.507 0.432 1.112 1.025 2.733 AVERAGE 9.018 8.473 36.382 1.784 1.808 2.618 2.511 6.937 HIGH 15.620 15.207 43.429 4.583 4.413 5.821 5.621 13.135

Monroe LOW 6.714 6.416 33.899 1.307 0.906 1.677 1.547 4.473 AVERAGE 12.755 12.401 37.373 5.522 5.228 5.144 5.299 10.580 HIGH 20.994 20.721 48.884 8.159 8.429 7.712 9.813 16.732

Nassau LOW 0.326 0.336 1.192 0.054 0.053 0.123 0.139 0.352 AVERAGE 0.902 0.798 1.877 0.148 0.133 0.285 0.293 0.726 HIGH 1.418 1.391 3.581 0.260 0.255 0.334 0.357 1.408

Okaloosa LOW 0.971 1.025 3.976 0.141 0.135 0.322 0.363 1.184 AVERAGE 2.629 2.646 5.901 0.499 0.506 0.847 0.937 2.447 HIGH 5.352 5.242 14.559 1.218 1.191 1.593 1.559 6.623

Okeechobee LOW 3.176 3.120 14.238 0.302 0.269 0.633 0.603 2.298 AVERAGE 5.404 4.946 14.860 0.703 0.636 0.952 1.194 2.911 HIGH 6.059 5.961 15.002 0.787 0.747 1.310 1.263 3.737

Orange LOW 0.998 0.988 4.083 0.066 0.063 0.195 0.190 0.613 AVERAGE 1.991 2.120 5.567 0.221 0.213 0.413 0.411 1.089 HIGH 2.926 2.888 6.632 0.416 0.400 0.573 0.565 2.343

Osceola LOW 1.024 1.017 4.075 0.119 0.093 0.242 0.232 0.535 AVERAGE 2.103 2.293 6.837 0.209 0.221 0.400 0.376 1.139 HIGH 4.837 4.765 10.996 0.702 0.567 0.807 0.782 4.394

Palm Beach LOW 5.279 5.099 19.842 0.431 0.372 0.898 0.852 3.380 AVERAGE 7.858 7.265 24.963 1.457 1.371 2.263 2.085 5.423 HIGH 13.240 12.888 34.349 3.538 3.396 4.588 4.421 10.900

Pasco LOW 1.148 1.136 4.639 0.125 0.116 0.248 0.270 0.801 AVERAGE 2.133 2.324 6.087 0.274 0.314 0.499 0.607 1.538 HIGH 3.248 3.192 7.247 0.481 0.466 0.747 0.722 2.737

Pinellas LOW 1.683 1.663 7.163 0.164 0.154 0.364 0.346 0.978 AVERAGE 3.789 3.646 8.940 0.602 0.623 1.052 1.082 2.432 HIGH 8.030 7.909 16.335 2.132 2.092 2.525 2.460 8.828

Polk LOW 1.088 1.077 4.437 0.100 0.092 0.255 0.225 0.685 AVERAGE 2.361 2.315 6.624 0.242 0.254 0.437 0.470 1.247 HIGH 4.454 4.401 10.534 0.536 0.510 0.924 0.898 3.439

Putnam LOW 0.543 0.537 2.005 0.065 0.063 0.178 0.135 0.487 AVERAGE 0.915 0.915 2.675 0.134 0.131 0.246 0.211 0.549 HIGH 1.484 1.459 3.369 0.172 0.167 0.282 0.265 0.989

St. Johns LOW 0.576 0.569 2.316 0.077 0.074 0.136 0.134 0.466 AVERAGE 1.026 1.266 3.249 0.196 0.204 0.357 0.431 0.920 HIGH 2.528 2.485 6.621 0.510 0.500 0.687 0.674 2.653

St. Lucie LOW 4.140 4.015 14.843 0.587 0.331 0.782 0.726 3.003 AVERAGE 6.959 5.963 18.285 1.384 1.218 2.153 1.948 4.695 HIGH 10.400 10.194 24.624 2.751 2.684 3.580 3.479 7.606

April 9, 2019 Applied Research Associates, Inc. 257 Appendix A - Forms 4/9/2019 11:00 AM

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Santa Rosa LOW 1.619 1.729 6.880 0.184 0.232 0.442 0.496 1.498 AVERAGE 3.361 3.370 9.742 0.739 0.737 1.665 1.866 3.017 HIGH 7.951 7.784 21.356 2.594 2.552 3.164 3.111 5.984

Sarasota LOW 2.432 2.399 9.422 0.220 0.186 0.444 0.430 1.280 AVERAGE 3.899 3.614 11.650 0.616 0.590 1.117 1.042 2.338 HIGH 6.627 6.503 15.483 1.313 1.260 1.864 1.803 4.734

Seminole LOW 0.921 0.914 4.398 0.103 0.106 0.218 0.229 0.506 AVERAGE 1.966 2.021 5.070 0.235 0.228 0.413 0.414 0.976 HIGH 2.863 2.817 6.224 0.378 0.369 0.587 0.560 1.740

Sumter LOW 0.941 0.880 3.482 0.080 0.052 0.205 0.197 0.773 AVERAGE 1.518 1.449 3.977 0.137 0.123 0.317 0.256 0.935 HIGH 2.421 2.247 5.135 0.315 0.266 0.387 0.373 1.055

Suwannee LOW 0.241 0.239 0.882 0.019 0.026 NA NA 0.099 AVERAGE 0.345 0.341 1.032 0.032 0.032 NA NA 0.170 HIGH 0.589 0.580 1.453 0.052 0.049 NA NA 0.273

Taylor LOW 0.155 0.159 0.481 0.021 0.022 0.052 0.065 0.125 AVERAGE 0.224 0.217 0.592 0.028 0.028 0.067 0.069 0.126 HIGH 0.337 0.333 0.695 0.031 0.040 0.079 0.078 0.137

Union LOW 0.359 0.368 1.256 0.048 0.043 NA NA NA AVERAGE 0.483 0.486 1.352 0.065 0.065 NA NA NA HIGH 0.629 0.620 1.365 0.070 0.072 NA NA NA

Volusia LOW 0.803 0.783 3.029 0.100 0.104 0.236 0.238 0.484 AVERAGE 2.222 2.094 4.881 0.308 0.300 0.712 0.846 1.362 HIGH 4.885 4.822 11.294 1.023 1.004 1.387 1.362 4.635

Wakulla LOW 0.176 0.176 0.581 0.027 0.030 0.065 0.066 0.088 AVERAGE 0.240 0.244 0.606 0.034 0.036 0.072 0.079 0.116 HIGH 0.483 0.476 1.107 0.043 0.042 0.083 0.081 0.181

Walton LOW 1.013 1.070 3.976 0.130 0.129 0.275 0.275 0.893 AVERAGE 2.109 1.891 4.968 0.255 0.246 0.643 0.585 1.564 HIGH 3.912 3.824 9.842 0.567 0.536 0.888 0.821 2.786

Washington LOW 0.699 0.693 2.591 0.077 0.076 0.256 NA 0.529 AVERAGE 1.006 1.001 2.990 0.126 0.118 0.256 NA 0.639 HIGH 1.576 1.430 3.296 0.207 0.200 0.256 NA 0.951

Statewide LOW 0.149 0.147 0.455 0.017 0.020 0.052 0.059 0.053 AVERAGE 2.480 4.237 7.559 0.438 0.741 0.817 1.565 3.483 HIGH 20.994 20.721 48.884 8.159 8.429 7.712 9.813 16.732

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Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Alachua LOW 0.146 0.148 1.014 0.002 0.003 0.006 0.005 0.104 AVERAGE 0.334 0.319 1.524 0.022 0.021 0.038 0.036 0.290 HIGH 0.668 0.647 1.984 0.077 0.074 0.085 0.079 0.517

Baker LOW 0.072 0.070 0.539 0.002 0.002 NA NA 0.203 AVERAGE 0.186 0.186 0.746 0.011 0.011 NA NA 0.203 HIGH 0.298 0.290 0.847 0.018 0.017 NA NA 0.203

Bay LOW 0.270 0.265 1.995 0.004 0.005 0.021 0.013 0.308 AVERAGE 0.806 0.731 2.885 0.063 0.064 0.128 0.122 0.932 HIGH 1.864 1.810 5.731 0.248 0.240 0.267 0.292 2.662

Bradford LOW 0.142 0.138 0.949 0.006 0.006 NA NA NA AVERAGE 0.275 0.277 1.113 0.023 0.021 NA NA NA HIGH 0.444 0.432 1.264 0.031 0.026 NA NA NA

Brevard LOW 1.090 1.065 5.164 0.098 0.044 0.115 0.056 0.517 AVERAGE 3.124 3.003 9.151 0.631 0.606 0.739 1.012 2.621 HIGH 6.573 6.442 17.388 1.664 1.621 1.978 1.916 5.199

Broward LOW 4.132 3.845 19.437 0.153 0.094 0.324 0.249 1.590 AVERAGE 6.058 5.638 22.143 0.915 0.873 1.268 1.206 4.620 HIGH 8.897 8.531 28.804 1.825 1.704 2.344 2.189 7.105

Calhoun LOW 0.093 0.100 0.764 0.001 0.001 NA NA NA AVERAGE 0.231 0.230 1.073 0.006 0.004 NA NA NA HIGH 0.469 0.457 1.355 0.015 0.013 NA NA NA

Charlotte LOW 1.637 1.600 9.749 0.087 0.048 0.121 0.109 1.119 AVERAGE 3.219 2.873 11.305 0.479 0.426 0.676 0.478 2.168 HIGH 4.455 4.346 13.036 0.848 0.815 1.082 1.033 3.017

Citrus LOW 0.401 0.348 2.427 0.018 0.007 0.046 0.039 0.353 AVERAGE 0.802 0.743 3.156 0.094 0.085 0.148 0.153 0.803 HIGH 1.254 1.213 3.650 0.207 0.201 0.253 0.243 1.316

Clay LOW 0.154 0.150 1.143 0.006 0.005 0.008 0.012 0.236 AVERAGE 0.353 0.348 1.297 0.043 0.041 0.046 0.039 0.320 HIGH 0.669 0.650 1.922 0.093 0.091 0.101 0.095 0.634

Collier LOW 1.911 1.850 10.053 0.065 0.049 0.156 0.113 1.405 AVERAGE 4.315 3.966 14.628 0.922 0.876 1.232 1.109 3.432 HIGH 10.884 10.694 31.448 2.549 2.483 3.004 2.911 7.393

Columbia LOW 0.061 0.060 0.509 0.001 0.001 0.008 0.007 0.102 AVERAGE 0.201 0.195 0.901 0.010 0.011 0.015 0.011 0.102 HIGH 0.354 0.344 1.043 0.025 0.024 0.022 0.020 0.102

DeSoto LOW 1.624 1.570 9.173 0.206 0.117 0.246 0.099 1.400 AVERAGE 3.215 3.039 10.751 0.482 0.398 0.487 0.369 1.989 HIGH 3.792 3.715 11.140 0.518 0.496 0.618 0.659 2.280

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Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Dixie LOW 0.088 0.095 0.592 0.004 0.004 0.005 0.006 0.113 AVERAGE 0.197 0.185 0.825 0.014 0.013 0.009 0.009 0.140 HIGH 0.294 0.286 0.846 0.021 0.014 0.012 0.011 0.199

Duval LOW 0.121 0.135 0.931 0.005 0.005 0.008 0.010 0.170 AVERAGE 0.470 0.471 1.480 0.073 0.078 0.077 0.086 0.410 HIGH 1.055 1.026 3.405 0.248 0.268 0.262 0.256 1.347

Escambia LOW 0.915 1.012 5.751 0.065 0.068 0.234 0.203 1.400 AVERAGE 2.755 2.744 8.976 0.593 0.630 0.981 1.083 3.013 HIGH 5.478 5.321 16.170 1.841 1.812 1.864 2.065 8.192

Flagler LOW 0.365 0.355 2.478 0.010 0.009 0.023 0.021 0.232 AVERAGE 0.687 0.652 3.056 0.076 0.069 0.142 0.089 0.537 HIGH 1.284 1.247 3.575 0.225 0.220 0.239 0.227 1.589

Franklin LOW 0.048 0.047 0.465 0.001 0.002 0.001 0.001 0.093 AVERAGE 0.152 0.153 0.645 0.006 0.009 0.004 0.004 0.098 HIGH 0.389 0.378 1.230 0.022 0.022 0.014 0.012 0.139

Gadsden LOW 0.027 0.026 0.303 0.000 0.000 NA NA 0.044 AVERAGE 0.079 0.084 0.383 0.002 0.002 NA NA 0.070 HIGH 0.176 0.172 0.518 0.003 0.002 NA NA 0.110

Gilchrist LOW 0.166 0.162 0.999 0.010 0.015 NA NA NA AVERAGE 0.314 0.311 1.280 0.037 0.034 NA NA NA HIGH 0.478 0.464 1.421 0.050 0.048 NA NA NA

Glades LOW 2.355 1.740 9.621 0.255 0.276 NA NA 1.731 AVERAGE 4.299 3.958 14.635 0.525 0.511 NA NA 2.383 HIGH 4.943 4.854 14.873 0.586 0.560 NA NA 2.843

Gulf LOW 0.107 0.119 0.995 0.001 0.002 0.002 0.003 0.174 AVERAGE 0.224 0.225 0.997 0.007 0.007 0.008 0.005 0.191 HIGH 0.351 0.343 0.999 0.009 0.008 0.016 0.014 0.323

Hamilton LOW 0.053 0.053 0.392 0.002 0.002 NA NA NA AVERAGE 0.103 0.101 0.448 0.005 0.004 NA NA NA HIGH 0.185 0.180 0.531 0.007 0.006 NA NA NA

Hardee LOW 1.385 1.198 7.323 0.125 0.110 0.441 NA 0.883 AVERAGE 2.549 2.427 7.949 0.306 0.290 0.441 NA 0.883 HIGH 3.072 3.012 8.817 0.406 0.396 0.441 NA 0.883

Hendry LOW 2.242 2.180 14.646 0.255 0.177 0.267 0.121 1.747 AVERAGE 4.187 3.766 14.692 0.536 0.480 0.606 0.528 2.173 HIGH 4.744 4.644 14.743 0.692 0.646 0.908 0.864 3.420

Hernando LOW 0.583 0.502 3.308 0.019 0.026 0.142 0.033 0.584 AVERAGE 1.424 1.411 3.950 0.137 0.153 0.259 0.252 0.936 HIGH 1.947 1.900 5.011 0.276 0.268 0.322 0.323 1.223

Highlands LOW 0.795 0.686 4.708 0.027 0.019 0.141 0.040 0.517 AVERAGE 2.241 2.098 7.081 0.183 0.167 0.282 0.256 1.157 HIGH 3.449 3.386 10.461 0.323 0.303 0.471 0.443 1.873

Hillsborough LOW 0.527 0.517 3.526 0.014 0.005 0.019 0.023 0.438 AVERAGE 1.681 1.681 5.470 0.180 0.168 0.249 0.259 1.265 HIGH 3.420 3.334 7.523 0.609 0.594 0.754 0.730 4.163

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Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Holmes LOW 0.225 0.253 1.739 0.008 0.007 NA NA 0.343 AVERAGE 0.460 0.437 1.913 0.025 0.023 NA NA 0.343 HIGH 0.853 0.831 2.337 0.036 0.032 NA NA 0.343

Indian River LOW 2.559 2.420 11.491 0.238 0.086 0.326 0.180 2.060 AVERAGE 4.608 3.937 14.590 1.070 0.970 1.240 1.296 3.692 HIGH 7.611 7.440 16.843 2.074 2.018 2.446 2.367 5.991

Jackson LOW 0.095 0.097 0.759 0.002 0.002 NA NA 0.117 AVERAGE 0.244 0.242 1.110 0.009 0.008 NA NA 0.235 HIGH 0.526 0.512 1.502 0.017 0.016 NA NA 0.504

Jefferson LOW 0.025 0.025 0.238 0.000 0.000 NA NA NA AVERAGE 0.057 0.055 0.265 0.001 0.001 NA NA NA HIGH 0.092 0.090 0.270 0.001 0.001 NA NA NA

Lafayette LOW 0.068 0.066 0.427 0.006 0.002 NA NA NA AVERAGE 0.113 0.109 0.476 0.006 0.005 NA NA NA HIGH 0.166 0.162 0.476 0.006 0.006 NA NA NA

Lake LOW 0.302 0.261 2.012 0.012 0.005 0.029 0.026 0.412 AVERAGE 1.321 1.275 4.180 0.098 0.093 0.215 0.191 0.896 HIGH 2.337 2.298 6.577 0.238 0.227 0.296 0.281 2.487

Lee LOW 1.709 1.654 10.660 0.082 0.059 0.143 0.125 1.135 AVERAGE 4.340 3.642 12.096 0.656 0.685 1.010 0.857 2.829 HIGH 8.710 8.505 23.231 2.503 2.434 2.965 2.868 7.130

Leon LOW 0.026 0.029 0.288 0.000 0.000 0.000 0.000 0.020 AVERAGE 0.072 0.071 0.306 0.002 0.002 0.002 0.002 0.050 HIGH 0.119 0.117 0.342 0.002 0.002 0.004 0.003 0.080

Levy LOW 0.231 0.225 1.333 0.017 0.022 0.025 0.033 0.317 AVERAGE 0.563 0.591 2.415 0.087 0.081 0.071 0.065 0.614 HIGH 1.236 1.201 4.007 0.251 0.176 0.083 0.077 1.237

Liberty LOW 0.049 0.053 0.464 0.000 0.001 NA NA NA AVERAGE 0.120 0.122 0.532 0.001 0.001 NA NA NA HIGH 0.212 0.207 0.569 0.002 0.002 NA NA NA

Madison LOW 0.030 0.029 0.262 0.000 0.001 NA NA NA AVERAGE 0.074 0.074 0.342 0.003 0.003 NA NA NA HIGH 0.148 0.144 0.449 0.007 0.007 NA NA NA

Manatee LOW 1.518 1.484 8.043 0.033 0.032 0.091 0.071 0.899 AVERAGE 3.198 2.662 9.139 0.428 0.381 0.733 0.708 1.965 HIGH 6.706 6.584 19.204 1.890 1.858 2.217 2.170 8.449

Marion LOW 0.206 0.203 1.594 0.006 0.002 0.023 0.020 0.322 AVERAGE 0.781 0.706 2.847 0.073 0.065 0.087 0.153 0.618 HIGH 1.339 1.298 4.112 0.222 0.216 0.230 0.216 1.696

Martin LOW 3.581 3.445 17.458 0.146 0.134 0.301 0.277 2.476 AVERAGE 6.477 5.719 20.082 1.851 1.604 2.001 2.106 5.142 HIGH 9.683 9.482 24.038 2.806 2.738 3.290 3.194 7.809

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Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Miami‐Dade LOW 4.640 4.480 23.457 0.199 0.150 0.416 0.332 1.843 AVERAGE 7.192 6.657 33.698 1.314 1.334 1.771 1.664 5.896 HIGH 13.425 13.015 40.607 3.911 3.757 4.738 4.543 11.959

Monroe LOW 5.438 5.142 31.420 0.933 0.499 1.101 0.814 3.483 AVERAGE 10.999 10.572 34.829 4.944 4.630 4.291 4.307 9.409 HIGH 18.864 18.592 46.120 7.376 7.758 6.700 8.675 15.493

Nassau LOW 0.097 0.107 0.776 0.006 0.006 0.032 0.032 0.222 AVERAGE 0.544 0.463 1.368 0.091 0.080 0.159 0.166 0.559 HIGH 0.939 0.913 2.840 0.210 0.206 0.209 0.238 1.280

Okaloosa LOW 0.410 0.457 2.892 0.019 0.016 0.059 0.057 0.860 AVERAGE 1.699 1.718 4.588 0.288 0.304 0.456 0.529 1.968 HIGH 3.964 3.858 12.526 1.016 0.997 1.181 1.152 6.117

Okeechobee LOW 2.015 1.960 12.017 0.146 0.124 0.209 0.214 1.570 AVERAGE 3.874 3.477 12.572 0.444 0.389 0.453 0.607 2.240 HIGH 4.429 4.333 12.698 0.493 0.468 0.695 0.653 3.191

Orange LOW 0.417 0.371 2.939 0.009 0.004 0.021 0.015 0.350 AVERAGE 1.170 1.259 4.228 0.084 0.080 0.125 0.122 0.796 HIGH 1.911 1.874 5.163 0.204 0.216 0.225 0.222 2.101

Osceola LOW 0.372 0.366 2.831 0.008 0.006 0.010 0.012 0.289 AVERAGE 1.237 1.375 5.298 0.073 0.084 0.105 0.092 0.821 HIGH 3.462 3.392 9.071 0.514 0.368 0.398 0.376 4.004

Palm Beach LOW 3.778 3.602 17.609 0.174 0.128 0.278 0.240 2.448 AVERAGE 6.151 5.558 22.485 1.041 0.959 1.495 1.323 4.521 HIGH 11.174 10.824 31.556 2.966 2.838 3.632 3.469 9.871

Pasco LOW 0.538 0.527 3.546 0.007 0.013 0.034 0.030 0.508 AVERAGE 1.373 1.531 4.853 0.122 0.150 0.191 0.274 1.216 HIGH 2.278 2.224 5.891 0.309 0.300 0.380 0.359 2.486

Pinellas LOW 0.960 0.941 5.900 0.031 0.025 0.071 0.048 0.622 AVERAGE 2.755 2.622 7.525 0.382 0.405 0.613 0.636 1.991 HIGH 6.492 6.373 14.491 1.822 1.791 1.855 1.804 8.217

Polk LOW 0.448 0.439 3.185 0.011 0.009 0.024 0.017 0.405 AVERAGE 1.443 1.400 5.118 0.100 0.111 0.137 0.156 0.920 HIGH 3.095 3.045 8.575 0.358 0.350 0.458 0.443 3.115

Putnam LOW 0.213 0.208 1.379 0.008 0.013 0.023 0.008 0.334 AVERAGE 0.472 0.467 1.898 0.049 0.045 0.075 0.054 0.395 HIGH 0.873 0.848 2.498 0.104 0.101 0.116 0.108 0.865

St. Johns LOW 0.241 0.235 1.672 0.015 0.006 0.014 0.013 0.333 AVERAGE 0.592 0.765 2.438 0.121 0.127 0.193 0.246 0.713 HIGH 1.743 1.702 5.390 0.425 0.418 0.489 0.479 2.433

St. Lucie LOW 2.844 2.740 12.840 0.303 0.110 0.246 0.201 2.167 AVERAGE 5.408 4.476 16.111 1.006 0.883 1.471 1.288 3.909 HIGH 8.606 8.403 22.132 2.291 2.286 2.784 2.689 6.825

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Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial County Loss Costs Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Santa Rosa LOW 0.870 0.935 5.457 0.044 0.050 0.070 0.113 1.107 AVERAGE 2.297 2.307 8.099 0.485 0.486 1.160 1.328 2.465 HIGH 6.292 6.129 18.988 2.297 2.266 2.612 2.566 5.128

Sarasota LOW 1.487 1.455 7.903 0.055 0.027 0.083 0.073 0.841 AVERAGE 2.796 2.531 9.990 0.369 0.349 0.632 0.568 1.856 HIGH 5.230 5.107 13.596 1.023 0.984 1.283 1.226 4.178

Seminole LOW 0.345 0.338 3.211 0.008 0.006 0.018 0.016 0.278 AVERAGE 1.159 1.193 3.809 0.087 0.082 0.120 0.119 0.711 HIGH 1.886 1.843 4.830 0.217 0.211 0.260 0.244 1.537

Sumter LOW 0.397 0.344 2.503 0.016 0.010 0.055 0.048 0.545 AVERAGE 0.900 0.839 2.974 0.059 0.049 0.104 0.080 0.681 HIGH 1.593 1.460 3.995 0.182 0.152 0.149 0.137 0.806

Suwannee LOW 0.086 0.084 0.573 0.003 0.002 NA NA 0.053 AVERAGE 0.158 0.155 0.693 0.009 0.009 NA NA 0.118 HIGH 0.327 0.319 1.035 0.022 0.021 NA NA 0.207

Taylor LOW 0.031 0.035 0.262 0.001 0.001 0.003 0.003 0.079 AVERAGE 0.079 0.074 0.350 0.003 0.003 0.005 0.005 0.080 HIGH 0.151 0.147 0.433 0.005 0.007 0.010 0.010 0.091

Union LOW 0.119 0.128 0.819 0.006 0.003 NA NA NA AVERAGE 0.220 0.221 0.911 0.015 0.013 NA NA NA HIGH 0.324 0.315 0.923 0.017 0.016 NA NA NA

Volusia LOW 0.334 0.300 2.132 0.011 0.009 0.023 0.020 0.272 AVERAGE 1.408 1.303 3.716 0.172 0.164 0.384 0.494 1.071 HIGH 3.639 3.578 9.518 0.843 0.830 0.994 0.974 4.261

Wakulla LOW 0.030 0.029 0.312 0.000 0.001 0.001 0.005 0.047 AVERAGE 0.072 0.074 0.330 0.002 0.003 0.006 0.011 0.068 HIGH 0.227 0.221 0.705 0.010 0.009 0.013 0.012 0.117

Walton LOW 0.436 0.485 2.892 0.007 0.012 0.014 0.013 0.623 AVERAGE 1.273 1.102 3.768 0.103 0.098 0.303 0.241 1.187 HIGH 2.724 2.639 8.117 0.378 0.356 0.554 0.452 2.323

Washington LOW 0.248 0.244 1.735 0.012 0.010 0.019 NA 0.351 AVERAGE 0.498 0.492 2.095 0.031 0.026 0.019 NA 0.475 HIGH 0.852 0.777 2.305 0.034 0.030 0.019 NA 0.826

Statewide LOW 0.025 0.025 0.238 0.000 0.000 0.000 0.000 0.020 AVERAGE 1.708 3.083 6.254 0.267 0.491 0.457 0.968 2.864 HIGH 18.864 18.592 46.120 7.376 7.758 6.700 8.675 15.493

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Form A-5: Percentage Change in Hurricane Output Ranges (2012 FHCF Exposure Data) I. Provide summaries of the percentage change in the average hurricane loss costs output range data compiled in Form A-4A, Hurricane Output Ranges (2012 FHCF Exposure Data), relative to the equivalent data compiled from the previously accepted hurricane model in the format shown in the file named “2017FormA5.xlsx.” For the change in hurricane output range exhibit, provide the summary by:  Statewide (overall percentage change),  By region, as defined in Figure 67 – North, Central and South,  By county, as defined in Figure 68 – Coastal and Inland. B. Provide this form in Excel format. The file name should include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include all tables in Form A-5, Percentage Change in Hurricane Output Ranges (2012 FHCF Exposure Data), in a submission appendix. C. Provide color-coded maps by county reflecting the percentage changes in the average hurricane loss costs based on the 2012 FHCF Exposure Data with specified deductibles for frame owners, masonry owners, frame renters, masonry renters, frame condo unit owners, masonry condo unit owners, manufactured homes, and commercial residential from the hurricane output ranges from the previously accepted hurricane model. Counties with a negative percentage change (reduction in hurricane loss costs) shall be indicated with shades of blue; counties with a positive percentage change (increase in hurricane loss costs) shall be indicated with shades of red; and counties with no percentage change shall be white. The larger the percentage change in the county, the more intense the color-shade.

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Figure 67. State of Florida by North/Central/South Regions

Figure 68. State of Florida by Coastal/Inland Counties

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Form A‐5 Percentage Change in Output Ranges

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 Model Release Date: 11/1/2018 Percentage Change in $0 Deductible Output Ranges

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial Region Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Coastal ‐10.4 ‐12.4 ‐8.3 ‐7.6 ‐6.5 ‐9.8 ‐8.6 ‐11.0 Inland ‐14.5 ‐15.2 ‐10.3 ‐5.5 ‐4.5 ‐9.7 ‐9.4 ‐11.8 North ‐5.0 ‐9.0 ‐10.6 ‐9.6 ‐10.5 ‐8.9 ‐8.5 ‐10.3 Central ‐14.4 ‐15.1 ‐10.5 ‐8.8 ‐8.4 ‐11.1 ‐11.4 ‐13.9 South ‐10.8 ‐11.5 ‐6.2 ‐4.3 ‐5.3 ‐8.8 ‐7.9 ‐10.3 Statewide ‐11.1 ‐12.7 ‐8.9 ‐7.3 ‐6.3 ‐9.8 ‐8.6 ‐11.0

Percentage Change in Specified Deductible Output Ranges

Frame Masonry Manufactured Frame Masonry Frame Masrony Commercial Region Owners Owners Homes Renters Renters Condo Unit Condo Unit Residential Coastal ‐12.1 ‐14.2 ‐9.1 ‐9.4 ‐7.7 ‐12.3 ‐10.3 ‐12.3 Inland ‐16.4 ‐17.4 ‐11.0 ‐4.6 ‐3.6 ‐8.3 ‐8.7 ‐13.2 North ‐5.8 ‐9.9 ‐11.3 ‐13.1 ‐13.9 ‐13.2 ‐14.9 ‐11.3 Central ‐16.5 ‐17.6 ‐11.4 ‐11.4 ‐10.8 ‐13.5 ‐14.1 ‐15.5 South ‐12.1 ‐13.1 ‐6.9 ‐4.8 ‐6.3 ‐10.8 ‐9.3 ‐11.7 Statewide ‐12.7 ‐14.5 ‐9.7 ‐9.0 ‐7.6 ‐12.1 ‐10.2 ‐12.3

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Figure 69. Frame Owners

Figure 70. Masonry Owners

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Figure 71. Manufactured Homes

Figure 72. Frame Renters

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Figure 73. Masonry Renters

Figure 74. Frame Condo Unit Owners

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Figure 75. Masonry Condo Unit Owners

Figure 76. Commercial Residential

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Form A-7: Percentage Change in Logical Relationship to Hurricane Risk A. Provide summaries of the percentage change in logical relationship to hurricane risk exhibits from the previously accepted hurricane model in the format shown in the file named “2017FormA7.xlsx.” B. Create exposure sets for each exhibit by modeling all of the coverages from the appropriate Notional Set listed below at each of the locations in “Location Grid B” as described in the file “NotionalInput17.xlsx.” Refer to the Notional Hurricane Policy Specifications provided in Form A-6, Logical Relationship to Hurricane Risk (Trade Secret Item), for additional modeling information. C. Explain any assumptions, deviations, and differences from the prescribed exposure information. In particular, explain how the treatment of unknown is handled in each sensitivity. Exhibit Notional Set Deductible Sensitivity Set 1 Policy Form Sensitivity Set 2 Policy Form/Construction Sensitivity Set 3 Coverage Sensitivity Set 4 Building Code/Enforcement (Year Built) Sensitivity Set 5 Building Strength Sensitivity Set 6 Condo Unit Floor Sensitivity Set 7 Number of Stories Sensitivity Set 8 D. Hurricane models shall treat points in “Location Grid B” as coordinates that would result from a geocoding process. Hurricane models shall treat points by simulating hurricane loss at exact location or by using the nearest modeled parcel/street/cell in the hurricane model. Provide the results statewide (overall percentage change) and by the regions defined in Form A-5, Percentage Change in Hurricane Output Ranges. J. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include all tables in Form A-7, Percentage Change in Logical Relationship to Hurricane Risk in a submission appendix. Percentage changes are provided in the file named ARA17FormA7.xlsx.

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Form A‐7: Percent Change in Logical Relationship to Risk ‐ Deductibles

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Construction / Percent Change in Loss Cost Region Policy $0 $500 1% 2% 5% 10% Coastal ‐10.0% ‐10.4% ‐10.8% ‐11.5% ‐13.5% ‐16.2% Inland ‐13.2% ‐13.9% ‐14.4% ‐15.3% ‐18.0% ‐20.9% North ‐9.7% ‐10.1% ‐10.4% ‐10.9% ‐12.5% ‐14.6% Frame Owners Central ‐13.8% ‐14.6% ‐15.2% ‐16.2% ‐19.1% ‐22.5% South ‐8.6% ‐8.9% ‐9.2% ‐9.8% ‐11.7% ‐14.4% Statewide ‐10.5% ‐10.9% ‐11.2% ‐11.9% ‐13.9% ‐16.6% Coastal ‐10.0% ‐10.4% ‐10.8% ‐11.5% ‐13.6% ‐16.4% Inland ‐13.2% ‐13.8% ‐14.4% ‐15.3% ‐18.0% ‐21.1% North ‐9.7% ‐10.1% ‐10.4% ‐10.9% ‐12.5% ‐14.8% Masonry Owners Central ‐13.7% ‐14.5% ‐15.1% ‐16.2% ‐19.1% ‐22.6% South ‐8.5% ‐8.8% ‐9.1% ‐9.8% ‐11.7% ‐14.6% Statewide ‐10.4% ‐10.8% ‐11.2% ‐11.9% ‐14.0% ‐16.8% Coastal ‐6.8% ‐7.1% ‐7.1% ‐7.3% ‐8.2% ‐9.4% Inland ‐12.3% ‐12.7% ‐12.7% ‐13.1% ‐14.4% ‐15.5% Manufactured North ‐8.2% ‐8.4% ‐8.4% ‐8.7% ‐9.3% ‐10.0% Homes Central ‐12.2% ‐12.7% ‐12.7% ‐13.3% ‐14.8% ‐16.5% South ‐5.0% ‐5.3% ‐5.3% ‐5.5% ‐6.2% ‐7.5% Statewide ‐7.5% ‐7.7% ‐7.7% ‐7.9% ‐8.7% ‐9.9% Coastal ‐6.6% ‐8.8% ‐8.3% ‐8.8% ‐9.8% ‐10.7% Inland ‐4.7% ‐8.2% ‐8.0% ‐8.2% ‐7.8% ‐6.6% North ‐9.0% ‐11.0% ‐10.6% ‐11.0% ‐12.0% ‐12.9% Frame Renters Central ‐9.2% ‐14.1% ‐13.4% ‐14.1% ‐15.1% ‐15.3% South ‐4.8% ‐6.6% ‐6.1% ‐6.6% ‐7.6% ‐8.5% Statewide ‐6.4% ‐8.8% ‐8.3% ‐8.8% ‐9.7% ‐10.5% Coastal ‐6.5% ‐8.9% ‐8.3% ‐8.9% ‐9.8% ‐10.5% Inland ‐4.4% ‐7.9% ‐7.7% ‐7.9% ‐7.5% ‐5.9% North ‐9.0% ‐11.1% ‐10.7% ‐11.1% ‐12.1% ‐12.9% Masonry Renters Central ‐8.9% ‐14.0% ‐13.4% ‐14.0% ‐15.0% ‐15.0% South ‐4.7% ‐6.6% ‐6.1% ‐6.6% ‐7.5% ‐8.4% Statewide ‐6.3% ‐8.8% ‐8.3% ‐8.8% ‐9.7% ‐10.3% Coastal ‐7.9% ‐9.7% ‐9.7% ‐10.5% ‐11.7% ‐12.4% Inland ‐8.8% ‐11.2% ‐11.2% ‐11.7% ‐11.2% ‐10.1% North ‐9.3% ‐11.0% ‐11.0% ‐11.6% ‐12.8% ‐13.5% Frame Condo Unit Central ‐11.0% ‐14.9% ‐14.9% ‐15.9% ‐17.0% ‐17.6% South ‐6.3% ‐7.7% ‐7.7% ‐8.5% ‐9.7% ‐10.3% Statewide ‐8.0% ‐9.8% ‐9.8% ‐10.6% ‐11.7% ‐12.3% Coastal ‐7.9% ‐9.8% ‐9.8% ‐10.6% ‐11.7% ‐12.4% Inland ‐8.7% ‐11.2% ‐11.2% ‐11.5% ‐10.6% ‐9.4% Masonry Condo North ‐9.3% ‐11.1% ‐11.1% ‐11.8% ‐12.9% ‐13.5% Unit Central ‐10.9% ‐14.9% ‐14.9% ‐15.9% ‐16.8% ‐17.3% South ‐6.2% ‐7.7% ‐7.7% ‐8.5% ‐9.6% ‐10.4% Statewide ‐7.9% ‐9.9% ‐9.9% ‐10.7% ‐11.6% ‐12.3% Construction / Percent Change in Loss Cost Region Policy $0 2% 3% 5% 10% Coastal ‐9.7% ‐10.6% ‐11.1% ‐12.2% ‐17.0% Inland ‐12.8% ‐13.9% ‐14.3% ‐15.7% ‐23.1% Commercial North ‐8.7% ‐9.0% ‐9.1% ‐9.5% ‐11.5% Residential Central ‐15.1% ‐16.8% ‐17.5% ‐19.3% ‐27.6% South ‐7.4% ‐8.1% ‐8.5% ‐9.5% ‐13.6% Statewide ‐10.1% ‐11.0% ‐11.5% ‐12.6% ‐17.5%

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Form A‐7: Percent Change in Logical Relationship to Risk ‐ Policy Form

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Percent Change in Loss Cost Policy Region Masonry Frame Coastal ‐10.0% ‐10.0% Inland ‐13.2% ‐13.2% North ‐9.7% ‐9.7% Owners Central ‐13.7% ‐13.8% South ‐8.5% ‐8.6% Statewide ‐10.4% ‐10.5% Coastal ‐6.5% ‐6.6% Inland ‐4.4% ‐4.7% North ‐9.0% ‐9.0% Renters Central ‐8.9% ‐9.2% South ‐4.7% ‐4.8% Statewide ‐6.3% ‐6.4% Coastal ‐7.9% ‐7.9% Inland ‐8.7% ‐8.8% North ‐9.3% ‐9.3% Condo Unit Central ‐10.9% ‐11.0% South ‐6.2% ‐6.3% Statewide ‐7.9% ‐8.0% Percent Change in Loss Cost Policy Region Concrete Coastal ‐9.7% Inland ‐12.8% Commercial North ‐8.7% Residential Central ‐15.1% South ‐7.4% Statewide ‐10.1%

Form A‐7: Percent Change in Logical Relationship to Risk ‐ Policy Form/Construction

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Percent Change in Loss Cost Region Frame Owners Masonry Owners Manufactured Homes

Coastal ‐10.0% ‐10.0% ‐6.8% Inland ‐13.2% ‐13.2% ‐12.3% North ‐9.7% ‐9.7% ‐8.2% Central ‐13.8% ‐13.7% ‐12.2% South ‐8.6% ‐8.5% ‐5.0% Statewide ‐10.5% ‐10.4% ‐7.5%

April 9, 2019 Applied Research Associates, Inc. 273 Appendix A - Forms 4/9/2019 11:00 AM

Form A‐7: Percent Change in Logical Relationship to Risk ‐ Coverage

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Construction / Percent Change in Loss Cost Region Policy Coverage ACoverage B Coverage C Coverage D Coastal ‐10.3% ‐10.3% ‐1.2% ‐13.3% Inland ‐13.5% ‐13.5% 1.3% ‐13.1% North ‐9.8% ‐9.8% ‐6.5% ‐13.8% Frame Owners Central ‐14.0% ‐14.0% ‐3.4% ‐18.3% South ‐8.9% ‐8.9% 0.9% ‐11.4% Statewide ‐10.7% ‐10.7% ‐1.0% ‐13.2% Coastal ‐10.2% ‐10.2% ‐1.1% ‐13.2% Inland ‐13.5% ‐13.5% 1.4% ‐12.8% North ‐9.8% ‐9.8% ‐6.5% ‐13.9% Masonry Owners Central ‐13.9% ‐13.9% ‐3.4% ‐18.2% South ‐8.8% ‐8.8% 1.0% ‐11.3% Statewide ‐10.7% ‐10.7% ‐0.9% ‐13.2% Coastal ‐8.1% ‐8.1% 1.7% ‐8.0% Inland ‐13.0% ‐13.0% ‐2.7% ‐11.9% Manufactured North ‐8.5% ‐8.5% ‐5.0% ‐9.6% Homes Central ‐12.9% ‐12.9% ‐4.8% ‐14.3% South ‐6.5% ‐6.5% 3.9% ‐6.2% Statewide ‐8.7% ‐8.7% 1.5% ‐8.2% Coastal ‐2.7% ‐14.1% Inland ‐1.2% ‐15.5% North ‐7.3% ‐14.1% Frame Renters Central ‐5.1% ‐19.4% South ‐0.7% ‐12.3% Statewide ‐2.6% ‐14.2% Coastal ‐2.8% ‐14.3% Inland ‐1.2% ‐15.3% North ‐7.3% ‐14.4% Masonry Renters Central ‐5.1% ‐19.4% South ‐0.8% ‐12.4% Statewide ‐2.7% ‐14.3% Coastal ‐10.2% ‐1.8% ‐13.7% Inland ‐12.4% 1.3% ‐13.8% North ‐9.7% ‐7.1% ‐14.3% Frame Condo Unit Central ‐13.4% ‐3.6% ‐18.7% South ‐8.9% 0.3% ‐11.8% Statewide ‐10.5% ‐1.5% ‐13.7% Coastal ‐10.2% ‐1.9% ‐13.8% Inland ‐12.4% 1.3% ‐13.6% Masonry Condo North ‐9.7% ‐7.1% ‐14.6% Unit Central ‐13.3% ‐3.7% ‐18.7% South ‐8.9% 0.2% ‐11.9% Statewide ‐10.5% ‐1.6% ‐13.8% Coastal ‐9.8% ‐3.0% ‐9.7% Inland ‐12.8% ‐7.6% ‐12.8% Commercial North ‐8.7% ‐5.7% ‐8.7% Residential Central ‐15.2% ‐10.9% ‐15.2% South ‐7.5% 0.1% ‐7.3% Statewide ‐10.2% ‐3.5% ‐10.1%

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Form A‐7: Percent Change in Logical Relationship to Risk ‐ Building Code / Enforcement (Year Built) Sensitivity

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Percent Change in Loss Cost Construction / Region Year Built Year Built Year Built Policy 1980 1998 2004 Coastal ‐9.2% ‐16.1% ‐12.7% Inland ‐17.7% ‐23.2% ‐24.9% North ‐6.5% 4.1% 9.0% Frame Owners Central ‐14.7% ‐22.2% ‐18.9% South ‐8.2% ‐16.2% ‐13.7% Statewide ‐10.4% ‐17.1% ‐14.2% Coastal ‐9.1% ‐16.3% ‐12.9% Inland ‐17.6% ‐23.2% ‐25.0% North ‐6.5% 4.3% 9.4% Masonry Owners Central ‐14.6% ‐22.2% ‐18.9% South ‐8.1% ‐16.6% ‐14.1% Statewide ‐10.4% ‐17.3% ‐14.4% Percent Change in Loss Cost Construction / Region Year Built Year Built Year Built Policy 1974 1992 2004 Coastal ‐5.6% ‐5.8% ‐8.3% Inland ‐16.4% ‐16.5% ‐17.5% Manufactured North ‐5.0% ‐5.0% ‐6.0% Homes Central ‐12.8% ‐13.0% ‐14.4% South ‐4.2% ‐4.4% ‐7.3% Statewide ‐7.0% ‐7.2% ‐9.6% Percent Change in Loss Cost Construction / Region Year Built Year Built Year Built Policy 1980 1998 2004 Coastal ‐5.3% ‐0.2% 1.9% Inland ‐12.0% ‐14.3% ‐6.7% North ‐4.7% 3.4% ‐7.4% Frame Renters Central ‐9.6% ‐9.2% ‐6.5% South ‐4.4% 2.3% 5.8% Statewide ‐5.9% ‐1.8% 1.0% Coastal ‐5.3% ‐0.6% 1.3% Inland ‐11.7% ‐14.4% ‐6.7% North ‐4.6% 3.8% ‐6.8% Masonry Renters Central ‐9.4% ‐9.3% ‐6.2% South ‐4.4% 1.7% 4.8% Statewide ‐5.9% ‐2.2% 0.5% Coastal ‐6.7% ‐7.3% ‐5.5% Inland ‐14.2% ‐18.3% ‐15.4% North ‐5.3% 3.2% ‐0.9% Frame Condo Unit Central ‐11.5% ‐14.9% ‐12.2% South ‐5.7% ‐6.4% ‐4.4% Statewide ‐7.5% ‐8.8% ‐6.7% Coastal ‐6.6% ‐7.8% ‐6.0% Inland ‐14.1% ‐18.4% ‐15.5% Masonry Condo North ‐5.3% 3.5% ‐0.4% Unit Central ‐11.4% ‐15.0% ‐12.2% South ‐5.7% ‐7.0% ‐5.3% Statewide ‐7.5% ‐9.2% ‐7.2% Coastal ‐8.6% ‐9.2% ‐9.2% Inland ‐17.0% ‐17.0% ‐17.3% Commercial North ‐7.0% ‐3.4% ‐7.5% Residential Central ‐13.8% ‐18.3% ‐15.7% South ‐7.8% ‐5.9% ‐7.2% Statewide ‐9.8% ‐10.3% ‐10.5% April 9, 2019 Applied Research Associates, Inc. 275 Appendix A - Forms 4/9/2019 11:00 AM

Form A‐7: Percent Change in Logical Relationship to Risk ‐ Building Strength

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Construction / Percent Change in Loss Cost Region Policy Weak Medium Strong Coastal ‐6.6% ‐14.5% ‐10.4% Inland ‐16.4% ‐21.7% ‐17.3% North ‐5.9% 1.3% ‐7.3% Frame Owners Central ‐13.1% ‐20.0% ‐15.0% South ‐5.4% ‐14.7% ‐9.7% Statewide ‐7.8% ‐15.6% ‐11.2% Coastal ‐6.6% ‐14.7% ‐10.3% Inland ‐16.3% ‐21.7% ‐17.1% North ‐5.9% 1.4% ‐7.2% Masonry Owners Central ‐13.0% ‐20.0% ‐14.8% South ‐5.3% ‐14.9% ‐9.6% Statewide ‐7.7% ‐15.7% ‐11.1% Coastal ‐5.6% ‐5.8% ‐8.3% Inland ‐16.4% ‐16.5% ‐17.5% Manufactured North ‐5.0% ‐5.0% ‐6.0% Homes Central ‐12.8% ‐13.0% ‐14.4% South ‐4.2% ‐4.4% ‐7.3% Statewide ‐7.0% ‐7.2% ‐9.6% Coastal ‐3.3% ‐4.5% ‐4.8% Inland ‐12.8% ‐14.2% ‐4.8% North ‐3.5% 2.2% ‐5.5% Frame Renters Central ‐9.8% ‐10.3% ‐4.1% South ‐2.1% ‐4.0% ‐5.1% Statewide ‐3.9% ‐5.3% ‐4.8% Coastal ‐3.2% ‐5.1% ‐4.0% Inland ‐12.6% ‐14.2% ‐3.0% North ‐3.5% 2.6% ‐5.0% Masonry Renters Central ‐9.6% ‐10.4% ‐2.4% South ‐2.1% ‐4.8% ‐4.5% Statewide ‐3.8% ‐5.9% ‐3.9% Coastal ‐3.9% ‐5.8% ‐8.0% Inland ‐14.7% ‐17.3% ‐14.8% North ‐4.2% 0.3% ‐6.5% Frame Condo Unit Central ‐10.9% ‐13.0% ‐12.4% South ‐2.5% ‐4.9% ‐7.2% Statewide ‐4.7% ‐6.9% ‐8.6% Coastal ‐3.8% ‐6.1% ‐7.8% Inland ‐14.7% ‐17.3% ‐13.9% Masonry Condo North ‐4.1% 0.7% ‐6.6% Unit Central ‐10.9% ‐12.9% ‐11.7% South ‐2.5% ‐5.3% ‐7.2% Statewide ‐4.7% ‐7.2% ‐8.4% Coastal ‐8.6% ‐9.2% ‐4.4% Inland ‐17.0% ‐17.0% ‐18.7% Commercial North ‐7.0% ‐3.4% ‐3.3% Residential Central ‐13.8% ‐18.3% ‐13.4% South ‐7.8% ‐5.9% ‐2.5% Statewide ‐9.8% ‐10.3% ‐6.8% April 9, 2019 Applied Research Associates, Inc. 276 Appendix A - Forms 4/9/2019 11:00 AM

Form A‐7: Percent Change in Logical Relationship to Risk ‐ Condo Unit Floor

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Construction / Percent Change in Loss Cost Region Policy 3rd Floor 9th Floor 15th Floor 20th Floor Coastal ‐6.2% ‐6.2% ‐6.2% ‐6.2% Inland ‐15.7% ‐15.3% ‐15.7% ‐15.7% North ‐6.4% ‐6.3% ‐6.4% ‐6.4% Condo Unit A Central ‐11.7% ‐11.5% ‐11.7% ‐11.7% South ‐5.3% ‐5.3% ‐5.3% ‐5.3% Statewide ‐7.7% ‐7.7% ‐7.7% ‐7.7% Coastal ‐6.4% ‐6.6% ‐6.4% ‐6.4% Inland ‐15.6% ‐15.4% ‐15.6% ‐15.6% North ‐6.2% ‐6.2% ‐6.2% ‐6.2% Condo Unit B Central ‐12.0% ‐12.0% ‐12.0% ‐12.1% South ‐5.4% ‐5.6% ‐5.4% ‐5.3% Statewide ‐7.7% ‐7.9% ‐7.7% ‐7.6%

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Form A‐7: Percent Change in Logical Relationship to Risk ‐ Number of Stories

Modeling Organization: ARA Model Name & Version Number: HurLoss 9.0 (vs. 8.0.a) Model Release Date: 11/1/2018

Construction / Percent Change in Loss Cost Region Policy 1 Story 2 Story Coastal ‐9.4% ‐8.9% Inland ‐17.7% ‐17.6% North ‐6.6% ‐6.3% Frame Owners Central ‐14.8% ‐14.5% South ‐8.4% ‐7.9% Statewide ‐10.6% ‐10.1% Coastal ‐9.3% ‐8.9% Inland ‐17.6% ‐17.5% North ‐6.6% ‐6.3% Masonry Owners Central ‐14.7% ‐14.4% South ‐8.3% ‐7.8% Statewide ‐10.5% ‐10.0% Coastal ‐5.7% ‐5.6% Inland ‐11.3% ‐13.8% North ‐4.9% ‐4.3% Frame Renters Central ‐9.4% ‐10.7% South ‐4.8% ‐4.4% Statewide ‐6.2% ‐6.3% Coastal ‐5.6% ‐5.5% Inland ‐11.0% ‐13.4% North ‐4.9% ‐4.3% Masonry Renters Central ‐9.1% ‐10.5% South ‐4.7% ‐4.4% Statewide ‐6.1% ‐6.2% Construction / Percent Change in Loss Cost Region Policy 5 Story 10 Story 20 Story Coastal ‐11.2% ‐9.1% ‐9.0% Inland ‐20.8% ‐17.3% ‐17.1% Commercial North ‐8.6% ‐5.9% ‐5.9% Residential Central ‐17.2% ‐16.4% ‐16.2% South ‐10.2% ‐7.1% ‐7.1% Statewide ‐12.0% ‐10.1% ‐10.1%

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Form A-8A: Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data) A. Provide a detailed explanation of how the Expected Annual Hurricane Losses and Return Periods are calculated. B. Complete Part A showing the personal and commercial residential hurricane probable maximum loss for Florida. For the Expected Annual Hurricane Losses column, provide personal and commercial residential, zero deductible statewide hurricane loss costs based on the 2012 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2012c.exe.” In the column, Return Period (Years), provide the return period associated with the average hurricane loss within the ranges indicated on a cumulative basis. For example, if the average hurricane loss is $4,705 million for the range $4,501 million to $5,000 million, provide the return period associated with a hurricane loss that is $4,705 million or greater. For each hurricane loss range in millions ($1,001-$1,500, $1,501-$2,000, $2,001- $2,500) the average hurricane loss within that range should be identified and then the return period associated with that hurricane loss calculated. The return period is then the reciprocal of the probability of the hurricane loss equaling or exceeding this average hurricane loss size. The probability of equaling or exceeding the average of each range should be smaller as the ranges increase (and the average hurricane losses within the ranges increase). Therefore, the return period associated with each range and average hurricane loss within that range should be larger as the ranges increase. Return periods shall be based on cumulative probabilities. A return period for an average hurricane loss of $4,705 million within the $4,501-$5,000 million range should be lower than the return period for an average hurricane loss of $5,455 million associated with a $5,001- $6,000 million range. C. Provide a graphical comparison of the current hurricane model Residential Return Periods hurricane loss curve to the previously accepted hurricane model Residential Return Periods hurricane loss curve. Residential Return Period (Years) shall be shown on the y-axis on a log 10 scale with Hurricane Losses in Billions shown on the x-axis. The legend shall indicate the corresponding hurricane model with a solid line representing the current year and a dotted line representing the previously accepted hurricane model. D. Provide the estimated hurricane loss and uncertainty interval for each of the Personal and Commercial Residential Return Periods given in Part B, Annual Aggregate and Part C, Annual Occurrence. Describe how the uncertainty intervals are derived. Also, provide Parts B and C, the Conditional Tail Expectation, the expected value of hurricane losses greater than the Estimated Hurricane Loss Level.

April 9, 2019 Applied Research Associates, Inc. 279 Appendix A - Forms 4/9/2019 11:00 AM

E. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-8A, Hurricane Probable Maximum Loss for Florida (2012 FHCF Exposure Data), in a submission appendix. A. Return time represents the mean return period associated with a storm producing a loss equal to or greater than the average loss within a given limit range (ai). The return time is the reciprocal of the annual probability of exceedance associated with the loss level of interest, which is estimated as fraction of years in the 250,000 year simulation in which the maximum event loss is equal to or greater than the loss level of interest. B. See Form A-8A, Part A. C. A graphical comparison of return times for the current submission and the previously accepted submission is provided in Figure 77. D. See Form A-8A, Part B and Part C. The uncertainty intervals given in Part B represent the 5th and 95th percentiles of the maximum loss observed in each consecutive n-year period of the 250,000 years of simulated losses, where n is 5, 10, ..., or 1,000 years. E. See file ARA17FormA8A_revised_2019-03-22.xlsx.

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Part A: Personal and Commercial Residential Probable Maximum Loss for Florida AVERAGE EXPECTED ANNUAL RETURN LOSS RANGE TOTAL LOSS NUMBER OF HURRICANE PERIOD (MILLIONS) LOSS (MILLIONS) HURRICANES LOSSES* (YEARS) $ ‐ to$ 500 15,707,481 87 180,401 62.8 2.0 $ 501 to$ 1,000 15,177,259 717 21,148 60.7 2.9 $ 1,001 to$ 1,500 14,207,428 1,231 11,539 56.8 3.3 $ 1,501 to$ 2,000 13,673,837 1,735 7,878 54.7 3.6 $ 2,001 to$ 2,500 13,495,501 2,240 6,024 54.0 3.9 $ 2,501 to$ 3,000 13,058,621 2,741 4,763 52.2 4.2 $ 3,001 to$ 3,500 13,028,304 3,243 4,017 52.1 4.4 $ 3,501 to$ 4,000 12,745,871 3,743 3,405 51.0 4.6 $ 4,001 to$ 4,500 12,867,040 4,247 3,029 51.5 4.8 $ 4,501 to$ 5,000 12,369,096 4,746 2,606 49.5 5.1 $ 5,001 to$ 6,000 25,420,680 5,482 4,637 101.7 5.4 $ 6,001 to$ 7,000 25,449,956 6,477 3,929 101.8 5.8 $ 7,001 to$ 8,000 25,228,248 7,483 3,371 100.9 6.2 $ 8,001 to$ 9,000 25,667,156 8,496 3,021 102.7 6.7 $ 9,001 to$ 10,000 26,190,851 9,496 2,758 104.8 7.1 $ 10,001 to$ 11,000 25,770,191 10,497 2,455 103.1 7.6 $ 11,001 to$ 12,000 25,403,294 11,494 2,210 101.6 8.1 $ 12,001 to$ 13,000 25,370,280 12,491 2,031 101.5 8.6 $ 13,001 to$ 14,000 24,840,355 13,492 1,841 99.4 9.1 $ 14,001 to$ 15,000 25,238,828 14,496 1,741 101.0 9.7 $ 15,001 to$ 16,000 24,520,446 15,489 1,583 98.1 10.3 $ 16,001 to$ 17,000 23,537,554 16,494 1,427 94.2 10.9 $ 17,001 to$ 18,000 22,550,043 17,480 1,290 90.2 11.5 $ 18,001 to$ 19,000 24,456,900 18,499 1,322 97.8 12.2 $ 19,001 to$ 20,000 22,434,850 19,491 1,151 89.7 12.9 $ 20,001 to$ 21,000 22,350,458 20,505 1,090 89.4 13.6 $ 21,001 to$ 22,000 21,792,973 21,492 1,014 87.2 14.3 $ 22,001 to$ 23,000 22,190,134 22,505 986 88.8 15.1 $ 23,001 to$ 24,000 21,576,927 23,478 919 86.3 16.0 $ 24,001 to$ 25,000 21,068,771 24,498 860 84.3 16.9 $ 25,001 to$ 26,000 19,276,902 25,498 756 77.1 17.8 $ 26,001 to$ 27,000 19,387,726 26,485 732 77.6 18.7 $ 27,001 to$ 28,000 18,948,054 27,500 689 75.8 19.7 $ 28,001 to$ 29,000 18,664,892 28,496 655 74.7 20.8 $ 29,001 to$ 30,000 16,983,943 29,486 576 67.9 21.8 $ 30,001 to$ 35,000 83,422,512 32,409 2,574 333.7 25.1 $ 35,001 to$ 40,000 69,523,731 37,398 1,859 278.1 31.9 $ 40,001 to$ 45,000 60,258,160 42,435 1,420 241.0 39.9 $ 45,001 to$ 50,000 55,513,091 47,447 1,170 222.1 50.1 $ 50,001 to$ 55,000 47,049,432 52,393 898 188.2 62.6 $ 55,001 to$ 60,000 40,705,000 57,411 709 162.8 78.2 $ 60,001 to$ 65,000 35,399,868 62,433 567 141.6 97.4 $ 65,001 to$ 70,000 26,761,694 67,409 397 107.0 119.2 $ 70,001 to$ 75,000 25,849,249 72,406 357 103.4 145.9 $ 75,001 to$ 80,000 22,406,430 77,530 289 89.6 179.3 $ 80,001 to$ 90,000 37,474,044 84,401 444 149.9 245.6 $ 90,001 to$ 100,000 24,181,577 94,459 256 96.7 368.2 $ 100,001 to Maximum 70,741,595 126,099 561 283.0 1,315.8 Total 1,309,937,254 299,355 5,239.7

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Figure 77. Comparison of Form A-8A Results to Prior Year’s Submission Part B: Personal and Commercial Residential Hurricane Probable Maximum Loss for Florida (Annual Aggregate)

Return Period Estimated Loss Uncertainty Interval Conditional Tail (Years) Level 5% 95% Expectation Top Event 307,959,953,615 N/A N/A N/A 1000 131,972,613,651 96,419,288,294 218,597,762,724 161,536,576,399 500 112,782,878,416 82,124,921,179 193,620,612,226 139,328,817,139 250 93,337,223,070 64,480,533,940 179,965,607,364 119,881,215,979 100 69,626,821,554 43,351,661,728 153,005,762,021 94,447,153,926 50 51,995,408,800 27,822,850,430 130,975,026,151 75,999,736,624 20 30,735,994,214 10,280,992,489 105,985,926,653 52,938,162,923 10 16,528,960,600 2,372,949,766 86,802,358,890 36,427,268,928 5 5,065,828,116 170,971,449 69,089,956,965 21,608,076,661

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Part C: Personal and Commercial Residential Hurricane Probable Maximum Loss for Florida (Annual Occurrence) Return Period Estimated Loss Uncertainty Interval Conditional Tail (Years) Level 5% 95% Expectation Top Event 307,959,953,615 N/A N/A N/A 1000 120,200,730,310 91,295,394,819 203,494,415,396 147,622,383,213 500 103,053,652,419 73,830,029,136 180,414,374,460 129,098,123,589 250 84,912,250,872 58,431,705,615 164,597,602,682 110,768,585,768 100 63,025,429,290 39,989,789,881 138,481,180,994 87,847,538,661 50 47,389,782,984 24,938,426,740 119,662,519,092 70,910,254,868 20 27,769,806,911 9,359,352,361 95,855,450,745 49,603,137,740 10 15,014,052,533 2,098,823,598 79,509,188,508 34,632,867,248 5 4,592,983,125 158,539,737 62,613,742,643 20,895,219,697

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Form A-8B: Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data) A. Provide a detailed explanation of how the Expected Annual Hurricane Losses and Return Periods are calculated. B. Complete Part A showing the personal and commercial residential hurricane probable maximum loss for Florida. For the Expected Annual Hurricane Losses column, provide personal and commercial residential, zero deductible statewide hurricane loss costs based on the 2017 Florida Hurricane Catastrophe Fund personal and commercial residential zero deductible exposure data found in the file named “hlpm2017c.exe.” In the column, Return Period (Years), provide the return period associated with the average hurricane loss within the ranges indicated on a cumulative basis. For example, if the average hurricane loss is $4,705 million for the range $4,501 million to $5,000 million, provide the return period associated with a hurricane loss that is $4,705 million or greater. For each hurricane loss range in millions ($1,001-$1,500, $1,501-$2,000, $2,001- $2,500) the average hurricane loss within that range should be identified and then the return period associated with that hurricane loss calculated. The return period is then the reciprocal of the probability of the hurricane loss equaling or exceeding this average hurricane loss size. The probability of equaling or exceeding the average of each range should be smaller as the ranges increase (and the average hurricane losses within the ranges increase). Therefore, the return period associated with each range and average hurricane loss within that range should be larger as the ranges increase. Return periods shall be based on cumulative probabilities. A return period for an average hurricane loss of $4,705 million within the $4,501-$5,000 million range should be lower than the return period for an average hurricane loss of $5,455 million associated with a $5,001- $6,000 million range.

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C. Provide a graphical comparison of the current hurricane model Residential Return Periods hurricane loss curve to the previously accepted hurricane model Residential Return Periods hurricane loss curve. Residential Return Period (Years) shall be shown on the y-axis on a log 10 scale with Hurricane Losses in Billions shown on the x-axis. The legend shall indicate the corresponding hurricane model with a solid line representing the current year and a dotted line representing the previously accepted hurricane model. D. Provide the estimated hurricane loss and uncertainty interval for each of the Personal and Commercial Residential Return Periods given in Part B, Annual Aggregate and Part C, Annual Occurrence. Describe how the uncertainty intervals are derived. Also, provide Parts B and C, the Conditional Tail Expectation, the expected value of hurricane losses greater than the Estimated Hurricane Loss Level. E. Provide this form in Excel format. The file name shall include the abbreviated name of the modeling organization, the hurricane standards year, and the form name. Also include Form A-8B, Hurricane Probable Maximum Loss for Florida (2017 FHCF Exposure Data), in a submission appendix. A. Return time represents the mean return period associated with a storm producing a loss equal to or greater than the average loss within a given limit range (ai). The return time is the reciprocal of the annual probability of exceedance associated with the loss level of interest, which is estimated as fraction of years in the 250,000 year simulation in which the maximum event loss is equal to or greater than the loss level of interest. B. See Form A-8B, Part A. C. A graphical comparison of return times for the current submission and the previously accepted submission is provided in Figure 78. D. See Form A-8B, Part B and Part C. The uncertainty intervals given in Part B represent the 5th and 95th percentiles of the maximum loss observed in each consecutive n-year period of the 250,0000 years of simulated losses, where n is 5, 10, ..., or 1,000 years. E. See file ARA17FormA8B_revised_2019-03-22.xlsx.

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Part A: Personal and Commercial Residential Probable Maximum Loss for Florida

AVERAGE EXPECTED ANNUAL RETURN LOSS RANGE TOTAL LOSS NUMBER OF HURRICANE PERIOD (MILLIONS) LOSS (MILLIONS) HURRICANES LOSSES* (YEARS) $ ‐ to$ 500 15,759,099 87 180,185 63.0 2.0 $ 501 to$ 1,000 15,467,344 718 21,536 61.9 2.9 $ 1,001 to$ 1,500 14,618,985 1,230 11,880 58.5 3.3 $ 1,501 to$ 2,000 13,890,463 1,736 7,998 55.6 3.7 $ 2,001 to$ 2,500 13,440,966 2,241 5,997 53.8 3.9 $ 2,501 to$ 3,000 12,928,589 2,739 4,719 51.7 4.2 $ 3,001 to$ 3,500 12,579,290 3,244 3,877 50.3 4.4 $ 3,501 to$ 4,000 12,894,927 3,744 3,444 51.6 4.7 $ 4,001 to$ 4,500 12,828,750 4,250 3,018 51.3 4.9 $ 4,501 to$ 5,000 11,961,664 4,750 2,518 47.8 5.1 $ 5,001 to$ 6,000 24,994,656 5,478 4,562 100.0 5.4 $ 6,001 to$ 7,000 25,592,743 6,475 3,952 102.4 5.8 $ 7,001 to$ 8,000 25,268,892 7,482 3,377 101.1 6.3 $ 8,001 to$ 9,000 25,784,271 8,487 3,038 103.1 6.7 $ 9,001 to$ 10,000 25,883,986 9,488 2,728 103.5 7.2 $ 10,001 to$ 11,000 26,366,923 10,483 2,515 105.5 7.7 $ 11,001 to$ 12,000 25,058,855 11,494 2,180 100.2 8.2 $ 12,001 to$ 13,000 25,782,860 12,485 2,065 103.1 8.7 $ 13,001 to$ 14,000 24,880,139 13,499 1,843 99.5 9.2 $ 14,001 to$ 15,000 25,600,737 14,504 1,765 102.4 9.8 $ 15,001 to$ 16,000 24,316,023 15,487 1,570 97.3 10.4 $ 16,001 to$ 17,000 23,332,955 16,478 1,416 93.3 11.1 $ 17,001 to$ 18,000 23,793,740 17,482 1,361 95.2 11.7 $ 18,001 to$ 19,000 23,778,231 18,490 1,286 95.1 12.4 $ 19,001 to$ 20,000 22,504,310 19,484 1,155 90.0 13.1 $ 20,001 to$ 21,000 23,293,435 20,504 1,136 93.2 13.9 $ 21,001 to$ 22,000 22,071,645 21,491 1,027 88.3 14.7 $ 22,001 to$ 23,000 21,746,856 22,488 967 87.0 15.5 $ 23,001 to$ 24,000 21,236,939 23,492 904 84.9 16.4 $ 24,001 to$ 25,000 20,895,428 24,496 853 83.6 17.4 $ 25,001 to$ 26,000 20,758,529 25,501 814 83.0 18.4 $ 26,001 to$ 27,000 18,962,526 26,483 716 75.9 19.4 $ 27,001 to$ 28,000 19,165,068 27,496 697 76.7 20.5 $ 28,001 to$ 29,000 17,423,292 28,469 612 69.7 21.6 $ 29,001 to$ 30,000 17,043,077 29,486 578 68.2 22.6 $ 30,001 to$ 35,000 82,931,613 32,357 2,563 331.7 26.2 $ 35,001 to$ 40,000 67,398,176 37,339 1,805 269.6 33.7 $ 40,001 to$ 45,000 62,683,799 42,382 1,479 250.7 42.7 $ 45,001 to$ 50,000 53,493,291 47,465 1,127 214.0 54.4 $ 50,001 to$ 55,000 44,846,865 52,330 857 179.4 68.8 $ 55,001 to$ 60,000 40,448,975 57,455 704 161.8 87.5 $ 60,001 to$ 65,000 30,888,260 62,400 495 123.6 110.1 $ 65,001 to$ 70,000 24,451,256 67,358 363 97.8 136.4 $ 70,001 to$ 75,000 26,930,843 72,394 372 107.7 170.9 $ 75,001 to$ 80,000 19,137,426 77,479 247 76.5 212.4 $ 80,001 to$ 90,000 32,358,603 84,487 383 129.4 296.9 $ 90,001 to$ 100,000 21,553,276 94,531 228 86.2 462.1 $ 100,001 to Maximum 55,544,536 125,382 443 222.2 1,644.7 Total 1,274,573,136 299,355 5,098.3

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Figure 78. Comparison of Form A-8B Results to Prior Year’s Submission Part B: Personal and Commercial Residential Hurricane Probable Maximum Loss for Florida (Annual Aggregate)

Return Period Estimated Loss Uncertainty Interval Conditional Tail (Years) Level 5% 95% Expectation Top Event 317,745,808,230 N/A N/A N/A 1000 124,978,922,848 94,020,816,352 216,682,929,815 153,668,076,656 500 106,432,677,406 78,641,562,958 188,289,246,913 132,446,842,863 250 88,873,537,707 62,003,878,447 171,597,216,136 113,847,247,356 100 66,575,034,048 42,113,963,963 144,168,077,338 89,984,508,982 50 50,155,680,871 27,286,279,155 124,391,367,816 72,567,728,192 20 30,017,194,198 10,080,105,056 100,558,842,124 50,867,194,148 10 16,237,022,359 2,307,169,614 83,260,359,822 35,212,173,692 5 4,988,953,981 173,844,071 66,227,536,607 20,987,753,221

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Part C: Personal and Commercial Residential Hurricane Probable Maximum Loss for Florida (Annual Occurrence) Return Period Estimated Loss Uncertainty Interval Conditional Tail (Years) Level 5% 95% Expectation Top Event 317,745,808,230 N/A N/A N/A 1000 114,015,042,318 87,231,195,919 189,387,648,320 140,276,026,715 500 97,025,388,168 70,257,106,938 172,410,541,106 122,279,039,002 250 81,216,188,950 56,212,993,666 157,786,843,096 105,008,831,214 100 60,134,060,439 38,739,776,591 131,730,549,646 83,460,468,199 50 45,627,706,096 24,431,417,204 113,172,202,829 67,673,128,238 20 27,069,005,639 9,264,209,871 90,985,062,218 47,654,400,847 10 14,807,076,189 2,047,027,405 75,086,555,122 33,508,469,782 5 4,512,611,161 161,145,972 59,734,879,123 20,303,122,549

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Appendix B - Acronyms

Acronyms

A – Building Loss AAL – Average Annual Loss ACV – Actual Cash Value ALE – Additional Living Expenses AMSS – Advanced Modeling and Software Systems ANOVA – Analysis of Variance ARA - Applied Research Associates, Inc. ASCE – American Society of Civil Engineers ASTM – American Society of Testing and materials BPMN – Business Process Model and Notation C – Contents Loss C# – Programming Language C++ – Programming Language CoV – Coefficient of Variation DEC – Digital Equipment Corporation DoD – Department of Defense DNA – Defense Nuclear Agency EIT – Engineer in Training EPA – Environmental Protection Agency ESDU – Engineering Design Methodology ESET NOS32 – Antivirus Software FCAS – Fellow of the Casualty Actuarial Society FCHLPM – Florida Commission on Hurricane Loss Projection Methodology FEMA – Federal Emergency Management Agency FIPS – Federal Information Processing Standards FORTRAN – FORmula TRANslation, computer programming language GIS – Geographical Information Systems HadISST – Hadley Centre Sea Ice and Sea Surface Temperature Data Set HAZUS – HAZards US HURDAT – Hurricane Database

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HURDAT2 – Hurricane Database 2 HurLoss – Hurricane Loss Estimation Software IBHS – Insurance Institute for Business & Home Safety IRIS – IntraRisk Inspection Service LULC – Land use and land cover MAAA – Member of the American Academy of Actuaries MRLC – Multi-Resolution Land Use Consortium NCAR – National Center for Atmospheric Research NIBS – National Institute of Building Sciences NIST – National Institute of Standards and Technology NLCD – National Land Cover Database NLCD – National Land Cover Database NSF – National Science Foundation NWS-38 – National Weather Service Technical Publication 38 PML – Probable Maximum Losses PRA – Probabilistic Risk Assessment QA – Quality Assessment RAM – Random Access Memory RCMP – Residential Construction Mitigation program RMW – Radius of Maximum Winds SAS – Statistical Analysis System SST – Sea Surface Temperature SSTD 12 – Standard for Hurricane-Resistant Construction TIGER – Topologically Integrated Geographic Encoding and Referencing TORSCR – TORmis SCoRe (TORMIS postprocessor code) T-SQL – Transact-SQL (Structured Query Language) UNICEDE/px – Data Format VAPO – Vulnerability Assessment and Protection Option ZIP – Zone Improvement Plan

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APPENDIX C – ACTUARIAL REVIEW LETTER

Actuarial Review Letter

Applied Research Associates, Inc. 291 March 21, 2019 Appendix C – Actuarial Review Letter 3/21/2019 2:35 PM

Applied Research Associates, Inc. 292 March 21, 2019 Appendix C – Actuarial Review Letter 3/21/2019 2:35 PM

Applied Research Associates, Inc. 293 March 21, 2019 Appendix C – Actuarial Review Letter 3/21/2019 2:35 PM