FLORIDA COMMISSION ON HURRICANE LOSS PROJECTION METHODOLOGY
November 2010 Submission May 17, 2011 Revision
Florida Hurricane Model 2011a
A Component of the EQECAT North Atlantic Hurricane Model in WORLDCATenterpriseTM / USWIND£
Submitted under the 2009 Standards of the FCHLPM
1 Frankfurt Irvine London Oakland Paris March 28, 2011 Tokyo Warrington Scott Wallace, Vice Chair Wilmington Florida Commission on Hurricane Loss Projection Methodology c/o Donna Sirmons Florida State Board of Administration 1801 Hermitage Boulevard, Suite 100 Tallahassee, FL 32308
Dear Mr. Wallace,
I am pleased to inform you that EQECAT, Inc. is ready for the Commission’s review and re-certification of the Florida Hurricane Model component of its WORLDCATenterpriseTM / USWIND£ software for use in Florida. As required by the Commission, enclosed are the data and analyses for the General, Meteorological, Vulnerability, Actuarial, Statistical, and Computer Standards, updated to reflect compliance with the Standards set forth in the Commission’s Report of Activities as of November 1, 2009. In addition, the EQECAT Florida Hurricane Model has been reviewed by professionals having credentials and/or experience in the areas of meteorology, engineering, actuarial science, statistics, and computer science, as documented in the signed Expert Certification (Forms G-1 to G-6). We have also completed the Editorial Certification (Form G-7).
Note that we are seeking certification for our Florida Hurricane Model, which is contained in both our standalone software USWIND and our client-server software WORLDCATenterprise, as the Florida Hurricane Model is the same in the two platforms. In our submission, for simplicity we refer to the Florida Hurricane loss model common to both platforms as USWIND, and only refer to specific platform or version numbers as relevant.
The following changes were made to the model between the previously accepted submission (Florida Hurricane Model 2009) and the current submission (Florida Hurricane Model 2011a):
1. The probabilistic hurricane database was regenerated to be consistent with the National Hurricane Center’s HURDAT data set as of June 7, 2009, and to additionally include the 2009 hurricane season. 2. The model was updated to use current scientifically accepted boundary layer methods and inflow angle to incorporate local friction and transitions between local land use / land cover categories, including sea-to-land transition. 3. The ZIP Code database has been updated to December 2009.
4. Land use and land cover data from the Florida Water Management District 2004-2008 was used to resolve the following land use categories: communication, utility, and transportation.
5. The incorporation of default structure types for North Florida and South Florida.
EQECAT is confident that its Florida Hurricane Model is in compliance with the Commission’s standards and is ready to be reviewed by the Professional Team.
Sincerely,
EQECAT, Inc. David F. Smith Senior Vice President, Technology Development and Consulting 2 Enclosures:
1. 20 bound copies of the EQECAT Submission
2. 20 CDs (labeled ‘FCHLPM – EQECAT 2009’) containing an electronic copy of the EQECAT Submission (FCHLPM_EQECAT2009_28March2011.pdf) and the following files:
• 2009FormM1_EQECAT_28March2011.xls • 2009FormM3_EQECAT_28March2011.xls • 2009FormV2_EQECAT_28March2011.xls • 2009FormA1_EQECAT_28March2011.xls • 2009FormA1_EQECAT_28March2011.pdf • 2009FormA3_EQECAT_28March2011.xls • 2009FormA4_EQECAT_28March2011.xls • 2009FormA5_EQECAT_28March2011.xls • 2009FormA6_EQECAT_28March2011.xls • 2009FormA7_EQECAT_28March2011.xls • 2009FormA9_EQECAT_28March2011.xls • 2009FormS6ExpectedLossCost_EQECAT_28March2011.dat • 2009FormS6ExpectedLossCost_EQECAT_28March2011.pdf • 2009FormS6LossCostContour_EQECAT_28March2011.dat • 2009FormS6LossCostContour_EQECAT_28March2011.pdf
■ EQECAT, INC., An ABS Group Company • 475 14th Street, 5th Floor, Suite 550 • Oakland, California 94612-1900 USA • Phone 510.817.3100 • Fax 510.663.1048 3 The Florida Commission on Hurricane Loss Projection Methodology
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 Certification Forms and states that professionals having credentials and/or experience in the areas of meteorology, engineering, actuarial science, statistics, and computer 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 secrets the modeling organization intends to present to the Professional Team X 4. Model Identification X 5. 20 Bound Copies (duplexed) X 6. 20 CD ROMs containing: X a. Submission text in PDF format X b. PDF file highlightable and 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. Forms A-1 and S-6 in PDF format X e. Forms M-1, M-3, V-2, A-1, A-3, A-4, A-5, A-6, A-7, and A-9 in Excel format X f. Form S-6 in ASCII format X 7. Table of Contents X 8. Materials consecutively numbered from beginning to end starting with the first page (including cover) using a single numbering system X 9. All tables, graphs, and other non-text items consecutively numbered using whole numbers X 10. All tables, graphs, and other non-text items specifically listed in Table of Contents X 11. All tables, graphs, and other non-text items clearly labeled with abbreviations defined X 12. All column headings shown and repeated at the top of every subsequent page for Forms and tables X 13. Standards, Disclosures, and Forms in italics, modeling organization responses in non- italics X 14. Graphs accompanied by legends and labels for all elements X 15. All units of measurement clearly identified with appropriate units used X 16. Hard copy of all Forms included in submission document except Forms A-1 and S-6 2. Explanation of “No” responses indicated above. (Attach additional pages if needed.)
EQECAT Florida Hurricane Model 2011a Mar. 28, 2011
Model Name Modeler Signature Date
4 The Florida Commission on Hurricane Loss Projection Methodology
Model Identification
Name of Model and Version: EQECAT Florida Hurricane Model 2011a
Name of Modeling Organization: EQECAT, INC.
Street Address: 475 14th Street, Suite 550
City, State, ZIP Code: Oakland, CA 94612-1900
Mailing Address, if different from above:
______
Contact Person: Justin Brolley
Phone Number: (510) 817-3100 Fax Number: (510) 663-1048
E-mail Address: [email protected]
5 The Florida Commission on Hurricane Loss Projection Methodology
Licenses and Trademarks
A number of trademarks and registered trademarks appear in this document. EQECAT, Inc. acknowledges all trademarks and the rights in the trademarks owned by the companies referred to herein.
• EQECAT£, USWIND£, USQUAKE£, WORLDCATenterprise™ are trademarks of EQECAT, Inc.
• Windows™ is a trademark of Microsoft Corporation.
• MapInfo£ is a trademark of the MapInfo Corporation / Pitney Bowes Business Insight. MapInfo£ contains data which is sublicensed from MapInfo Corporation / Pitney Bowes Business Insight. MapInfo Corporation / Pitney Bowes Business Insight has obtained this data under license from other third party vendors as noted below.
5-Digit ZIP Code data for the United States, Puerto Rico, and the District of Columbia. Copyright© 1993-2009 Tele Atlas Maps. All Rights Reserved.
6 The Florida Commission on Hurricane Loss Projection Methodology
TABLE OF CONTENTS 2009 STANDARDS Page
GENERAL STANDARDS ...... 11
G-1 Scope of the Computer Model and Its Implementation ...... 11 G-2 Qualifications of Modeling Organization Personnel and Consultants...... 29 G-3 Risk Location ...... 38 G-4 Independence of Model Components ...... 40 G-5 Editorial Compliance ...... 41 Form G-1: General Standards Expert Certification ...... 42 Form G-2: Meteorological Standards Expert Certification ...... 43 Form G-3: Vulnerability Standards Expert Certification ...... 44 Form G-4: Actuarial Standards Expert Certification ...... 45 Form G-5: Statistical Standards Expert Certification ...... 46 Form G-6: Computer Standards Expert Certification ...... 47 Form G-7: Editorial Certification ...... 48
METEOROLOGICAL STANDARDS ...... 49
M-1 Base Hurricane Storm Set ...... 49 M-2 Hurricane Parameters and Characteristics ...... 51 M-3 Hurricane Probabilities ...... 56 M-4 Hurricane Windfield Structure ...... 59 M-5 Landfall and Over-Land Weakening Methodologies ...... 64 M-6 Logical Relationships of Hurricane Characteristics ...... 67 Form M-1: Annual Occurrence Rates ...... 68 Form M-2: Maps of Maximum Winds ...... 72 Form M-3: Radius of Maximum Winds and Radii of Standard Wind Thresholds ...... 76
VULNERABILITY STANDARDS ...... 80
V-1 Derivation of Vulnerability Functions ...... 80 V-2 Mitigation Measures ...... 87 Form V-1: One Hypothetical Event ...... 89 Form V-2: Mitigation Measures – Range of Changes in Damage ...... 93
ACTUARIAL STANDARDS ...... 95
A-1 Modeled Loss Costs and Probable Maximum Loss Levels ...... 95 A-2 Underwriting Assumptions ...... 96 A-3 Loss Cost Projections and Probable Maximum Loss Levels ...... 99 A-4 Demand Surge...... 102 A-5 User Inputs ...... 103 A-6 Logical Relationship to Risk...... 112 A-7 Deductibles and Policy Limits ...... 117 A-8 Contents ...... 122 7 The Florida Commission on Hurricane Loss Projection Methodology
A-9 Time Element Coverage ...... 124 A-10 Output Ranges ...... 126 A-11 Probable Maximum Loss ...... 129 Form A-1: Personal Residential Loss Costs ...... 130 Form A-2: Zero Deductible Personal Residential Loss Costs by ZIP Code ...... 133 Form A-3: Base Hurricane Storm Statewide Loss Costs ...... 136 Form A-4: Hurricane Andrew (1992) Percent of Losses ...... 139 Form A-5: Cumulative Losses from the 2004 Hurricane Season...... 148 Form A-6: Personal Residential Output Ranges ...... 181 Form A-7: Percentage Change In Personal Residential Output Ranges ...... 222 Form A-8: Percentage Change in Personal Residential Output Ranges by County ...... 225 Form A-9: Probable Maximum Loss for Florida ...... 229
STATISTICAL STANDARDS ...... 236
S-1 Modeled Results and Goodness-of-Fit...... 236 S-2 Sensitivity Analysis for Model Output ...... 241 S-3 Uncertainty Analysis for Model Output ...... 243 S-4 County Level Aggregation ...... 245 S-5 Replication of Known Hurricane Losses ...... 246 S-6 Comparison of Projected Hurricane Loss Costs ...... 247 Form S-1: Probability and Frequency of Florida Landfalling Hurricanes per Year...... 249 Form S-2: Examples of Loss Exceedance Estimates ...... 250 Form S-3: Distributions of Stochastic Hurricane Parameters ...... 252 Form S-4: Validation Comparisons ...... 253 Form S-5: Average Annual Zero Deductible Statewide Loss Costs – Historical versus Modeled . 259 Form S-6: Hypothetical Events for Sensitivity and Uncertainty Analysis ...... 262
COMPUTER STANDARDS ...... 268
C-1 Documentation ...... 268 C-2 Requirements ...... 269 C-3 Model Architecture and Component Design ...... 270 C-4 Implementation ...... 271 C-5 Verification ...... 273 C-6 Model Maintenance and Revision ...... 275 C-7 Security ...... 277 Appendix 1 - Credentials of Selected Personnel ...... 278 Appendix 2 - Independent Review ...... 281
TABLES
Table 1. Key classes of the USWIND wind speed and damage calculation ...... 20 Table 2. Example damage to loss simulation ...... 120 Table 3. Comparison of point location observations with model-generated winds ...... 237
8 The Florida Commission on Hurricane Loss Projection Methodology
FIGURES
Figure 1. Flowchart – USWIND Probabilistic Analysis ...... 18 Figure 2. Flowchart – USWIND Hazard and Damage Calculation Procedure ...... 19 Figure 3. Flowchart - Object Deployment for USWIND Hazard and Damage Calculations ...... 21 Figure 4. Impact on average annual zero deductible loss costs - Frequency update ...... 26 Figure 5. Impact on average annual zero deductible loss costs - Local friction / transition update 27 Figure 6. Impact on average annual zero deductible loss costs - All updates ...... 28 Figure 7. Business Workflow Diagram ...... 34 Figure 8. Wind Profile for Average Florida Hurricane...... 60 Figure 9. Wind field for Hurricane Wilma (2005)...... 62 Figure 10. Hurricane Opal (1995) ...... 65 Figure 11. Hurricane Frances (2004) ...... 65 Figure 12. State of Florida and Neighboring States by Region ...... 70 Figure 13. Hurricane Frequencies by Category by Region ...... 71 Figure 14. Contour Map - Maximum Winds For Modeled Version Of Base Hurricane Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star...... 73 Figure 15. Contour Map - Maximum Winds For 100-Year Return Period From Stochastic Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star...... 74 Figure 16. Contour Map - Maximum Winds For 250-Year Return Period From Stochastic Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star...... 75 Figure 17. Rmax vs. Central Pressure – Box plot ...... 77 Figure 18. Rmax and Central Pressure – Histograms. Histogram for Rmax is presented in panel (a); histogram for Central Pressure is presented in panel (b)...... 78 Figure 19. Flowchart – Vulnerability Development ...... 83 Figure 20. Plot of Form V-1 Part A data...... 92 Figure 21. Loss Cost Relationships by Coverage ...... 113 Figure 22. Loss Costs for Coastal Counties...... 115 Figure 23. Integration of Uncertainty on Hazard and Damage ...... 117 Figure 24. Integration of Damage Distribution to Calculate Loss ...... 118 Figure 25. Relationship Between Building and Contents Losses ...... 123 Figure 26. Ground-up Loss Costs for Frame Structures ...... 133 Figure 27. Ground-up Loss Costs for Masonry Structures ...... 134 Figure 28. Ground-up Loss Costs for Mobile Home Structures ...... 135 Figure 29. Hurricane Andrew % of Loss for FHCF2007 Personal Residential by ZIP Code ...... 147 Figure 30. Hurricane Andrew % of Loss for FHCF2007 Commercial Residential by ZIP Code ...... 147 Figure 31. Hurricane Charley % of Loss for FHCF2007 Personal Residential by Zip Code ...... 171 Figure 32. Hurricane Frances % of Loss for FHCF2007 Personal Residential by Zip Code ...... 172 Figure 33. Hurricane Ivan % of Loss for FHCF2007 Personal Residential by Zip Code ...... 173 Figure 34. Hurricane Jeanne % of Loss for FHCF2007 Personal Residential by Zip Code ...... 174 Figure 35. 2004 Season % of Loss for FHCF2007 Personal Residential by Zip Code ...... 175 Figure 36. Hurricane Charley % of Loss for FHCF2007 Commercial Residential by Zip Code ...... 176 Figure 37. Hurricane Frances % of Loss for FHCF2007 Commercial Residential by Zip Code ...... 177 Figure 38. Hurricane Ivan % of Loss for FHCF2007 Commercial Residential by Zip Code ...... 178 Figure 39. Hurricane Jeanne % of Loss for FHCF2007 Commercial Residential by Zip Code ...... 179 Figure 40. 2004 Season % of Loss for FHCF2007 Commercial Residential by Zip Code ...... 180 Figure 41. State of Florida by North/Central/South Regions ...... 222 Figure 42. State of Florida by Coastal/Inland Counties ...... 223 Figure 43. Frame Owners - % changes by county ...... 225 Figure 44. Masonry Owners - % changes by county ...... 226 Figure 45. Mobile Homes - % changes by county ...... 226 9 The Florida Commission on Hurricane Loss Projection Methodology
Figure 46. Frame Renters - % changes by county ...... 227 Figure 47. Masonry Renters - % changes by county ...... 227 Figure 48. Frame Condos - % changes by county ...... 228 Figure 49. Masonry Condos - % changes by county ...... 228 Figure 50. Current Submission Return Periods vs. Prior Year’s Submission Return Periods ...... 233 Figure 51. Uncertainty Analysis for Frequency ...... 238 Figure 52. Goodness-of-fit for Translational Speed ...... 239 Figure 53. Goodness-of-fit for Hurricane Frequency in Florida ...... 240 Figure 54. Historical vs. Modeled Losses for Companies A to F ...... 254 Figure 55. Historical vs. Modeled Losses by LOB for Company C ...... 255 Figure 56. Historical vs. Modeled Losses by County for Company D ...... 256 Figure 57. Historical vs. Modeled Losses by LOB for Company E ...... 257 Figure 58. Historical vs. Modeled Losses – Commercial Residential ...... 258 Figure 59. Cumulative Distributions of Loss Costs ...... 262 Figure 60. Contour Plot of Loss Cost for a Category 1 Hurricane ...... 263 Figure 61. Contour Plot of Loss Cost for a Category 3 Hurricane ...... 264 Figure 62. Contour Plot of Loss Cost for a Category 5 Hurricane ...... 264 Figure 63. SRCs for Expected Loss Cost for all Input Variables for all Hurricane Categories ...... 266 Figure 64. EPRs for Expected Loss Cost for all Input Variables for all Hurricane Categories ...... 267
10 The Florida Commission on Hurricane Loss Projection Methodology General Standards
GENERAL STANDARDS
G-1 Scope of the Computer Model and Its Implementation
The computer model shall project loss costs and probable maximum loss levels for residential property insured damage from hurricane events.
USWIND projects loss costs for residential property from hurricane events. For purposes of the Commission’s review and determination of acceptability, the loss costs and probable maximum loss levels submitted for this review are expected losses resulting from hurricanes. Wind losses resulting from a hurricane are included even if wind speeds fall below hurricane force. The vulnerability functions are based to a large degree on hurricane claims data, which includes wind speeds above and below the hurricane threshold of 74 mph. Expected loss costs include primary structure, appurtenant structures, contents, other covered personal property, and additional living expenses.
Disclosures
1. Specify the model and program version number.
EQECAT Florida Hurricane Model 2011a. The version number is designated by the year of completion. If subsequent model revisions occur, the version numbers would have a letter appended after the year (2011a, 2011b, etc.)
2. Provide a comprehensive summary of the model. This summary shall include a technical description of the model including each major component of the model used to produce residential loss costs and probable maximum loss levels in the State of Florida. Describe the theoretical basis of the model and include a description of the methodology, particularly the wind components, the damage components, and the insured loss components used in the model. The description shall be complete and shall not reference unpublished work.
General description of WORLDCATenterprise / USWIND
WORLDCATenterprise is EQECAT’s global catastrophe management software, covering over 90 countries and the perils of hurricane / typhoon / cyclone (in Florida and elsewhere), windstorm, winterstorm, tornado, hail, wildfire, earthquake (ground shaking, fire following, sprinkler leakage, workers comp), and flood.
The WORLDCATenterprise platform is a networked, multi-user, client server architecture enabling enterprise-wide analysis using centralized and sharable databases. WORLDCATenterprise uses a cost efficient industry standard
11 The Florida Commission on Hurricane Loss Projection Methodology General Standards
computer infrastructure that can easily expand to meet growing user demand. WORLDCATenterprise uses standard PCs for end user ‘clients’ running ordinary internet browsers. All users are networked to standard Windows based servers which can be configured in scalable clusters to provide higher performance and capacity.
WORLDCATenterprise enables insurer and reinsurer analysis of multiple perils for over 90 countries. A single product platform and user interface provides primary, facultative, treaty underwriting and accumulation management capability across all lines of business with aggregation up to the corporate level. WORLDCATenterprise also provides underwriters with important information about risk volatility and the impact of writing a new program on available capacity to enable real-time portfolio optimization.
One of the components of WORLDCATenterprise, and also available as standalone software, is USWIND, a probabilistic model designed to estimate damage and insured losses due to the occurrence of hurricanes along the 3100 miles of US coastline from Texas to Maine. USWIND estimates the full probabilistic distribution of damage and loss for any scenario storm event. USWIND also calculates Average Annual Damage and Loss estimates, as well as annual probability exceedances using a database of 47,315 stochastic storm simulation results to develop average annual loss rates for each property site. Scenario and average annual damage and losses can be calculated for individual property sites or for entire portfolios of residential and commercial properties.
Scenario storms, derived from HURDAT, are used to estimate expected and probable maximum damage and loss due to a single event. USWIND models damage and loss due to scenario storms in several ways. Any of the over 100 years of historical storms contained in the storm database can be selected by users to calculate damage and loss. In addition, the USWIND Landfall Series enables users to select scenario storms by stating either the return period or the SSI intensity level desired and choosing from any or all of 3,100 individual landfalls from Texas to Maine. This enables users to define from 16 different storm types at each of 3,100 landfalls (or 49,600 different scenario events). A third scenario storm option enables users to define a virtually unlimited variety of user defined storm events. User-defined Storms can be created by modifying historical tracks or drawing entirely new tracks and then specifying the storm parameter values to be utilized. User-defined storms are often used to model incoming storms at a variety of potential landfall locations.
Probabilistic Annual Damage & Loss is computed using the results of 47,315 stochastic storm simulation results. Annual damage and loss estimates are developed for each individual site and aggregated, if desired, to overall portfolio damage and loss amounts. USWIND’s climatological models are based on NOAA (National Oceanic & Atmospheric Administration)/NWS
12 The Florida Commission on Hurricane Loss Projection Methodology General Standards
(National Weather Service) Technical Reports. Climatological probability distributions (i.e., for storm parameters) were developed using an Adaptive Kernel Smoothing technique applied to the historical hurricane record published by NOAA.
Overall Model Methodology
USWIND modeling methodology can be segmented into four components: 1) the Hazard definition, 2) Propagation of the hazard to a site, 3) Damage estimate, and 4) Loss estimation.
1. Hazard Definition
The storm database used by USWIND is a combination of historical and stochastic storms. Wind speed probabilistic distributions are calculated using the probabilistic distributions of all important storm parameters. The storm intensity is driven directly from the coastline-dependent smoothed wind speed distributions generated from the information in the National Hurricane Center HURDAT. The distributions for radius of maximum winds and translational speed are derived from NOAA Technical Report NWS 38 [Ho et al. 1987], and the National Hurricane Center’s Tropical Cyclone Reports and Advisories. A proprietary wind speed equation based upon the NOAA model as published in NWS 23 [Schwerdt, Ho, and Watkins 1979] and NWS 38 [Ho et al. 1987], modified and generalized to properly simulate wind speeds for all SSI categories of storms, computes a central pressure, which is used to apply inland decay [Vickery and Twisdale 1995] and as an input to the determination of the radius of maximum winds for severe storms. The equation then computes wind speeds using the storm’s maximum sustained windspeed, the filling rate, radius to maximum winds, the storm track, translation speed, the gust factor [Krayer and Marshall 1992], the storm profile (attenuation of wind speed outward from the center), and the friction caused by local terrain and man-made structures.
2. Propagation of the Hazard to the Site
USWIND utilizes an embedded commercial GIS (Geographic Information System), MapInfo, to compute the latitude and longitude of each site analyzed. The street address level, where such data is available, is used to geocode to the lat./long. coordinates. Failing the presence of a street address, the geocoding can be done at a ZIP Code, City, or County centroid basis. Wind speed distributions at the site locations are computed taking local friction into account.
3. Estimation of Damage
USWIND provides the facility to define each of the property assets being analyzed in order to compute resulting damage. Damage can be calculated 13 The Florida Commission on Hurricane Loss Projection Methodology General Standards
for Structure, Contents, Time Element (such as Additional Living Expense (ALE) or Business Interruption (BI)), and up to three additional user defined coverage types. Site information includes the latitude and longitude of the locations, the structure types (96 types), structure details such as number of stories, insured value, cladding type and a class of occupancy type (12 types). Vulnerability functions may be modified by the incorporation of secondary structural components such as roof type, roof strength, roof-wall strength, wall-floor strength, wall-foundation strength, opening protection, and wind-door-skylight strength. Damage is estimated using vulnerability functions associated with the structure definition and occupancy type and the distribution of peak gust wind speeds at each site. The vulnerability functions used by USWIND have been derived through three methods: empirical data, expert opinion, and engineering analysis [Fujita 1992, McDonald-Mehta Engineers 1993, Simiu and Scanlan 1996].
The probabilistic distribution of damage (for each coverage and site) is derived through the integration of the probabilistic distribution of wind speeds for the site with the probabilistic distributions of damage for given wind speeds. Damage distributions for each of the sites are aggregated into an overall portfolio distribution of damage.
Since there can be a high degree of damage correlation for similar structure types within a geographic area, USWIND properly takes into account site and coverage level correlations when aggregating individual site damage into an overall portfolio damage amount.
4. Estimation of Loss
Insurance information in the form of insured values, limits, deductibles and facultative and/or treaty reinsurance are then integrated with the probabilistic distribution of computed damage for each site to determine the probabilistic distribution of “insured loss” amount. Correlation is properly taken into account when aggregating individual site loss into an overall portfolio loss amount.
Reports
USWIND produces a vast array of management information, more than 200 reports in all. Report categories include:
Underwriting. TIV and premium can be mapped by geographical segmentation (state, county or ZIP Code) or reported by corporate segmentation (company, division, branch, line of business, policy type, producer, account, policy or site). Profiles of the deductibles and limits in the portfolio can also be displayed.
14 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Scenario Storms. Damage (ground-up effects), gross loss (including deductibles and limits), net loss (including facultative reinsurance) can be reported at all of the levels noted in the underwriting reports. Mean values and an upper bound corresponding to a prescribed non-exceedance level are provided.
Probabilistic. In a manner similar to Scenario Storms, the damage, gross loss, and net loss can be reported, including non-exceedances. Additional reports displaying portfolio damage and loss for different non-exceedance levels, for either annual aggregate or per occurrence analysis methods, are available.
Reinsurance. Scenario and probabilistic results are displayed by reinsurer (including facultative reinsurance) or by treaty. Probabilistic results include the probability of penetrating and exceeding treaty layers.
Landfall Series. An abbreviated set of reports is available from running a series of storms against the portfolio. The series of storms can be either of uniform intensity (as denoted by the SSI scale) or uniform recurrence levels. The storm series can have landfalls at 1, 10 or 35 mile intervals.
Probability Distributions
In many instances, probability distributions have been developed from historical data, e.g., storm parameters such as radius to maximum winds, forward speed, etc.; and vulnerability functions. Goodness-of-fit tests have been used to compare modeled distributions of various parameters with the underlying historical data.
Sensitivity and Uncertainty Analyses
Many sensitivity and uncertainty analyses have been performed in the development of USWIND. For example, sensitivity analyses have been performed on track spacing; on the number of attack angles given landfall; on the number of wind speed class intervals given landfall and attack angle; and on the number of other storm parameter samples used in the stochastic hurricane database. A number of uncertainty analyses have been performed as well, including studies on the impact of vulnerability uncertainty on the loss exceedance curve.
Software/Hardware
WORLDCATenterprise
The requirements for the WORLDCATenterprise™ (WCe) hardware configuration consist of a Master Server and one or more Analysis Servers.
15 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Applications running on the Master Server include the Master database, the Web Server, and the Java Server. EQECAT processes, including the importing of portfolio data and some analyses also run on the Master Server.
Master database: Contains WCe System tables, customer portfolio data, and final analysis results.
Web Server: Handles communications between the remote Client PCs and communicates with the Java Server.
Java Server: Manages the activities performed on the Master and Analysis Server(s) and the Master and Results Databases.
The Analysis Server houses the Results Database, containing the intermediate results tables, and runs most of the analysis calculations. WCe users access the Master Server via Internet Explorer web browsers commonly installed on the Client PCs. The Client PC may access the system via the LAN or via a WAN/Internet.
Minimum Client Requirements:
• Operating System: Windows XP or Vista. • Processor: 2.4 GHz or higher. • RAM: 1 GB minimum (2 GB is recommended). • Microsoft Office 2000 or later (Office is only required if using the spreadsheet import option in WCe). • Browser: Microsoft Internet Explorer Version 5.5 or later. • Monitor: Screen resolution of 1280 by 800 or greater; screen color depth of 256 colors or greater.
Minimum Server Hardware Requirements: (Master Server and Analysis Server(s))
• Operating System: Windows 2003 Server (SP2), 32 bit or 64 bit OS. • Processors: 1-Quad Core CPU, 2.66 GHz or higher. • RAM: 12 GB. • Hard Drives: Capacity to house eight 146 Gigabyte drives. • NTFS File System. • DVD. • NIC: 1.0 Gigabit.
USWIND
• Operating System: Windows XP or Vista. • Processor: 2.4 GHz or higher (Core 2 Duo recommended). • RAM: 2 GB minimum (3 GB is recommended). 16 The Florida Commission on Hurricane Loss Projection Methodology General Standards
• Hard Drive: 100 GB. • NTFS File System. • DVD. • Monitor: Screen resolution of 1280 by 800 or greater; screen color depth of 256 colors or greater.
The model structure is translated to the program structure using Object Oriented Design and Analysis methodology. Physical and abstract entities in the model structure are mapped to objects of the program structure. The interactions between objects are captured using Flowcharts and Event diagrams. Object oriented practices (data encapsulation, abstraction, inheritance and polymorphism) are extensively used to derive the benefits of Object Oriented approach.
USWIND’s climatological models are based on NOAA/NWS Technical Reports [Schwerdt, et. al.; Ho, et. al.]. Climatological probability distributions (i.e., for storm parameters) were developed using Adaptive Kernel Smoothing [Scott] applied to the historical hurricane record published by NOAA [Jarvinen, et. al.; Cry]. The maximum wind speed and overwater wind field modeling was developed from NOAA/NWS equations [Schwerdt, et. al.], with some empirical adjustment in order to generalize the equations for lower intensity storms. The model uses current scientifically accepted boundary layer methods to convert a marine surface (10-meter 1-minute) windfield to one which incorporates local land friction when over land. The friction factors were developed by weighting and averaging surface roughness within 20 km of a location and within a given directional sector. Vulnerability relationships were developed from several sources, including observed damage relationships in historical storms [Friedman 1972, 1984; numerous Travelers Insurance Company internal memoranda] and engineering studies [McDonald-Mehta]. The simulation methodology combines several standard techniques including physical modeling [Friedman 1975], Monte Carlo simulation [Metropolis and Ulam] and Variance Reduction Techniques [Kahn; Rubinstein]. The evaluation of loss costs and other risk measures is based on standard actuarial theory [Beard, et. al.].
3. Provide a flow diagram that illustrates interactions among major model components.
USWIND is a complex system made up of many components, databases, and data files. The flowcharts, class diagrams, and tables on the following pages summarize the key aspects of the system. These aspects include the representation of physical entities of the hurricane catastrophe domain (e.g. storm, site, portfolio, etc.) as classes and objects within the program (Figure 1); the procedural flow of information and steps within the program (Figure 2); and the exchange of information among various components of the system
17 The Florida Commission on Hurricane Loss Projection Methodology General Standards
(e.g. portfolio tables, storm database, results tables, etc.) (Table 1 and Figure 3).
Figure 1. Flowchart – USWIND Probabilistic Analysis 18 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Begin
Read Site's Information Portfolio from Database Tables
Compute Hazard at the Site
Compute Damage to the Site due to calculated hazard
Output hazard and Results Damage Results Tables
End of Portfolio ? No
Yes
End
Figure 2. Flowchart – USWIND Hazard and Damage Calculation Procedure
19 The Florida Commission on Hurricane Loss Projection Methodology General Standards
TABLE 1. KEY CLASSES OF THE USWIND WIND SPEED AND DAMAGE CALCULATION
No. of Class Owner(s) Responsibilities Instances • Principal object that serves as starting point. • Connects to Database. • Opens Input and Output tables. • Performs static initializations (like Cportfolio Once Main() loading binary files into memory) • Creates CSite objects (one at time) • Creates the Peril objects (CStormPeril) • Analyzes the portfolio using the Peril objects • Holds site specific information • Calculates information necessary for Csite Multiple CPortfolio performing hazard and damage computations. • Represents the Peril • Loads storm information from CstormPeril Multiple CPortfolio Database and prepares the storm • Uses CSiteWindHazard object to perform hazard calculations • Holds the storm information read from Database. Cstorm Multiple CStormPeril • Calculates storm parameters necessary for subsequent computations. • Calculates hazard from a given Storm CsiteWindHa to a given Site. Once CStormPeril zard • Uses CStormPeril, CStorm, CSite objects to perform hazard calculations • Calculates damage to a site from a given hazard. CSiteWindH • Uses CSite, CSiteWindHazard and CsiteWindDa Once azard, other objects (e.g. CCoverage for mage CStormPeril coverage information, CDamage for damage curves, CResult for storing results information etc.)
20 The Florida Commission on Hurricane Loss Projection Methodology General Standards
1. Create a CSite object with information read about the site from Portfolio CPortfolio Tables object CSite Object
(sitepar.cpp)
s s s
e e
es e
s s
2. Ask CStormPeril objects us s
u u to analyze this site u
Creates CSiteWindHazard object to perform Hazard Calculations
CStormPeril es CSiteWindHazard s Object u object (storm.cpp) (sitewind.cpp)
es us
Creates a CSiteWindDamage object CSiteWindDamage to perform Damage object Calculations (sitewdmg.cpp)
Object Deployment for Hazard and Damage Calculations
Figure 3. Flowchart - Object Deployment for USWIND Hazard and Damage Calculations
4. Provide a comprehensive list of complete references pertinent to the submission by Standard grouping, according to professional citation standards.
List of References: Meteorology Standards Cry, G. W. (1965). Tropical Cyclones of the North Atlantic Ocean, Technical Paper No. 55, U.S. Department of Commerce, Weather Bureau, Washington, DC.
21 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Franklin, J.L., M.L. Black, and K. Valde (2003). “GPS dropwindsonde wind profiles in hurricanes and their operational implications”, Weather and Forecasting, Vol. 18, No. 1, pp. 32-44. Ho, F. P., Su, J. C., Hanevich, K. L., Smith, R. J., and Richards, F. P. (1987). Hurricane Climatology for the Atlantic and Gulf Coasts of the United States, NOAA Technical Report NWS 38, U.S. Department of Commerce, National Oceanographic and Atmospheric Administration, National Weather Service, Washington, DC. Homer, C. C. Huang, L. Yang, B. Wylie and M. Coan (2004). “Development of a 2001 National Landcover Database for the United States”. Photogrammetric Engineering and Remote Sensing, Vol. 70, No. 7, July 2004, pp. 829-840 Houston, S.H., and M.D. Powell (2003). “Surface wind fields for Florida Bay Hurricanes”, Journal of Coastal Research, Vol. 19, pp. 503-513. Jarvinen, B. R., Neumann, C. J., and Davis, M. A. S. (1984). A Tropical Cyclone Data Tape for the North Atlantic Basin, Technical Memorandum NWS NHC 22, National Oceanic and Atmospheric Administration and National Weather Service, Washington, DC. Krayer, W.R., and Marshall, R.D. (1992). “Gust factors applied to hurricane winds,” Bulletin of the American Meteorological Society, Vol. 73, No. 5, pp. 613-617. Kwon, I.H., and Cheong, H.B. (2010). "Tropical Cyclone Initialization with a Spherical High-Order Filter and an Idealized Three-Dimensional Bogus Vortex," Monthly Weather Review, Vol. 138, No. 4, pp. 1344-1367. Landsea, C. W. et al (2004). “A Reanalysis of Hurricane Andrew’s Intensity,” Bulletin of the American Meteorological Society, Vol. 85, No. 11, pp. 1699- 1712. Powell, M.D., D. Bowman, D. Gilhousen, S. Murillo, N. Carrasco, and R. St. Fluer (2004). “Tropical Cyclone Winds at Landfall”, Bulletin of the American Meteorological Society, Vol. 85, No. 6, pp. 845-851. Schwerdt, R. W., Ho, F. P., and Watkins, R. R. (1979). Meteorological Criteria for Standard Project Hurricane and Maximum Probable Hurricane Wind Fields, Gulf and East Coasts of the United States, NOAA Technical Report NWS 23, U.S. Department of Commerce, National Oceanographic and Atmospheric Administration, National Weather Service, Washington, DC. Simiu, E., Vickery, P., and Kareem, A. (2007), “Relation between Saffir- Simpson Hurricane Scale Wind Speeds and Peak 3-s Gust Speeds over Open Terrain,” Journal of Structural Engineering, Vol. 133, No. 7, 1043- 1045.
22 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Vickery, P.J. and Twisdale, L.A. (1995). “Wind-Field and Filling Models for Hurricane Wind-Speed Predictions,” Journal of Structural Engineering, Vol. 121, No. 11, pp. 1700-1709. Vihma, T. and Savijarvi, H. (1991) “On the Effective Roughness Length for Heterogeneous Terrain,” Quarterly Journal of Royal Meteorological Society, Vo. 117, pp. 399-407. Westerink, J.J., et al. (2008). “A Basin- to Channel-Scale Unstructured Grid Hurricane Storm Surge Model Applied to Southern Louisiana,” Monthly Weather Review, Vol. 136, No. 3, pp. 833-864. Vulnerability Standards Florida Building Code (2001). State of Florida, Tallahassee, Florida. Fujita, T. T. (1992). “Damage survey of Hurricane Andrew in south Florida,” Storm Data, Vol. 34, pp. 25–30. McDonald-Mehta Engineers (1993). Vulnerability Functions for Estimating Wind Damage to Buildings, for EQE Engineering and Design, Texas Tech University, Lubbock, TX. (Available on-site, only) Simiu, E. and Scanlan, R. H. (1996). Wind Effects on Structures, John Wiley and Sons, New York, NY. South Florida Building Code (1994). Metropolitan Dade County, Miami, Florida. Secondary Structural Modifiers: Features and Model Description, ABS Consulting/EQECAT Report, Rev. 1, 2008. Actuarial Standards Friedman, D. G. (1972). "Insurance and the natural hazards," 9th ASTIN Colloquium, International Congress of Actuaries, Randers, Denmark, International Journal for Actuarial Studies in Non-Life Insurance and Risk Theory, Amsterdam, The Netherlands, Vol. VII, Part 1, pp. 4-58. Friedman, D. G. (1984). "Natural hazard risk assessment for an insurance program," The Geneva Papers on Risk and Insurance, Vol. 9, pp. 57-128. Statistical Standards Beard, R. E., Pentikäinen, T., and Pesonen, E. (1984). Risk Theory: The Stochastic Basis of Insurance, London: Chapman and Hall. Chaudhuri, P. and Marron, J.S. (1999). “SiZer for Exploration of Structures in Curves”, Journal of the American Statistical Association, Vol. 94, pp. 807- 823 Kahn, H. (1950). “Modifications of the Monte Carlo method,” in Proceedings, Seminar on Scientific Computations, November 16-18, 1949, Hurd, C. C., ed., pp. 20-27, International Business Machines, New York, NY.
23 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Metropolis, N., and Ulam, S. (1949). “The Monte Carlo method,” Journal of the American Statistical Association, Volume 44, page 335. Rubinstein, R. Y. (1981). Simulation and the Monte Carlo Method, John Wiley and Sons, New York, NY. Scott, D. W. (1992). Multivariate Density Estimation: Theory, Practice, and Visualization, John Wiley and Sons, New York, NY.
Computer Standards Friedman, D. G. (1975). Computer Simulation in Natural Hazard Assessment, Monograph NSF-RA-E-75-002. Institute of Behavioral Sciences, University of Colorado, Boulder, CO.
24 The Florida Commission on Hurricane Loss Projection Methodology General Standards
5. Provide the following information related to changes in the model from the previously accepted submission to the initial submission this year:
A. A summary description of the significant changes and a list of non-significant changes,
The following significant changes were made to the model between the previously accepted submission (EQECAT Florida Hurricane Model 2009) and the current submission (EQECAT Florida Hurricane Model 2011a):
1. The probabilistic hurricane database was regenerated to be consistent with the National Hurricane Center’s HURDAT data set as of June 7, 2009, and to additionally include the 2009 hurricane season.
2. The model was updated to use current scientifically accepted boundary layer methods and inflow angle to incorporate local friction and transitions between local land use / land cover categories, including sea-to-land transition.
The following non-significant change was made to the model between the previously accepted submission (EQECAT Florida Hurricane Model 2009) and the current submission (EQECAT Florida Hurricane Model 2011a):
3. The ZIP Code database has been updated to December 2009.
4. Land use and land cover data from the Florida Water Management District 2004-2008 was used to resolve the following land use categories: communication, utility, and transportation.
5. The incorporation of default structure types for North Florida and South Florida.
B. Percentage difference in average annual zero deductible statewide loss costs for:
1. All changes combined,
The average annual zero deductible statewide loss cost has decreased by 6.6% as a result of all changes combined.
2. Each significant model component change, and
The average annual zero deductible statewide loss cost has increased by 8.3% as a result of the probabilistic hurricane database update, and has decreased by 25 The Florida Commission on Hurricane Loss Projection Methodology General Standards
14.6% as a result of the updated incorporation of local friction and transitions between local land use / land cover categories. (The average annual zero deductible statewide loss cost has decreased by 0.3% as a result of the ZIP Code database update.)
C. Color-coded maps by county reflecting the percentage difference in average annual zero deductible statewide loss costs for each significant model component change.
. Figure 4. Impact on average annual zero deductible loss costs - Frequency update
26 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Figure 5. Impact on average annual zero deductible loss costs - Local friction / transition update
27 The Florida Commission on Hurricane Loss Projection Methodology General Standards
Figure 6. Impact on average annual zero deductible loss costs - All updates
28 The Florida Commission on Hurricane Loss Projection Methodology General Standards
G-2 Qualifications of Modeling Organization Personnel and Consultants
A. 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.
The model construction, testing, and evaluation was performed by a team of individuals who possess the necessary skills, formal education, and experience to develop hurricane loss projection methodologies, and who abide by the standards of professional conduct adopted by their profession. B. The model or any modifications to an accepted model shall be reviewed by either modeling organization personnel or consultants in the following professional disciplines: structural/wind engineering (licensed Professional Engineer), statistics (advanced degree), actuarial science (Associate or Fellow of Casualty Actuarial Society), meteorology (advanced degree), and computer/information science (advanced degree). These individuals shall be signatories on Forms G-1 through G-6 as applicable and shall abide by the standards of professional conduct if adopted by their profession.
The model and all modifications to it have been reviewed by modeler personnel or consultants in the following professional disciplines, if relevant: structural/wind engineering (licensed Professional Engineer), statistics (advanced degree), actuarial science (Associate or Fellow of Casualty Actuarial Society), meteorology (advanced degree), and computer/information science (advanced degree). These individuals are signatories on Forms G-1 through G-6 as applicable and abide by the standards of professional conduct if adopted by their profession.
Disclosures
1. Organization Background
A. Describe the ownership structure of the modeling organization. Describe affiliations with other companies and the nature of the relationship, if any. Indicate if your organization has changed its name and explain the circumstances.
EQECAT, Inc. is a wholly owned subsidiary of ABS Group, Inc.
B. If the model is developed by an entity other than a modeling company, describe its organizational structure and indicate how proprietary rights and control over the model and its critical components is exercised. If more than one entity is involved in the development of the model, describe all involved. 29 The Florida Commission on Hurricane Loss Projection Methodology General Standards
USWIND is developed by EQECAT, Inc., a modeling company.
C. If the model is developed by an entity other than a modeling company, describe the funding source for the model.
USWIND is developed by EQECAT, Inc., a modeling company.
D. Describe the modeling organization’s services.
EQECAT, Inc. provides a complete range of catastrophe management services: portfolio analysis; consulting on product pricing, structure, and underwriting guidelines; training for underwriters and loss control staff on critical structural details; securitization; information on scientific developments and hazard investigations from its own research and via links to key sites on the World Wide Web from the EQECAT home page; engineering evaluations of major individual risks; assistance with large claims settlements; and hazard modeling software.
E. Indicate if the modeling organization has ever been involved directly in litigation or challenged by a statutory authority where the credibility of one of its U. S. hurricane model versions for projection of loss costs or probable maximum loss levels was disputed. Describe the nature of the case and the conclusion.
EQECAT has engaged in a review of the model with the Hawaii Insurance Division, which is a requirement for all hurricane loss models to be used in residential rate filings in Hawaii.
In February 2009, EQECAT sent a submission of Hawaii Insurance Division Memorandum 2007-2R. This submission is expected to resolve the follow-up questions the Division had with respect to EQECAT’s prior filing of Memorandum 2003-3R. The follow-up questions from the Hawaii Insurance Division were of clarification nature and have no bearing on any aspect of the model applicable to Florida.
30 The Florida Commission on Hurricane Loss Projection Methodology General Standards
2. Professional Credentials
A. Provide in a chart 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 involved in acceptability process or in any of the following aspects of the model:
1. Meteorology 2. Vulnerability 3. Actuarial Science 4. Statistics 5. Computer Science
The tables below summarize the credentials for the individuals involved in the development and maintenance of USWIND. More detailed credentials for selected personnel are provided in Appendix 1.
1. Meteorology
Employee Name Highest Degree Relevant Experience Since Ph.D. Meteorology Annes Meteorology, hurricane Cochin University of 2009 Haseemkunju analysis Science and Technology Ph.D. Meteorology Meteorology, hurricane Justin Brolley 2007 Florida State University analysis Mahmoud Ph.D. Structural Engineering Model design, probabilistic 1988 Khater Cornell University analysis M.S. Meteorology Fan Lei 2007 Meteorology University of Maryland Ph.D. Applied Mathematics / Zhiyuan Liu Meteorology, University of 2007 Meteorology Wisconsin - Milwaukee M.S. Meteorology John Mangano 2008 Meteorology Rutgers University M.S. Geophysics Meteorology, hurricane David Smith 1994 Yale University analysis Ph.D. Atmospheric Science Jingyun Wang 2007 Meteorology Boston University
31 The Florida Commission on Hurricane Loss Projection Methodology General Standards
2. Vulnerability
Employee Name Highest Degree Relevant Experience Since James R. (Bob) Ph.D. Civil Engineering Consultant Wind engineering Bailey Texas Tech University Ph.D. Civil Engineering Surya Gunturi 2007 Structural engineering Stanford University Ph.D. Civil Engineering Omar Khemici 1990 Structural engineering Stanford University Ph.D. Structural Engineering YoungSuk Kim 2007 Structural engineering University of Illinois Kamban Ph.D. Civil Engineering 2007 Structural engineering Parasuraman University of Saskatchewan
3. Actuarial Science
Employee Name Highest Degree Relevant Experience Since Paul Vendetti, B.A. Political Science Consultant Actuarial science FCAS, MAAA Amherst College
4. Statistics
Employee Name Highest Degree Relevant Experience Since Ph.D. Civil Engineering James Johnson Consultant Probabilistic analysis University of Illinois Ph.D. Civil Engineering Petros University of California, 1999 Probabilistic analysis Keshishian Berkeley Mahmoud Ph.D. Structural Engineering Model design, probabilistic 1988 Khater Cornell University analysis Kamban Ph.D. Civil Engineering 2007 Probabilistic analysis Parasuraman University of Saskatchewan M.S. Geophysics Model design, probabilistic David Smith 1994 Yale University analysis Ph.D. Statistics Statistics, probabilistic Kunshan Yin 2007 University of Texas, Dallas analysis
32 The Florida Commission on Hurricane Loss Projection Methodology General Standards
5. Computer Science
Employee Name Highest Degree Relevant Experience Since M.S. Electrical Engineering Branimir Betov Technical University of 1998 Software development Sofia, Bulgaria B.S. Electrical Engineering Phil Burtis 1996 Software development Iowa State University M.S. Structural Analysis and Design Software quality Kent David 1987 University of California, assurance Berkeley M.B.A. Aarti Dinesh University of Missouri, 2007 Product management St. Louis M.B.A. Ray Kincaid 1985 Software development Pepperdine University M. Eng. Structural Model design, software Engineering Tom Larsen 1989 development, software University of California, product management Berkeley B.S. Computer Engineering Jason Mok 2006 Software development San Jose State University B.S. Electrical Engineering Sergey Petrochemical and Gas 1995 Software development Pasternak Industry Institute, Moscow, Russia M.S. Geophysics Model design, software David Smith 1994 Yale University development B.S. Computer Science and Engineering Vinh Thach 2007 Software development University of California, Davis M.S. Software Development Alexander International Technological 2008 Software development Volkov University, Sunnyvale B.S. Computer Science Kerry California State University, 1997 Software development Zimmerman San Luis Obispo
B. Identify any new employees or consultants (since the previous submission) working on the model or the acceptability process.
Paul Vendetti, a senior consulting actuary with a private actuarial firm, provides advice in the area of actuarial science.
C. Provide visual business workflow documentation connecting all personnel related to model design, testing, execution, maintenance, and decision-making. 33 The Florida Commission on Hurricane Loss Projection Methodology General Standards
See Figure 7 below.
Product M anage m ent (T o m Larsen)
M ethodology Development (Mahm oud Khater, David Smith)
M o d e l D e v e lo p m e n t GUI Development (Mahm oud Khater, (Ray Kincaid, David Smith) Phil Burtis)
Docum entation/Publications Configuration Managem nt (Mahm oud Khater, (Ray Kincaid, David Smith, P h il B u rtis ) Ray Kincaid, P h il B u rtis )
Q uality Assurance Shipping (Kent David) (Ray Kincaid, P h il B u rtis )
Customer
Customer Service (Tom Larsen)
Figure 7. Business Workflow Diagram
D. Indicate specifically whether individuals listed in A. and B. are associated with the insurance industry, a consumer advocacy group, or a government entity as well as their involvement in consulting activities.
None of the individuals listed in A. and B. including the consultants Paul Vendetti (credentials above); Dr. James Johnson (credentials above and
34 The Florida Commission on Hurricane Loss Projection Methodology General Standards
in Appendix 1); and Dr. James R. (Bob) Bailey are associated with the insurance industry, a consumer advocacy group, or a government entity.
Paul Vendetti, a senior consulting actuary with a private actuarial firm, provides advice in the area of actuarial science.
Dr. James Johnson provides advice in the area of probabilistic analysis.
Dr. James R. (Bob) Bailey provides support in the area of mitigation measures within vulnerability.
3. Independent Peer Review
A. Provide dates of external independent peer reviews that have been performed on the following components as currently functioning in the model:
1. Meteorology 2. Vulnerability 3. Actuarial Science 4. Statistics 5. Computer Science
1. Meteorology
Professor Robert Tuleya performed a review of the hurricane windfield model in February 2011. His comments included the following: “I reviewed the EQECAT revised wind field model. The review was composed of several presentations by EQECAT, review of several scientific references as well as fruitful discussion between EQECAT and myself. This model is a parametric model, which estimates the evolution of the inland surface wind field given the values of several parameters describing the low-level wind field just off shore. The model uses as observed input the storm intensity, radial extent of winds and the storm track. It also assumes a standard filling rate as the storm progresses inland. The EQECAT model uses a sophisticated high resolution land use field to diagnose the effect of upwind roughness effects accurately. The terrain roughness was shown to have a dual role of reducing the damaging wind field due to frictional retardation but also to a lesser extent increasing the possible wind effects by contributing to a larger gust factor with increasing roughness. The presentation indicated realistic wind behavior for an incoming storm making landfall. The time evolution of the EQECAT model was quite similar to more sophisticated 3-D NWP operational and research models, lending credibility to their model product. EQECAT also showed comparisons and verification to observed surface wind field as well. The model has a deviational component to account for statistical variation in results. This estimate appears to be handled well, with the model for the most part, verifying well compared to observations. Overall, I believe the 35 The Florida Commission on Hurricane Loss Projection Methodology General Standards
EQECAT revised model should model observed landfall wind evolution quite well for both individual storms as well as for estimating a climatological group of storms.”
2. Vulnerability
Dr. Kishor Mehta, Dr. James McDonald, and Dr. C. Allin Cornell performed independent reviews of the vulnerability model in 1995.
3. Actuarial Science
Discussed in conjunction with Statistics below.
4. Statistics
Dr. C. Allin Cornell and Dr. Richard Mensing reviewed the overall methodology and technical approach in 1995. Their comments were as follows: Cornell - suggested we make the procedure more transparent in order to facilitate communication and learning by the users - “simple, brute force Monte Carlo simulation is about as straight-forward as you can be... but you are doing something smarter and hence more difficult to grasp.” Further suggestions were for a thorough sensitivity study and ideas for the treatment of uncertainty. Mensing - “Overall, I believe the methodology represents a very good approach to a probabilistic analysis of the damages and losses associated with hurricanes.” His suggestions were to review the treatment of uncertainty and verify the adequacy of the portfolio input data. Additional studies were done to address these issues prior to the release of USWIND.
Mr. Peter Kelly and Dr. Lixin Zeng of Arkwright Mutual Insurance Company reviewed all aspects of the USWIND model in their paper ‘The Engineering, Statistical, and Scientific Validity of EQECAT USWIND Modeling Software’ in 1996. They stated the following in their review:
“The validity of EQECAT USWIND modeling software is reviewed from several perspectives. Using several external sources for hurricane data, it is found that the storm data set represents the historical and expected long term storm patterns well and generally without bias. By reviewing storm damage estimates against a theoretical understanding of the wind effects on structures as well as actual experience, it was found that the model’s damage estimates reasonably reflect the physical properties of force and damage and that the system has no systematic bias in its damage estimation logic.”
A copy of their review is provided in Appendix 2.
36 The Florida Commission on Hurricane Loss Projection Methodology General Standards
5. Computer Science
Daryl Orts and Chuck Walrad performed independent reviews of the computer science aspects of the model in 1998.
B. Provide documentation of independent peer reviews directly relevant to the modeling organization’s responses to the current Standards, Disclosures, or Forms. Identify any unresolved or outstanding issues as a result of these reviews.
Refer to the Appendix for documentation. There are no unresolved or outstanding issues resulting from the reviews.
C. Describe the nature of any on-going or functional relationship the organization has with any of the persons performing the independent peer reviews.
Dr. Cornell has also done a peer review on our USQUAKE model. Dr. Mensing was a full-time employee of EQECAT for several years and continues as a consultant to EQECAT, although he was an independent consultant at the time he performed the review described above. Drs. Cornell and Mensing and Professor Tuleya were compensated for their time by EQECAT.
4. Provide a completed Form G-1, General Standards Expert Certification.
5. Provide a completed Form G-2, Meteorological Standards Expert Certification.
6. Provide a completed Form G-3, Vulnerability Standards Expert Certification.
7. Provide a completed Form G-4, Actuarial Standards Expert Certification.
8. Provide a completed Form G-5, Statistical Standards Expert Certification.
9. Provide a completed Form G-6, Computer Standards Expert Certification.
See Forms G-1 to G-6 at the end of this section.
37 The Florida Commission on Hurricane Loss Projection Methodology General Standards
G-3 Risk Location
A. ZIP Codes used in the model shall not differ from the United States Postal Service publication date by more than 24 months at the date of submission of the model. ZIP Code information shall originate from the United States Postal Service.
The USWIND ZIP Code database was updated in October 2010, based on information originating from the United States Postal Service current as of December 2009.
B. ZIP Code centroids, when used in the model, shall be based on population data.
The ZIP Code centroids used in USWIND are derived using population.
C. ZIP Code information purchased by the modeling organization shall be verified by the modeling organization for accuracy and appropriateness.
EQECAT verifies each new ZIP Code database through a suite of procedures, including automated numeric tests and visual tests.
Disclosures
1. List the current ZIP Code databases used by the model and the components of the model to which they relate. Provide the effective (official United States Postal Service) date corresponding to the ZIP Code databases.
USWIND uses Dynamap 5-Digit ZIP Codes distributed by MapInfo / Pitney Bowes Business Insight. The source of the data is Tele Atlas Maps. Tele Atlas Maps created the data using a combination of its DYNAMAP/2000 data, the United States Postal Service (USPS) ZIP+4 Data File, the USPS National 5-Digit ZIP Code and Post Office Directory, USPS ZIP+4 State Directories, and the USPS City State File.
The ZIP Code data is used in the import component of the model.
The effective date of the ZIP Code data is December 2009.
2. Describe in detail how invalid ZIP Codes are handled.
Invalid ZIP Codes in input data are generated from many sources, including (a) typographical errors in the insurers’ data, (b) usage of mailing address instead of site address, or (c) usage of an out of date ZIP Code. The USWIND program attempts to locate any invalid sites to the most refined level 38 The Florida Commission on Hurricane Loss Projection Methodology General Standards possible, the data quality permitting. At the end of the ‘geocoding’ process, USWIND echoes the status of the quality of the data, indicating how many locations were mapped to the street address level, to ZIP Code centroids, city centroids, and to county centroids.
In addition, if users are uncertain of the quality of street address information, they can enter latitude and longitude coordinates.
The steps in the geocoding process are as follows:
1. If the street address is available, the program attempts to geocode the location to its exact location, to within approximately 400 feet in most urban areas.
2. If the program was unable to calculate the exact street location, the program looks at the site ZIP Code. If the input ZIP Code exactly matches a ZIP Code in our database, the geocoding stops.
3. If the exact ZIP Code was not matched, the program then looks through the database of ‘point’ ZIP Codes. Point ZIP Codes indicate Post Office boxes or private entities who desire their own ZIP Code. The location of these point ZIP Codes is provided by the US Government. For displaying maps of exposure and losses, these ZIP Codes are also ‘mapped’ to regional ZIP Codes which correspond to the ZIP Code area which the point ZIP Code is in.
4. If the location is still not found, the program next looks at the city name in the input data. If the city name was included in the input data, and the city name is in the USWIND databases, then the location is geocoded to a city centroid, and the geocoding summary is updated to indicate this.
5. If the location is still not found, the program next looks at the county name in the input data. If the county name was included in the input data, and the county name is in the USWIND databases, then the location is geocoded to a county centroid, and the geocoding summary is updated to indicate this.
6. If the data provided fails these steps then the risk is removed from the database.
39 The Florida Commission on Hurricane Loss Projection Methodology General Standards
G-4 Independence of Model Components
The meteorological, vulnerability, and actuarial components of the model shall each be theoretically sound without compensation for potential bias from the other two components.
The meteorology, vulnerability, and actuarial components of USWIND have been independently developed, verified, and validated. The meteorology component, completely independent of the other components, calculates wind speed at each site. The vulnerability component is entirely independent of all other calculations, e.g. meteorological, loss, etc. Validation of the vulnerability functions has been performed independently from other validation tests, e.g. whenever the vulnerability functions have been validated using claims data from a historical storm, the wind field for that storm has first been validated independently. If any of the other calculation modules were changed, no changes would be necessary to the vulnerability functions. The loss distributions are calculated using the damage distribution at each site and the policy structure. Finally, the site distributions (damage and loss) are combined statistically to estimate the expected annual loss and the loss exceedance curve for the portfolio. All components together have been validated and verified to produce reasonable and consistent results.
40 The Florida Commission on Hurricane Loss Projection Methodology General Standards
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 that the submission has been personally reviewed.
All documents provided to the Commission by EQECAT throughout the review process have been reviewed and edited by a person or persons with experience in reviewing technical documents. This has been certified on Form G-7
Disclosure
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.
Data in the paper (Word document) version is copied directly from the electronic versions of specific files. In order to ensure consistency, data from both the Word document and the electronic files are copied onto a Microsoft Excel document for comparison.
2. Describe the process used by the signatories on 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 EQECAT responses for each standard and form within the relevant set of standards, including data, maps, and exhibits provided, to ensure that the responses are consistent with the model being submitted and with any relevant EQECAT procedures.
3. Provide a completed Form G-7, Editorial Certification.
See Form G-7 at the end of this section.
41
The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Meteorological Standards
M-1 Base Hurricane Storm Set
A. Annual frequencies used in both model calibration and model validation shall be based upon the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009 (or later). Complete additional season increments based on updates to HURDAT approved by the Tropical Prediction Center/National Hurricane Center are acceptable modifications to these storm sets. Peer reviewed atmospheric science literature can be used to justify modifications to the Base Hurricane Storm Set.
The storm set used is the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009, with the 2009 hurricane season additionally included.
B. Any trends, weighting or partitioning shall be justified and consistent with currently accepted scientific literature and statistical techniques. Calibration and validation shall encompass the complete Base Hurricane Storm Set as well as any partitions.
No trending, weighting, or partitioning has been performed with respect to the Base Hurricane Storm Set.
Disclosures
1. Identify the Base Hurricane Storm Set, the release date, and the time period included to develop and implement landfall and by-passing storm frequencies into the model.
The storm set used is the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009, with the 2009 hurricane season additionally included.
2. If the modeling organization has made any modifications to the Base Hurricane Storm Set related to landfall frequency and characteristics, provide justification for such modifications.
EQECAT has not modified the Base Hurricane Storm Set.
3. Where the model incorporates short-term or long-term modification of the historical data leading to differences between modeled climatology and that in the entire Base Hurricane Storm Set, describe how this is incorporated.
49 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
The model considers only the long term view of hurricane frequencies, i.e. it makes no modification of the frequencies implied by the entire Base Hurricane Storm Set.
4. Provide a completed Form M-1, Annual Occurrence Rates.
See Form M-1 at the end of this section.
50 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
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, strike probabilities, tracks, spatial and time variant windfields, and conversion factors, shall be based on information documented in currently accepted scientific literature.
The modeling of hurricane parameters and characteristics is based on information documented by currently accepted scientific literature or on EQECAT analyses of meteorological data.
Disclosures
1. Identify the hurricane parameters (e.g., central pressure or radius of maximum winds) that are used in the model.
The following parameter descriptions all pertain specifically to the USWIND probabilistic analysis. Use of USWIND in a ‘user storm’ scenario mode may allow much greater flexibility in some parameters (i.e., landfall location, track direction, etc.) than the discrete, categorized values used in the probabilistic database.
Hurricane Parameters in the Model:
1. Landfall Location: Landfall segments 10 nautical miles in length run along the coastline from south of the Texas-Mexico border through Maine There are 310 discrete landfall segments used to develop the probabilistic hurricane data set. The Florida coast runs from landfall segment #84 (Escambia county, FL-Alabama border), through segment #180 (Nassau county, FL-Georgia border). That is, from coastal milepost 840 through 1800. The historical data used is the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009, with the 2009 hurricane season additionally included.
2. Track Direction: Distributions for storm direction vary geographically and are based on smoothed historical data. The historical data used is the portion of the National Hurricane Center HURDAT from 1900 through 2001 as of June 1, 2003. All hurricanes in HURDAT from 1900 through 2001 were used.
3. Maximum One-Minute Sustained Wind Speed: The maximum one-minute sustained wind speed is the main parameter used to define hurricane intensity, and is one of the most critical items when considering loss sensitivity. The possible range in landfall values is from 74 mph to 180 mph, although the model will run at lower values (weaker storms) to accommodate inland filling. The storm strength is driven directly from the 51 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
coastline-dependent smoothed wind speed distributions generated from the information in the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009, with the 2009 hurricane season additionally included. All hurricanes in this data set were used.
4. Radius of Maximum Winds: This is the distance from the geometric center of the storm to the region of highest winds, typically within the eye wall of a well-developed hurricane. This parameter, after landfall location and central pressure (storm strength), is the next most critical in terms of loss sensitivity. It can range from 4 to 69 miles, and is statistically dependent on coastline location and storm strength. The historical data used is information contained in NOAA Technical Report NWS 38, updated through the 2004 hurricane season with information from the National Hurricane Center's Tropical Cyclone Reports and Advisories. All hurricanes in HURDAT from 1900 through 2004 were used.
5. Translational Speed: This is the speed of the movement of the entire storm system itself. It is generally responsible for the asymmetry of a hurricane’s wind field. It also has an effect on the distance which the highest winds are carried inland as the time-dependent filling weakens the storm. This parameter can range from about 4 mph to 50 mph, though the high end of this range would only apply in the Northeastern / New England region. The parameter is statistically dependent on coastline location and storm strength, and in Florida, averages about 12-14 mph. The historical data used is information contained in NOAA Technical Report NWS 38, updated through the 2004 hurricane season with information from the National Hurricane Center's Tropical Cyclone Reports. All hurricanes in the Official Hurricane Set were used. All hurricanes in HURDAT from 1900 through 2004 were used.
6. Filling Rate (inland decay rate): Overland attenuation (filling) is described by exponential decay of the hurricane central pressure deficit (difference between the background pressure and the storm central pressure). The filling rate is the parameter specifying the rate of this exponential decay. The historical data used is the National Hurricane Center HURDAT starting at 1900 as of June 1, 2007.
7. Profile Factor: This is a dimensionless shape parameter that varies the drop-off of winds outward from the hurricane’s eye. Since an individual hurricane’s profile may differ from the average, this parameter allows the user to best fit an actual storm’s profile when modeling the specific event. In the probabilistic hurricane database, the profile factor is based on the profile factors of historical storms that have made landfall near the location of the probabilistic storm subject to a maximum that is dependent on the radius of maximum winds. The historical data used is the National Hurricane Center Marine Exposure from the Advisory Archives (1963- 1967,1992-2008) and surface windspeed observations.
52 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
8. Inflow Angle: This is the angle between purely circular (tangential) motion and the actual direction of air flowing in towards the center of the hurricane. Modeling of the Inflow Angle is based on Kwon and Cheong (2010).
9. The model also considers air density and the Coriolis parameter, among other variables.
2. Describe the dependencies among variables in the windfield component and how they are represented in the model, including the mathematical dependence of modeled windfield as a function of distance and direction from the center position.
The model considers the radius of maximum winds to be dependent on central pressure for hurricanes with central pressure < 930 mb.
We have analyzed the dependence of the radius of maximum winds (Rmax) on central pressure (P0) using the empirical data taken from NWS 38 Tables 1 and 2. For storms with P0 greater than 930 mbar, we have not found any statistically significant correlation between Rmax and P0. This result is consistent with the findings of NWS 38. Therefore, for storms with P0 greater than 930 mbar, we use Rmax as a function of landfall location only, as given by NWS 38 Figures 37 and 38.
For stronger storms with P0 less than 930 mbar, we have found a statistically significant correlation between P0 and Rmax. This is consistent with the results of NWS 38. Therefore, below 930 mbar, we use a piecewise linear relationship to model the dependence of Rmax on P0. This information is reflected in Form M-2.
Also, the profile factor is subject to a maximum that is dependent on the radius of maximum winds.
Within the radius of maximum winds, the Inflow Angle is dependent on the distance from the storm center, and it is a constant at distances greater than the radius of maximum winds. The modeling of the Inflow Angle is based on Kwon and Cheong (2010).
Aside from these dependencies, all variables in the wind field component of the model are considered to be independent.
3. Identify whether hurricane parameters are modeled as random variables, as functions, or as fixed values for the stochastic storm set. Provide rationale for the choice of parameter representations.
The joint probability distribution for landfall location, track direction, and maximum one-minute sustained wind speed is obtained from a Maximum Likelihood Estimation kernel smoothing technique applied to the historical data. Radius to maximum winds and translational speed are modeled using 53 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
lognormal distributions, the parameters of which vary smoothly along the coast. The profile factor or size of hurricane in the stochastic set is specified probabilistically as a function of the location of landfall, and an upper bound is additionally imposed as a function of the radius of maximum winds. In the historical set, the profile factor is derived from the quadrant wind radii information in the archived NHC forecast advisories (and their predecessors for events prior to 1995). The filling rate is modeled using a normal distribution. The modeling of the Inflow Angle is based on Kwon and Cheong (2010)..
The parameter representations have been selected so as to provide agreement with historical data and to extrapolate to the full range of potential values, or to provide the best fit to historical data among commonly used distributions.
4. Describe how any hurricane parameters are treated differently in the historical and stochastic storm sets (e.g., has a fixed value in one set and not the other).
All hurricane parameters are treated consistently in the historical and stochastic storm sets.
The treatment of decay rates for stochastic and historical hurricanes in the EQECAT model is the same, except that for historical hurricanes the storm intensity is fixed every six hours with the observed storm intensities. Specifically, the decay rate is a regionally-dependent parameter for stochastic hurricanes, whereas for historical hurricanes a decay rate is fitted for each six-hourly track segment and used to interpolate the intensity between the six- hourly observations.
5. State whether the 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.
The model directly simulates surface winds.
6. Describe how the windspeeds generated in the windfield model are converted from sustained to gust and identify the averaging time.
USWIND converts one-minute sustained 10-meter wind speeds to peak gust 10-meter wind speeds using a gust factor function that takes surface friction from land use and land cover into account (rougher terrain has a higher gust factor). The uncertainty on the gust factor depends on the input one-minute
54 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
sustained wind speed (higher wind speeds have less uncertainty on the gust factor). The averaging interval for gust wind speeds is defined as 2 seconds.
7. Describe the historical data used as the basis for the model’s hurricane tracks. Discuss the appropriateness of the model stochastic hurricane tracks with reference to the historical storm database.
In the probabilistic database, distributions for storm direction vary geographically and are based on smoothed historical data. The historical data used is the portion of the National Hurricane Center HURDAT from 1900 through 2001 as of June 1, 2003. All hurricanes in HURDAT from 1900 through 2001 were used.
8. If the historical data are partitioned or modified, describe how the hurricane parameters are affected.
The historical data are not partitioned or modified.
9. Describe how the coastline is segmented (or partitioned) in determining the parameters for hurricane frequency used in the model. Provide the hurricane frequency distribution by intensity for each segment.
In the probabilistic analysis, the coast is divided into a series of 10 nautical mile (nmi) segments. The landfall frequency is a smooth curve developed along the entire coast using an adaptive smoothing procedure on the milepost locations of the historic storm set landfalls. Distributions of the other modeling parameters were similarly developed. Frequencies, parameters, and distributions thus change smoothly from one segment to the next. For hurricane frequency distributions by intensity and segment, see Form M-1.
10. Describe any evolution of the functional representation of hurricane parameters during an individual storm life cycle.
The EQECAT model has no changes in the functional representation of hurricane parameters during an individual storm life cycle, although local wind speeds are modified according to frictional effects, often resulting in substantial changes in wind speeds over short distances, particularly near the coast.
55 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
M-3 Hurricane Probabilities
A. Modeled probability distributions of hurricane parameters and characteristics shall be consistent with historical hurricanes in the Atlantic basin.
Modeled probability distributions of hurricane parameters and characteristics are consistent with historical hurricanes in the Atlantic basin. B. Modeled hurricane landfall strike probabilities 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).
Modeled hurricane landfall strike probabilities reflect the base hurricane storm set and are consistent with those observed for each coastal segment of Florida and other states along the Atlantic and Gulf Coasts. C. 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 strike probabilities 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 scale.
Saffir-Simpson Hurricane Scale:
Category Winds (mph) Damage 1 74 - 95 Minimal 2 96 - 110 Moderate 3 111 - 130 Extensive 4 131 - 155 Extreme 5 Over 155 Catastrophic
USWIND uses maximum one-minute sustained 10-meter wind speed when defining hurricane landfall intensity. The USWIND pressure-wind speed relationship generates wind speeds which are in agreement with the Saffir-Simpson category definition. Wind speeds developed for historical hurricanes are also consistent with the observed values
56 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Disclosures
1. List assumptions used in creating the hurricane characteristic databases.
NOAA Publication NWS-38 covers the period 1900-1984, and was the main source for compiling information on hurricane modeling parameters, (radius of maximum winds, direction of motion, translation speed, etc.) Data for later storms (1985-2004) were obtained in specific reports or publications from the National Hurricane Center (including Tropical Cyclone Reports and Advisories), analyses from the Hurricane Research Division, or from other scientifically accepted publications. These publications include Powell, M.D., D. Bowman, D. Gilhousen, S. Murillo, N. Carrasco, and R. St. Fluer, “Tropical Cyclone Winds at Landfall”, Bulletin of the American Meteorological Society 85(6): 845-851 (2004); Franklin, J.L., M.L. Black, and K. Valde, “GPS dropwindsonde wind profiles in hurricanes and their operational implications”, Weather and Forecasting, 18(1): 32-44 (2003); and Houston, S.H., and M.D. Powell, “Surface wind fields for Florida Bay Hurricanes”, Journal of Coastal Research, 19: 503-513 (2003). Coastline-dependent landfall frequency and severity distributions for the state of Florida were developed from the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009, with the 2009 hurricane season additionally included.
Standard statistical techniques were used to develop the hurricane parameter and frequency distributions. The underlying assumption is that the period 1900 through 2009 is representative in terms of hurricane climatology in Florida and adjacent areas.
57 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
2. Provide a brief rationale for the probability distributions used for all hurricane parameters and characteristics.
Data sources include the following:
Landfall Maximum Sustained Windspeed: the National Hurricane Center HURDAT starting at 1900 as of June 7, 2009 (1900-2008).
Radius of Maximum Winds: NOAA Technical Report NWS 38 (up to 1984), National Hurricane Center’s Tropical Cyclone Reports and Advisories (1985- 2004)
Translation Speed: NOAA Technical Report NWS 38 (up to 1984), National Hurricane Center’s Tropical Cyclone Reports and Advisories (1985-2004)
Filling Rate: Developed from HURDAT (1900-2006)
Profile Factor: National Hurricane Center Marine Exposure from the Advisory Archives (1963-1967,1992-2008) and surface windspeed observations
The parameter representations have been selected so as to provide agreement with historical data and to extrapolate to the full range of potential values, or to provide the best fit to historical data among commonly used distributions.
58 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
M-4 Hurricane Windfield Structure
A. Windfields generated by the model shall be consistent with observed historical storms affecting Florida.
Windfields generated by the model are consistent with observed historical storms. B. 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.
The translation of land use and land cover information into a surface roughness distribution in the model is consistent with current state-of-the-science, and has been implemented with appropriate GIS data. C. With respect to multi-story structures, the model windfield shall account for the effects of vertical variation of winds if not accounted for in the vulnerability functions.
The model accounts for vertical variation of winds for multi-story structures in the vulnerability functions.
Disclosures
1. Provide a rotational windspeed (y-axis) versus radius (x-axis) plot of the average or default symmetric wind profile used in the model and justify the choice of this wind profile.
Figure 8 below shows the minimum, mean, and maximum profiles used in Florida in the current submission. The profiles for the current submission were developed from historical data in Florida.
59 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Wind Profile for Average Florida Hurricane
120 Maximum Winds = 105 mph Radius of Maximum Winds = 20 miles
100
Maximum 80 Profile = 2.44
60 Mean Maximum Profile = 1.16 Speed (mph) Speed
40 Minimum Profile = 0.38
20
Minimum
0 0 50 100 150 200 250 300 350 400 Distance (miles) Figure 8. Wind Profile for Average Florida Hurricane.
2. If the model windfield has been modified in any way from the previous submission, provide a rotational windspeed (y-axis) versus radius (x-axis) plot of the average or default symmetric wind profile for both the new and old functions. The choice of average or default shall be consistent for the new and old functions.
The current model windfield incorporates an updated inflow angle function, but the storm radial wind profile has not been modified from the previous submission, and is plotted in Figure 8.
3. If the model windfield has been modified in any way from the previous submission, describe variations between the new and old windfield functions with reference to historical storms.
The model was updated to use current scientifically accepted boundary layer methods and inflow angle to incorporate local friction and transitions between local land use / land cover categories, including sea-to-land transition. We have examined the impact of these updates on historical windfields in a number of ways – for example, Figure 9 (Windfield for Hurricane Wilma) and Table 3 (Comparison of Point Location Observations with Model-Generated Winds).
60 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
4. Describe how the vertical variation of winds is accounted for in the model where applicable. Document and justify any difference in the methodology for treating historical and stochastic storm sets.
The model accounts for vertical variation of winds for multi-story structures in the vulnerability functions.
5. Describe the relevance of the formulation of gust factor(s) used in the model.
USWIND converts one-minute sustained 10-meter wind speeds to peak gust 10-meter wind speeds using a gust factor function that takes surface friction from land use and land cover into account (rougher terrain has a higher gust factor). The uncertainty on the gust factor depends on the input one-minute sustained wind speed (higher wind speeds have less uncertainty on the gust factor). The gust factor is based on information in Krayer and Marshall, 1992: Gust factors applied to hurricane winds, Bulletin of the American Meteorological Society, Volume 73, pp. 613-617, and other scientifically accepted studies.
As discussed in the vulnerability standards, the EQECAT model uses peak gust wind speed because damage is believed to be better correlated with peak gusts than with long-term sustained wind speeds.
6. Identify all non-meteorological variables that affect the windspeed estimation (e.g., surface roughness, topography, etc.)
Surface roughness, as determined by land use and land cover data, affects the local wind speeds in the model.
7. Provide the collection and publication dates of the land use and land cover data used in the model and justify their timeliness for Florida.
In Florida, USWIND uses land use and land cover data provided in the National Land Cover Database 2001 (NLCD 2001). The collection dates for these data vary between 1999 and 2003. Initial publication dates for Florida vary between 2003 and 2006. The database was completed for the conterminous United States and published in April 2007. This is the latest consistent high-resolution (30-meter) data set for Florida. Additionally, several land use classes from the Florida Water Management District (FWMD 2004-2008) were used to augment the NLCD data.
8. Describe the methodology used to convert land use and land cover information into a spatial distribution of roughness coefficients in Florida and adjacent states.
A roughness length is assigned to each land use / land cover category in the data provided in the National Land Cover Database 2001 (NLCD 2001), based on recent meteorological references. These values are then spatially averaged into 16 directional effective roughness lengths using currently 61 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
accepted methods. Each of the 16 values is then converted to a frictional wind-reduction factor using standard, scientifically accepted.boundary layer similarity theory.
9. Demonstrate the consistency of the spatial distribution of model-generated winds with observed windfields for hurricanes affecting Florida.
EQECAT regularly reviews modeled versus observed hurricane wind fields. Figure 9 below is a comparison of modeled (shading) and observed (numbers) surface winds in mph gust for Hurricane Wilma (2005).
Figure 9. Wind field for Hurricane Wilma (2005)
10. Describe how the model’s windfield is consistent with the inherent differences in windfields for such diverse hurricanes as Hurricane Charley (2004), Hurricane Katrina (2005), and Hurricane Wilma (2005).
The parameters used to define a hurricane in the EQECAT wind field model provide enough control to capture a wide variety of storm characteristics. Obvious features such as the landfall location, storm track, and intensity of the storm in terms of one-minute sustained winds are included, and further definition of the event is provided by the radius to maximum winds and profile 62 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
factor to describe the ‘width’ of the storm, and by the translational speed to describe the asymmetry between the right and left sides of the storm. All of these parameters can vary widely from event to event.
11. Describe any variations in the treatment of the model windfield for stochastic versus historical storms and justify this variation.
The treatment of the model windfield for stochastic and historical storms is the same, except that for historical hurricanes the storm intensity is fixed every six hours with the observed storm intensities (using HURDAT). Specifically, the decay rate is a regionally-dependent parameter for stochastic hurricanes, whereas for historical hurricanes a decay rate is fitted for each six-hourly track segment and used to interpolate the intensity between the six-hourly observations.
12. 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.
See Form M-2 at the end of this Section.
The updated model improves on the treatment of the time evolution of the windfield, the directional impact of upwind surface roughness conditions, and the inflow angle. These updates provide for more refined modeling of local effects, especially along complex coastlines and coastal waterways such as bays and estuaries, and for improved modeling of transitions from one land use / land cover category to another.
The spatial distribution of maximum winds for historic hurricanes show the general characteristic of lower winds near the coast, as well as lower winds inland when the actual local terrain conditions are used relative to a uniformly smooth "open terrain". Some notable differences well inland can also be seen, where lower winds occur when rougher terrain is taken into account (e.g., metro-Orlando, Panhandle forested areas) compared with using only open terrain.
63 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
M-5 Landfall and Over-Land Weakening Methodologies
A. The hurricane over-land weakening rate methodology used by the model shall be consistent with the historical records and with current state-of-the-science.
The hurricane over-land weakening rate methodology used by USWIND for hurricanes in Florida is based on and consistent with historical records and the current state-of-the-science.
B. The transition of winds from over-water to over-land within the model shall be consistent with current state of the science.
USWIND uses land friction to produce a reduction of the marine (overwater) wind speeds when moving over land which is consistent with the accepted scientific literature and with geographic surface roughness. The directionally averaged surface roughness friction factors produce a smooth transition of windspeeds from over-water to over-land exposure.
Disclosures
1. Describe and justify the functional form of hurricane decay rates used by the model.
Overland attenuation (filling) is handled by exponential decay formulas fit to historical data. The basic form of this equation is:
DP(t) = DP(0) exp [ -mu * t ]
where DP(0) is the hurricane central pressure deficit (difference in the ambient pressure of 1013 mb and the storm central pressure) at landfall; t is the time after landfall; and mu is the decay rate parameter. The formula estimates the pressure deficit at any time t after landfall. The decay parameter, mu, is a function of the initial pressure deficit, derived from historical data using methodology consistent with Vickery and Twisdale (1995).
2. Provide a graphical representation of the modeled decay rates for Florida hurricanes over time compared to wind observations.
The decay rates for two Florida hurricanes are shown in Figures 10 and 11.
64 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Hurricane Opal (1995)
140 Modeled Observed 120
100
80
60
40 Maximum Sustained Windspeed (mph) Windspeed Sustained Maximum
20
0 0 5 10 15 20 Time After Landfall (hours)
Figure 10. Hurricane Opal (1995)
Hurricane Frances (2004)
120
Modeled 100 Observed
80
60
40 Maximum Sustained Windspeed (mph)
20
0 0 5 10 15 20 25 Time After Landfall (hours)
Figure 11. Hurricane Frances (2004)
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3. Describe the transition from over-water to over-land boundary layer simulated in the model.
The model uses current scientifically accepted boundary layer methods to convert a marine surface (10-meter 1-minute) windfield to one which incorporates local land friction when over land. The friction factors were developed by weighting and averaging surface roughness within 20 km of a location and within a given directional sector. Application of these directional friction factors produce a smooth transition of windspeeds from over-water to over-land exposure.
4. Describe any changes in hurricane parameters, other than intensity, resulting from the transition from over-water to over-land.
There are no changes in hurricane parameters when a storm moves from over-water to over-land, other than its intensity via the filling rate.
5. Describe the representation in the model of the passage over non-continental U.S. land masses on hurricanes affecting Florida.
Intensities for stochastic storms are based on the statistical analyses of historical storms by location. An historical storm crossing over a non- continental U.S. land mass (such as Cuba) would have an impact on the storm’s intensity. This intensity would then have an impact on the intensities of the stochastic storm set. The final intensity upon reaching Florida, however, has already been accounted for in the coastline-dependent intensity distribution.
6. Document any differences between the treatment of decay rates in the model for stochastic hurricanes compared to historical hurricanes affecting Florida.
The treatment of decay rates for stochastic and historical hurricanes in the EQECAT model is the same, except that for historical hurricanes the storm intensity is fixed every six hours with the observed storm intensities (using HURDAT). Specifically, the decay rate is a regionally-dependent parameter for stochastic hurricanes, whereas for historical hurricanes a decay rate is fitted for each six-hourly track segment and used to interpolate the intensity between the six-hourly observations.
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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.
The magnitude of asymmetry in USWIND increases as the translation speed increases, all other factors held constant. B. The mean wind speed shall decrease with increasing surface roughness (friction), all other factors held constant.
The mean wind speed in USWIND decreases with increasing surface roughness (friction), all other factors held constant.
Disclosure
1. Describe how the asymmetric structure of hurricanes is represented in the model.
The asymmetric nature of hurricanes is modeled using an Asymmetry Term, which is a function of the translational speed of the storm, as well as the angle between a given location within the windfield and the storm’s direction of motion.
Starting with a stationary marine windfield, the term will generally add to windspeeds on the right side of the storm (when looking in the direction of storm motion), and subtract from windspeeds on the left. This asymmetry of the overall windfield will become stronger as the translational speed of the storm increases.
2. Provide a completed Form M-3, Radius of Maximum Winds and Radii of Standard Wind Thresholds.
See Form M-3 at the end of this section.
3. Discuss the radii values for each wind threshold in Form M-3 with reference to available hurricane observations.
The radii values for each wind threshold in Form M-3 are consistent with available hurricane observations.
67 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Form M-1: Annual Occurrence Rates
A. Provide annual occurrence rates for landfall from the data set defined by marine exposure that the model generates by hurricane category (defined by maximum windspeed at landfall in the Saffir-Simpson scale) for the entire state of Florida and selected regions as defined in Figure 12 below. 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 Set as defined in Standard M-1.
See the tables below. B. Describe model variations from the historical frequencies.
Model variations from the historical frequencies are primarily due to the sparseness in the historical data. The development of the stochastic event set has included smoothing this data, resulting in what we believe is the best estimate of hurricane frequencies by location and intensity. C. Provide vertical bar graphs depicting distributions of hurricane frequencies by category by region of Florida (Figure 12 below) and for the neighboring states of Alabama/Mississippi and Georgia. For the neighboring states, statistics based on the closest milepost to the state boundaries used in the model are adequate.
See Figure 13 below. 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.
The data have not been partitioned or modified. E. List all hurricanes added, removed, or modified from the previously accepted submission version of the Base Hurricane Storm Set. The base storm set has been updated to reflect the reanalysis that has been performed by the Hurricane Research Division on the 1921-1925 hurricanes. In addition to the 1921-1925 hurricane seasons, other storms have been updated in order to have SSI intensities consistent with wind speeds around landfall. These storms include the following: NoName4-1901, NoName-14-1916, NoName-15-1916 (removed), NoName-2-1919, NoName-6-1921, NoName-4-1924, NoName-7-1924, NoName-2-1925, NoName-4-1928, NoName-2-1929, NoName-2-1935, NoName-5- 1941, NoName-9-1945, NoName-7-1948, NoName-2-1949, Isbell-1964, Gladys- 1968, Kate-1985, Erin-1995, Katrina-2005, and Rita-2005. F. Provide this Form on CD in Excel format. The file name shall include the abbreviated name of the modeling organization, the Standards year, and the Form name. A hard copy of Form M-1 shall be included in the submission.
68 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Modeled Annual Occurrence Rates
Entire State Region A – NW Florida Historical Modeled Historical Modeled Category Number Rate Number Rate Number Rate Number Rate 1 25 0.23 29 0.27 15 0.14 14 0.13 2 14 0.11 14 0.13 4 0.04 60.06 3 18 0.17 15 0.14 4 0.04 40.04 4 8 0.07 90.08 0 0.00 10.01 5 2 0.02 10.01 0 0.00 00.00
Region B – SW Florida Region C – SE Florida Historical Modeled Historical Modeled Category Number Rate Number Rate Number Rate Number Rate 1 8 0.07 70.07 7 0.06 90.08 2 1 0.01 30.03 5 0.05 60.05 3 8 0.07 70.06 6 0.06 60.05 4 3 0.03 30.02 5 0.05 60.05 5 1 0.01 00.00 1 0.01 10.01
Region D – NE Florida Florida By-Passing Hurricanes Historical Modeled Historical Modeled Category Number Rate Number Rate Number Rate Number Rate 1 1 0.01 20.02 5 0.05 40.04 2 2 0.02 10.01 6 0.06 30.03 3 0 0.00 00.00 5 0.05 30.03 4 0 0.00 00.00 0 0.00 10.01 5 0 0.00 00.00 0 0.00 10.01
Region E – Georgia Region F – Alabama/Mississippi Historical Modeled Historical Modeled Category Number Rate Number Rate Number Rate Number Rate 1 4 0.04 10.01 8 0.07 40.04 2 0 0.00 10.01 3 0.03 30.02 3 0 0.00 00.00 5 0.05 30.03 4 0 0.00 00.00 1 0.01 10.01 5 0 0.00 00.00 1 0.01 00.00
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 landfall in that region. However, each hurricane is counted only once in the Entire State totals. Hurricanes recorded for adjacent states need not have reported damaging winds in Florida.
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(FORM M-1 CONTINUED)
81.45 W 30.71 N
87.55 W 30.27 N
Figure 12. State of Florida and Neighboring States by Region
70 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
0.3
SSI 1 - Historical SSI 1 - Modeled SSI 2 - Historical 0.25 SSI 2 - Modeled SSI 3 - Historical SSI 3 - Modeled SSI 4 - Historical 0.2 SSI 4 - Modeled SSI 5 - Historical SSI 5 - Modeled
0.15
0.1 Annual Landfall/By-pass Frequency Landfall/By-pass Annual
0.05
0 Entire FL Region A - NW Region B - SW Region C - SE Region D - NE By-Passing GA AL/MS (Excluding By- Florida Florida Florida Florida Storms Passing Storms)
Figure 13. Hurricane Frequencies by Category by Region
71 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Form M-2: Maps of Maximum Winds
A. Provide color maps of the maximum winds for the modeled version of the Base Hurricane Storm Set for both open terrain and actual terrain.
See Figure 14 below.
B. Provide color maps of the maximum winds for a 100-year and a 250-year return period from the stochastic storm set for both open terrain and actual terrain.
See Figures 15 and 16 below.
C. Provide the maximum winds plotted on each contour map and plot their location.
Actual terrain is the roughness distribution used in the standard version of the model. Open terrain uses the same roughness value of 0.03 meters at all land points.
All maps shall be color coded at the ZIP Code level.
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 seven isotach values and interval color coding:
(1) 50 mph Blue (2) 65 mph Medium Blue (3) 80 mph Light Blue (4) 95 mph White (5) 110 mph Light Red (6) 125 mph Medium Red (7) 140 mph Red
Contouring in addition to these isotach values may be included.
The maximum historical windspeed plotted is 167 mph and 168 mph for actual and open terrain respectively; the maximum stochastic windspeed for the 100-year return period is 131 mph and 136 mph for actual and open terrain respectively. The maximum stochastic windspeed for the 250-year return period is 144 mph and 149 mph for actual and open terrain respectively. Locations of maximum windspeed are marked with a gray star. 72 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
(FORM M-2 CONTINUED) a)
b)
Figure 14. Contour Map - Maximum Winds For Modeled Version Of Base Hurricane Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star. 73 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
(FORM M-2 CONTINUED) a)
b)
Figure 15. Contour Map - Maximum Winds For 100-Year Return Period From Stochastic Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star. 74 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
(FORM M-2 CONTINUED) a)
b)
Figure 16. Contour Map - Maximum Winds For 250-Year Return Period From Stochastic Storm Set for actual terrain (a) and open terrain (b). Wind Speeds Are One-Minute Sustained mph. Locations of maximum windspeed are marked with a grey star.
75 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
Form M-3: Radius of Maximum Winds and Radii of Standard Wind Thresholds
A. For the central pressures in the table below, provide the minimum and maximum values for 1) the radius of maximum winds (Rmax) used by the model to create the stochastic storm set, and the minimum and maximum values for the outer radii (R) of 2) Category 3 winds (>110 mph), 3) Category 1 winds (>73 mph), and 4) gale force winds (>40 mph). This information should be readily calculated from the windfield formula input to the model and does not require running the stochastic storm set. Describe the procedure used to complete this Form.
Central Rmax Outer Radii Outer Radii Outer Radii Pressure (mb) (mi) (>110 mph) (>73 mph) (>40 mph) (mi) (mi) (mi) Min Max Min Max Min Max Min Max 990 6 69 n/a n/a 7 94 20 400 980 6 68 n/a n/a 11 142 29 519 970 6 68 6 53 13 181 37 572 960 6 68 6 75 16 227 42 623 950 6 68 11 91 19 247 50 671 940 6 68 9 116 17 293 48 704 930 6 67 10 132 20 321 52 740 920 4 67 15 131 29 296 70 727 910 4 34 11 122 20 273 49 571 900 4 23 8 87 16 188 38 395
B. Identify the other variables that influence Rmax.
For a given hurricane, central pressure is the only variable that influences Rmax.
C. 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.
A box plot of Rmax vs. Central Pressure is provided in Figure 17 below. Histograms are provided in Figure 18 below.
76 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
70
60
50
40
30
20 Radius to Maximum Winds (miles)
10
0 900 910 920 930 940 950 960 970 980 990 Central Pressure (mb)
Figure 17. Rmax vs. Central Pressure – Box plot
77 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
(a) 45
40
35
30
25
20 Frequency (%) 15
10
5
0 <10 10-20 20-30 30-40 40-50 50-60 >60 (b) Rmax (Miles) 35
30
25
20
15 Frequency (%) Frequency
10
5
0 900 910 920 930 940 950 960 970 980 990 Central Pressure (mb)
Figure 18. Rmax and Central Pressure – Histograms. Histogram for Rmax is presented in panel (a); histogram for Central Pressure is presented in panel (b).
78 The Florida Commission on Hurricane Loss Projection Methodology Meteorological Standards
D. Provide this Form on CD in Excel format. The file name shall include the abbreviated name of the modeling organization, the Standards year, and the Form name. A hard copy of Form M-3 shall be included in the submission.
79 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Vulnerability Standards
V-1 Derivation of Vulnerability Functions
A. Development of the vulnerability functions is to be based on a combination of the following: (1) historical data, (2) tests, (3) structural calculations, (4) expert opinion, or (5) site inspections. Any development of the vulnerability functions based on structural calculations or expert opinion shall be supported by tests, site inspections, and historical data.
USWIND vulnerability functions are based on historically observed damage (in terms of both claims data and post-hurricane field surveys), experimental research conducted by Professors Kishor Mehta and James McDonald at Texas Tech, and structural calculations performed by EQE / EQECAT engineers. The claims data analyzed are from two basic sources: (1) claims data from all major storms during the period 1954 - 1994 analyzed by Dr. Don Friedman and John Mangano while managing the Natural Hazard Research Service (NHRS) effort for The Travelers Insurance Company; and (2) claims data from Hurricanes Alicia (1983), Elena (1985), Gloria (1985), Juan (1985), Kate (1985), Hugo (1989), Bob (1991), Andrew (1992), Iniki (1992), Erin (1995), and Opal (1995) provided to EQECAT by the insurance companies assisting with the development of USWIND. In addition, EQECAT has analyzed claims data from Hurricanes Charley (2004), Frances (2004), Ivan (2004), Jeanne (2004), Katrina (2005), and Wilma (2005); this analysis resulted in an update to the mobile home vulnerability in Florida in June 2008 (first included in USWIND Version 5.13 / WORLDCATenterprise Version 3.11), but it has not resulted in any other updates to the vulnerability functions in Florida. EQE / EQECAT teams have conducted post-disaster field surveys for several storms in the past few years, including Hurricanes Andrew (1992), Iniki (1992), Luis (1995), Marilyn (1995), Opal (1995), Georges (1998), Irene (1999), Lili (2002), Fabian (2003), Isabel (2003), Charley (2004), Frances (2004), Ivan (2004), Jeanne (2004), Katrina (2005), Rita (2005), and Ike (2008); Typhoon Paka (1997); and the Oklahoma City (1999), Fort Worth (2000), and Midwest (2003) tornado outbreaks. In addition, the research of Professors Mehta and McDonald incorporates a large amount of investigation into the effects of all major storms over a 25 year period.
80 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
B. The method of derivation of the vulnerability functions and associated uncertainties shall be theoretically sound.
The method of derivation of the USWIND vulnerability functions and associated uncertainties is theoretically sound.
C. Building height, construction type and construction characteristics shall be used in the derivation and application of vulnerability functions.
USWIND allows a user to account for the unique features of individual buildings, including building height, construction type, and construction characteristics. Such features modify the vulnerability functions.
D. In the derivation and application of vulnerability functions, assumptions concerning building code revisions and building code enforcement shall be justified.
When the user provides the year of construction for a building, USWIND takes into account the impact of design codes as applied during a particular period (or era) of construction. In addition, the Secondary Structural Modifiers also allow the user to input additional, more detailed information to account for the unique characteristics of individual buildings. Many of these features are often related to code enforcement: roof-to-wall anchorage, foundation anchorage, and debris potential from nearby buildings, for example. USWIND’s capability to handle site-specific features also extends beyond those factors affected by codes or code enforcement. This capability acknowledges the fact that, among structural engineers trained in the analysis and design of buildings, it is generally accepted that code enforcement is only one variable among many which affect building performance. Most of these features vary structure by structure, while code enforcement tends to vary more by region. How a building will respond in a windstorm, or for that matter in an earthquake or under ordinary conditions, will depend not just on the building code and how well it was enforced, but also on the building’s materials, configuration, and detailing; the quality of structural and architectural design; the skill, experience, and care exercised by the construction contractors; the degree to which the building’s structural and architectural systems have been maintained or modified over time; and the location and features of the local environment surrounding the building. It is easy to see that code enforcement is, in fact, only indirectly related to expected building performance. Professional, conscientious building designers and contractors can construct a well designed, well built home regardless of how frequently a local building official inspects the construction site.
81 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
E. Vulnerability functions shall be separately derived for building structures, mobile homes, appurtenant structures, contents, and time element coverages.
The USWIND vulnerability functions separately compute damages for building structures, mobile homes, appurtenant structures, contents, and time element coverages. F. The minimum wind speed that generates damage shall be reasonable.
The USWIND vulnerability functions calculate damage for all peak gust wind speeds greater than or equal to 40 miles per hour. G. Vulnerability functions shall include damage due to hurricane hazards such as windspeed and wind pressure, water infiltration, and missile impact. Vulnerability functions shall not include explicit damage due to flood, storm surge, or wave action.
The USWIND vulnerability functions include damage due to hurricane hazards such as windspeed and wind pressure, water infiltration, and missile impact. The USWIND vulnerability functions do not include explicit damage due to flood, storm surge, or wave action.
Disclosures
1. Provide a flow chart documenting the process by which the vulnerability functions are derived and implemented.
Figure 19 below summarizes the process by which EQECAT develops its vulnerability functions.
82 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Review claims data for consistency, errors
Group data into construction classes
Correct for under-insurance
Calculate ground up loss for each claim
Apply corrections for unreported data
Associate a wind speed with each claim, from the best available information
Perform regression analysis, sometimes involving merging with previously analyzed claims
Validate vulnerability curves with actual insured losses
Figure 19. Flowchart – Vulnerability Development
2. Describe the nature and extent of actual insurance claims data used to develop the model’s vulnerability functions. Describe in detail what is included, such as, number of policies, number of insurers, date of loss, and number of units of dollar exposure, separated into personal residential, commercial residential, and mobile home.
The primary set of claims data used to develop the vulnerability functions contains over 13 million policies from 6 insurers, with a total exposure of about $2.2 trillion. By far the majority of this data is from personal lines, but about 120,000 of the policies are from commercial residential lines, and about 125,000 of the policies are from mobile homes. The corresponding exposures are about $73 billion for commercial residential lines and about $8 billion for mobile homes. The data set includes claims from 18 hurricanes since 1983. The commercial residential data is from all eight 2004 and 2005 storms that affected Florida.
In addition, the EQECAT vulnerability functions are based on a large body of claims data from the Natural Hazard Research Service (NHRS), covering all major storms during the period 1954 – 1994.
3. Summarize site inspections, including the source, and provide a brief description of the resulting use of these data in development, validation, or verification of vulnerability functions.
83 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Site inspections for storms prior to 2004 are summarized in the EQECAT document ‘Secondary Structural Modifiers: Features and Model Description’, Rev. 1, 2008. The primary use of these site inspections was to calibrate and validate the secondary structural module of the software. ABS Consulting/EQECAT engineers also performed site inspections after Hurricanes Charley, Frances, Ivan, and Jeanne in 2004; Hurricane Katrina in 2005; and Hurricane Ike in 2008.
Following major windstorms, ABS Consulting/EQECAT engineers conduct reconnaissance field surveys of the affected areas to collect data. This information enables us to verify that the overall building performance of different structures matches the damage functions in our model. In addition, these events offer us the unique opportunity to gather evidence on failure modes of secondary features, which allows us to constantly enhance the mitigation measures component of the model.
4. Describe research used in the development of the model’s vulnerability functions.
Claims data from all major storms during the period 1954 – 1994 analyzed by Dr. Friedman and John Mangano while managing the Natural Hazard Research Service (NHRS) effort for the Travelers Insurance Company. Research conducted by Professors Mehta and McDonald at Texas Tech over a 25-year period by investigating damage in all major hurricanes and tornadoes. Investigations by EQE / EQECAT of Hurricanes Andrew, Iniki, Luis, Marilyn, Opal, Charley, Frances, Ivan, Jeanne, Katrina, and Rita; and Typhoon Paka (investigations of Typhoon Paka and the 2004 and 2005 hurricanes were used to validate rather than modify the vulnerability functions). Analysis of claims from Hurricanes Alicia, Elena, Gloria, Juan, Kate, Hugo, Bob, Andrew, Iniki, Erin, Opal, Charley, Frances, Ivan, Jeanne, Katrina, Rita, and Wilma provided by companies assisting with the development of USWIND. In addition, EQECAT has analyzed claims data from Hurricanes Charley (2004), Frances (2004), Ivan (2004), Jeanne (2004), Katrina (2005), and Wilma (2005); this analysis has resulted in an update to the mobile home vulnerability in Florida, but it has not resulted in any other updates to the vulnerability functions in Florida.
5. Describe the number of categories of the different vulnerability functions. Specifically, include descriptions of the structure types and characteristics, building height, year of construction, and coverages in which a unique vulnerability function is used.
USWIND uses 96 basic construction types, 21 of which are low-rise residential types, applicable to building heights from one to three stories; and 9 of which are mid/high-rise types, applicable to building heights of four or more stories, with distinct vulnerability functions for each structure type applicable to building heights from four to seven stories (mid-rise) and more than seven stories (high-rise).
84 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
They are characterized by four parameters: occupancy, number of stories, structural system, and exterior cladding strength. USWIND uses occupancies rather than line of business, because empirical evidence has shown that the former is more relevant to building performance. USWIND has distinct vulnerability functions for structure and contents, and describes time element losses as a function of direct damage and detailed occupancy type.
For low-rise residential structures, the 21 structure types are as follows:
9 residential ISO classes plus one curve for average residential ISO: • ISO Residential Class 1:Frame • ISO Residential Class 2:Joisted Masonry • ISO Residential Class 3:Non-combustible • ISO Residential Class 4:Masonry Non-combustible • ISO Residential Class 5:Modified Fire-resistive • ISO Residential Class 6:Fire-resistive • ISO Residential Class 7:Heavy Timber Joisted Masonry • ISO Residential Class 8:Super Non-combustible • ISO Residential Class 9:Super Masonry Non-combustible • ISO Residential Average
9 engineering classifications: • Residential, Low-Rise, Reinforced-Masonry, Strong-Cladding • Residential, Low-Rise, Reinforced-Masonry, Weak-Cladding • Residential, Low-Rise, Reinforced-Masonry, Average-Cladding • Residential, Low-Rise, Timber, Strong-Cladding • Residential, Low-Rise, Timber, Weak-Cladding • Residential, Low-Rise, Timber, Average-Cladding • Residential, Low-Rise, Unreinforced-Masonry, Strong-Cladding • Residential, Low-Rise, Unreinforced-Masonry, Weak-Cladding • Residential, Low-Rise, Unreinforced-Masonry, Average-Cladding
2 mobile home curves: • Residential, Low-Rise, Mobile Home - Tied Down • Residential, Low-Rise, Mobile Home - Not Tied Down
For mid/high-rise structures, the 9 structure types are as follows: • Mid/High-rise, Concrete, Strong-Cladding • Mid/High-rise, Concrete, Weak-Cladding • Mid/High-rise, Concrete, Average-Cladding • Mid/High-rise, Heavy-Steel, Strong-Cladding • Mid/High-rise, Heavy-Steel, Weak-Cladding • Mid/High-rise, Heavy-Steel, Average-Cladding • Mid/High-rise, Reinforced-Masonry, Strong-Cladding • Mid/High-rise, Reinforced-Masonry, Weak-Cladding 85 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
• High-rise, Reinforced-Masonry, Average-Cladding
6. Describe the process by which local construction and building code criteria are considered in the model.
Features pertaining to local construction and building code criteria are identified as secondary structural features in the model and can be selected by the users.
7. Identify the one-minute average sustained wind speed at which the model begins to estimate damage.
The model begins estimating damage at a peak gust wind speed of 40 mph. An equivalent one-minute average wind speed can be estimated, but will vary depending on terrain conditions and elevation. For open terrain and an elevation of 10 meters, 40 mph peak gusts equate approximately with a one-minute average wind speed of 35 mph. At other elevations and on different terrain, the one-minute average may be significantly different from this amount. For detail on this issue, the reader is referred to Simiu and Scanlan, 1996, Wind Effects on Structures, 3rd ed., John Wiley and Sons, New York, section 2.3.6. Note that USWIND uses peak gust wind speed because damage is believed to be better correlated with peak gusts than with long-term sustained wind speeds. This approach is consistent with standard structural design philosophy: one designs for extreme, or peak, conditions, such as the momentary resting of a heavy piece of equipment on an inadequately strong patch of roof. It is the load at that moment that causes the equipment to punch through the roof, not the load averaged over the previous minute.
Ted Fujita, of the University of Chicago, also pointed out (following Hurricanes Andrew and Iniki) that the gusts should be more important than the sustained wind when considering damage production. In his concluding remarks in an analysis of a videotape of a roof being blown from a house during Hurricane Iniki, he states: "It is important to realize that the roof can be blown away by 1 to 2 sec winds rather than a sustained wind" (Storm Data, Sept. 1992, Vol. 34, page 27).
8. Describe how the duration of wind speeds at a particular location over the life of a hurricane is considered.
The duration of wind speeds is not explicitly considered in the model, although duration effects are included in the claims data used to develop the vulnerability functions.
9. Provide a completed Form V-1, One Hypothetical Event. Please see Form V-1 at the end of this section. 86 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
V-2 Mitigation Measures
A. Modeling of mitigation measures to improve a structure’s wind resistance and the corresponding effects on vulnerability shall be theoretically sound. These measures shall include fixtures or construction techniques that enhance:
• Roof strength • Roof covering performance • Roof-to-wall strength • Wall-to-floor-to-foundation strength • Opening protection • Window, door, and skylight strength.
The USWIND model allows for modifications to the vulnerability curves in the secondary structural component of the model if additional knowledge about the construction characteristics is available. Such construction characteristics include roof strength, roof covering performance, roof-to-wall strength, wall-to- floor-to-foundation strength, opening protection, and window, door, and skylight strength.
B. Application of mitigation measures shall be empirically justified both individually and in combination.
The application of modifications to the vulnerability curves in the secondary structural component of USWIND is reasonable both individually and in combination.
Disclosures
1. Provide a completed Form V-2, Mitigation Measures – Range of Changes in Damage.
See Form V-2 at the end of this section.
2. Provide a description of the mitigation measures used by the model that are not listed in Form V-2.
A large number of mitigation measures relevant to residential structures including mobile homes are available in the model. These measures are provided as various options under about 30 different secondary structural features. There are both a number of features available that are not used in Form V-2, e.g. glazing extent, as well as a number of options within each feature, e.g. additional roof profile types beyond braced gable and hip.
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3. Describe how mitigation is implemented in the model. Identify any assumptions.
The options selected for each of the different secondary structural features are used in conjunction to modify the base vulnerability curve. The nature of the modification depends on a scoring system that is based on the relative merit of various features and accounts for interaction among features (two important classes of such interaction relate to the roof-to-wall connection and the wall-to-floor-to-foundation connection). The scoring system and accompanying modifications to the base vulnerability curves are based primarily on post-disaster field surveys, engineering calculations, and engineering judgement.
4. Describe the process used to ensure that multiple mitigation factors are correctly combined in the model.
The scoring system used to modify the vulnerability functions accounts for interaction among features (two important classes of such interaction relate to the roof-to-wall connection and the wall-to-floor-to-foundation connection).
88 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Form V-1: One Hypothetical Event
A. Wind speeds for 335 ZIP Codes and sample personal and commercial residential exposure data are provided in the file named “FormV1Input09.xls.” The wind speeds and ZIP Codes represent a hypothetical hurricane track. Model the sample personal and commercial residential exposure data provided in the file named against these wind speeds at the specified ZIP Codes and provide the damage ratios summarized by wind speed (mph) and construction type.
The wind speeds provided are one-minute sustained 10-meter wind speeds. The sample personal and commercial residential exposure data provided consists of four structures (one of each construction type – wood frame, masonry, mobile home, and concrete) individually placed at the population centroid of each of the ZIP Codes provided. Each ZIP Code is subjected to a specific wind speed. For completing Part A, Estimated Damage for each individual wind speed range is the sum of Ground Up Loss to all structures in the ZIP Codes subjected to that individual wind speed range, excluding demand surge and storm surge. Subject Exposure is all exposures in the ZIP Codes subjected to that individual wind speed range. For completing Part B, Estimated Damage is the sum of the Ground Up Loss to all structures of a specific type (wood frame, masonry, mobile home, or concrete) in all of the wind speed 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 Normal shingles (55mph) Normal shingles (55mph) ½” plywood deck ½” plywood deck 6d nails, deck to roof members 6d nails, deck to roof members Toe nail truss to wall anchor Toe nail truss to wall anchor 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 1980 Constructed in 1980
89 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Reference Mobile Home Structure: Reference Concrete Structure: Tie downs Reinforced concrete moment- Single unit resisting frame Manufactured in 1980 Twenty story Constructed in 1980
B. Confirm that the structures used in completing the Form are identical to those in the above table. If additional assumptions are necessary to 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 the Form are identical to those in the above table. The input one-minute sustained 10-meter wind speeds were assumed to be over- land and were converted to peak gust wind speeds.
90 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Form V-1: One Hypothetical Event
Part A Estimated Damage/ Windspeed (mph) Subject Exposure
41 – 50 0.14%
51 – 60 0.32%
61 – 70 0.93%
71 – 80 1.82%
81 – 90 3.56%
91 – 100 6.80%
101 – 110 11.28%
111 – 120 23.27%
121 – 130 32.50%
131 – 140 48.26%
141 – 150 61.31%
151 – 160 68.03%
161 – 170 74.89%
Part B Estimated Damage/ Construction Type Subject Exposure
Wood Frame 7.18%
Masonry 6.11%
Mobile Home 10.35%
Concrete 1.91%
91 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
C. Provide a plot of the Form V-1, Part A data.
A plot of the Form V-1 Part A data is provided in Figure 20 below.
80.00%
70.00%
60.00%
50.00%
40.00% % Damage
30.00%
20.00%
10.00%
0.00% 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 Wind Speed (1-minute MPH)
Figure 20. Plot of Form V-1 Part A data.
92 The Florida Commission on Hurricane Loss Projection Methodology Vulnerability Standards
Form V-2: Mitigation Measures – Range of Changes in Damage
A. Provide the change in the zero deductible personal residential reference structure damage rate (not loss cost) for each individual mitigation measure listed in Form V-2 as well as for the combination of the four mitigation measures provided for the Mitigated Frame Structure and the Mitigated Masonry Structure 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 on CD in both Excel and PDF format. The file name shall include the abbreviated name of the modeling organization, the Standards year, and the Form name. A hard copy of Form V-2 shall be included in the submission.
Reference Frame Structure: Reference Masonry Structure: One story One story Unbraced gable end roof Unbraced gable end roof Normal shingles (55mph) Normal shingles (55mph) ½” plywood deck ½” plywood deck 6d nails, deck to roof members 6d nails, deck to roof members Toe nail truss to wall anchor Toe nail truss to wall anchor 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 1980 Constructed in 1980 Mitigated Frame Structure: Mitigated Masonry Structure: Rated shingles (110mph) Rated shingles (110mph) 8d nails, deck to roof members 8d nails, deck to roof members Truss straps at roof Truss straps at roof Plywood Shutters Plywood Shutters
Reference and mitigated structures are $100,000 fully insured structures with a zero deductible policy as indicated under “Owners” Policy Type for Form A-6.
Place the reference structure at the population centroid for ZIP Code 33921 located in Lee County.
Windspeeds used in the Form are one-minute sustained 10-meter windspeeds
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Form V-2: Mitigation Measures – Range of Changes in Damage
PERCENTAGE CHANGES IN DAMAGE* (REFERENCE DAMAGE RATE - MITIGATED DAMAGE RATE) /
INDIVIDUAL REFERENCE DAMAGE RATE * 100 MITIGATION MEASURES FRAME STRUCTURE MASONRY STRUCTURE WINDSPEED (MPH) WINDSPEED (MPH) 60 85 110 135 160 60 85 110 135 160 REFERENCE STRUCTURE 0 0 0 0 0 0 0 0 0 0
ROOF BRACED GABLE ENDS 15.4% 15.1% 12.9% 10.4% 5.0% 13.1% 13.5% 11.7% 9.5% 5.9% STRENGTH HIP ROOF 19.5% 18.8% 16.2% 13.1% 6.5% 17.3% 17.3% 15.1% 12.3% 7.9% METAL 0.0% 0.0% 0.0% 0.0% 0.0% -2.6% -2.7% -2.3% -1.9% -1.2%
ROOF RATED SHINGLES (110 MPH) 8.0% 7.9% 6.8% 5.4% 2.5% 5.3% 5.4% 4.7% 3.8% 2.4% COVERING MEMBRANE 2.7% 2.6% 2.3% 1.8% 0.8% 0.0% 0.0% 0.0% 0.0% 0.0% NAILING OF DECK 8d 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%
ROOF-WALL CLIPS 19.5% 18.8% 16.2% 13.1% 6.5% 15.2% 15.4% 13.4% 10.9% 6.9% STRENGTH STRAPS 19.5% 18.8% 16.2% 13.1% 6.5% 15.2% 15.4% 13.4% 10.9% 6.9%
WALL-FLOOR TIES OR CLIPS 8.0% 7.9% 6.8% 5.4% 2.5% 5.3% 5.4% 4.7% 3.8% 2.4% STRENGTH STRAPS 8.0% 7.9% 6.8% 5.4% 2.5% 5.3% 5.4% 4.7% 3.8% 2.4% LARGER ANCHORS 0.0% 0.0% 0.0% 0.0% 0.0% - - - - - WALL- OR CLOSER SPACING FOUNDATION STRENGTH STRAPS 8.0% 7.9% 6.8% 5.4% 2.5% - - - - - VERTICAL REINFORCING ------WINDOW PLYWOOD 10.7% 10.6% 9.0% 7.2% 3.4% 10.5% 10.8% 9.4% 7.6% 4.7%
OPENING SHUTTERS STEEL 10.7% 10.6% 9.0% 7.2% 3.4% 10.5% 10.8% 9.4% 7.6% 4.7% PROTECTION ENGINEERED 17.4% 17.0% 14.5% 11.7% 5.7% 17.3% 17.3% 15.1% 12.3% 7.9% DOOR AND SKYLIGHT COVERS 15.4% 15.1% 12.9% 10.4% 5.0% 10.5% 10.8% 9.4% 7.6% 4.7% WINDOW, WINDOWS LAMINATED 10.7% 10.6% 9.0% 7.2% 3.4% 7.9% 8.1% 7.0% 5.7% 3.5% DOOR, SKYLIGHT IMPACT GLASS 10.7% 10.6% 9.0% 7.2% 3.4% 7.9% 8.1% 7.0% 5.7% 3.5% STRENGTH PERCENTAGE CHANGES IN DAMAGE* (REFERENCE DAMAGE RATE - MITIGATED DAMAGE RATE) / MITIGATION MEASURES IN REFERENCE DAMAGE RATE * 100 COMBINATION FRAME STRUCTURE MASONRY STRUCTURE WINDSPEED (MPH) WINDSPEED (MPH) 60 85 110 135 160 60 85 110 135 160 STRUCTURE MITIGATED STRUCTURE 25.7% 24.4% 21.0% 17.3% 8.7% 23.5% 23.0% 20.2% 16.6% 10.9%
* Note: 8d nails vs. 6d nails: not currently distinguished in the model, as other aspects are deemed more important; nail spacing and contact with rafter are also important. Larger or closer spaced anchor bolts: not currently distinguished in the model, as other aspects are deemed more important; also difficult to ascertain vertical reinforcing for masonry walls: this feature is accounted for through the selection of the base structure; vertically reinforced masonry walls are considered by the EQECAT model as Reinforced Masonry (RM).
The input one-minute sustained 10-meter wind speeds were assumed to be over-water and were converted to over-land peak gust wind speeds using the minimum direction- dependent roughness length for the ZIP Code centroid and the model’s standard gust factor formulation.
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Actuarial Standards
A-1 Modeled Loss Costs and Probable Maximum Loss Levels
Modeled loss costs and probable maximum loss levels shall reflect all insured wind related damages from storms that reach hurricane strength and produce minimum damaging wind speeds or greater on land in Florida.
Modeled loss costs and probable maximum loss levels reflect all damages starting when damage is first caused in Florida from an event modeled as a hurricane at that point in time and will include all subsequent damage in Florida from that event.
Disclosure
1. Describe how damage from model generated storms (landfalling and by-passing) is excluded or included in the calculation of loss costs and probable maximum loss levels for the state of Florida.
All damage from any storm that makes landfall or close bypass at hurricane status (Category 1 or above) is included in the calculation of loss costs and probable maximum loss levels, including portions below Category 1 strength.
2. Describe how damage resulting from concurrent or preceding flood or hurricane storm surge is treated in the calculation of loss costs and probable maximum loss levels for the state of Florida.
Residential property damage from storm surge is not explicitly calculated by the model. However, to the extent that a fraction of such flood damage is included in the claims data, this damage will also be reflected in the damage estimation and hence in the loss costs and probable maximum loss levels.
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A-2 Underwriting Assumptions
A. When used in the modeling process or for verification purposes, adjustments, edits, inclusions, or deletions to insurance company input data used by the modeling organization shall be based upon accepted actuarial, underwriting, and statistical procedures.
When used in the modeling process or for verification purposes, adjustments, edits, inclusions, or deletions to insurance company input data used by the modeler are based upon accepted actuarial, underwriting, and statistical procedures. B. For loss cost and probable maximum loss level estimates derived from or validated with historical insured hurricane losses, the assumptions in the derivations concerning (1) construction characteristics, (2) policy provisions, (3) claim payment practices, (4) coinsurance, (5) contractual provisions, and (6) relevant underwriting practices underlying those losses, as well as any actuarial modifications, shall be appropriate.
Vulnerability functions in USWIND are based on claims data obtained from insurance companies. For each data set obtained, the following process is used to incorporate the data into new or existing vulnerability functions: 1. Review claims data to ensure consistency, correct any errors through interactions with the insurance company that provided the data and determine all of the elements included within the claims data (e.g., allocated loss adjustment expense, etc.).
2. Group the data into appropriate construction classes, and ensure consistency between definitions of different insurers. This includes incorporating consideration of the relevant underwriting practices of the insurance company that provided the data.
3. Correct insured values to include under-insurance, if any (e.g., 80% insured to value clause in many homeowner policies). This process is done by consulting with the insurance company that provided the data.
4. Calculate ground up loss for each coverage, using the paid claim amount and the deductible.
5. Apply corrections to account for unreported data, e.g. damage below the deductible. This correction is generally negligible for residential claims, which typically have low deductibles.
6. Associate a wind speed to each location using the best available official historical information.
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7. Perform regression analysis to derive the vulnerability functions by construction class and coverage. This process may involve merging the new data set with previously analyzed claims.
8. Validate curves against loss experience from various insurance portfolios.
Disclosures
1. Identify the assumptions used to develop loss costs for unknown residential construction types.
Unknown residential structures are handled one of two ways. We prefer that our engineers and data specialists work with the insurer to determine the most likely mix of known types comprising the unknown sites. This mix is then entered into a simple lookup table, and USWIND automatically calculates the weighted-average vulnerability function for the unknown sites.
The alternative is to use the default residential structure type - a built-in vulnerability function we developed by fitting a smooth curve to all residential claims and exposure data, regardless of structure type. These data include several hundred thousand residential structures throughout the eastern US that have been subjected to hurricanes over the last 50 years.
2. Identify the assumptions used to develop loss costs for commercial residential construction types.
Loss costs for commercial residential construction types are computed analogously to those for personal residential construction types. The relevant construction types available in the model are listed in the vulnerability standards. There is a vulnerability function specific to each construction type.
3. Identify the assumptions used to account for the effects of coinsurance on commercial residential construction loss costs.
For each set of claims data used to derive or validate the commercial residential vulnerability functions, EQECAT has clarified any potential issues, including the effects of coinsurance, with the company providing the data.
4. Describe the assumptions included in model development and validation concerning insurance company claim payment practices including the effects of contractual obligations on the claim payment process.
The claim payment practices of the insurance companies providing the claims data used to develop the vulnerability functions are implicit in both model development and validation.
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5. Identify depreciation assumptions and describe the methods and assumptions used to reduce insured losses on account of depreciation. Provide a sample calculation for determining the amount of depreciation and the actual cash value (ACV) losses.
USWIND does not calculate a depreciation factor.
6. Identify insurance-to-value assumptions and describe the methods and assumptions used to determine the true property value and associated losses. Provide a sample calculation for determining the property value and guaranteed replacement cost losses.
The USWIND model does not make any insurance-to-value assumption to determine the true property replacement cost. Hence, no such correction is made by the model in the course of a portfolio analysis. The assumption made is that the total insured value provided represents true property value, so no under insurance factor is necessary. However, EQECAT uses insurance-to-value information provided by insurance companies to assess property replacement values when processing claims data for the development of vulnerability functions.
7. Describe how loss adjustment expenses are considered within the loss cost and probable maximum loss level estimates.
Loss adjustment expenses are not considered.
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A-3 Loss Cost Projections and Probable Maximum Loss Levels
A. Loss cost projections and probable maximum loss levels produced by hurricane loss projection models shall not include expenses, risk load, investment income, premium reserves, taxes, assessments, or profit margin.
Loss cost projections and probable maximum loss levels produced do not include expenses, risk load, investment income, premium reserves, taxes, assessments, or profit margin. B. Loss cost projections and probable maximum loss levels shall not make a prospective provision for economic inflation.
The model does not make a prospective provision for economic inflation with regard to losses, probable maximum loss levels, or policy limits. C. Loss cost projections and probable maximum loss levels shall not include any provision for direct hurricane storm surge losses.
The model does not include any provision for hurricane storm surge with regard to losses or probable maximum loss levels. D. Loss cost projections and probable maximum loss levels shall be capable of being calculated at a geocode (latitude-longitude) level of resolution.
The model can calculate loss costs and probable maximum loss levels for specific latitude-longitude coordinates.
Disclosures
1. Describe the method or methods used to estimate annual loss costs and probable maximum loss levels needed for ratemaking. Identify any source documents used and research performed.
Overall Model Methodology
USWIND modeling methodology can be segmented into four components: 1) the Hazard definition, 2) Propagation of the hazard to a site, 3) Damage estimate, and 4) Loss estimation.
1. Hazard Definition
The storm database used by USWIND is a combination of historical and stochastic storms. Wind speed probabilistic distributions are calculated using the probabilistic distributions of all important storm parameters. The storm intensity is driven directly from the coastline-dependent smoothed wind speed distributions generated from the information in the National Hurricane Center HURDAT. The distributions for radius of maximum winds and translational 99 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards speed are derived from NOAA Technical Report NWS 38 [Ho et al. 1987], and the National Hurricane Center’s Tropical Cyclone Reports and Advisories. A proprietary wind speed equation based upon the NOAA model as published in NWS 23 [Schwerdt, Ho, and Watkins 1979] and NWS 38 [Ho et al. 1987], modified and generalized to properly simulate wind speeds for all SSI categories of storms, computes a central pressure, which is used to apply inland decay [Vickery and Twisdale 1995] and as an input to the determination of the radius of maximum winds for severe storms. The equation then computes wind speeds using the storm’s maximum sustained windspeed, the filling rate, radius to maximum winds, the storm track, translation speed, the gust factor [Krayer and Marshall 1992], the storm profile (attenuation of wind speed outward from the center), and the friction caused by local terrain and man-made structures.
2. Propagation of the Hazard to the Site
USWIND utilizes an embedded commercial GIS (Geographic Information System), MapInfo, to compute the latitude and longitude of each site analyzed. The street address level, where such data is available, is used to geocode to the lat./long. coordinates. Failing the presence of a street address, the geocoding can be done at a ZIP Code, City, or County centroid basis. Wind speed distributions at the site locations are computed taking local friction into account.
3. Estimation of Damage
USWIND provides the facility to define each of the property assets being analyzed in order to compute resulting damage. Damage can be calculated for Structure, Contents, Time Element (such as Additional Living Expense (ALE) or Business Interruption (BI)), and up to three additional user defined coverage types. Site information includes the latitude and longitude of the locations, the structure types (96 types), structure details such as number of stories, insured value, cladding type and a class of occupancy type (12 types). Vulnerability functions may be modified by the incorporation of secondary structural components such as roof type, roof strength, roof-wall strength, wall-floor strength, wall-foundation strength, opening protection, and wind-door-skylight strength. Damage is estimated using vulnerability functions associated with the structure definition and occupancy type and the distribution of peak gust wind speeds at each site. The vulnerability functions used by USWIND have been derived through three methods: empirical data, expert opinion, and engineering analysis [Fujita 1992, McDonald-Mehta Engineers 1993, Simiu and Scanlan 1996].
The probabilistic distribution of damage (for each coverage and site) is derived through the integration of the probabilistic distribution of wind speeds for the site with the probabilistic distributions of damage for given wind
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speeds. Damage distributions for each of the sites are aggregated into an overall portfolio distribution of damage.
Since there can be a high degree of damage correlation for similar structure types within a geographic area, USWIND properly takes into account site and coverage level correlations when aggregating individual site damage into an overall portfolio damage amount.
4. Estimation of Loss
Insurance information in the form of insured values, limits, deductibles and facultative and/or treaty reinsurance are then integrated with the probabilistic distribution of computed damage for each site to determine the probabilistic distribution of “insured loss” amount. Correlation is properly taken into account when aggregating individual site loss into an overall portfolio loss amount.
2. Identify the highest level of resolution for which loss costs and probable maximum loss levels can be provided. Identify all possible resolutions available for the reported output ranges.
Loss costs can be provided at state, county, ZIP Code, and site (specific latitude-longitude) levels. For the reported output ranges, all analyses were performed at the ZIP Code level.
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A-4 Demand Surge
A. Demand surge shall be included in the model’s calculation of loss costs and probable maximum loss levels using relevant data.
Demand surge has been included in all analyses submitted for review by the Commission, using relevant data. B. The methods, data, and assumptions used in the estimation of demand surge shall be actuarially sound.
The methods, data, and assumptions used in the estimation of demand surge are actuarially sound.
Disclosures
1. Describe how the model incorporates demand surge in the calculation of loss costs and probable maximum loss levels.
The USWIND model offers the option to either include or exclude the increased loss resulting from the effect of demand surge which is observed following major cat events.
Two indices are calculated to determine the magnitude of the demand surge at any given location subjected to a windspeed V. The Cat Index is a function of the storm intensity and the landfall milepost. This index is a function of the storm ground-up damage on one hand, and the availability of building materials and construction labor in the affected region on the other hand. The Cat Inflation Index represents the factor by which repair cost increases in a cat event as a function of V.
2. Provide citations to published papers, if any, that were used to develop how the model estimates demand surge.
The demand surge algorithm used in USWIND is strictly based on EQECAT research.
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A-5 User Inputs
All modifications, adjustments, assumptions, inputs and/or input file identification, and defaults necessary to use the model shall be actuarially sound and shall be included with the model output report. Treatment of missing values for user inputs required to run the model shall be actuarially sound and described with the model output report.
Any assumption or method used by EQECAT’s hurricane loss projection model that relates to a specific insurer’s inputs to the model, if any, for the purposes of preparing the insurer’s rate filing is clearly identified. EQECAT will disclose any implicit assumptions relating to insurance to value, the prevalence of appurtenant structures, or demographic risk characteristics.
Disclosures
1. Describe the methods used to distinguish among policy form types (e.g., homeowners, dwelling property, mobile home, tenants, condo unit owners).
USWIND has no pre-determined policy form types in it. The user must specify the format of the policy form in the input file. The model can accept a wide variety of combinations of deductible and limits. The primary assumption in the analysis of different policy forms is that the user has input the data correctly. USWIND has many reports which the user can use to validate the correctness of the data, but the responsibility for the correctness of the analysis resides with the user. The model can produce loss costs for different types of policies. All the elements of the loss are retained following an analysis. With a properly formatted input file, the user can produce reports which detail many breakdowns of the data, not just by Policy Type, but also by ZIP Code, county, state, line of business, branch, division, etc. The user has to select the correct identification codes for the various reports needed.
2. Disclose, in a model output report, the specific type of input that is required to use the model or model output in a residential property insurance rate filing. Such input includes, but is not limited to, optional features of the model, type of data to be supplied by the model user and needed to derive loss projections from the model, and any variables that a model user is authorized to set in using the model. Include the model name and version number on the model output report. All items included in the output form submitted to the Commission shall be clearly labeled and defined.
The output reports on the next four pages provide an example of the information given. In the reports, ‘Multiple Layer Flag’, if ‘On’, indicates that policies having the same account number should be treated as layers of a single policy, and ‘Global Limits/Deductibles’, if other than ‘None Applied’, indicates that the limits and/or deductibles in the portfolio have been overridden with some user-specified global values.
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Geocode Statistics by State for Portfolio case1
Number of Building Contents Total Property Time Element Total Geocode Statistics Locations TIV TIV TIV TIV TIV $(Thousands) $(Thousands) $(Thousands) $(Thousands) $(Thousands)
State: Florida Postal Code 2 200 0 200 0 200 Florida State Total 2 $200 $0 $200 $0 $200
Total for All States 2 $200 $0 $200 $0 $200
Factors Used in Analysis: Peril Type: Hurricane Multiple Layer Flag: Off
Product Version: EQECAT: USWIND 5.18.01 User ID = 1, Window ID = 1 Florida Hurricane Model Version: 2011a Page 1 of 1 March 17, 2011 4:36 PM
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Quality Factor by State for Portfolio case1
Number of Building Contents Total Property Time Element Total Quality Factor Locations TIV TIV TIV TIV TIV $(Thousands) $(Thousands) $(Thousands) $(Thousands) $(Thousands)
State: Florida 50 2 200 0 200 0 200 Florida State Total 2 $200 $0 $200 $0 $200
Total for All States 2 $200 $0 $200 $0 $200
Factors Used in Analysis: Peril Type: Hurricane Multiple Layer Flag: Off
Product Version: EQECAT: USWIND 5.18.01 User ID = 1, Window ID = 1 Florida Hurricane Model Version: 2011a Page 1 of 1 March 17, 2011 4:36 PM
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Structure Types by State for Portfolio case1
Number of Building Contents Total Property Time Element Total Structure Types Locations TIV TIV TIV TIV TIV $(Thousands) $(Thousands) $(Thousands) $(Thousands) $(Thousands)
State: Florida Commercial, Low-Rise, Unreinforced-Masonry, 1 100 0 100 0 100 Average-Cladding Residential, Low-Rise, Timber, Average-Cladding 1 100 0 100 0 100 Florida State Total 2 $200 $0 $200 $0 $200
Total for All States 2 $200 $0 $200 $0 $200
Factors Used in Analysis: Peril Type: Hurricane Multiple Layer Flag: Off
Product Version: EQECAT: USWIND 5.18.01 User ID = 1, Window ID = 1 Florida Hurricane Model Version: 2011a Page 1 of 1 March 17, 2011 4:36 PM
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Hurricane - Expected Annual Damage and Loss by State for Portfolio case1
Total No. of Expected Annual Damage Expected Annual Gross Loss Expected Annual Expected Annual Net Loss
State TIV Bldgs. % Total % Total Fac. Cessions % Total $(Thousands) $(Thousands) TIV $(Thousands) TIV $(Thousands) $(Thousands) TIV
Florida 200 2 0.96 0.4801 0.65 0.3251 0.00 0.65 0.3251 Total for All States $200 2 $0.96 0.4801% $0.65 0.3251% $0.00 $0.65 0.3251%
Factors Used in Analysis:
Demand Surge Factor: Demand Surge Not Included Region: U.S. Mainland Global Limits/Deductibles: None Applied Multiple Layer Flag: Off
Product Version: EQECAT: USWIND 5.18.01 User ID = 1, Window ID = 2 Florida Hurricane Model Version: 2011a Page 1 of 1 March 17, 2011 4:36 PM
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3. Provide a copy of the input form used by a model user to provide input criteria to be used in the model. Describe the process followed by the user to generate the model output produced from the input form. Include the model name and version number on the input form. All items included in the input form submitted to the Commission shall be clearly labeled and defined.
An example USWIND input form is shown below. The field names are in the first column, and arranged into six groups (P for policy information, PC for policy coverage information, PF for policy facultative reinsurance, S for site information, and SC for site coverage information). The example below has five records of data (policy numbers FLP001 through FLP005). To generate the model output, a user of the model imports the import form using functionality built into the EQECAT software, selects the relevant analysis options and desired output reports, and executes the analysis.
Florida Hurricane Model 2011a P_PolNum FLP001 FLP002 FLP003 FLP004 FLP005 P_InsName P_AcctNum P_AcctName P_Company C1 C1 C1 C1 C1 P_Division NY NY FL FL NY P_Branch Mia Mia Mia Mia Mia P_LineBus HO HO MP MP HO P_PolTyp COMF COMF HO HO HO P_PolStats IN IN IN IN IN P_IncpDate 20020901 20021101 20021201 20020901 20021101 P_ExprDate 20030831 20031031 20031130 20030831 20031031 P_Producer 9912 4412 7413 1284 9912 P_TransID 99 99 99 99 99 PC_PerlTyp Wind Wind Wind Wind Wind PC_CvgTyp Bldg Cont Time Time ALE PC_LmtAmt 500 333 111 222 67 PC_LmtTyp CovSpec CovSpec CovSpec CovSpec CovSpec PC_DedAmt 1000 1000 1000 1000 1000 PC_DedTyp CovSpec CovSpec CovSpec CovSpec CovSpec PC_PolPrm 600 600 600 600 600 PC_AttcPnt 00000 PC_ProRata 100 100 100 100 100 PF_CertNum PF_PerlTyp PF_CvgTyp PF_ReinApp PF_AttPnt PF_LayAmt PF_CedPcnt PF_ReinTyp PF_AggLmt PF_Reinsr PF_Broker PF_CertSta PF_ReinPrm PF_TrtyNum
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S_Number 1 1 1 1 1 S_Name S_StrAddr 400 S Greenwood 2040 Whitfield 7400 Nw 19 2801 Rosselle 4586 Palm Ave S_City Clearwater Sarasota Miami Jacksonville Hialeah S_County Pinellas Manatee Dade Duval Dade S_State FL FL FL FL FL S_Zip_5dg 34616 34243 33147 32205 33012 S_WndStruc SC52 SC52 SC654 SC654 SC654 S_WndOccpy OC1 OC1 OC1 OC1 OC1 S_YrBuilt 1968 1980 1934 1942 1960 S_NumStory 1 2 1 1 1 S_NumStruc 11111 SC_PerlTyp Wind Wind Wind Wind Wind SC_CvgTyp Bldg Cont Time Time ALE SC_CovQual 50 50 50 50 50 SC_TIV 600 350 150 250 75 SC_LmtAmt 500 333 111 222 67 SC_LmtTyp CovSpec CovSpec CovSpec CovSpec CovSpec SC_DedAmt 1000 1000 1000 1000 1000 SC_DedTyp CovSpec CovSpec CovSpec CovSpec CovSpec SC_Prem 600 600 600 600 600 SF_CertNum SF_PerlTyp SF_CvgTyp SF_ReinApp SF_AttPnt SF_LayAmt SF_CedPcnt SF_ReinTyp SF_Reinsr SF_Broker SF_CertSta SF_Prem SF_TrtyNum
The table below provides descriptions for each of the input data fields.
Field Name Data Group Description P_PolNum Policy Policy Number P_InsName Policy Insured Name P_AcctNum Policy Account Number P_AcctName Policy Account Name P_Company Policy Company P_Division Policy Division P_Branch Policy Branch P_LineBus Policy Line of Business P_PolTyp Policy Policy Type P_PolStats Policy Policy Status P_IncpDate Policy Inception Date P_ExprDate Policy Expiration Date P_Producer Policy Producer P_TransID Policy Translation ID PC_PerlTyp Policy Coverage Peril Type PC_CvgTypPolicy Coverage Coverage Type PC_LmtAmt Policy Coverage Limit Amount PC_LmtTypPolicy Coverage Limit Type 109 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Field Name Data Group Description PC_DedAmt Policy Coverage Deductible Amount PC_DedTyp Policy Coverage Deductible Type PC_PolPrm Policy Coverage Policy Premium PC_AttcPnt Policy Coverage Attachment Point PC_ProRata Policy Coverage Prorata PF_CertNum Policy Facultative Certificate Number PF_PerlTypPolicy Facultative Peril Type PF_CvgTyp Policy Facultative Coverage Type PF_ReinApp Policy Facultative Reinsurance Applies PF_AttPnt Policy Facultative Attachment Point PF_LayAmt Policy Facultative Layer Amount PF_CedPcnt Policy Facultative Ceded Percentage PF_ReinTypPolicy Facultative Reinsurance Type PF_AggLmt Policy Facultative Aggregate Limit PF_Reinsr Policy Facultative Reinsurer PF_Broker Policy Facultative Broker PF_CertSta Policy Facultative Certificate Status PF_ReinPrm Policy Facultative Reinsurance Premium PF_TrtyNum Policy Facultative Treaty Number S_Number Site Site Number S_Name Site Site Name S_StrAddr Site Street Address S_City Site City S_County Site County S_State Site State S_Zip_5dg Site ZIP Code S_WndStruc Site Wind Structure Type S_WndOccpy Site Wind Occupancy Type S_YrBuilt Site Year Built S_NumStory Site Number of Stories S_NumStruc Site Number of Structures SC_PerlTypSite CoveragePeril Type SC_CvgTyp Site Coverage Coverage Type SC_CovQual Site Coverage Coverage Quality SC_TIV Site Coverage Total Insured Value SC_LmtAmt Site Coverage Limit Amount SC_LmtTypSite Coverage Limit Type SC_DedAmt Site Coverage Deductible Amount SC_DedTypSite Coverage Deductible Type SC_Prem Site Coverage Premium SF_CertNum Site Facultative Certificate Number SF_PerlTyp Site Facultative Peril Type SF_CvgTyp Site Facultative Coverage Type SF_ReinApp Site Facultative Reinsurance Applies SF_AttPnt Site Facultative Attachment Point SF_LayAmt Site Facultative Layer Amount SF_CedPcnt Site Facultative Ceded Percentage SF_ReinTyp Site Facultative Reinsurance Type SF_Reinsr Site Facultative Reinsurer SF_Broker Site Facultative Broker SF_CertSta Site Facultative Certificate Status SF_Prem Site Facultative Reinsurance Premium SF_TrtyNum Site Facultative Treaty Number
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4. Describe actions performed to ensure the validity of insurer data used for model inputs or validation/verification.
Client data are extensively tested during the import process into the EQECAT system to confirm their accuracy. Field level validation is performed to confirm that every data element within each record falls within known ranges. Data not falling within known ranges are marked as errors or a warning in a log depending upon the severity of the problem. Child/parent and other key relationships are also checked. A summary log is displayed at the end of import process denoting the number records which have warnings or errors.
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A-6 Logical Relationship to Risk
A. Loss costs shall not exhibit an illogical relation to risk, nor shall loss costs exhibit a significant change when the underlying risk does not change significantly.
EQECAT’s loss costs exhibit logical relation to risk. Loss costs produced by the model do not exhibit a significant change when the underlying risk does not change significantly. B. Loss costs produced by the model shall be positive and non-zero for all valid Florida ZIP Codes.
Loss costs produced by the model are positive and non-zero for all valid Florida ZIP Codes. C. Loss costs cannot increase as the quality of construction type, materials and workmanship increases, all other factors held constant.
Loss costs do not increase as the quality of construction type, materials, and workmanship increases, all other factors held constant. D. Loss costs cannot increase as the presence of fixtures or construction techniques designed for hazard mitigation increases, all other factors held constant.
Loss costs do not increase with the presence of fixtures or construction techniques designed for hazard mitigation, all other factors held constant. E. Loss costs cannot increase as the quality of building codes and enforcement increases, all other factors held constant.
Loss costs do not increase as the quality of building codes and enforcement increases, all other factors held constant. F. Loss costs shall decrease as deductibles increase, all other factors held constant.
Loss costs decrease as deductibles increase, all other factors held constant. G. The relationship of loss costs for individual coverages, (e.g., structures and appurtenant structures, contents, and time element) shall be consistent with the coverages provided.
Relationships among the loss costs for coverages A,B,C,D are consistent with the coverages provided.
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Disclosures
1. Demonstrate that loss cost relationships by type of coverage (structures, appurtenant structures, contents, time element) are consistent with actual insurance data.
Figure 21 below compares a representative sample of Hurricane Andrew claims data with the statewide weighted average zero deductible loss costs for wood frame and masonry. All values have been normalized to the corresponding coverage A value.
1.0
0.9
0.8 Representative Hurricane Andrew Claims Statewide Wtd Ave Loss Cost - Frame 0.7 Statewide Wtd Ave Loss Cost - Masonry
0.6
0.5
0.4
Loss RelativeLoss Cov A Loss to 0.3
0.2
0.1
0.0 Cov A Cov B Cov C Cov D
Figure 21. Loss Cost Relationships by Coverage
2. Demonstrate that loss cost relationships by construction type are consistent with actual insurance data.
Looking at a representative sample of Hurricane Andrew claims data, we found that among ZIP Codes having claims for wood frame, masonry, and mobile homes, the average ratio of the percentage loss for wood frame to the percentage loss for masonry was 2.2, and the average ratio of the percentage
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loss for mobile home to the percentage loss for masonry was 7.9. This relationship is consistent with the loss costs produced by the EQECAT model.
3. Demonstrate that loss cost relationships among coverages, territories, and regions are consistent and reasonable.
We have conducted several analyses to demonstrate how the loss cost (Average Annual Loss or AAL) relationships produced by USWIND are consistent with actual insurance data. Using our large empirical data set of exposure loss information from historical storms, we have calculated expected ratios of loss rates between coverages and between structure types by peak gust wind speeds. We compared these ratios at various wind speeds to corresponding ratios for AAL. We looked at various different AAL ratios including the average and 75th percentile over all ZIP Codes for each corresponding group. The results highlighted how the AAL relationships are within the expectations derived from actual insurance data.
As an example of the consistency of the loss cost relationships between structure types, the ratio of expected loss between Construction Type #1 and Construction Type #2 varied between 56% and 93% for gust wind speeds between 70 and 200 mph. The average ratio of AALs between these two construction types over all ZIP Codes was 57%, and the 75th percentile was 68%.
Demonstrating the consistency of the relationships between loss costs and territories, Figure 22 displays USWIND’s loss cost estimates. Depicted here are the loss costs for all construction types and all coverages. The horizontal axis lists all coastal counties starting with the north-eastern most county of Nassau and ending with the western most county of Escambia. The chart below the graph in the figure illustrates the corresponding historical events by SSI category for these regions.
The progression from north to south and then back up to the panhandle coincides with the historical storm activity. For example, the southeast region has historically seen the most frequent and most severe storms and therefore yields the highest loss costs.
Please note that the erratic behavior of the graph in certain regions can be explained by the fact that counties have varying geographic area.
USWIND produces loss costs that are highly correlated to historical data.
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Figure 22. Loss Costs for Coastal Counties
4. Explain any anomalies or special circumstances that might preclude any of the above conditions from occurring.
There are no such anomalies.
5. Provide a completed Form A-1, Personal Residential Loss Costs.
See Form A-1 at the end of this section.
6. Provide a completed Form A-2, Zero Deductible Personal Residential Loss Costs by ZIP Code.
See Form A-2 at the end of this section.
7. Provide a completed Form A-3, Base Hurricane Storm Set Statewide Loss Costs.
See Form A-3 at the end of this section.
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8. Provide a completed Form A-4, Hurricane Andrew (1992) Percent of Losses.
See Form A-4 at the end of this section.
9. Provide a completed Form A-5, Cumulative Losses from the 2004 Hurricane Season.
See Form A-5 at the end of this section.
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A-7 Deductibles and Policy Limits
A. The methods used in the development of mathematical distributions to reflect the effects of deductibles, policy limits, and coinsurance shall be actuarially sound.
The methods used in the development of mathematical distributions to reflect the effects of deductibles and policy limits are actuarially sound. B. The relationship among the modeled deductible loss costs shall be reasonable.
USWIND estimates the damage distribution for a given site through the integration of the site hazard distribution and the corresponding vulnerability function as shown in Figure 23 below.
Figure 23. Integration of Uncertainty on Hazard and Damage
The loss distribution is estimated through the integration of the site damage distribution, taking into account deductibles and limits, as shown in Figure 24 below.
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Damage PDF Loss = f(Damage, Deductible, Limit,...)
Deductible Limit
$ Dmg
Loss
Figure 24. Integration of Damage Distribution to Calculate Loss
C. Deductible loss costs shall be calculated in accordance with s. 627.701(5)(a), F.S.
All loss costs have been calculated in accordance with s.627.701(5)(a), F.S.
D. The effects of coinsurance on commercial residential loss costs produced by the model shall be actuarially sound.
The effects of coinsurance on commercial residential loss costs produced by the model are actuarially sound, both in terms of derivation of the vulnerability functions, and it terms of the capacity of the model to incorporate the effects of coinsurance in the loss calculation.
Disclosures
1. Describe the methods used in the model to treat deductibles (both flat and percentage), policy limits, replacement costs, and insurance-to-value when projecting loss costs.
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The model assumes that the user has correctly input the replacement cost of all coverages in the portfolio. The input replacement cost must include any adjustments for insurance-to-value, as the model does not make any corrections for this. The deductible is also a user input value. The user may input a flat deductible (i.e., a fixed dollar amount) or a percentage amount (a percentage of the TIV). Deductibles may be applied separately to each coverage, or applied to aggregated damage. The allowed aggregations are Blanket (i.e., all coverages subject to one deductible) or Property Damage / Business Interruption (PD/BI) (i.e. all real property coverages are subject to one deductible, and the Time Element coverage is subject to a different deductible). Limits are input by the user, in a manner similar to that for deductibles. Limits are input as a dollar amount, to be applied either to (a) all coverages separately, (b) all coverages in aggregate, or (c) two limits, one for real property, and one for Time Element. Internally, the program calculates the loss by integrating over the probability distribution function (PDF) of the damage.
2. Provide an example of how insurer loss (loss net of deductibles) is calculated. Discuss data or documentation used to confirm or validate the method used by the model.
Example:
(A) (B) (C) (D)=(A)*(C) (E)=(D)-(B) Structure Policy Damage Zero Deductible Loss Net of Value Limit Deductible Ratio Loss Deductible 100,000 90,000 500 2% 2,000 1,500
Consider the property in the example above with given value, limit, and deductible, subject to a wind speed with average damage ratio as given. Assume further that the vulnerability functions specify the range of possible outcomes as follows:
Probability of Zero Damage = 0.50
Probability of Damage Greater 0.50 than Zero =
Probability Distribution of Positive {Lognormal with mean=4% Damages = and standard deviation=6%} truncated at 100%
(Note: this functional distribution is only used for illustrative purposes and does not necessarily reflect the method contained within USWIND.)
Then the average damage rate (mathematical expectation) is 0.5 x 4% = 2%, as specified, providing an expected damage amount (ground up loss) of $100,000 x 2% = $2000. 119 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
For any given property, the insurer loss is the greater of two quantities: (1) zero, and (2) the damage minus the deductible, but not greater than the policy limit. Because the damage is a random variable, i.e., it is associated with a probability distribution, so too is the insurer loss. However, we can calculate the average insurer loss (mathematical expectation) by the following expression:
0.9+.005 1 100,000 • [ ³ (x-0.005) • f(x)dx + ³ (0.9) • f(x)dx] 0.005 0.9 + .005 where f(x) is the probability density function defined above. In this case, the result comes out to be an expected insurer loss of $1752. This is substantially higher than $1500 because the expectation combines the probabilities of high-loss outcomes, where the deductible is fully applied, with low-loss outcomes, where the deductible does not fully apply.
The foregoing example illustrates the actuarial theory behind the application of deductibles and limits. USWIND implements this theory in loss cost calculations by a Latin Hypercube Sampling. For each property, one thousand instances of the random damage ratio are drawn from the model's probability distribution for damage ratio. The deductibles and limits are applied to each outcome and the results are averaged. Table 2 illustrates this process.
TABLE 2. EXAMPLE DAMAGE TO LOSS SIMULATION
Instance # Damage Ratio Ground Up Loss Insurer Loss
1 0.00 0.00 0.00
2 2% 2,000.00 1,500.00
......
999 0.37% 370.00 0.00
1000 10% 10,000.00 9,500.00
Total 2,000,765 1,751,942.00
Average 2.001% 2,001.00 1.752.00
The theoretical calculation presented above is standard in the actuarial literature. See, for example, chapter 3 of R. E. Beard, T. Pentikainen, and E. Pesonen's Risk Theory: the Stochastic Basis of Insurance (3rd Edition, New
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York: Chapman and Hall) or chapter 5 of R. V. Hogg and S. A. Klugman's Loss Distributions (New York: John Wiley and Sons).
The implementation by way of simulation is standard in the simulation literature. See, for example, chapter 4 of R. Y. Rubenstein's Simulation and the Monte Carlo Method (New York: John Wiley and Sons) or chapter 5 of J. M. Hammersley and D. C. Handscomb's Monte Carlo Methods (New York: Barnes & Noble), or M.P. Bohn, et. al., “Application of the SSMRP Methodology to the Seismic Risk at the Zion Nuclear Plant,” prepared for the U.S. Nuclear Regulatory Commission, Lawrence Livermore National Laboratory.
The specifics of the distributional models are based both on engineering studies of the variability of damage from winds and on extensive historical datasets detailing losses risk-by-risk.
3. Describe how the model calculates annual deductibles.
All results in this submission, where annual deductibles are required, were compiled through the post-processing of intermediate results generated by the standard EQECAT model. The handling of the annual deductibles was done according to the 627.701(5)(a) Florida Statutes.
Using stratified sampling, for each year, a number of events are simulated from the hurricane frequency distribution. As each simulated year progresses, losses from each hurricane during that year are tracked by policy and the corresponding effect on the remaining amount of the hurricane deductible evaluated. The results are used to quantify the annual deductible effects.
4. Describe the methods used in the model to account for coinsurance.
For each set of claims data used to derive or validate the commercial residential vulnerability functions, EQECAT has clarified any potential issues, including the effects of coinsurance, with the company providing the data. The effects of coinsurance are incorporated in the loss calculation in terms of a specified share of the loss.
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A-8 Contents
A. The methods used in the development of contents loss costs shall be actuarially sound.
The methods used in the development of contents loss costs are actuarially sound. B. The relationship between the modeled structure and contents loss costs shall be reasonable, based on the relationship between historical structure and contents losses.
EQECAT’s model calculates damage to contents separately from damage to buildings and appurtenant structures. Content vulnerability curves in USWIND are based on claims data. Information regarding relationships among loss costs by coverage has been submitted in Forms A-1 and A-2.
Disclosure
1. Describe the methods used in the model to calculate loss costs for contents coverage associated with personal and commercial residential structures.
Residential content vulnerability functions were developed by regressing historic content claims against peak gust wind speed, using claims data gathered and analyzed over the last 40 years. In USWIND, the user identifies the structure type containing the contents, choosing from one or a combination of the basic structure types available in USWIND. That is not to say that content vulnerability is the same as building vulnerability: there are two sets of vulnerability functions for each of the basic types, one set for contents and one set for buildings. The content vulnerability is a function of the structure type, but it is not a direct function of the building vulnerability function. At this point, it would be helpful to clarify the distinction between “content vulnerability,” “building vulnerability,” and “structure type.” Structure type refers to the building’s structural system: whether the building is wood- frame, masonry, concrete, etc.; whether the exterior wall material is strong or not; whether the windows are large or small; and so on. When we say building vulnerability, we mean the degree to which a building of a given structure type is estimated to be damaged at a given wind speed. A building with a concrete structure type is likely to be less vulnerable than a building with a timber structure type. Similarly, content vulnerability refers to the degree to which contents within a building of a given structure type are estimated to be damaged at a given wind speed. Contents in a building with a concrete structure type are less vulnerable to wind damage than contents in a building with a timber structure type. Building vulnerability and content vulnerability are both functions of structure type, but content vulnerability is not a function of building vulnerability.
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To the extent that both building damage and content damage increase at higher wind speeds, and to the extent that both building and content damage are generally higher in more vulnerable structure types, the two are positively correlated, but there is no direct functional dependency defined in USWIND between the content vulnerability function and the building vulnerability for the same structure type -- there is no magic factor applied to building damage to get content damage, nor should there be in the best designed model. To impose such a direct dependency would produce poorer vulnerability functions than are incorporated in USWIND. Regarding a minimum threshold, see our answer to question III.1: Content damage, like building damage, is estimated when peak gust wind speed (2 second averaging time) exceeds 40 mph. Loss is calculated based on damage, deductible, limits, etc.
Figure 25 below demonstrates the relationship between building and contents losses exhibited in a series of hypothetical storms run in the model.
16,000
14,000
12,000
10,000
8,000
6,000 Contents Loss ($1,000s) Loss Contents
4,000
2,000
0 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Building Loss ($1,000s)
Figure 25. Relationship Between Building and Contents Losses
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A-9 Time Element Coverage
A. The methods used in the development of time element coverage loss costs shall be actuarially sound.
The methods used in the development of time element loss costs are actuarially sound. B. Time element loss cost derivations shall consider the estimated time required to repair or replace the property.
Time element loss cost derivations consider the estimated time required to repair or replace the property. C. The relationship between the modeled structure and time element loss costs shall be reasonable, based on the relationship between historical structure and time element losses.
EQECAT’s model calculates time element damage as a function of building and content damage. Time element vulnerability curves in USWIND are based on claims data. Information regarding relationships among loss costs by coverage has been submitted in Form A-1. D. Time element loss costs produced by the model shall appropriately consider time element claims arising from indirect loss.
Time element vulnerability curves in USWIND are based on claims data.
Disclosures
1. Describe the methods used to develop loss cost for time element coverage. State whether the model considers both direct and indirect loss to the insured property. For example, direct loss could be for expenses paid to house policyholders in an apartment while their home is being repaired. Indirect loss could be for expenses incurred for loss of power (e.g., food spoilage).
USWIND estimates time element costs as a function of building damage, content damage, and occupancy. The program first determines the greater of building or content damage (as percentages of the coverage value) and then evaluates the time-element vulnerability function at this x-value. There is no minimum threshold at which time element loss is calculated. That is to say, if a site experiences significant structure or content damage, some time- element cost is estimated to occur. The size of the storm, even if it is “merely” a category 1 event, is irrelevant to the policyholder and the insurer; all that matters is whether the home is occupiable under the terms of the policy. Nor would a threshold structure damage make sense: even if the structure experiences minimal damage, such as just a few broken windows, significant damage to contents can result in significant time-element costs. It is for this 124 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
reason that USWIND uses both structure and content damage, as well as occupancy, in determining time-element costs.
We recognize that the ideal model would also include explicit consideration of lifeline functionality, for example, whether electrical power and water are available at the insured’s home. Unfortunately, proper analysis of lifeline functionality is a complex issue. Merely to begin such an analysis requires detailed information on the lifeline facilities, such as the locations, structural characteristics, and links between utility elements like local water mains, pumping stations, power plants, etc. Suffice it to say this type of data is tightly controlled by the multitude of public utilities involved, and is generally unavailable at the local level. The reader should not infer from this that USWIND underestimates time-element costs by an amount equal to lifeline- related effects. There is a strong positive correlation between local lifeline damage and damage to a policyholder’s home. That correlation results from a common cause: higher wind speeds generally result in higher damage to homes, power lines, and even underground water mains, which can experience damage from uprooted trees. The historical data that go into USWIND’s time-element vulnerability functions therefore account for lifeline damage, if only in an indirect, average way, because they are based on damage that is correlated with lifeline damage.
2. State the minimum threshold at which time element loss is calculated (e.g., loss is estimated for structure damage greater than 20% or only for category 3, 4, 5 events). Provide documentation of validation test results to verify the approach used.
The minimum threshold at which time element loss is calculated is the point at which either building or contents damage becomes nonzero (i.e., at 40 mph gust).
A simple validation test looked at a representative sample of claims data from Hurricane Andrew, and found that only 0.21% of the total dollar value of time element claims came from policies having no corresponding building or content claim. In many of these cases, building or content damage may have occurred below the level of the deductible.
3. Describe how modeled time element loss costs take into consideration the damage (including damage due to storm surge, flood, and wind) to local and regional infrastructure.
Storm surge and flood damage are not modeled explicitly in USWIND. However, to the extent that such perils (in addition to wind damage) affect time element claims through damage to the infrastructure, they are implicitly included in the USWIND time element vulnerability functions.
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A-10 Output Ranges
A. Output ranges shall be logical and any deviations supported.
The output ranges produced by the model are logical and any deviations are supported. B. All other factors held constant, output ranges produced by the model shall reflect lower loss costs for:
1. masonry construction versus frame construction, The output ranges produced by the model reflect lower loss costs for masonry construction versus frame construction, subject to the discussion in Disclosure 1 below. 2. personal residential risk exposure versus mobile home risk exposure, The output ranges produced by the model reflect lower loss costs for personal residential risk exposure versus mobile home risk exposure, subject to the discussion in Disclosure 1 below. 3. in general, inland counties versus coastal counties, and The output ranges produced by the model reflect lower loss costs, in general, for inland counties versus coastal counties. 4. in general, northern counties versus southern counties. The output ranges produced by the model reflect lower loss costs, in general, for northern counties versus southern counties.
Disclosures
1. Provide an explanation for all anomalies in the loss costs that are not consistent with the requirements of this Standard.
All the loss costs shown in Forms A-6 are consistent with the requirements of this standard, except:
• Statewide weighted average loss costs for masonry are higher than the corresponding statewide weighted average loss costs for frame for all coverage types, policy types, and deductibles in Form A-6. This is due to the masonry exposures generally being more heavily weighted than the frame exposures in areas having higher levels of hazard.
• Weighted average loss costs for masonry owners are equal to or higher than the corresponding maximum/minimum loss costs for frame owners for certain coverage types and deductibles for a number of counties in Form A-6. This is due to variations in secondary structural modifiers and a few ZIP Codes whose exposures lack frame or masonry coverages. Weighted average loss costs for masonry renters and condos are equal to or higher than the corresponding weighted average loss costs for frame 126 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
renters and condos for certain coverage types and deductibles for a number of counties in Form A-6. All of these situations are due to the masonry exposures in these counties being more heavily weighted than the frame exposures in areas having higher levels of hazard and the variations of secondary structural modifiers and age groups.
2. Provide an explanation of the differences in the personal residential output ranges using the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data between the previously accepted submission and the current submission.
The following changes were made to the model between the previously accepted submission (Florida Hurricane Model 2009) and the current submission (Florida Hurricane Model 2011a):
1. The probabilistic hurricane database was regenerated to be consistent with the National Hurricane Center’s HURDAT data set as of June 7, 2009, and to additionally include the 2009 hurricane season.
2. The model was updated to use current scientifically accepted boundary layer methods and inflow angle to incorporate local friction and transitions between local land use / land cover categories, including sea-to-land transition.
3. The ZIP Code database has been updated to December 2009.
4. Land use and land cover data from the Florida Water Management District 2004-2008 was used to resolve the following land use categories: communication, utility, and transportation.
5. The incorporation of default structure types for North Florida and South Florida.
3. Provide a completed Form A-6, Personal Residential Output Ranges using the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data.
See Form A-6.
4. Provide a completed Form A-7, Percentage Change in Personal Residential Output Ranges using the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data.
See Form A-7.
5. Provide a completed Form A-8, Percentage Change in Personal Residential Output Ranges by County using the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data. 127 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
See Form A-8.
6. Provide a sample output range report produced by the model for commercial residential loss costs.
Output range reports for commercial residential loss costs have the same format as those for personal residential loss costs. See Standard A-5.
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A-11 Probable Maximum Loss
The methods, data, and assumptions used in the estimation of probable maximum loss levels shall be actuarially sound.
The methods, data, and assumptions used in the estimation of probable maximum loss levels are actuarially sound.
Disclosures
1. Describe how the model produces probable maximum loss levels.
The model simulates 150,000 years of North Atlantic hurricane events. Occurrence exceedance probabilities are based on the maximum loss within each of the simulated years; annual aggregate exceedance probabilities are based on the sum of the losses within each of the simulated years.
2. Provide citations to published papers, if any that were used to estimate probable maximum loss levels.
No specific papers were used as the basis for the estimation of probable maximum loss levels.
3. Provide a completed Form A-9, Probable Maximum Loss for Florida.
See Form A-9.
4. Describe how the probable maximum loss levels produced by the model include the effects of personal and commercial residential insurance coverage.
Probable maximum loss levels produced by the model incorporate damage and insured loss calculations for both personal and commercial residential exposures. The methodology to compute probable maximum loss levels is consistent between personal and commercial residential exposures, and is based on a 150,000 year simulation.
5. Explain any differences between the values provided on Form A-9 and those provided on Form S-2.
The FHCF results on Form A-9 represent zero deductible losses; the FHCF results on Form S-2 represent insured losses incorporating policy conditions.
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Form A-1: Personal Residential Loss Costs
A. Provide the expected annual personal residential loss costs by construction type and coverage for each ZIP Code in the sample data set named “FormA1Input09.xls.” Refer to assumption information for “FormA1Input09.xls” provided under Submission Data. Loss costs shall be rounded to six decimal places. There are 1,479 ZIP Codes and three construction types; therefore, the completed file should have 4,437 records in total. The following is a description of the requested file layout. Follow the instructions on Form A-1 below and in the Submission Data description. Note that fields 2-9 are the exposure fields from the sample data set. Fields 10-13 are for the loss costs (net of deductibles).
B. If there are ZIP Codes in the sample data set that the model does not recognize as “valid,” provide a list in the submission document of such ZIP Codes and provide either a) the new ZIP Code to which the original one was mapped, or b) an indication that the insured values from this ZIP Code were not modeled.
Loss cost data shall be provided for all ZIP Codes given in the sample data set. That is, if no losses were modeled, the record should still be included in the completed file with loss cost of zero, and if a ZIP Code was mapped to a new one, the resulting loss costs should be reported with the original ZIP Code.
C. Provide the results on CD in Excel and PDF format using the following file layout. The file name shall include the abbreviated name of the modeling organization, the standards year, and the form name. The first row of the file shall contain the field names below. No. Field Name Description Exposure Fields from Sample Data Set 1 Analysis Date Date of Analysis – YYYY/MM/DD 2 County Code FIPS County Code 3 ZIP Code 5-digit ZIP Code 4 Construction Type Use the following: 1 = Wood Frame, 2 = Masonry, 3 = Mobile Home 5 Annual Deductible 2% (of the Structure Value) policy deductible for each record (i.e., 0.02*$100,000) 6 Structure Value $100,000 for each record 7 Appurtenant Structures Value $10,000 for each record 8 Contents Value $50,000 for each record 9 Additional Living Expense Value $20,000 for each record Loss Costs (net of deductibles) 10 Structure Loss Cost Projected expected annual loss cost for structure divided by the structure value modeled for each record ($100,000) 11 Appurtenant Structures Loss Cost Projected expected annual loss cost for appurtenant structures divided by the appurtenant structures value modeled for each record ($10,000) 12 Contents Loss Cost Projected expected annual loss cost for contents divided by the contents value modeled for each record ($50,000) 13 Additional Living Expense Loss Cost Projected expected annual loss cost for additional living expense divided by the additional living expense value modeled for each record ($20,000) 130 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
All deductibles are a percentage of the Structure Value and are policy-level deductibles; however, for reporting purposes, the policy deductible shall be pro-rated to the individual coverage losses in proportion to the loss. The default all-other perils deductible is $500.
Example Assume that a model analyzing Wood Frame properties in ZIP Code 33102 (Miami-Dade County) estimated the following: Field Name Value Analysis Date 1999/11/15 County Code Miami-Dade County = 86 ZIP Code 33102 Construction Type Wood Frame = 1 Annual Deductible 2% = 0.02*$100,000 = $2,000 Structure Value $100,000 Appurtenant Structures Value $10,000 Contents Value $50,000 Additional Living Expense Value $20,000 Structure Loss Cost* $10,000 Appurtenant Structures Loss Cost* $1,000 Contents Loss Cost* $2,500 Additional Living Expense Loss Cost* $500 *Represents first dollar losses (i.e., prior to application of deductibles)
The $2,000 hurricane deductible would be applied as follows: Annual Deductible 2% = 0.02*$100,000=$2,000 Structure Loss Cost $10,000-[($10,000÷$14,000)x$2,000]=$8,571.43 Appurtenant Structures Loss Cost $1,000-[($1,000÷$14,000)x$2,000]=$857.14 Contents Loss Cost $2,500-[($2,500÷$14,000)x$2,000]=$2,142.86 Additional Living Expense Loss Cost $500-[($500÷$14,000)x$2,000]=$428.57 The reported Form A-1 data are shown below: Field Name Value Analysis Date 1999/11/15 County Code Miami-Dade County = 86 ZIP Code 33102 Construction Type Wood Frame = 1 Annual Deductible 2% = 0.02 Structure Value $100,000 Appurtenant Structures Value $10,000 Contents Value $50,000 Additional Living Expense Value $20,000 Structure Loss Cost $8,571.43÷$100,000 = 0.085714 Appurtenant Structures Loss Cost $857.14÷$10,000 = 0.085714 Contents Loss Cost $2,142.86÷$50,000 = 0.042857 Additional Living Expense Loss Cost $428.57÷$20,000 = 0.021429
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Based on the above information, the data shall be reported in the following format: 1999/11/15,86,33102,1,0.02,100000,10000,50000,20000,0.085714,0.085714,0.042857,0.021429 This information is provided in the file 2009FormA1_EQECAT_28March2011.xls.
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Form A-2: Zero Deductible Personal Residential Loss Costs by ZIP Code
Provide a map color-coded by ZIP Code (with a minimum of 6 value ranges) displaying zero deductible personal residential loss costs for frame, masonry, and mobile home.
Thematic maps displaying zero deductible loss costs by 5-digit ZIP Code for frame, masonry, and mobile home are provided in Figures 26 to 28.
Figure 26. Ground-up Loss Costs for Frame Structures
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(FORM A-2 CONTINUED)
Figure 27. Ground-up Loss Costs for Masonry Structures
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(FORM A-2 CONTINUED)
Figure 28. Ground-up Loss Costs for Mobile Home Structures
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Form A-3: Base Hurricane Storm Statewide Loss Costs
A. Provide the total insured loss and the dollar contribution to the average annual loss assuming personal residential zero deductible policies from each specific hurricane in the Base Hurricane Storm Set, as defined in Standard M-1, for the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe.” B. Provide the total insured loss and the dollar contribution to the average annual loss assuming commercial residential zero deductible policies from each specific hurricane in the Base Hurricane Storm Set, as defined in Standard M-1, for the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal and commercial residential exposure data, type of business 1, found in the file named “hlpm2007c.exe.”
The table below contains the minimum number of hurricanes from HURDAT to be included in the Base Hurricane Storm Set. Each hurricane has been assigned an ID number. Additional hurricanes included in the model’s Base Hurricane Storm Set shall be added to the table below and assigned an ID number as the hurricane falls within the given ID numbers.
C. Provide this form on CD in Excel format. The file name shall include the abbreviated name of the modeling organization, the standards year, and the form name. A hard copy of Form A-3 shall be included in the submission. Total Total Personal Commercial Residential Residential Insured Insured Losses Dollar Losses Dollar ID Date Year Name (1000$) Contribution (1000$) Contribution 005 8/15/1901 1901 NoName 4-1901 227,326 2,067 19,378 176 010 9/12/1903 1903 NoName 3-1903 2,986,517 27,150 508,024 4,618 015 10/17/1904 1904 NoName 3-1904 603,104 5,483 158,436 1,440 020 6/18/1906 1906 NoName 2-1906 2,176,717 19,788 467,229 4,248 025 9/27/1906 1906 NoName 6-1906 1,064,475 9,677 72,188 656 030 10/17/1906 1906 NoName 8-1906 1,784,507 16,223 424,566 3,860 035 10/11/1909 1909 NoName 10-1909 1,027,491 9,341 226,925 2,063 040 10/17/1910 1910 NoName 5-1910 8,430,417 76,640 1,264,956 11,500 045 8/12/1911 1911 NoName 2-1911 392,817 3,571 29,623 269 050 9/14/1912 1912 NoName 4-1912 41,612 378 2,256 21 055 8/1/1915 1915 NoName 1-1915 409,619 3,724 36,047 328 060 9/4/1915 1915 NoName 4-1915 115,137 1,047 5,689 52 065 7/6/1916 1916 NoName 2-1916 682,858 6,208 49,237 448 070 10/18/1916 1916 NoName 14-1916 749,969 6,818 48,349 440 075 9/29/1917 1917 NoName 4-1917 2,490,007 22,636 270,897 2,463 080 9/10/1919 1919 NoName 2-1919 6,270,728 57,007 1,062,780 9,662 085 10/25/1921 1921 NoName 6-1921 10,973,579 99,760 1,218,834 11,080 090 9/15/1924 1924 NoName 4-1924 57,119 519 2,863 26 095 10/21/1924 1924 NoName 7-1924 768,924 6,990 173,722 1,579
136 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Total Total Personal Commercial Residential Residential Insured Insured Losses Dollar Losses Dollar ID Date Year Name (1000$) Contribution (1000$) Contribution 100 12/1/1925 1925 NoName 2-1925 671,360 6,103 78,275 712 105 7/28/1926 1926 NoName 1-1926 3,701,273 33,648 386,266 3,512 110 9/18/1926 1926 NoName 6-1926 42,965,090 390,592 10,952,034 99,564 115 8/8/1928 1928 NoName 1-1928 1,983,294 18,030 294,763 2,680 120 9/17/1928 1928 NoName 4-1928 24,868,249 226,075 3,035,997 27,600 125 9/28/1929 1929 NoName 2-1929 4,759,891 43,272 840,204 7,638 130 9/1/1932 1932 NoName 3-1932 457,824 4,162 56,157 511 135 7/30/1933 1933 NoName 5-1933 455,596 4,142 46,402 422 140 9/4/1933 1933 NoName 12-1933 7,266,833 66,062 1,034,476 9,404 145 9/3/1935 1935 NoName 2-1935 5,063,211 46,029 870,383 7,913 150 11/4/1935 1935 NoName 6-1935 1,557,478 14,159 416,187 3,784 155 7/31/1936 1936 NoName 5-1936 1,155,968 10,509 130,772 1,189 160 8/11/1939 1939 NoName 2-1939 901,744 8,198 68,769 625 165 10/6/1941 1941 NoName 5-1941 10,927,487 99,341 1,977,319 17,976 170 10/19/1944 1944 NoName 11-1944 9,446,917 85,881 1,209,128 10,992 175 6/24/1945 1945 NoName 1-1945 1,079,027 9,809 56,674 515 180 9/16/1945 1945 NoName 9-1945 12,403,218 112,757 1,859,665 16,906 185 10/8/1946 1946 NoName 5-1946 802,790 7,298 97,184 883 190 9/17/1947 1947 NoName 4-1947 37,987,818 345,344 7,966,017 72,418 195 10/12/1947 1947 NoName 8-1947 1,212,224 11,020 288,168 2,620 200 9/22/1948 1948 NoName 7-1948 1,834,449 16,677 303,476 2,759 205 10/5/1948 1948 NoName 8-1948 474,271 4,312 107,024 973 210 8/27/1949 1949 NoName 2-1949 15,381,108 139,828 2,356,737 21,425 215 8/31/1950 1950 Baker-1950 162,933 1,481 10,459 95 220 9/5/1950 1950 Easy-1950 8,314,349 75,585 681,009 6,191 225 10/18/1950 1950 King-1950 5,767,256 52,430 1,669,819 15,180 230 9/26/1953 1953 Florence-1953 338,117 3,074 39,114 356 235 9/25/1956 1956 Flossy-1956 559,188 5,084 62,214 566 240 9/10/1960 1960 Donna-1960 12,282,041 111,655 1,671,037 15,191 245 8/27/1964 1964 Cleo-1964 4,018,379 36,531 925,529 8,414 250 9/10/1964 1964 Dora-1964 2,776,235 25,238 168,356 1,531 255 10/14/1964 1964 Isbell-1964 4,462,449 40,568 886,494 8,059 260 9/8/1965 1965 Betsy-1965 5,632,142 51,201 1,165,894 10,599 265 6/9/1966 1966 Alma-1966 557,887 5,072 61,521 559 270 10/4/1966 1966 Inez-1966 298,132 2,710 59,211 538 275 10/19/1968 1968 Gladys-1968 1,877,467 17,068 117,591 1,069 280 6/19/1972 1972 Agnes-1972 69,124 628 3,741 34 285 9/23/1975 1975 Eloise-1975 703,472 6,395 97,661 888 290 9/4/1979 1979 David-1979 3,995,294 36,321 631,550 5,741 295 9/13/1979 1979 Frederic-1979 556,208 5,056 40,111 365 300 9/2/1985 1985 Elena-1985 2,286,449 20,786 195,958 1,781 305 11/21/1985 1985 Kate-1985 320,325 2,912 16,002 145 310 10/21/1987 1987 Floyd-1987 38,492 350 5,802 53 315 8/24/1992 1992 Andrew-1992 22,623,830 205,671 3,299,790 29,998 320 8/2/1995 1995 Erin-1995 1,052,269 9,566 83,907 763 325 10/4/1995 1995 Opal-1995 1,318,634 11,988 114,166 1,038 330 7/19/1997 1997 Danny-1997 141,286 1,284 7,278 66 137 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Total Total Personal Commercial Residential Residential Insured Insured Losses Dollar Losses Dollar ID Date Year Name (1000$) Contribution (1000$) Contribution 335 9/3/1998 1998 Earl-1998 145,221 1,320 8,834 80 340 9/28/1998 1998 Georges-1998 363,356 3,303 51,437 468 345 10/15/1999 1999 Irene-1999 2,571,969 23,382 517,502 4,705 350 8/13/2004 2004 Charley-2004 9,614,666 87,406 745,445 6,777 355 9/5/2004 2004 Frances-2004 8,348,772 75,898 1,050,669 9,552 360 9/16/2004 2004 Ivan-2004 4,622,589 42,024 350,311 3,185 365 9/26/2004 2004 Jeanne-2004 8,197,337 74,521 780,288 7,094 370 7/10/2005 2005 Dennis-2005 1,310,660 11,915 80,176 729 375 8/26/2005 2005 Katrina-2005 1,566,116 14,237 450,821 4,098 380 9/21/2005 2005 Rita-2005 159,124 1,447 17,704 161 385 10/24/2005 2005 Wilma-2005 10,260,171 93,274 2,165,742 19,689 Other hurricanes included: 028 9/21/1909 1909 NoName 8-1909 104,589 951 5,889 54 111 10/21/1926 1926 NoName 10-1926 1,666,455 15,150 425,944 3,872 141 10/5/1933 1933 NoName 18-1933 531,831 4,835 105,593 960 143 6/16/1934 1934 NoName 2-1934 15,840 144 546 5 241 9/15/1960 1960 Ethel-1960 4,698 43 137 1 276 8/18/1969 1969 Camille-1969 32,798 298 1,741 16 299 9/25/1985 1985 Bob-1985 100,617 915 7,718 70 379 9/8/2005 2005 Ophelia-2005 138,829 1,262 8,531 78 Total 3,259,251 Total 538,757
Note: Total dollar contributions should agree with the total average annual zero deductible statewide loss costs provided in Form S-5 for current year.
138 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-4: Hurricane Andrew (1992) Percent of Losses
A. Provide the percentage of personal residential zero deductible losses, rounded to four decimal places, from Hurricane Andrew (1992) for each affected ZIP Code. Include all ZIP Codes where losses are equal to or greater than $500,000.
See the table below. B. Provide the percentage of commercial residential zero deductible losses, rounded to four decimal places, from Hurricane Andrew (1992) for each affected ZIP Code. Include all ZIP Codes where losses are equal to or greater than $500,000.
See the table below. C. Provide a map color-coded by ZIP Code depicting the percentage of total personal residential losses from Hurricane Andrew below latitude 27o N 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%
See Figure 29 below. D. Provide a map color-coded by ZIP Code depicting the percentage of total commercial residential losses from Hurricane Andrew below latitude 27o N 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%
See Figure 30 below. E. Provide this Form on CD in Excel format. The file name shall include the abbreviated name of the modeling organization, the standards year, and the form name. A hard copy of Form A-4 shall be included in the submission.
139 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Rather than using directly a published windfield for Hurricane Andrew (1992), the winds underlying the loss cost calculations must be produced by the model being evaluated and should be the same hurricane parameters as used in completing Form A-3. Use the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe.” for personal residential losses and the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal and commercial residential exposure data, type of business 1, found in the file named “hlpm2007c.exe” for commercial residential losses.
140 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-4 CONTINUED)
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33004 7,908 0.0350% 3,376 0.1027% 33009 25,286 0.1118% 41,390 1.2596% 33010 32,874 0.1454% 5,140 0.1564% 33012 42,500 0.1880% 14,195 0.4320% 33013 34,546 0.1528% 1,408 0.0428% 33014 43,792 0.1937% 12,648 0.3849% 33015 35,201 0.1557% 6,641 0.2021% 33016 35,554 0.1573% 16,266 0.4950% 33018 46,484 0.2056% 3,741 0.1138% 33019 29,835 0.1320% 19,146 0.5827% 33020 22,179 0.0981% 9,374 0.2853% 33021 33,783 0.1494% 5,987 0.1822% 33023 51,340 0.2271% 1,436 0.0437% 33024 36,672 0.1622% 2,129 0.0648% 33025 27,540 0.1218% 7,768 0.2364% 33026 25,060 0.1108% 1,939 0.0590% 33027 44,939 0.1988% 1,184 0.0360% 33028 22,602 0.1000% 0 0.0000% 33029 54,369 0.2405% 0 0.0000% 33030 472,710 2.0907% 37,750 1.1488% 33031 168,278 0.7443% 0 0.0000% 33032 321,701 1.4228% 11,069 0.3368% 33033 362,233 1.6021% 12,195 0.3711% 33034 90,943 0.4022% 17,860 0.5435% 33035 56,846 0.2514% 12,080 0.3676% 33036 1,574 0.0070% 0 0.0000% 33037 32,890 0.1455% 4,974 0.1514% 33054 16,755 0.0741% 867 0.0264% 33055 29,953 0.1325% 0 0.0000% 33056 22,875 0.1012% 827 0.0252% 33060 7,668 0.0339% 2,313 0.0704% 33062 11,055 0.0489% 14,444 0.4396% 33063 10,527 0.0466% 3,206 0.0976% 33064 12,982 0.0574% 2,473 0.0753% 33065 8,758 0.0387% 2,317 0.0705% 33066 2,941 0.0130% 4,160 0.1266% 33067 9,633 0.0426% 0 0.0000% 33068 9,463 0.0419% 1,078 0.0328% 33069 2,947 0.0130% 3,689 0.1123% 33070 3,052 0.0135% 0 0.0000% 33071 12,183 0.0539% 1,111 0.0338% 33073 5,702 0.0252% 518 0.0158%
141 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33076 11,096 0.0491% 0 0.0000% 33109 71,973 0.3183% 55,157 1.6786% 33116 0 0.0000% 729 0.0222% 33122 0 0.0000% 963 0.0293% 33125 111,812 0.4945% 24,336 0.7406% 33126 68,404 0.3025% 40,019 1.2179% 33127 47,973 0.2122% 7,029 0.2139% 33128 5,860 0.0259% 3,198 0.0973% 33129 132,896 0.5878% 133,869 4.0740% 33130 22,058 0.0976% 22,701 0.6909% 33131 28,580 0.1264% 75,230 2.2895% 33132 4,731 0.0209% 34,690 1.0557% 33133 653,693 2.8912% 100,103 3.0464% 33134 347,944 1.5389% 30,547 0.9296% 33135 80,298 0.3552% 18,329 0.5578% 33136 10,426 0.0461% 17,080 0.5198% 33137 45,057 0.1993% 22,813 0.6943% 33138 93,754 0.4147% 28,478 0.8666% 33139 165,235 0.7308% 257,594 7.8393% 33140 226,978 1.0039% 147,646 4.4932% 33141 71,830 0.3177% 81,578 2.4826% 33142 81,470 0.3603% 3,109 0.0946% 33143 939,055 4.1533% 81,581 2.4827% 33144 112,772 0.4988% 3,993 0.1215% 33145 219,141 0.9692% 13,458 0.4096% 33146 407,534 1.8025% 19,560 0.5953% 33147 60,862 0.2692% 1,496 0.0455% 33149 551,053 2.4372% 299,553 9.1162% 33150 34,645 0.1532% 2,676 0.0814% 33153 0 0.0000% 2,877 0.0876% 33154 62,183 0.2750% 70,620 2.1492% 33155 370,456 1.6385% 15,532 0.4727% 33156 2,214,890 9.7962% 103,731 3.1568% 33157 1,484,619 6.5663% 79,824 2.4293% 33158 481,620 2.1301% 19,519 0.5940% 33160 48,025 0.2124% 97,103 2.9551% 33161 47,936 0.2120% 13,274 0.4039% 33162 35,530 0.1571% 6,973 0.2122% 33165 423,914 1.8749% 10,635 0.3236% 33166 57,611 0.2548% 9,277 0.2823% 33167 21,137 0.0935% 1,374 0.0418% 33168 28,976 0.1282% 0 0.0000% 33169 31,782 0.1406% 2,823 0.0859%
142 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33170 156,365 0.6916% 5,150 0.1567% 33172 33,330 0.1474% 62,368 1.8980% 33173 649,716 2.8736% 76,818 2.3378% 33174 97,789 0.4325% 19,701 0.5996% 33175 482,323 2.1333% 28,556 0.8690% 33176 1,844,057 8.1560% 114,177 3.4747% 33177 657,173 2.9066% 6,450 0.1963% 33178 110,990 0.4909% 29,776 0.9062% 33179 33,039 0.1461% 14,326 0.4360% 33180 41,299 0.1827% 62,304 1.8961% 33181 31,915 0.1412% 18,558 0.5648% 33182 98,443 0.4354% 2,108 0.0642% 33183 435,812 1.9275% 65,118 1.9817% 33184 117,305 0.5188% 4,889 0.1488% 33185 321,951 1.4240% 1,082 0.0329% 33186 1,638,955 7.2489% 102,850 3.1300% 33187 369,800 1.6356% 0 0.0000% 33189 426,277 1.8854% 36,629 1.1147% 33190 83,414 0.3689% 3,197 0.0973% 33193 497,977 2.2025% 85,988 2.6168% 33194 45,011 0.1991% 0 0.0000% 33196 1,236,042 5.4669% 65,658 1.9982% 33197 671 0.0030% 0 0.0000% 33256 833 0.0037% 0 0.0000% 33301 16,043 0.0710% 3,478 0.1059% 33304 8,790 0.0389% 6,481 0.1972% 33305 8,809 0.0390% 2,375 0.0723% 33306 2,678 0.0118% 798 0.0243% 33308 24,342 0.1077% 15,335 0.4667% 33309 9,282 0.0411% 1,981 0.0603% 33311 12,387 0.0548% 2,303 0.0701% 33312 27,858 0.1232% 1,711 0.0521% 33313 8,161 0.0361% 4,355 0.1325% 33314 8,637 0.0382% 1,941 0.0591% 33315 7,699 0.0341% 1,593 0.0485% 33316 15,096 0.0668% 8,509 0.2590% 33317 16,695 0.0738% 1,508 0.0459% 33319 10,731 0.0475% 4,528 0.1378% 33321 10,140 0.0448% 4,370 0.1330% 33322 15,119 0.0669% 4,476 0.1362% 33323 8,548 0.0378% 0 0.0000% 33324 16,549 0.0732% 5,446 0.1657% 33325 17,192 0.0760% 558 0.0170%
143 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33326 19,193 0.0849% 2,632 0.0801% 33327 17,634 0.0780% 0 0.0000% 33328 24,185 0.1070% 1,030 0.0313% 33330 18,661 0.0825% 0 0.0000% 33331 26,711 0.1181% 0 0.0000% 33332 10,633 0.0470% 0 0.0000% 33334 11,385 0.0504% 2,804 0.0853% 33351 7,405 0.0327% 1,395 0.0425% 33401 1,067 0.0047% 792 0.0241% 33404 1,058 0.0047% 537 0.0163% 33405 2,505 0.0111% 0 0.0000% 33406 1,633 0.0072% 0 0.0000% 33407 1,159 0.0051% 0 0.0000% 33408 2,677 0.0118% 1,242 0.0378% 33409 1,051 0.0046% 0 0.0000% 33410 2,473 0.0109% 0 0.0000% 33411 4,343 0.0192% 0 0.0000% 33412 1,207 0.0053% 0 0.0000% 33413 803 0.0036% 0 0.0000% 33414 5,924 0.0262% 0 0.0000% 33415 1,552 0.0069% 632 0.0192% 33417 1,067 0.0047% 777 0.0237% 33418 3,786 0.0167% 0 0.0000% 33426 2,922 0.0129% 0 0.0000% 33428 9,739 0.0431% 1,374 0.0418% 33431 5,819 0.0257% 1,932 0.0588% 33432 11,652 0.0515% 4,538 0.1381% 33433 11,460 0.0507% 2,647 0.0805% 33434 6,524 0.0289% 2,227 0.0678% 33435 3,314 0.0147% 1,687 0.0513% 33436 6,186 0.0274% 1,126 0.0343% 33437 9,607 0.0425% 1,321 0.0402% 33440 679 0.0030% 0 0.0000% 33441 5,237 0.0232% 2,217 0.0675% 33442 5,278 0.0233% 3,894 0.1185% 33444 3,333 0.0147% 915 0.0279% 33445 6,163 0.0273% 2,421 0.0737% 33446 5,648 0.0250% 1,708 0.0520% 33455 1,825 0.0081% 0 0.0000% 33458 2,662 0.0118% 0 0.0000% 33460 3,201 0.0142% 582 0.0177% 33461 1,693 0.0075% 567 0.0173% 33462 4,196 0.0186% 825 0.0251%
144 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33463 4,033 0.0178% 685 0.0208% 33467 6,954 0.0308% 0 0.0000% 33469 1,753 0.0078% 0 0.0000% 33470 1,921 0.0085% 0 0.0000% 33477 2,002 0.0089% 935 0.0284% 33478 902 0.0040% 0 0.0000% 33480 10,599 0.0469% 2,636 0.0802% 33483 5,240 0.0232% 3,111 0.0947% 33484 4,609 0.0204% 1,843 0.0561% 33486 6,548 0.0290% 881 0.0268% 33487 8,662 0.0383% 4,557 0.1387% 33496 11,693 0.0517% 1,181 0.0359% 33498 5,605 0.0248% 0 0.0000% 33901 938 0.0041% 0 0.0000% 33903 1,786 0.0079% 0 0.0000% 33904 5,118 0.0226% 549 0.0167% 33905 1,737 0.0077% 0 0.0000% 33907 971 0.0043% 0 0.0000% 33908 4,552 0.0201% 1,253 0.0381% 33909 1,193 0.0053% 0 0.0000% 33912 3,460 0.0153% 0 0.0000% 33913 1,542 0.0068% 0 0.0000% 33914 4,572 0.0202% 0 0.0000% 33917 2,005 0.0089% 0 0.0000% 33919 2,738 0.0121% 800 0.0244% 33921 2,215 0.0098% 0 0.0000% 33924 1,576 0.0070% 0 0.0000% 33928 3,446 0.0152% 783 0.0238% 33931 2,635 0.0117% 1,010 0.0307% 33935 707 0.0031% 0 0.0000% 33936 2,061 0.0091% 0 0.0000% 33947 599 0.0026% 0 0.0000% 33948 631 0.0028% 0 0.0000% 33950 1,374 0.0061% 0 0.0000% 33952 973 0.0043% 0 0.0000% 33955 630 0.0028% 0 0.0000% 33956 980 0.0043% 0 0.0000% 33957 6,338 0.0280% 1,688 0.0514% 33967 1,112 0.0049% 0 0.0000% 33971 2,050 0.0091% 0 0.0000% 33972 983 0.0043% 0 0.0000% 33981 585 0.0026% 0 0.0000% 33983 572 0.0025% 0 0.0000%
145 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Hurricane Andrew Losses by ZIP Code
Personal Residential Commercial Residential ZIP Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33990 2,616 0.0116% 0 0.0000% 33991 1,332 0.0059% 0 0.0000% 33993 1,381 0.0061% 0 0.0000% 34102 19,231 0.0851% 2,881 0.0877% 34103 9,033 0.0399% 6,389 0.1944% 34104 9,513 0.0421% 3,113 0.0947% 34105 9,189 0.0406% 1,956 0.0595% 34108 12,094 0.0535% 3,467 0.1055% 34109 8,686 0.0384% 2,170 0.0660% 34110 8,194 0.0362% 2,282 0.0695% 34112 14,085 0.0623% 4,936 0.1502% 34113 13,251 0.0586% 2,960 0.0901% 34114 21,250 0.0940% 6,079 0.1850% 34116 6,855 0.0303% 730 0.0222% 34117 4,408 0.0195% 0 0.0000% 34119 12,365 0.0547% 1,544 0.0470% 34120 8,177 0.0362% 0 0.0000% 34134 7,616 0.0337% 1,464 0.0445% 34135 8,920 0.0395% 1,521 0.0463% 34138 1,251 0.0055% 0 0.0000% 34139 2,485 0.0110% 0 0.0000% 34140 1,293 0.0057% 0 0.0000% 34145 111,925 0.4950% 55,494 1.6888% 34223 666 0.0029% 0 0.0000% 34224 901 0.0040% 0 0.0000% 34238 623 0.0028% 0 0.0000% 34275 551 0.0024% 0 0.0000% 34286 535 0.0024% 0 0.0000% 34287 907 0.0040% 0 0.0000% 34293 874 0.0039% 0 0.0000% 34952 1,154 0.0051% 0 0.0000% 34957 751 0.0033% 0 0.0000% 34974 623 0.0028% 0 0.0000% 34990 1,342 0.0059% 0 0.0000% 34996 860 0.0038% 0 0.0000% 34997 1,733 0.0077% 0 0.0000%
146 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-4 CONTINUED)
Figure 29. Hurricane Andrew % of Loss for FHCF2007 Personal Residential by ZIP Code
Figure 30. Hurricane Andrew % of Loss for FHCF2007 Commercial Residential by ZIP Code 147 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-5: Cumulative Losses from the 2004 Hurricane Season
A. Provide the percentage of personal residential zero deductible cumulative losses, rounded to four decimal places, from Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) for each affected ZIP Code. Include all ZIP Codes where losses are equal to or greater than $500,000.
See the table below. B. Provide the percentage of personal residential zero deductible cumulative losses, rounded to four decimal places, from Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) for each affected ZIP Code. Include all ZIP Codes where losses are equal to or greater than $500,000.
See the table below. C. Provide maps color-coded by ZIP Code depicting the percentage of total personal residential losses from each hurricane, Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) and for the cumulative 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%
See Figures 31 to 35 below. D. Provide maps color-coded by ZIP Code depicting the percentage of total commercial residential losses from each hurricane, Hurricane Charley (2004), Hurricane Frances (2004), Hurricane Ivan (2004), and Hurricane Jeanne (2004) and for the cumulative 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%
See Figures 36 to 40 below. 148 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
E. Provide this Form on CD in Excel format. The file name shall include the abbreviated name of the modeling organization, the standards year, and the form name. A hard copy of Form A- 5 shall be included in the submission.
Rather than using directly a specific published windfield, the winds underlying the loss cost calculations must be produced by the model being evaluated and should be the same hurricane parameters as used in completing Form A-3. Use the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe.” for personal residential losses and the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal and commercial residential exposure data, type of business 1, found in the file named “hlpm2007c.exe” for commercial residential losses.
149 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32003 5,001 0.0163% 0 0.0000% 32008 728 0.0024% 0 0.0000% 32011 727 0.0024% 0 0.0000% 32024 3,260 0.0106% 0 0.0000% 32025 2,081 0.0068% 0 0.0000% 32033 1,166 0.0038% 0 0.0000% 32034 6,239 0.0203% 0 0.0000% 32038 1,553 0.0051% 0 0.0000% 32040 545 0.0018% 0 0.0000% 32043 4,181 0.0136% 0 0.0000% 32054 1,075 0.0035% 0 0.0000% 32055 2,254 0.0073% 0 0.0000% 32060 2,778 0.0090% 0 0.0000% 32063 532 0.0017% 0 0.0000% 32065 2,794 0.0091% 0 0.0000% 32068 3,883 0.0126% 0 0.0000% 32071 596 0.0019% 0 0.0000% 32073 5,137 0.0167% 0 0.0000% 32080 14,933 0.0486% 3,021 0.1049% 32082 21,327 0.0694% 1,424 0.0494% 32084 9,053 0.0295% 803 0.0279% 32086 9,115 0.0297% 586 0.0203% 32091 1,433 0.0047% 0 0.0000% 32092 5,469 0.0178% 0 0.0000% 32095 2,053 0.0067% 0 0.0000% 32097 1,145 0.0037% 0 0.0000% 32102 1,279 0.0042% 0 0.0000% 32110 2,072 0.0067% 0 0.0000% 32112 1,283 0.0042% 0 0.0000% 32113 1,354 0.0044% 0 0.0000% 32114 10,398 0.0338% 2,686 0.0932% 32117 12,175 0.0396% 998 0.0346% 32118 20,497 0.0667% 17,282 0.5998% 32119 21,419 0.0697% 2,329 0.0809% 32124 2,259 0.0074% 0 0.0000% 32127 37,209 0.1211% 3,602 0.1250% 32128 18,631 0.0606% 503 0.0175% 32129 14,665 0.0477% 606 0.0210% 32130 2,529 0.0082% 0 0.0000% 32131 1,152 0.0037% 0 0.0000% 32132 9,580 0.0312% 0 0.0000% 32134 1,027 0.0033% 0 0.0000% 150 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32136 10,123 0.0329% 802 0.0278% 32137 29,401 0.0957% 1,798 0.0624% 32139 567 0.0018% 0 0.0000% 32141 23,248 0.0756% 0 0.0000% 32145 1,177 0.0038% 0 0.0000% 32148 1,454 0.0047% 0 0.0000% 32159 55,474 0.1805% 0 0.0000% 32162 58,225 0.1894% 0 0.0000% 32164 16,527 0.0538% 0 0.0000% 32168 24,635 0.0802% 556 0.0193% 32169 22,071 0.0718% 10,999 0.3817% 32174 51,760 0.1684% 891 0.0309% 32176 22,785 0.0741% 3,940 0.1367% 32177 2,746 0.0089% 0 0.0000% 32179 3,164 0.0103% 0 0.0000% 32180 1,020 0.0033% 0 0.0000% 32181 569 0.0019% 0 0.0000% 32189 1,035 0.0034% 0 0.0000% 32195 2,924 0.0095% 0 0.0000% 32204 557 0.0018% 0 0.0000% 32205 3,314 0.0108% 0 0.0000% 32206 939 0.0031% 0 0.0000% 32207 3,692 0.0120% 0 0.0000% 32208 1,904 0.0062% 0 0.0000% 32209 1,396 0.0045% 0 0.0000% 32210 4,261 0.0139% 0 0.0000% 32211 2,561 0.0083% 0 0.0000% 32216 3,096 0.0101% 0 0.0000% 32217 2,346 0.0076% 0 0.0000% 32218 3,682 0.0120% 0 0.0000% 32219 597 0.0019% 0 0.0000% 32220 913 0.0030% 0 0.0000% 32221 1,932 0.0063% 0 0.0000% 32222 676 0.0022% 0 0.0000% 32223 4,500 0.0146% 0 0.0000% 32224 4,911 0.0160% 0 0.0000% 32225 8,466 0.0275% 0 0.0000% 32226 1,894 0.0062% 0 0.0000% 32233 4,145 0.0135% 0 0.0000% 32244 3,762 0.0122% 0 0.0000% 32246 3,945 0.0128% 0 0.0000% 32250 6,734 0.0219% 681 0.0236% 32254 656 0.0021% 0 0.0000% 151 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32256 3,662 0.0119% 511 0.0178% 32257 4,317 0.0140% 0 0.0000% 32258 2,602 0.0085% 0 0.0000% 32259 5,228 0.0170% 0 0.0000% 32266 2,544 0.0083% 0 0.0000% 32277 2,917 0.0095% 0 0.0000% 32301 4,035 0.0131% 0 0.0000% 32302 683 0.0022% 0 0.0000% 32303 7,679 0.0250% 0 0.0000% 32304 2,150 0.0070% 645 0.0224% 32305 1,576 0.0051% 0 0.0000% 32308 5,732 0.0186% 0 0.0000% 32309 5,719 0.0186% 0 0.0000% 32310 1,810 0.0059% 0 0.0000% 32311 3,071 0.0100% 0 0.0000% 32312 8,659 0.0282% 0 0.0000% 32317 2,929 0.0095% 0 0.0000% 32320 1,813 0.0059% 0 0.0000% 32322 833 0.0027% 0 0.0000% 32327 2,265 0.0074% 0 0.0000% 32328 4,811 0.0157% 0 0.0000% 32333 1,408 0.0046% 0 0.0000% 32340 1,100 0.0036% 0 0.0000% 32344 1,653 0.0054% 0 0.0000% 32346 870 0.0028% 0 0.0000% 32347 1,653 0.0054% 0 0.0000% 32348 1,200 0.0039% 0 0.0000% 32351 1,551 0.0050% 0 0.0000% 32401 11,631 0.0378% 599 0.0208% 32404 15,945 0.0519% 0 0.0000% 32405 14,526 0.0473% 0 0.0000% 32407 9,892 0.0322% 3,198 0.1110% 32408 37,624 0.1224% 8,788 0.3050% 32409 3,956 0.0129% 0 0.0000% 32410 1,774 0.0058% 0 0.0000% 32411 592 0.0019% 0 0.0000% 32413 25,620 0.0834% 5,692 0.1976% 32420 627 0.0020% 0 0.0000% 32421 524 0.0017% 0 0.0000% 32425 3,016 0.0098% 0 0.0000% 32428 3,647 0.0119% 0 0.0000% 32431 882 0.0029% 0 0.0000% 32433 10,883 0.0354% 0 0.0000% 152 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32435 2,238 0.0073% 0 0.0000% 32438 593 0.0019% 0 0.0000% 32439 9,919 0.0323% 0 0.0000% 32440 1,428 0.0046% 0 0.0000% 32443 536 0.0017% 0 0.0000% 32444 11,390 0.0371% 0 0.0000% 32446 1,873 0.0061% 0 0.0000% 32448 1,246 0.0041% 0 0.0000% 32455 1,070 0.0035% 0 0.0000% 32456 8,681 0.0282% 0 0.0000% 32459 52,381 0.1704% 7,435 0.2581% 32461 2,107 0.0069% 0 0.0000% 32462 842 0.0027% 0 0.0000% 32464 828 0.0027% 0 0.0000% 32465 832 0.0027% 0 0.0000% 32466 1,670 0.0054% 0 0.0000% 32501 109,814 0.3573% 8,774 0.3045% 32502 17,064 0.0555% 0 0.0000% 32503 299,903 0.9758% 13,465 0.4673% 32504 230,046 0.7485% 10,210 0.3544% 32505 104,143 0.3388% 2,490 0.0864% 32506 216,334 0.7039% 7,286 0.2529% 32507 231,486 0.7532% 46,477 1.6131% 32508 1,929 0.0063% 551 0.0191% 32509 0 0.0000% 564 0.0196% 32514 212,600 0.6917% 8,510 0.2953% 32526 173,223 0.5636% 4,746 0.1647% 32530 1,516 0.0049% 0 0.0000% 32531 7,874 0.0256% 0 0.0000% 32533 127,474 0.4148% 0 0.0000% 32534 67,090 0.2183% 0 0.0000% 32535 8,266 0.0269% 0 0.0000% 32536 26,760 0.0871% 0 0.0000% 32539 23,233 0.0756% 0 0.0000% 32541 112,713 0.3667% 30,573 1.0611% 32542 1,058 0.0034% 0 0.0000% 32547 78,424 0.2552% 4,703 0.1632% 32548 60,096 0.1955% 13,912 0.4828% 32550 68,094 0.2216% 26,214 0.9098% 32561 391,751 1.2746% 56,024 1.9444% 32563 249,744 0.8126% 2,058 0.0714% 32564 2,750 0.0089% 0 0.0000% 32565 14,836 0.0483% 0 0.0000% 153 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32566 210,501 0.6849% 10,376 0.3601% 32567 1,530 0.0050% 0 0.0000% 32568 5,069 0.0165% 0 0.0000% 32569 84,671 0.2755% 2,738 0.0950% 32570 107,101 0.3485% 1,411 0.0490% 32571 153,945 0.5009% 516 0.0179% 32577 18,301 0.0595% 0 0.0000% 32578 120,747 0.3929% 3,620 0.1257% 32579 46,076 0.1499% 0 0.0000% 32580 9,870 0.0321% 0 0.0000% 32583 116,515 0.3791% 0 0.0000% 32601 1,555 0.0051% 0 0.0000% 32605 5,815 0.0189% 0 0.0000% 32606 4,701 0.0153% 657 0.0228% 32607 4,044 0.0132% 857 0.0298% 32608 6,206 0.0202% 771 0.0268% 32609 1,864 0.0061% 0 0.0000% 32615 3,149 0.0102% 0 0.0000% 32617 1,270 0.0041% 0 0.0000% 32618 1,325 0.0043% 0 0.0000% 32619 762 0.0025% 0 0.0000% 32621 1,200 0.0039% 0 0.0000% 32625 1,067 0.0035% 0 0.0000% 32626 1,665 0.0054% 0 0.0000% 32640 2,318 0.0075% 0 0.0000% 32641 1,189 0.0039% 0 0.0000% 32643 2,123 0.0069% 0 0.0000% 32653 3,497 0.0114% 0 0.0000% 32656 2,824 0.0092% 0 0.0000% 32666 1,568 0.0051% 0 0.0000% 32667 1,079 0.0035% 0 0.0000% 32668 2,259 0.0074% 0 0.0000% 32669 2,873 0.0093% 0 0.0000% 32680 994 0.0032% 0 0.0000% 32686 1,720 0.0056% 0 0.0000% 32693 1,634 0.0053% 0 0.0000% 32696 2,888 0.0094% 0 0.0000% 32701 16,926 0.0551% 4,495 0.1560% 32702 1,277 0.0042% 0 0.0000% 32703 45,313 0.1474% 673 0.0234% 32707 37,931 0.1234% 2,591 0.0899% 32708 57,807 0.1881% 2,062 0.0716% 32709 2,375 0.0077% 0 0.0000% 154 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32712 56,277 0.1831% 1,347 0.0467% 32713 17,760 0.0578% 0 0.0000% 32714 28,230 0.0919% 3,888 0.1349% 32720 18,054 0.0587% 2,026 0.0703% 32724 22,480 0.0731% 1,234 0.0428% 32725 35,104 0.1142% 0 0.0000% 32726 23,061 0.0750% 704 0.0244% 32730 4,852 0.0158% 0 0.0000% 32732 6,267 0.0204% 0 0.0000% 32735 4,807 0.0156% 0 0.0000% 32736 5,124 0.0167% 0 0.0000% 32738 33,774 0.1099% 0 0.0000% 32744 2,069 0.0067% 0 0.0000% 32746 52,328 0.1703% 1,156 0.0401% 32750 26,998 0.0878% 0 0.0000% 32751 37,486 0.1220% 4,528 0.1572% 32754 18,576 0.0604% 0 0.0000% 32757 26,803 0.0872% 1,062 0.0368% 32759 3,971 0.0129% 0 0.0000% 32763 11,269 0.0367% 0 0.0000% 32764 2,811 0.0091% 0 0.0000% 32765 58,471 0.1902% 1,407 0.0488% 32766 22,643 0.0737% 0 0.0000% 32767 1,063 0.0035% 0 0.0000% 32771 37,903 0.1233% 1,467 0.0509% 32773 17,653 0.0574% 795 0.0276% 32775 507 0.0016% 0 0.0000% 32776 7,765 0.0253% 0 0.0000% 32777 639 0.0021% 0 0.0000% 32778 32,149 0.1046% 938 0.0325% 32779 57,361 0.1866% 3,931 0.1364% 32780 53,622 0.1745% 3,870 0.1343% 32784 7,176 0.0233% 0 0.0000% 32789 68,819 0.2239% 3,216 0.1116% 32792 40,662 0.1323% 4,866 0.1689% 32796 27,486 0.0894% 1,386 0.0481% 32798 7,961 0.0259% 0 0.0000% 32801 9,280 0.0302% 3,496 0.1213% 32803 37,019 0.1204% 3,789 0.1315% 32804 40,751 0.1326% 1,495 0.0519% 32805 15,438 0.0502% 0 0.0000% 32806 50,907 0.1656% 3,025 0.1050% 32807 24,942 0.0812% 2,661 0.0924% 155 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32808 36,816 0.1198% 2,511 0.0872% 32809 34,802 0.1132% 3,208 0.1114% 32810 30,773 0.1001% 1,638 0.0569% 32811 15,790 0.0514% 8,813 0.3059% 32812 40,791 0.1327% 3,165 0.1099% 32814 8,036 0.0261% 620 0.0215% 32817 27,173 0.0884% 836 0.0290% 32818 44,137 0.1436% 2,123 0.0737% 32819 77,238 0.2513% 7,023 0.2437% 32820 10,584 0.0344% 0 0.0000% 32821 23,731 0.0772% 2,372 0.0823% 32822 34,584 0.1125% 8,626 0.2994% 32824 52,292 0.1701% 2,358 0.0818% 32825 62,500 0.2034% 1,538 0.0534% 32826 17,318 0.0563% 1,068 0.0371% 32827 15,882 0.0517% 0 0.0000% 32828 62,376 0.2030% 1,322 0.0459% 32829 20,280 0.0660% 2,442 0.0848% 32832 29,635 0.0964% 2,126 0.0738% 32833 11,769 0.0383% 0 0.0000% 32835 56,798 0.1848% 14,868 0.5160% 32836 62,327 0.2028% 2,044 0.0709% 32837 86,737 0.2822% 3,827 0.1328% 32839 23,934 0.0779% 4,141 0.1437% 32901 55,612 0.1809% 6,201 0.2152% 32903 76,340 0.2484% 11,647 0.4042% 32904 77,205 0.2512% 4,256 0.1477% 32905 84,540 0.2751% 9,216 0.3199% 32907 136,199 0.4431% 0 0.0000% 32908 33,163 0.1079% 0 0.0000% 32909 105,838 0.3444% 613 0.0213% 32920 11,377 0.0370% 13,997 0.4858% 32922 11,915 0.0388% 1,327 0.0461% 32926 32,678 0.1063% 0 0.0000% 32927 33,593 0.1093% 625 0.0217% 32931 41,172 0.1340% 28,915 1.0036% 32934 52,724 0.1715% 0 0.0000% 32935 90,374 0.2940% 6,527 0.2265% 32937 99,687 0.3243% 13,800 0.4790% 32940 94,914 0.3088% 7,254 0.2518% 32948 11,122 0.0362% 0 0.0000% 32949 25,980 0.0845% 0 0.0000% 32950 29,808 0.0970% 0 0.0000% 156 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 32951 146,313 0.4761% 13,903 0.4826% 32952 54,627 0.1777% 1,229 0.0427% 32953 37,961 0.1235% 1,251 0.0434% 32955 70,060 0.2280% 3,740 0.1298% 32957 2,459 0.0080% 0 0.0000% 32958 236,615 0.7699% 7,173 0.2489% 32960 100,333 0.3265% 16,704 0.5797% 32961 740 0.0024% 0 0.0000% 32962 99,817 0.3248% 13,181 0.4575% 32963 412,937 1.3436% 87,700 3.0438% 32964 1,390 0.0045% 0 0.0000% 32966 108,705 0.3537% 7,772 0.2698% 32967 105,615 0.3436% 9,220 0.3200% 32968 76,368 0.2485% 0 0.0000% 32969 513 0.0017% 0 0.0000% 32970 1,288 0.0042% 0 0.0000% 32976 219,670 0.7147% 0 0.0000% 33004 3,435 0.0112% 1,447 0.0502% 33009 6,266 0.0204% 10,026 0.3480% 33010 3,931 0.0128% 599 0.0208% 33012 7,277 0.0237% 2,369 0.0822% 33013 4,622 0.0150% 0 0.0000% 33014 7,007 0.0228% 1,986 0.0689% 33015 12,360 0.0402% 2,255 0.0783% 33016 6,207 0.0202% 2,796 0.0970% 33018 9,029 0.0294% 702 0.0244% 33019 6,724 0.0219% 3,864 0.1341% 33020 7,225 0.0235% 2,977 0.1033% 33021 17,174 0.0559% 2,919 0.1013% 33023 16,616 0.0541% 0 0.0000% 33024 21,566 0.0702% 1,211 0.0420% 33025 12,933 0.0421% 3,505 0.1216% 33026 15,203 0.0495% 1,049 0.0364% 33027 20,480 0.0666% 0 0.0000% 33028 12,911 0.0420% 0 0.0000% 33029 29,485 0.0959% 0 0.0000% 33030 4,038 0.0131% 0 0.0000% 33031 2,375 0.0077% 0 0.0000% 33032 3,740 0.0122% 0 0.0000% 33033 4,673 0.0152% 0 0.0000% 33034 1,351 0.0044% 0 0.0000% 33035 830 0.0027% 0 0.0000% 33036 2,479 0.0081% 517 0.0179% 157 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33037 6,799 0.0221% 1,038 0.0360% 33040 10,867 0.0354% 2,092 0.0726% 33042 4,981 0.0162% 0 0.0000% 33043 1,997 0.0065% 0 0.0000% 33050 3,844 0.0125% 0 0.0000% 33051 664 0.0022% 0 0.0000% 33054 3,800 0.0124% 0 0.0000% 33055 10,877 0.0354% 0 0.0000% 33056 6,942 0.0226% 0 0.0000% 33060 12,071 0.0393% 3,550 0.1232% 33062 16,692 0.0543% 20,916 0.7259% 33063 28,341 0.0922% 8,406 0.2917% 33064 31,479 0.1024% 5,879 0.2040% 33065 33,093 0.1077% 8,528 0.2960% 33066 7,644 0.0249% 10,411 0.3614% 33067 38,363 0.1248% 1,650 0.0573% 33068 22,042 0.0717% 2,457 0.0853% 33069 6,312 0.0205% 7,534 0.2615% 33070 2,513 0.0082% 0 0.0000% 33071 38,630 0.1257% 3,426 0.1189% 33073 20,067 0.0653% 1,780 0.0618% 33076 37,325 0.1214% 0 0.0000% 33109 1,299 0.0042% 1,110 0.0385% 33125 3,683 0.0120% 746 0.0259% 33126 2,784 0.0091% 1,570 0.0545% 33127 2,152 0.0070% 0 0.0000% 33129 2,608 0.0085% 2,465 0.0856% 33130 503 0.0016% 0 0.0000% 33131 0 0.0000% 944 0.0328% 33132 0 0.0000% 928 0.0322% 33133 11,582 0.0377% 1,775 0.0616% 33134 10,597 0.0345% 875 0.0304% 33135 2,193 0.0071% 512 0.0178% 33136 0 0.0000% 509 0.0177% 33137 1,923 0.0063% 748 0.0260% 33138 4,759 0.0155% 1,347 0.0467% 33139 6,670 0.0217% 11,191 0.3884% 33140 10,265 0.0334% 6,820 0.2367% 33141 5,622 0.0183% 6,047 0.2099% 33142 4,338 0.0141% 0 0.0000% 33143 11,657 0.0379% 1,206 0.0419% 33144 3,767 0.0123% 0 0.0000% 33145 4,923 0.0160% 0 0.0000% 158 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33146 6,349 0.0207% 0 0.0000% 33147 4,732 0.0154% 0 0.0000% 33149 5,777 0.0188% 3,713 0.1289% 33150 2,457 0.0080% 0 0.0000% 33154 6,407 0.0208% 7,682 0.2666% 33155 8,617 0.0280% 0 0.0000% 33156 17,617 0.0573% 827 0.0287% 33157 13,245 0.0431% 788 0.0273% 33158 2,886 0.0094% 0 0.0000% 33160 7,074 0.0230% 12,795 0.4441% 33161 5,592 0.0182% 1,502 0.0521% 33162 6,165 0.0201% 1,158 0.0402% 33165 10,456 0.0340% 0 0.0000% 33166 4,059 0.0132% 673 0.0234% 33167 2,619 0.0085% 0 0.0000% 33168 3,910 0.0127% 0 0.0000% 33169 6,474 0.0211% 533 0.0185% 33170 1,847 0.0060% 0 0.0000% 33172 1,456 0.0047% 2,965 0.1029% 33173 7,433 0.0242% 1,024 0.0355% 33174 3,579 0.0116% 736 0.0255% 33175 11,567 0.0376% 754 0.0262% 33176 14,300 0.0465% 1,009 0.0350% 33177 9,488 0.0309% 0 0.0000% 33178 8,243 0.0268% 2,360 0.0819% 33179 8,611 0.0280% 3,653 0.1268% 33180 7,560 0.0246% 9,991 0.3468% 33181 2,721 0.0089% 1,351 0.0469% 33182 4,149 0.0135% 0 0.0000% 33183 5,749 0.0187% 979 0.0340% 33184 4,000 0.0130% 0 0.0000% 33185 6,324 0.0206% 0 0.0000% 33186 15,704 0.0511% 1,095 0.0380% 33187 4,807 0.0156% 0 0.0000% 33189 3,568 0.0116% 0 0.0000% 33190 1,050 0.0034% 0 0.0000% 33193 7,320 0.0238% 1,516 0.0526% 33194 1,038 0.0034% 0 0.0000% 33196 10,254 0.0334% 790 0.0274% 33301 9,551 0.0311% 1,854 0.0643% 33304 5,672 0.0185% 3,981 0.1382% 33305 6,269 0.0204% 1,620 0.0562% 33306 2,227 0.0072% 642 0.0223% 159 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33308 17,365 0.0565% 10,109 0.3509% 33309 14,309 0.0466% 2,962 0.1028% 33311 14,825 0.0482% 2,693 0.0935% 33312 21,727 0.0707% 1,299 0.0451% 33313 12,507 0.0407% 6,476 0.2248% 33314 6,214 0.0202% 1,378 0.0478% 33315 5,286 0.0172% 1,068 0.0371% 33316 8,053 0.0262% 4,145 0.1439% 33317 22,449 0.0730% 1,951 0.0677% 33319 19,996 0.0651% 8,138 0.2824% 33321 25,969 0.0845% 10,824 0.3757% 33322 25,359 0.0825% 7,233 0.2510% 33323 14,846 0.0483% 503 0.0175% 33324 21,396 0.0696% 6,784 0.2354% 33325 21,287 0.0693% 676 0.0235% 33326 22,198 0.0722% 2,923 0.1014% 33327 21,123 0.0687% 0 0.0000% 33328 18,758 0.0610% 745 0.0259% 33330 14,282 0.0465% 0 0.0000% 33331 20,568 0.0669% 0 0.0000% 33332 9,191 0.0299% 0 0.0000% 33334 10,498 0.0342% 2,521 0.0875% 33351 14,842 0.0483% 2,707 0.0940% 33401 29,351 0.0955% 22,506 0.7811% 33403 12,810 0.0417% 5,210 0.1808% 33404 38,866 0.1265% 20,782 0.7213% 33405 34,949 0.1137% 2,770 0.0961% 33406 35,628 0.1159% 3,452 0.1198% 33407 40,072 0.1304% 11,411 0.3960% 33408 72,454 0.2357% 32,931 1.1429% 33409 30,649 0.0997% 13,459 0.4671% 33410 113,669 0.3698% 13,693 0.4753% 33411 184,488 0.6003% 17,681 0.6136% 33412 75,358 0.2452% 0 0.0000% 33413 27,641 0.0899% 1,186 0.0412% 33414 206,670 0.6724% 8,985 0.3118% 33415 47,688 0.1552% 19,676 0.6829% 33417 35,304 0.1149% 26,293 0.9126% 33418 219,690 0.7148% 15,730 0.5459% 33424 0 0.0000% 1,001 0.0348% 33426 32,990 0.1073% 3,869 0.1343% 33427 521 0.0017% 0 0.0000% 33428 49,726 0.1618% 6,805 0.2362% 160 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33430 17,276 0.0562% 986 0.0342% 33431 25,531 0.0831% 8,251 0.2864% 33432 26,867 0.0874% 9,896 0.3435% 33433 55,071 0.1792% 12,440 0.4318% 33434 42,310 0.1377% 14,145 0.4909% 33435 37,861 0.1232% 18,735 0.6502% 33436 98,765 0.3213% 16,951 0.5883% 33437 167,134 0.5438% 22,511 0.7813% 33438 1,393 0.0045% 0 0.0000% 33440 33,469 0.1089% 885 0.0307% 33441 12,283 0.0400% 5,080 0.1763% 33442 18,597 0.0605% 13,321 0.4624% 33444 18,980 0.0618% 5,106 0.1772% 33445 47,132 0.1534% 18,028 0.6257% 33446 64,093 0.2085% 19,233 0.6675% 33455 114,461 0.3724% 7,035 0.2442% 33458 159,352 0.5185% 16,105 0.5590% 33460 35,801 0.1165% 6,307 0.2189% 33461 38,147 0.1241% 12,725 0.4417% 33462 64,458 0.2097% 12,441 0.4318% 33463 92,269 0.3002% 15,354 0.5329% 33467 204,056 0.6639% 11,033 0.3829% 33469 92,323 0.3004% 16,083 0.5582% 33470 89,390 0.2908% 0 0.0000% 33471 13,443 0.0437% 0 0.0000% 33475 849 0.0028% 0 0.0000% 33476 11,625 0.0378% 0 0.0000% 33477 74,457 0.2423% 34,895 1.2111% 33478 56,387 0.1835% 0 0.0000% 33480 157,121 0.5112% 37,471 1.3005% 33483 29,954 0.0975% 17,209 0.5973% 33484 40,542 0.1319% 15,763 0.5471% 33486 28,645 0.0932% 3,776 0.1311% 33487 33,750 0.1098% 17,176 0.5961% 33493 2,840 0.0092% 0 0.0000% 33496 82,642 0.2689% 8,204 0.2847% 33498 38,116 0.1240% 0 0.0000% 33510 28,077 0.0914% 506 0.0176% 33511 47,402 0.1542% 1,897 0.0658% 33513 6,921 0.0225% 0 0.0000% 33514 1,480 0.0048% 0 0.0000% 33523 12,235 0.0398% 0 0.0000% 33525 27,850 0.0906% 0 0.0000% 161 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33527 15,663 0.0510% 0 0.0000% 33534 9,268 0.0302% 0 0.0000% 33538 3,283 0.0107% 0 0.0000% 33540 11,939 0.0388% 0 0.0000% 33541 31,030 0.1010% 0 0.0000% 33542 23,463 0.0763% 809 0.0281% 33543 39,643 0.1290% 1,072 0.0372% 33544 21,109 0.0687% 0 0.0000% 33547 34,094 0.1109% 0 0.0000% 33548 7,288 0.0237% 0 0.0000% 33549 21,732 0.0707% 0 0.0000% 33556 31,517 0.1025% 517 0.0179% 33558 18,706 0.0609% 1,516 0.0526% 33559 8,747 0.0285% 0 0.0000% 33563 17,177 0.0559% 0 0.0000% 33565 19,890 0.0647% 0 0.0000% 33566 26,830 0.0873% 0 0.0000% 33567 16,638 0.0541% 0 0.0000% 33569 74,297 0.2417% 3,248 0.1127% 33570 20,048 0.0652% 0 0.0000% 33572 30,201 0.0983% 0 0.0000% 33573 23,798 0.0774% 7,400 0.2568% 33576 6,612 0.0215% 0 0.0000% 33584 28,664 0.0933% 0 0.0000% 33585 1,127 0.0037% 0 0.0000% 33592 7,156 0.0233% 0 0.0000% 33594 97,154 0.3161% 1,231 0.0427% 33597 8,937 0.0291% 0 0.0000% 33598 7,625 0.0248% 0 0.0000% 33602 7,022 0.0228% 3,385 0.1175% 33603 12,524 0.0407% 0 0.0000% 33604 20,427 0.0665% 647 0.0225% 33605 6,691 0.0218% 758 0.0263% 33606 21,186 0.0689% 1,389 0.0482% 33607 8,137 0.0265% 0 0.0000% 33609 18,012 0.0586% 1,178 0.0409% 33610 15,806 0.0514% 779 0.0270% 33611 26,275 0.0855% 3,396 0.1179% 33612 17,106 0.0557% 2,149 0.0746% 33613 17,737 0.0577% 3,529 0.1225% 33614 15,350 0.0499% 3,788 0.1315% 33615 24,365 0.0793% 1,819 0.0631% 33616 7,594 0.0247% 520 0.0181% 162 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33617 19,368 0.0630% 4,702 0.1632% 33618 25,512 0.0830% 2,141 0.0743% 33619 16,390 0.0533% 717 0.0249% 33624 37,086 0.1207% 995 0.0345% 33625 16,620 0.0541% 0 0.0000% 33626 25,206 0.0820% 709 0.0246% 33629 38,287 0.1246% 2,907 0.1009% 33634 10,666 0.0347% 0 0.0000% 33635 9,146 0.0298% 740 0.0257% 33637 5,999 0.0195% 1,084 0.0376% 33647 44,734 0.1455% 2,940 0.1020% 33701 5,418 0.0176% 2,086 0.0724% 33702 18,411 0.0599% 2,527 0.0877% 33703 20,085 0.0653% 1,779 0.0617% 33704 16,557 0.0539% 0 0.0000% 33705 11,292 0.0367% 623 0.0216% 33706 16,873 0.0549% 8,956 0.3108% 33707 18,861 0.0614% 3,826 0.1328% 33708 10,984 0.0357% 4,975 0.1727% 33709 8,886 0.0289% 994 0.0345% 33710 17,695 0.0576% 800 0.0278% 33711 8,996 0.0293% 1,782 0.0618% 33712 12,726 0.0414% 890 0.0309% 33713 13,622 0.0443% 0 0.0000% 33714 5,828 0.0190% 781 0.0271% 33715 10,970 0.0357% 7,829 0.2717% 33716 1,700 0.0055% 3,493 0.1212% 33755 14,705 0.0478% 752 0.0261% 33756 20,260 0.0659% 2,266 0.0787% 33759 8,471 0.0276% 1,292 0.0449% 33760 4,774 0.0155% 1,411 0.0490% 33761 12,310 0.0401% 3,080 0.1069% 33762 6,486 0.0211% 1,022 0.0355% 33763 8,396 0.0273% 864 0.0300% 33764 15,201 0.0495% 2,125 0.0738% 33765 5,887 0.0192% 1,174 0.0407% 33767 10,441 0.0340% 7,592 0.2635% 33770 17,809 0.0579% 692 0.0240% 33771 12,297 0.0400% 2,023 0.0702% 33772 13,211 0.0430% 1,378 0.0478% 33773 8,569 0.0279% 703 0.0244% 33774 12,212 0.0397% 2,068 0.0718% 33776 11,731 0.0382% 0 0.0000% 163 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33777 9,263 0.0301% 1,328 0.0461% 33778 9,092 0.0296% 0 0.0000% 33781 8,819 0.0287% 508 0.0176% 33782 9,587 0.0312% 1,051 0.0365% 33785 6,635 0.0216% 5,757 0.1998% 33786 4,722 0.0154% 545 0.0189% 33801 56,672 0.1844% 6,791 0.2357% 33802 0 0.0000% 1,329 0.0461% 33803 60,210 0.1959% 3,814 0.1324% 33805 25,137 0.0818% 2,066 0.0717% 33809 54,802 0.1783% 1,617 0.0561% 33810 79,123 0.2574% 655 0.0227% 33811 37,271 0.1213% 0 0.0000% 33812 16,501 0.0537% 0 0.0000% 33813 122,740 0.3994% 1,835 0.0637% 33815 12,417 0.0404% 532 0.0185% 33820 1,010 0.0033% 0 0.0000% 33823 90,587 0.2947% 0 0.0000% 33825 148,568 0.4834% 2,646 0.0918% 33827 23,592 0.0768% 0 0.0000% 33830 61,037 0.1986% 857 0.0297% 33834 11,837 0.0385% 0 0.0000% 33835 1,081 0.0035% 0 0.0000% 33837 64,617 0.2102% 0 0.0000% 33838 11,570 0.0376% 0 0.0000% 33839 6,553 0.0213% 0 0.0000% 33840 594 0.0019% 0 0.0000% 33841 22,350 0.0727% 0 0.0000% 33843 79,377 0.2583% 0 0.0000% 33844 123,476 0.4018% 2,355 0.0817% 33846 899 0.0029% 0 0.0000% 33847 1,050 0.0034% 0 0.0000% 33848 1,213 0.0039% 0 0.0000% 33849 1,032 0.0034% 0 0.0000% 33850 21,419 0.0697% 0 0.0000% 33851 3,375 0.0110% 0 0.0000% 33852 108,339 0.3525% 1,123 0.0390% 33853 56,257 0.1830% 1,439 0.0500% 33854 617 0.0020% 0 0.0000% 33855 6,309 0.0205% 0 0.0000% 33857 8,615 0.0280% 0 0.0000% 33858 578 0.0019% 0 0.0000% 33859 51,796 0.1685% 530 0.0184% 164 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33860 37,671 0.1226% 1,033 0.0359% 33865 3,008 0.0098% 0 0.0000% 33867 1,252 0.0041% 0 0.0000% 33868 20,864 0.0679% 0 0.0000% 33870 72,891 0.2372% 4,675 0.1623% 33872 127,516 0.4149% 2,329 0.0808% 33873 35,984 0.1171% 0 0.0000% 33875 47,396 0.1542% 0 0.0000% 33876 19,442 0.0633% 1,005 0.0349% 33877 1,300 0.0042% 0 0.0000% 33880 82,663 0.2690% 2,942 0.1021% 33881 103,641 0.3372% 2,209 0.0767% 33884 117,375 0.3819% 4,628 0.1606% 33890 25,881 0.0842% 0 0.0000% 33896 16,102 0.0524% 2,781 0.0965% 33897 52,218 0.1699% 0 0.0000% 33898 99,381 0.3234% 1,213 0.0421% 33901 22,881 0.0744% 5,393 0.1872% 33903 96,988 0.3156% 5,598 0.1943% 33904 182,789 0.5947% 17,935 0.6225% 33905 31,159 0.1014% 1,240 0.0430% 33907 18,780 0.0611% 8,844 0.3069% 33908 122,671 0.3991% 33,295 1.1556% 33909 62,711 0.2040% 2,008 0.0697% 33912 49,168 0.1600% 5,346 0.1855% 33913 17,303 0.0563% 3,457 0.1200% 33914 405,901 1.3207% 13,395 0.4649% 33916 8,775 0.0286% 1,486 0.0516% 33917 82,073 0.2670% 2,236 0.0776% 33919 61,985 0.2017% 18,965 0.6582% 33920 7,530 0.0245% 0 0.0000% 33921 307,179 0.9995% 23,695 0.8224% 33922 144,638 0.4706% 11,376 0.3948% 33924 285,137 0.9277% 13,939 0.4838% 33928 27,337 0.0889% 6,234 0.2164% 33931 79,143 0.2575% 30,214 1.0486% 33932 0 0.0000% 635 0.0220% 33935 17,654 0.0574% 0 0.0000% 33936 24,967 0.0812% 824 0.0286% 33938 0 0.0000% 1,768 0.0614% 33945 3,570 0.0116% 0 0.0000% 33946 126,766 0.4125% 16,531 0.5737% 33947 93,097 0.3029% 3,673 0.1275% 165 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 33948 183,595 0.5974% 5,957 0.2067% 33949 867 0.0028% 0 0.0000% 33950 752,415 2.4481% 89,294 3.0992% 33951 1,059 0.0034% 0 0.0000% 33952 265,265 0.8631% 8,928 0.3099% 33953 49,677 0.1616% 3,207 0.1113% 33954 261,187 0.8498% 0 0.0000% 33955 177,229 0.5766% 22,228 0.7715% 33956 130,279 0.4239% 819 0.0284% 33957 648,457 2.1099% 142,349 4.9406% 33960 2,259 0.0074% 0 0.0000% 33966 5,646 0.0184% 1,901 0.0660% 33967 9,844 0.0320% 0 0.0000% 33971 27,600 0.0898% 0 0.0000% 33972 13,475 0.0438% 0 0.0000% 33980 169,425 0.5513% 11,359 0.3942% 33981 84,147 0.2738% 2,211 0.0767% 33982 159,924 0.5203% 723 0.0251% 33983 408,478 1.3291% 23,647 0.8207% 33990 118,977 0.3871% 3,155 0.1095% 33991 143,776 0.4678% 2,188 0.0759% 33993 278,546 0.9063% 0 0.0000% 34102 40,436 0.1316% 5,726 0.1987% 34103 22,661 0.0737% 15,087 0.5236% 34104 14,004 0.0456% 4,284 0.1487% 34105 20,370 0.0663% 4,056 0.1408% 34108 42,815 0.1393% 11,883 0.4124% 34109 24,858 0.0809% 5,891 0.2045% 34110 32,104 0.1045% 8,608 0.2988% 34112 16,602 0.0540% 5,453 0.1893% 34113 10,021 0.0326% 2,075 0.0720% 34114 7,520 0.0245% 2,090 0.0725% 34116 10,168 0.0331% 1,025 0.0356% 34117 6,908 0.0225% 0 0.0000% 34119 29,192 0.0950% 3,397 0.1179% 34120 12,181 0.0396% 536 0.0186% 34134 49,197 0.1601% 9,559 0.3318% 34135 40,832 0.1329% 6,776 0.2352% 34142 2,020 0.0066% 0 0.0000% 34145 27,201 0.0885% 12,960 0.4498% 34201 6,613 0.0215% 0 0.0000% 34202 26,418 0.0860% 2,009 0.0697% 34203 20,785 0.0676% 1,162 0.0403% 166 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 34205 11,854 0.0386% 1,432 0.0497% 34207 9,881 0.0321% 1,461 0.0507% 34208 15,760 0.0513% 919 0.0319% 34209 24,059 0.0783% 2,984 0.1036% 34210 6,867 0.0223% 4,293 0.1490% 34211 4,854 0.0158% 0 0.0000% 34212 17,554 0.0571% 930 0.0323% 34215 678 0.0022% 0 0.0000% 34216 2,262 0.0074% 0 0.0000% 34217 10,385 0.0338% 3,644 0.1265% 34219 19,590 0.0637% 0 0.0000% 34221 33,214 0.1081% 846 0.0294% 34222 12,507 0.0407% 0 0.0000% 34223 78,719 0.2561% 8,255 0.2865% 34224 103,598 0.3371% 7,263 0.2521% 34228 13,091 0.0426% 10,687 0.3709% 34229 10,987 0.0357% 578 0.0201% 34231 26,206 0.0853% 5,198 0.1804% 34232 21,171 0.0689% 1,730 0.0600% 34233 11,872 0.0386% 1,487 0.0516% 34234 9,058 0.0295% 756 0.0262% 34235 9,649 0.0314% 3,442 0.1195% 34236 13,124 0.0427% 6,009 0.2086% 34237 6,118 0.0199% 1,120 0.0389% 34238 17,954 0.0584% 2,899 0.1006% 34239 13,413 0.0436% 642 0.0223% 34240 24,129 0.0785% 0 0.0000% 34241 23,458 0.0763% 1,238 0.0430% 34242 14,976 0.0487% 8,033 0.2788% 34243 21,782 0.0709% 3,030 0.1052% 34250 802 0.0026% 0 0.0000% 34251 20,584 0.0670% 0 0.0000% 34265 738 0.0024% 0 0.0000% 34266 263,452 0.8572% 0 0.0000% 34267 787 0.0026% 0 0.0000% 34268 782 0.0025% 0 0.0000% 34269 88,621 0.2883% 6,947 0.2411% 34275 24,634 0.0801% 1,128 0.0391% 34285 19,686 0.0641% 5,732 0.1989% 34286 136,178 0.4431% 0 0.0000% 34287 393,262 1.2795% 2,986 0.1036% 34288 70,059 0.2279% 3,188 0.1106% 34289 7,281 0.0237% 1,450 0.0503% 167 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 34292 34,747 0.1131% 4,953 0.1719% 34293 81,938 0.2666% 7,043 0.2444% 34420 6,507 0.0212% 0 0.0000% 34428 4,840 0.0157% 0 0.0000% 34429 7,504 0.0244% 0 0.0000% 34431 4,792 0.0156% 0 0.0000% 34432 10,201 0.0332% 0 0.0000% 34433 3,628 0.0118% 0 0.0000% 34434 5,282 0.0172% 0 0.0000% 34436 5,751 0.0187% 0 0.0000% 34442 14,461 0.0471% 0 0.0000% 34446 18,601 0.0605% 0 0.0000% 34448 9,346 0.0304% 0 0.0000% 34449 901 0.0029% 0 0.0000% 34450 7,367 0.0240% 0 0.0000% 34452 6,973 0.0227% 0 0.0000% 34453 7,313 0.0238% 0 0.0000% 34461 8,139 0.0265% 0 0.0000% 34465 14,275 0.0464% 0 0.0000% 34470 6,780 0.0221% 0 0.0000% 34471 11,777 0.0383% 0 0.0000% 34472 11,147 0.0363% 0 0.0000% 34473 9,525 0.0310% 0 0.0000% 34474 8,135 0.0265% 824 0.0286% 34475 2,405 0.0078% 0 0.0000% 34476 16,032 0.0522% 0 0.0000% 34479 4,530 0.0147% 0 0.0000% 34480 9,472 0.0308% 0 0.0000% 34481 12,337 0.0401% 0 0.0000% 34482 8,573 0.0279% 0 0.0000% 34484 2,785 0.0091% 0 0.0000% 34488 2,908 0.0095% 0 0.0000% 34491 34,433 0.1120% 0 0.0000% 34601 12,139 0.0395% 0 0.0000% 34602 8,518 0.0277% 0 0.0000% 34604 4,140 0.0135% 0 0.0000% 34606 22,414 0.0729% 0 0.0000% 34607 6,327 0.0206% 0 0.0000% 34608 25,890 0.0842% 0 0.0000% 34609 30,526 0.0993% 0 0.0000% 34610 11,872 0.0386% 0 0.0000% 34613 20,181 0.0657% 0 0.0000% 34614 4,147 0.0135% 0 0.0000% 168 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 34637 4,091 0.0133% 0 0.0000% 34638 14,739 0.0480% 0 0.0000% 34639 25,665 0.0835% 0 0.0000% 34652 13,905 0.0452% 1,967 0.0683% 34653 15,876 0.0517% 1,269 0.0440% 34654 16,294 0.0530% 646 0.0224% 34655 32,782 0.1067% 1,961 0.0681% 34667 22,696 0.0738% 974 0.0338% 34668 23,982 0.0780% 1,488 0.0516% 34669 9,623 0.0313% 0 0.0000% 34677 13,644 0.0444% 1,580 0.0548% 34681 1,832 0.0060% 0 0.0000% 34683 31,505 0.1025% 2,620 0.0909% 34684 19,025 0.0619% 3,136 0.1089% 34685 15,406 0.0501% 811 0.0281% 34688 7,608 0.0248% 665 0.0231% 34689 19,275 0.0627% 2,053 0.0713% 34690 6,696 0.0218% 0 0.0000% 34691 9,765 0.0318% 557 0.0193% 34695 15,484 0.0504% 683 0.0237% 34698 34,457 0.1121% 5,230 0.1815% 34705 5,422 0.0176% 0 0.0000% 34711 130,006 0.4230% 2,734 0.0949% 34714 19,892 0.0647% 4,170 0.1447% 34715 22,041 0.0717% 0 0.0000% 34731 14,459 0.0470% 0 0.0000% 34734 9,041 0.0294% 0 0.0000% 34736 22,719 0.0739% 0 0.0000% 34737 5,828 0.0190% 0 0.0000% 34739 4,575 0.0149% 0 0.0000% 34741 49,813 0.1621% 13,481 0.4679% 34743 77,891 0.2534% 1,839 0.0638% 34744 106,278 0.3458% 3,663 0.1271% 34746 113,744 0.3701% 10,739 0.3727% 34747 66,992 0.2180% 13,192 0.4579% 34748 70,994 0.2310% 941 0.0327% 34753 5,172 0.0168% 0 0.0000% 34755 1,057 0.0034% 0 0.0000% 34756 10,441 0.0340% 0 0.0000% 34758 73,261 0.2384% 0 0.0000% 34759 76,751 0.2497% 0 0.0000% 34760 2,664 0.0087% 0 0.0000% 34761 56,010 0.1822% 1,963 0.0681% 169 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Cumulative Losses from the 2004 Hurricane Season
Personal Residential Commercial Residential Zip Percent of Percent of Monetary Contribution Monetary Contribution Code Losses (%) Losses (%) ($1000s) ($1000s) 34762 941 0.0031% 0 0.0000% 34769 73,774 0.2400% 4,494 0.1560% 34771 48,181 0.1568% 0 0.0000% 34772 84,698 0.2756% 0 0.0000% 34773 7,650 0.0249% 879 0.0305% 34785 10,086 0.0328% 0 0.0000% 34786 134,041 0.4361% 0 0.0000% 34787 98,309 0.3199% 3,589 0.1246% 34788 28,518 0.0928% 0 0.0000% 34797 3,059 0.0100% 0 0.0000% 34945 18,822 0.0612% 0 0.0000% 34946 20,054 0.0652% 0 0.0000% 34947 27,389 0.0891% 14,475 0.5024% 34949 56,724 0.1846% 61,316 2.1281% 34950 21,805 0.0709% 2,025 0.0703% 34951 101,185 0.3292% 1,030 0.0357% 34952 177,918 0.5789% 8,396 0.2914% 34953 187,895 0.6113% 0 0.0000% 34956 13,506 0.0439% 0 0.0000% 34957 130,626 0.4250% 12,858 0.4463% 34972 50,803 0.1653% 0 0.0000% 34973 587 0.0019% 0 0.0000% 34974 141,217 0.4595% 554 0.0192% 34981 11,166 0.0363% 0 0.0000% 34982 88,479 0.2879% 6,666 0.2313% 34983 131,007 0.4263% 900 0.0312% 34984 52,634 0.1713% 0 0.0000% 34986 110,331 0.3590% 3,844 0.1334% 34987 20,392 0.0663% 867 0.0301% 34990 161,649 0.5260% 8,641 0.2999% 34991 0 0.0000% 1,081 0.0375% 34994 38,063 0.1238% 15,722 0.5457% 34996 90,918 0.2958% 27,659 0.9600% 34997 176,245 0.5734% 14,965 0.5194%
170 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 31. Hurricane Charley % of Loss for FHCF2007 Personal Residential by Zip Code
171 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 32. Hurricane Frances % of Loss for FHCF2007 Personal Residential by Zip Code
172 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 33. Hurricane Ivan % of Loss for FHCF2007 Personal Residential by Zip Code
173 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 34. Hurricane Jeanne % of Loss for FHCF2007 Personal Residential by Zip Code
174 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 35. 2004 Season % of Loss for FHCF2007 Personal Residential by Zip Code
175 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 36. Hurricane Charley % of Loss for FHCF2007 Commercial Residential by Zip Code
176 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 37. Hurricane Frances % of Loss for FHCF2007 Commercial Residential by Zip Code
177 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 38. Hurricane Ivan % of Loss for FHCF2007 Commercial Residential by Zip Code
178 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 39. Hurricane Jeanne % of Loss for FHCF2007 Commercial Residential by Zip Code
179 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
(FORM A-5 CONTINUED)
Figure 40. 2004 Season % of Loss for FHCF2007 Commercial Residential by Zip Code
180 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-6: Personal Residential Output Ranges
A. Provide personal residential output ranges in the format shown in the file named “2009FormA6.xls” by using an automated program or script. A hard copy of the personal residential output range spreadsheets shall be included in the submission. Provide the personal residential output ranges on CD in Excel format. The file name shall include the abbreviated name of the modeler, the standards year, and the form name.
B. Provide loss costs by county. Within each county, loss costs shall be shown separately per $1,000 of exposure for personal residential, tenants, condo unit owners, and mobile home; for each major deductible option; and by construction type. For each of these categories using ZIP Code centroids, the personal residential output range shall show the highest loss cost, the lowest loss cost, and the weighted average loss cost based on the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data provided in the file named “hlpm2007.exe”. The aggregate personal residential exposure data for this form shall be developed from the information in the file named “hlpm2007.exe,” except for insured value and deductibles information. Insured values shall be based on the personal residential output range specifications on the following pages. Deductible amounts prescribed in “2009FormA6.xls” for each column will be assumed to be uniformly applied to all risks. When calculating the weighted average loss costs, weight the loss costs by the total insured value calculated above. Include the statewide range of loss costs (i.e., low, high, and weighted average). For each of the loss costs provided, identify what that loss cost represents by line of business, deductible option, construction type, and coverages included, i.e., structure, contents, appurtenant structures, or additional living expenses as specified.
C. If a modeling organization has loss costs for a ZIP Code for which there is no exposure, give the 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 loss costs for a ZIP Code for which there is some exposure, do not assume such loss costs are zero, but use only the exposures for which there are loss costs in calculating the weighted average loss costs. Provide a list in the submission document of the ZIP Codes where this occurs.
E. All anomalies in loss costs that are not consistent with the requirements of Standard A-10 and have been explained in Disclosure A-10.1 shall be shaded.
Indicate if per diem is used in producing loss costs for Coverage D (ALE) in the personal residential output ranges. If a per diem rate is used in the submission, a rate of $150.00 per day per policy shall be used.
181 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
The following ZIP Codes are in the 2007 FHCF exposure but do not have loss costs in USWIND: 32267, 32290, 32335, 32454, 32592, 32613, 32890, 33110, 33121, 33148, 33188, 33195, 33447, 33697.
The Form A-6 results appear in the file 2009FormA6_EQECAT_28March2011.xls.
182 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Personal Residential Output Range Specifications “Owners” Policy Type
Coverage A: Structure
• Amount of Insurance = $100,000 • Replacement Cost Included Subject to Coverage “A” Limit • Ordinance or Law Not Included
Coverage B: Appurtenant Structures
• Amount of Insurance = 10% of Coverage “A” Amount • Replacement Cost Included Subject to Coverage “B” Limit • Ordinance or Law Not Included
Coverage C: Contents
• Amount of Insurance = 50% of Coverage “A” Amount • Replacement Cost Included Subject to Coverage “C” Limit
Coverage D: Additional Living Expense
• Amount of Insurance = 20% of Coverage “A” Amount • Time Limit = 12 Months • Per Diem = $150.00/day per policy, if used
¾ Loss Costs per $1,000 shall be related to the Coverage “A” Amount.
¾ Loss Costs for the various deductibles shall be determined based on annual deductibles.
¾ All-other perils deductible shall be $500.
¾ Explain any deviations and differences from the prescribed format above.
¾ Specify the model name and version number reflecting the release date as a footnote on each page of the output.
183 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Personal Residential Output Range Specifications “Tenants” Policy Type
Coverage C: Contents
• Amount of Insurance = $25,000 • Replacement Cost Included Subject to Coverage “C” Limit
Coverage D: Additional Living Expense
• Amount of Insurance = 40% of Coverage “C” Amount • Time Limit = 12 Months • Per Diem = $150.00/day per policy, if used
¾ Loss Costs per $1,000 shall be related to the Coverage “C” Amount.
¾ Loss Costs for the various deductibles shall be determined based on annual deductibles.
¾ All-other perils deductible shall be $500.
¾ Explain any deviations and differences from the prescribed format above.
¾ Specify the model name and version number reflecting the release date as a footnote on each page of the output.
184 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Personal Residential Output Range Specifications “Condo Unit Owners” Policy Type
Coverage A: Structure
• Amount of Insurance = 10% of Coverage “C” Amount • Replacement Cost Included Subject to Coverage “A” Limit
Coverage C: Contents
• Amount of Insurance = $50,000 • Replacement Cost Included Subject to Coverage “C” Limit
Coverage D: Additional Living Expense
• Amount of Insurance = 40% of Coverage “C” Amount • Time Limit = 12 Months • Per Diem = $150.00/day per policy, if used
¾ Loss Costs per $1,000 shall be related to the Coverage “C” Amount.
¾ Loss costs for the various deductibles shall be determined based on annual deductibles.
¾ All-other perils deductible shall be $500.
¾ Explain any deviations and differences from the prescribed format above.
¾ Specify the model name and version number reflecting the release date as a footnote on each page of the output.
185 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Personal Residential Output Range Specifications “Mobile Home Owners” Policy Type
Coverage A: Structure
• Amount of Insurance = $50,000 • Replacement Cost Included Subject to Coverage “A” Limit
Coverage B: Appurtenant Structures
• Amount of Insurance = 10% of Coverage “A” Amount • Replacement Cost Included Subject to Coverage “B” Limit
Coverage C: Contents
• Amount of Insurance = 50% of Coverage “A” Amount • Replacement Cost Included Subject to Coverage “C” Limit
Coverage D: Additional Living Expense
• Amount of Insurance = 20% of Coverage “A” Amount • Time Limit = 12 Months • Per Diem = $150.00/day per policy, if used
¾ Loss Costs per $1,000 shall be related to the Coverage “A” Amount
¾ Loss Costs for the various deductibles shall be determined based on annual deductibles.
¾ All-other perils deductible shall be $500.
¾ Explain any deviations and differences from the prescribed format above.
¾ Specify the model name and version number reflecting the release date as a footnote on each page of the output.
186 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 Personal Residential -- Owners -- FRAME $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.456 0.050 0.046 0.054 0.402 0.307 0.163 0.307 0.198 0.072 HIGH 0.796 0.099 0.080 0.076 0.782 0.642 0.401 0.642 0.463 0.217 WGHTD AVE 0.545 0.061 0.055 0.059 0.504 0.398 0.227 0.398 0.269 0.110
BAKER LOW 0.246 0.022 0.025 0.056 0.202 0.143 0.067 0.143 0.084 0.025 HIGH 0.351 0.034 0.035 0.062 0.300 0.222 0.112 0.222 0.138 0.046 WGHTD AVE 0.330 0.032 0.033 0.060 0.281 0.206 0.103 0.206 0.127 0.041
BAY LOW 0.981 0.137 0.098 0.059 0.998 0.839 0.538 0.839 0.618 0.294 HIGH 4.880 1.458 0.488 0.290 6.596 6.246 5.432 6.246 5.672 4.520 WGHTD AVE 2.631 0.592 0.264 0.134 3.203 2.938 2.366 2.938 2.529 1.789
BRADFORD LOW 0.430 0.043 0.043 0.070 0.380 0.288 0.153 0.288 0.185 0.066 HIGH 0.468 0.048 0.047 0.073 0.417 0.318 0.172 0.318 0.207 0.076 WGHTD AVE 0.452 0.046 0.045 0.072 0.402 0.306 0.165 0.306 0.199 0.073
BREVARD LOW 1.732 0.275 0.173 0.094 1.884 1.646 1.168 1.646 1.299 0.744 HIGH 7.702 2.374 0.770 0.477 10.639 10.173 9.059 10.173 9.391 7.769 WGHTD AVE 3.142 0.682 0.318 0.162 3.804 3.484 2.790 3.484 2.987 2.092
BROWARD LOW 5.620 1.242 0.562 0.308 7.095 6.683 5.655 6.683 5.961 4.496 HIGH 12.575 3.861 1.258 0.879 17.757 17.216 15.820 17.216 16.250 14.055 WGHTD AVE 7.320 1.716 0.748 0.431 9.489 9.026 7.862 9.026 8.212 6.488
CALHOUN LOW 0.701 0.083 0.070 0.047 0.677 0.553 0.329 0.553 0.387 0.161 HIGH 0.874 0.113 0.087 0.054 0.869 0.722 0.448 0.722 0.520 0.233 WGHTD AVE 0.809 0.101 0.081 0.050 0.798 0.660 0.405 0.660 0.472 0.207
CHARLOTTE LOW 2.341 0.471 0.234 0.117 2.769 2.515 1.956 2.515 2.115 1.394 HIGH 4.182 1.187 0.418 0.259 5.586 5.278 4.583 5.278 4.785 3.827 WGHTD AVE 3.016 0.663 0.303 0.160 3.708 3.426 2.810 3.426 2.986 2.176
CITRUS LOW 0.772 0.100 0.077 0.055 0.767 0.635 0.403 0.635 0.464 0.221 HIGH 1.121 0.162 0.112 0.081 1.180 1.012 0.692 1.012 0.778 0.418 WGHTD AVE 0.946 0.134 0.095 0.064 0.979 0.833 0.558 0.833 0.631 0.330
CLAY LOW 0.394 0.039 0.039 0.052 0.342 0.256 0.132 0.256 0.162 0.056 HIGH 0.797 0.093 0.080 0.073 0.771 0.629 0.382 0.629 0.445 0.197 WGHTD AVE 0.544 0.063 0.054 0.065 0.504 0.397 0.226 0.397 0.268 0.110
COLLIER LOW 2.591 0.490 0.259 0.133 3.034 2.743 2.092 2.743 2.277 1.450 HIGH 5.835 1.664 0.583 0.347 7.857 7.462 6.530 7.462 6.805 5.465 WGHTD AVE 3.712 0.867 0.384 0.208 4.672 4.341 3.602 4.341 3.815 2.825
COLUMBIA LOW 0.313 0.029 0.031 0.055 0.265 0.193 0.096 0.193 0.118 0.038 HIGH 0.490 0.056 0.049 0.072 0.450 0.353 0.200 0.353 0.238 0.097 WGHTD AVE 0.405 0.043 0.041 0.062 0.361 0.275 0.147 0.275 0.178 0.067
DESOTO LOW 2.297 0.462 0.230 0.127 2.710 2.458 1.917 2.458 2.070 1.385 HIGH 2.639 0.506 0.264 0.137 3.080 2.786 2.153 2.786 2.332 1.530 WGHTD AVE 2.606 0.501 0.260 0.136 3.043 2.755 2.132 2.755 2.308 1.517
DIXIE LOW 0.522 0.062 0.052 0.056 0.493 0.394 0.232 0.394 0.273 0.118 HIGH 1.082 0.182 0.108 0.085 1.166 1.006 0.709 1.006 0.787 0.460 WGHTD AVE 0.665 0.090 0.066 0.062 0.660 0.545 0.347 0.545 0.398 0.198
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 187 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 Personal Residential -- Owners -- FRAME $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.278 0.026 0.028 0.043 0.231 0.166 0.079 0.166 0.100 0.030 HIGH 1.030 0.161 0.103 0.081 1.092 0.933 0.642 0.933 0.719 0.404 WGHTD AVE 0.598 0.073 0.061 0.057 0.574 0.464 0.280 0.464 0.326 0.147
ESCAMBIA LOW 1.011 0.138 0.101 0.058 1.047 0.893 0.596 0.893 0.675 0.343 HIGH 5.469 1.605 0.547 0.317 7.408 7.044 6.188 7.044 6.442 5.202 WGHTD AVE 2.842 0.622 0.284 0.148 3.452 3.164 2.539 3.164 2.718 1.899
FLAGLER LOW 0.708 0.081 0.071 0.062 0.674 0.544 0.323 0.544 0.380 0.161 HIGH 1.976 0.375 0.198 0.111 2.269 2.028 1.535 2.028 1.671 1.078 WGHTD AVE 0.999 0.146 0.103 0.070 1.023 0.860 0.566 0.860 0.643 0.333
FRANKLIN LOW 1.203 0.200 0.120 0.068 1.281 1.100 0.751 1.100 0.844 0.462 HIGH 3.701 0.982 0.370 0.205 4.780 4.466 3.756 4.466 3.962 3.002 WGHTD AVE 2.381 0.542 0.239 0.127 2.879 2.621 2.073 2.621 2.227 1.540
GADSDEN LOW 0.278 0.027 0.028 0.030 0.231 0.168 0.077 0.168 0.098 0.027 HIGH 0.562 0.062 0.056 0.043 0.532 0.429 0.246 0.429 0.292 0.115 WGHTD AVE 0.376 0.037 0.038 0.039 0.332 0.255 0.132 0.255 0.162 0.054
GILCHRIST LOW 0.594 0.073 0.059 0.061 0.567 0.456 0.273 0.456 0.319 0.144 HIGH 0.631 0.082 0.063 0.062 0.611 0.496 0.305 0.496 0.353 0.166 WGHTD AVE 0.620 0.079 0.062 0.061 0.598 0.484 0.295 0.484 0.343 0.159
GLADES LOW 2.803 0.461 0.280 0.126 3.160 2.840 2.116 2.840 2.322 1.402 HIGH 3.419 0.624 0.342 0.156 3.972 3.616 2.788 3.616 3.028 1.935 WGHTD AVE 3.393 0.617 0.338 0.154 3.937 3.583 2.759 3.583 2.997 1.911
GULF LOW 0.944 0.127 0.094 0.057 0.948 0.791 0.500 0.791 0.577 0.267 HIGH 2.640 0.659 0.264 0.142 3.305 3.042 2.473 3.042 2.635 1.897 WGHTD AVE 2.398 0.534 0.240 0.122 2.908 2.663 2.141 2.663 2.289 1.622
HAMILTON LOW 0.231 0.021 0.023 0.046 0.188 0.131 0.059 0.131 0.075 0.022 HIGH 0.281 0.027 0.028 0.057 0.237 0.173 0.084 0.173 0.104 0.033 WGHTD AVE 0.256 0.024 0.026 0.054 0.213 0.152 0.072 0.152 0.090 0.028
HARDEE LOW 2.040 0.339 0.204 0.106 2.298 2.037 1.487 2.037 1.640 0.971 HIGH 2.266 0.385 0.227 0.115 2.541 2.261 1.666 2.261 1.833 1.105 WGHTD AVE 2.116 0.356 0.212 0.110 2.365 2.102 1.547 2.102 1.702 1.025
HENDRY LOW 3.255 0.597 0.325 0.149 3.788 3.448 2.664 3.448 2.890 1.862 HIGH 4.839 0.980 0.484 0.225 5.865 5.459 4.443 5.459 4.743 3.289 WGHTD AVE 3.765 0.722 0.370 0.173 4.439 4.076 3.218 4.076 3.467 2.315
HERNANDO LOW 0.889 0.117 0.089 0.055 0.909 0.770 0.507 0.770 0.577 0.289 HIGH 1.448 0.249 0.145 0.086 1.618 1.432 1.060 1.432 1.162 0.720 WGHTD AVE 1.171 0.189 0.117 0.072 1.267 1.104 0.787 1.104 0.872 0.509
HIGHLANDS LOW 2.216 0.352 0.222 0.113 2.427 2.140 1.529 2.140 1.699 0.970 HIGH 3.236 0.603 0.324 0.148 3.767 3.429 2.648 3.429 2.872 1.860 WGHTD AVE 2.648 0.457 0.266 0.129 2.990 2.676 1.989 2.676 2.183 1.329
HILLSBOROUGH LOW 0.994 0.148 0.099 0.066 1.037 0.885 0.599 0.885 0.675 0.362 HIGH 3.137 0.817 0.314 0.191 4.058 3.799 3.232 3.799 3.394 2.641 WGHTD AVE 1.839 0.372 0.189 0.112 2.172 1.964 1.536 1.964 1.655 1.130
HOLMES LOW 0.754 0.094 0.075 0.049 0.749 0.624 0.390 0.624 0.451 0.207 HIGH 0.950 0.131 0.095 0.057 0.975 0.826 0.541 0.826 0.617 0.304 WGHTD AVE 0.923 0.125 0.092 0.055 0.944 0.798 0.519 0.798 0.593 0.288
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 188 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 Personal Residential -- Owners -- FRAME $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 2.911 0.535 0.291 0.134 3.342 3.005 2.264 3.005 2.475 1.525 HIGH 7.117 2.123 0.712 0.435 9.729 9.275 8.187 9.275 8.511 6.933 WGHTD AVE 5.150 1.309 0.535 0.282 6.673 6.266 5.322 6.266 5.599 4.285
JACKSON LOW 0.623 0.074 0.062 0.046 0.596 0.483 0.285 0.483 0.336 0.139 HIGH 0.947 0.131 0.095 0.058 0.976 0.830 0.547 0.830 0.623 0.312 WGHTD AVE 0.728 0.090 0.073 0.049 0.713 0.588 0.360 0.588 0.419 0.186
JEFFERSON LOW 0.239 0.022 0.024 0.036 0.197 0.143 0.066 0.143 0.084 0.023 HIGH 0.340 0.033 0.034 0.043 0.301 0.229 0.120 0.229 0.146 0.050 WGHTD AVE 0.277 0.026 0.028 0.040 0.235 0.173 0.084 0.173 0.105 0.032
LAFAYETTE LOW 0.406 0.044 0.041 0.048 0.368 0.285 0.158 0.285 0.189 0.074 HIGH 0.410 0.044 0.041 0.048 0.374 0.291 0.162 0.291 0.193 0.075 WGHTD AVE 0.406 0.044 0.041 0.048 0.368 0.285 0.158 0.285 0.189 0.074
LAKE LOW 0.825 0.094 0.082 0.065 0.792 0.643 0.386 0.643 0.452 0.193 HIGH 2.326 0.408 0.233 0.122 2.616 2.331 1.721 2.331 1.891 1.152 WGHTD AVE 1.549 0.235 0.156 0.090 1.645 1.423 0.982 1.423 1.100 0.604
LEE LOW 2.175 0.413 0.217 0.125 2.482 2.208 1.637 2.208 1.795 1.110 HIGH 7.769 2.485 0.777 0.505 10.919 10.495 9.472 10.495 9.778 8.270 WGHTD AVE 3.937 0.861 0.403 0.211 4.916 4.590 3.865 4.590 4.074 3.099
LEON LOW 0.284 0.026 0.028 0.032 0.239 0.175 0.084 0.175 0.106 0.031 HIGH 0.576 0.065 0.058 0.054 0.547 0.442 0.257 0.442 0.304 0.121 WGHTD AVE 0.402 0.040 0.040 0.043 0.354 0.272 0.144 0.272 0.175 0.061
LEVY LOW 0.460 0.052 0.046 0.040 0.438 0.351 0.208 0.351 0.244 0.105 HIGH 1.247 0.227 0.125 0.082 1.381 1.207 0.876 1.207 0.964 0.594 WGHTD AVE 0.856 0.120 0.085 0.068 0.866 0.729 0.485 0.729 0.548 0.293
LIBERTY LOW 0.425 0.044 0.043 0.036 0.384 0.300 0.161 0.300 0.195 0.069 HIGH 0.455 0.047 0.046 0.038 0.415 0.326 0.176 0.326 0.213 0.075 WGHTD AVE 0.453 0.047 0.045 0.037 0.413 0.324 0.175 0.324 0.212 0.075
MADISON LOW 0.242 0.022 0.024 0.041 0.200 0.141 0.067 0.141 0.084 0.025 HIGH 0.335 0.034 0.033 0.056 0.291 0.218 0.112 0.218 0.137 0.048 WGHTD AVE 0.302 0.030 0.030 0.045 0.262 0.195 0.099 0.195 0.121 0.041
MANATEE LOW 1.825 0.359 0.182 0.108 2.117 1.906 1.464 1.906 1.587 1.043 HIGH 5.362 1.676 0.536 0.364 7.446 7.120 6.366 7.120 6.587 5.520 WGHTD AVE 2.624 0.572 0.265 0.150 3.209 2.963 2.436 2.963 2.585 1.907
MARION LOW 0.468 0.047 0.047 0.052 0.421 0.327 0.178 0.327 0.215 0.079 HIGH 1.375 0.197 0.138 0.098 1.440 1.235 0.844 1.235 0.948 0.520 WGHTD AVE 1.095 0.152 0.108 0.085 1.116 0.941 0.622 0.941 0.705 0.363
MARTIN LOW 5.172 1.197 0.517 0.263 6.554 6.151 5.143 6.151 5.443 4.007 HIGH 8.637 2.610 0.864 0.535 11.894 11.406 10.213 11.406 10.571 8.778 WGHTD AVE 6.531 1.770 0.655 0.371 8.663 8.221 7.159 8.221 7.475 5.940
MIAMI-DADE LOW 5.451 1.119 0.545 0.303 6.753 6.345 5.339 6.345 5.639 4.201 HIGH 15.786 4.962 1.579 1.147 22.768 22.172 20.602 22.172 21.088 18.558 WGHTD AVE 8.440 2.199 0.874 0.556 11.312 10.820 9.584 10.820 9.958 8.098
MONROE LOW 8.437 2.525 0.844 0.542 11.617 11.104 9.887 11.104 10.250 8.462 HIGH 15.550 5.439 1.555 1.183 22.838 22.274 20.786 22.274 21.251 18.838 WGHTD AVE 9.963 3.297 0.999 0.679 14.063 13.530 12.234 13.530 12.625 10.670
NASSAU LOW 0.251 0.023 0.025 0.039 0.206 0.146 0.069 0.146 0.087 0.025 HIGH 0.887 0.134 0.089 0.070 0.925 0.783 0.527 0.783 0.594 0.318 WGHTD AVE 0.613 0.081 0.060 0.056 0.595 0.485 0.301 0.485 0.348 0.164
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 189 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 Personal Residential -- Owners -- FRAME $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 1.105 0.160 0.110 0.061 1.150 0.980 0.649 0.980 0.738 0.369 HIGH 4.566 1.270 0.457 0.251 6.040 5.694 4.896 5.694 5.130 4.008 WGHTD AVE 2.758 0.638 0.279 0.143 3.394 3.119 2.524 3.119 2.694 1.917
OKEECHOBEE LOW 3.502 0.670 0.350 0.161 4.108 3.749 2.912 3.749 3.153 2.044 HIGH 5.635 1.349 0.563 0.279 7.137 6.722 5.661 6.722 5.978 4.466 WGHTD AVE 4.782 1.082 0.448 0.232 5.904 5.509 4.535 5.509 4.821 3.468
ORANGE LOW 1.022 0.132 0.102 0.068 0.986 0.802 0.476 0.802 0.559 0.237 HIGH 2.218 0.365 0.222 0.114 2.463 2.187 1.601 2.187 1.764 1.051 WGHTD AVE 1.583 0.226 0.162 0.088 1.659 1.423 0.955 1.423 1.081 0.555
OSCEOLA LOW 1.062 0.134 0.106 0.068 1.035 0.849 0.511 0.849 0.599 0.256 HIGH 2.630 0.477 0.263 0.131 3.009 2.710 2.055 2.710 2.240 1.415 WGHTD AVE 1.625 0.252 0.159 0.087 1.728 1.493 1.019 1.493 1.147 0.611
PALM BEACH LOW 4.883 1.057 0.488 0.260 6.030 5.634 4.653 5.634 4.944 3.565 HIGH 15.653 5.349 1.565 1.129 22.777 22.191 20.628 22.191 21.111 18.604 WGHTD AVE 7.156 1.875 0.750 0.412 9.460 8.994 7.850 8.994 8.192 6.519
PASCO LOW 0.970 0.155 0.097 0.066 1.020 0.871 0.594 0.871 0.667 0.366 HIGH 2.147 0.502 0.215 0.127 2.649 2.436 1.987 2.436 2.114 1.546 WGHTD AVE 1.319 0.223 0.133 0.081 1.451 1.273 0.925 1.273 1.019 0.618
PINELLAS LOW 1.428 0.264 0.143 0.086 1.621 1.443 1.084 1.443 1.183 0.754 HIGH 5.237 1.605 0.524 0.346 7.226 6.905 6.159 6.905 6.377 5.323 WGHTD AVE 2.450 0.553 0.250 0.139 3.025 2.798 2.311 2.798 2.450 1.817
POLK LOW 1.189 0.160 0.119 0.071 1.190 0.991 0.622 0.991 0.719 0.332 HIGH 2.596 0.454 0.260 0.131 3.011 2.689 1.993 2.689 2.189 1.321 WGHTD AVE 1.933 0.324 0.198 0.106 2.152 1.900 1.376 1.900 1.521 0.895
PUTNAM LOW 0.443 0.045 0.044 0.052 0.396 0.305 0.164 0.305 0.198 0.071 HIGH 1.032 0.128 0.103 0.081 1.028 0.856 0.543 0.856 0.624 0.294 WGHTD AVE 0.729 0.084 0.073 0.067 0.694 0.561 0.333 0.561 0.391 0.167
SAINT JOHNS LOW 0.334 0.036 0.033 0.042 0.276 0.201 0.096 0.201 0.121 0.036 HIGH 1.200 0.195 0.120 0.081 1.283 1.100 0.761 1.100 0.851 0.477 WGHTD AVE 0.738 0.103 0.075 0.064 0.734 0.606 0.389 0.606 0.445 0.225
SAINT LUCIE LOW 4.283 0.970 0.428 0.218 5.294 4.886 3.961 4.886 4.228 2.989 HIGH 8.632 2.677 0.863 0.543 11.999 11.494 10.273 11.494 10.639 8.839 WGHTD AVE 5.222 1.260 0.523 0.266 6.637 6.196 5.182 6.196 5.478 4.074
SANTA ROSA LOW 1.241 0.182 0.124 0.069 1.311 1.131 0.772 1.131 0.869 0.462 HIGH 5.392 1.580 0.539 0.318 7.281 6.950 6.078 6.950 6.339 5.074 WGHTD AVE 2.833 0.639 0.282 0.148 3.457 3.194 2.585 3.194 2.760 1.961
SARASOTA LOW 1.481 0.295 0.148 0.104 1.678 1.480 1.094 1.480 1.198 0.756 HIGH 4.568 1.320 0.457 0.293 6.166 5.871 5.163 5.871 5.370 4.379 WGHTD AVE 2.962 0.699 0.300 0.168 3.725 3.479 2.919 3.479 3.080 2.336
SEMINOLE LOW 1.206 0.162 0.121 0.075 1.201 0.998 0.625 0.998 0.723 0.333 HIGH 1.962 0.303 0.196 0.101 2.125 1.850 1.306 1.850 1.455 0.818 WGHTD AVE 1.443 0.198 0.144 0.083 1.491 1.267 0.842 1.267 0.956 0.485
SUMTER LOW 0.991 0.130 0.099 0.063 1.001 0.841 0.550 0.841 0.626 0.315 HIGH 1.462 0.218 0.146 0.095 1.555 1.345 0.930 1.345 1.043 0.572 WGHTD AVE 1.091 0.157 0.110 0.086 1.101 0.918 0.594 0.918 0.678 0.342
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 190 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 Personal Residential -- Owners -- FRAME $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.354 0.036 0.035 0.050 0.312 0.235 0.122 0.235 0.149 0.053 HIGH 0.506 0.059 0.051 0.057 0.470 0.371 0.214 0.371 0.253 0.106 WGHTD AVE 0.405 0.043 0.041 0.051 0.363 0.279 0.152 0.279 0.183 0.070
TAYLOR LOW 0.235 0.022 0.024 0.034 0.198 0.145 0.070 0.145 0.087 0.026 HIGH 0.479 0.060 0.048 0.051 0.446 0.358 0.213 0.358 0.249 0.110 WGHTD AVE 0.441 0.049 0.044 0.047 0.408 0.321 0.182 0.321 0.217 0.086
UNION LOW 0.398 0.039 0.040 0.065 0.348 0.262 0.136 0.262 0.167 0.058 HIGH 0.419 0.042 0.042 0.071 0.371 0.281 0.151 0.281 0.182 0.067 WGHTD AVE 0.399 0.040 0.040 0.068 0.349 0.262 0.138 0.262 0.167 0.059
VOLUSIA LOW 0.733 0.084 0.073 0.053 0.692 0.556 0.319 0.556 0.378 0.150 HIGH 2.779 0.576 0.278 0.151 3.307 3.002 2.365 3.002 2.544 1.743 WGHTD AVE 1.392 0.197 0.141 0.079 1.451 1.245 0.848 1.245 0.955 0.513
WAKULLA LOW 0.342 0.034 0.034 0.032 0.297 0.225 0.111 0.225 0.139 0.043 HIGH 1.102 0.170 0.110 0.064 1.151 0.980 0.654 0.980 0.740 0.385 WGHTD AVE 0.495 0.052 0.052 0.037 0.450 0.360 0.208 0.360 0.246 0.102
WALTON LOW 0.925 0.127 0.092 0.055 0.944 0.798 0.517 0.798 0.592 0.284 HIGH 4.093 1.143 0.409 0.240 5.380 5.039 4.275 5.039 4.497 3.455 WGHTD AVE 2.428 0.553 0.242 0.133 2.948 2.686 2.133 2.686 2.289 1.590
WASHINGTON LOW 0.871 0.115 0.087 0.053 0.878 0.736 0.469 0.736 0.539 0.251 HIGH 1.193 0.174 0.119 0.066 1.253 1.074 0.720 1.074 0.816 0.412 WGHTD AVE 0.962 0.134 0.096 0.057 0.985 0.833 0.543 0.833 0.620 0.303
Statewide LOW 0.231 0.021 0.023 0.030 0.188 0.131 0.059 0.131 0.075 0.021 HIGH 15.786 5.439 1.579 1.183 22.838 22.266 20.761 22.266 21.227 18.800 WGHTD AVE 2.243 0.429 0.237 0.123 2.617 2.393 1.927 2.393 2.058 1.471
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 191 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL -Owners -- MASONRY 0% 0% $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.324 0.039 0.032 0.053 0.280 0.208 0.104 0.208 0.129 0.042 HIGH 0.540 0.073 0.054 0.071 0.518 0.413 0.242 0.413 0.285 0.121 WGHTD AVE 0.388 0.048 0.039 0.058 0.354 0.272 0.149 0.272 0.179 0.067
BAKER LOW 0.165 0.017 0.017 0.056 0.134 0.091 0.041 0.091 0.052 0.014 HIGH 0.239 0.026 0.024 0.061 0.201 0.144 0.069 0.144 0.086 0.025 WGHTD AVE 0.223 0.025 0.022 0.060 0.187 0.132 0.062 0.132 0.078 0.023
BAY LOW 0.693 0.103 0.069 0.051 0.684 0.558 0.334 0.558 0.392 0.167 HIGH 3.784 1.228 0.378 0.217 5.149 4.848 4.169 4.848 4.367 3.436 WGHTD AVE 1.738 0.398 0.175 0.091 2.060 1.850 1.421 1.850 1.540 1.021
BRADFORD LOW 0.281 0.032 0.028 0.068 0.242 0.176 0.087 0.176 0.108 0.033 HIGH 0.318 0.037 0.032 0.073 0.279 0.205 0.105 0.205 0.129 0.044 WGHTD AVE 0.311 0.036 0.031 0.072 0.273 0.201 0.103 0.201 0.126 0.042
BREVARD LOW 1.148 0.194 0.115 0.076 1.210 1.025 0.681 1.025 0.772 0.404 HIGH 5.494 1.846 0.549 0.338 7.637 7.248 6.360 7.248 6.619 5.385 WGHTD AVE 2.196 0.533 0.224 0.123 2.654 2.396 1.873 2.396 2.018 1.389
BROWARD LOW 3.031 0.653 0.303 0.196 3.623 3.298 2.587 3.298 2.787 1.891 HIGH 8.229 2.706 0.823 0.571 11.627 11.170 10.060 11.170 10.393 8.755 WGHTD AVE 4.965 1.192 0.508 0.271 6.299 5.907 4.978 5.907 5.251 3.957
CALHOUN LOW 0.470 0.060 0.047 0.042 0.434 0.339 0.183 0.339 0.222 0.078 HIGH 0.632 0.089 0.063 0.049 0.615 0.498 0.292 0.498 0.345 0.142 WGHTD AVE 0.571 0.077 0.057 0.045 0.548 0.440 0.254 0.440 0.301 0.119
CHARLOTTE LOW 1.474 0.313 0.147 0.081 1.688 1.488 1.088 1.488 1.197 0.730 HIGH 2.968 0.910 0.297 0.186 3.968 3.713 3.168 3.713 3.323 2.605 WGHTD AVE 1.911 0.455 0.191 0.109 2.310 2.086 1.629 2.086 1.755 1.195
CITRUS LOW 0.502 0.071 0.050 0.047 0.481 0.383 0.224 0.383 0.264 0.111 HIGH 0.738 0.116 0.074 0.071 0.748 0.620 0.414 0.620 0.468 0.247 WGHTD AVE 0.610 0.092 0.061 0.056 0.604 0.494 0.304 0.494 0.353 0.163
CLAY LOW 0.254 0.028 0.025 0.053 0.213 0.152 0.072 0.152 0.091 0.027 HIGH 0.541 0.069 0.054 0.072 0.511 0.403 0.230 0.403 0.273 0.108 WGHTD AVE 0.387 0.049 0.039 0.063 0.355 0.272 0.148 0.272 0.179 0.067
COLLIER LOW 1.538 0.299 0.154 0.091 1.696 1.471 1.030 1.471 1.149 0.652 HIGH 4.036 1.207 0.404 0.229 5.387 5.059 4.321 5.059 4.535 3.523 WGHTD AVE 2.393 0.573 0.251 0.136 2.929 2.667 2.126 2.667 2.277 1.606
COLUMBIA LOW 0.205 0.022 0.021 0.052 0.171 0.119 0.055 0.119 0.070 0.020 HIGH 0.324 0.040 0.032 0.072 0.289 0.217 0.114 0.217 0.138 0.049 WGHTD AVE 0.271 0.032 0.027 0.061 0.237 0.173 0.088 0.173 0.108 0.036
DESOTO LOW 1.586 0.317 0.159 0.095 1.795 1.576 1.142 1.576 1.260 0.755 HIGH 1.831 0.375 0.183 0.105 2.101 1.863 1.381 1.863 1.513 0.941 WGHTD AVE 1.760 0.364 0.176 0.102 2.022 1.795 1.334 1.795 1.460 0.911
DIXIE LOW 0.337 0.044 0.034 0.052 0.307 0.235 0.128 0.235 0.154 0.058 HIGH 0.730 0.133 0.073 0.075 0.773 0.650 0.438 0.650 0.493 0.271 WGHTD AVE 0.391 0.052 0.038 0.053 0.364 0.285 0.163 0.285 0.193 0.079
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 192 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL -Owners -- MASONRY 0% 0% $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.193 0.021 0.019 0.041 0.160 0.111 0.051 0.111 0.065 0.018 HIGH 0.858 0.216 0.086 0.081 1.199 1.043 0.757 1.043 0.833 0.514 WGHTD AVE 0.423 0.057 0.043 0.055 0.400 0.315 0.181 0.315 0.214 0.088
ESCAMBIA LOW 0.731 0.107 0.073 0.051 0.741 0.618 0.391 0.618 0.451 0.210 HIGH 3.528 1.099 0.353 0.211 4.744 4.448 3.797 4.448 3.985 3.105 WGHTD AVE 2.121 0.504 0.212 0.114 2.566 2.325 1.824 2.325 1.965 1.339
FLAGLER LOW 0.454 0.057 0.045 0.051 0.403 0.306 0.158 0.306 0.194 0.067 HIGH 1.300 0.264 0.130 0.087 1.460 1.273 0.918 1.273 1.012 0.614 WGHTD AVE 0.555 0.083 0.057 0.056 0.527 0.416 0.239 0.416 0.283 0.119
FRANKLIN LOW 0.976 0.175 0.098 0.061 1.041 0.887 0.598 0.887 0.674 0.362 HIGH 2.936 0.845 0.294 0.159 3.813 3.543 2.948 3.543 3.118 2.335 WGHTD AVE 1.770 0.440 0.177 0.099 2.144 1.932 1.498 1.932 1.618 1.093
GADSDEN LOW 0.211 0.024 0.021 0.030 0.174 0.124 0.055 0.124 0.071 0.019 HIGH 0.392 0.048 0.039 0.042 0.360 0.280 0.150 0.280 0.182 0.064 WGHTD AVE 0.263 0.030 0.026 0.038 0.227 0.168 0.082 0.168 0.102 0.031
GILCHRIST LOW 0.396 0.054 0.040 0.057 0.369 0.287 0.162 0.287 0.192 0.079 HIGH 0.445 0.063 0.044 0.059 0.423 0.334 0.196 0.334 0.230 0.099 WGHTD AVE 0.430 0.060 0.042 0.058 0.405 0.319 0.185 0.319 0.218 0.093
GLADES LOW 1.837 0.315 0.184 0.091 1.998 1.739 1.205 1.739 1.351 0.733 HIGH 2.357 0.451 0.236 0.112 2.668 2.374 1.734 2.374 1.912 1.128 WGHTD AVE 2.346 0.448 0.235 0.111 2.653 2.360 1.722 2.360 1.900 1.119
GULF LOW 0.714 0.103 0.071 0.053 0.707 0.579 0.351 0.579 0.410 0.177 HIGH 2.202 0.601 0.220 0.115 2.783 2.554 2.068 2.554 2.206 1.584 WGHTD AVE 1.809 0.450 0.181 0.096 2.204 2.004 1.589 2.004 1.705 1.192
HAMILTON LOW 0.153 0.016 0.015 0.045 0.124 0.082 0.036 0.082 0.046 0.012 HIGH 0.191 0.021 0.019 0.057 0.159 0.112 0.052 0.112 0.066 0.019 WGHTD AVE 0.174 0.019 0.017 0.054 0.143 0.098 0.045 0.098 0.057 0.016
HARDEE LOW 1.364 0.247 0.136 0.084 1.519 1.325 0.914 1.325 1.025 0.560 HIGH 1.547 0.278 0.155 0.090 1.690 1.466 1.023 1.466 1.142 0.638 WGHTD AVE 1.446 0.257 0.145 0.086 1.574 1.363 0.948 1.363 1.060 0.588
HENDRY LOW 1.905 0.364 0.191 0.099 2.118 1.854 1.315 1.854 1.462 0.834 HIGH 3.379 0.720 0.338 0.159 4.023 3.680 2.856 3.680 3.105 2.034 WGHTD AVE 2.735 0.558 0.267 0.129 3.167 2.859 2.171 2.859 2.366 1.497
HERNANDO LOW 0.555 0.085 0.055 0.048 0.538 0.432 0.258 0.432 0.302 0.138 HIGH 0.945 0.180 0.094 0.068 1.025 0.885 0.636 0.885 0.703 0.423 WGHTD AVE 0.824 0.144 0.082 0.062 0.874 0.743 0.505 0.743 0.568 0.310
HIGHLANDS LOW 1.505 0.253 0.150 0.088 1.599 1.370 0.922 1.370 1.041 0.544 HIGH 2.092 0.408 0.209 0.106 2.361 2.088 1.513 2.088 1.671 0.991 WGHTD AVE 1.794 0.326 0.180 0.098 1.971 1.720 1.209 1.720 1.348 0.758
HILLSBOROUGH LOW 0.702 0.112 0.070 0.057 0.715 0.595 0.384 0.595 0.439 0.217 HIGH 2.638 0.739 0.264 0.159 3.423 3.185 2.675 3.185 2.819 2.156 WGHTD AVE 1.192 0.241 0.121 0.080 1.350 1.188 0.879 1.188 0.963 0.607
HOLMES LOW 0.525 0.071 0.053 0.043 0.508 0.410 0.240 0.410 0.283 0.117 HIGH 0.665 0.097 0.066 0.050 0.663 0.546 0.335 0.546 0.390 0.174 WGHTD AVE 0.647 0.094 0.065 0.049 0.642 0.528 0.321 0.528 0.375 0.165
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 193 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL -Owners -- MASONRY 0% 0% $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 1.575 0.297 0.157 0.086 1.694 1.446 0.967 1.446 1.095 0.569 HIGH 4.796 1.539 0.480 0.295 6.544 6.170 5.329 6.170 5.573 4.423 WGHTD AVE 3.271 0.878 0.345 0.188 4.174 3.851 3.162 3.851 3.357 2.473
JACKSON LOW 0.442 0.057 0.044 0.042 0.413 0.325 0.180 0.325 0.216 0.080 HIGH 0.654 0.097 0.065 0.051 0.654 0.539 0.331 0.539 0.385 0.173 WGHTD AVE 0.514 0.068 0.051 0.046 0.491 0.393 0.225 0.393 0.267 0.106
JEFFERSON LOW 0.163 0.017 0.016 0.036 0.134 0.093 0.041 0.093 0.053 0.013 HIGH 0.223 0.025 0.022 0.042 0.191 0.139 0.067 0.139 0.084 0.025 WGHTD AVE 0.185 0.020 0.018 0.040 0.153 0.108 0.049 0.108 0.063 0.017
LAFAYETTE LOW 0.282 0.034 0.028 0.047 0.253 0.191 0.101 0.191 0.123 0.044 HIGH 0.286 0.035 0.029 0.048 0.256 0.193 0.103 0.193 0.124 0.046 WGHTD AVE 0.286 0.035 0.029 0.048 0.256 0.193 0.102 0.193 0.124 0.045
LAKE LOW 0.546 0.068 0.055 0.055 0.507 0.397 0.220 0.397 0.264 0.098 HIGH 1.517 0.282 0.152 0.093 1.653 1.429 0.991 1.429 1.108 0.618 WGHTD AVE 1.091 0.179 0.109 0.075 1.125 0.943 0.611 0.943 0.698 0.349
LEE LOW 1.448 0.289 0.145 0.088 1.604 1.393 0.982 1.393 1.092 0.630 HIGH 4.384 1.500 0.438 0.300 6.141 5.828 5.132 5.828 5.332 4.379 WGHTD AVE 1.934 0.434 0.198 0.111 2.285 2.044 1.559 2.044 1.692 1.111
LEON LOW 0.186 0.020 0.019 0.030 0.153 0.107 0.047 0.107 0.061 0.016 HIGH 0.404 0.049 0.040 0.051 0.373 0.291 0.156 0.291 0.190 0.067 WGHTD AVE 0.278 0.031 0.028 0.043 0.239 0.178 0.088 0.178 0.109 0.034
LEVY LOW 0.288 0.036 0.029 0.036 0.261 0.200 0.108 0.200 0.130 0.047 HIGH 0.942 0.188 0.094 0.073 1.043 0.901 0.641 0.901 0.709 0.428 WGHTD AVE 0.554 0.083 0.056 0.064 0.544 0.441 0.271 0.441 0.314 0.148
LIBERTY LOW 0.288 0.033 0.029 0.035 0.251 0.188 0.093 0.188 0.115 0.035 HIGH 0.319 0.037 0.032 0.037 0.281 0.213 0.107 0.213 0.133 0.041 WGHTD AVE 0.315 0.036 0.031 0.035 0.277 0.210 0.105 0.210 0.130 0.040
MADISON LOW 0.164 0.018 0.016 0.041 0.136 0.094 0.043 0.094 0.055 0.015 HIGH 0.223 0.026 0.022 0.057 0.189 0.136 0.065 0.136 0.082 0.025 WGHTD AVE 0.200 0.022 0.020 0.044 0.170 0.121 0.058 0.121 0.072 0.021
MANATEE LOW 1.095 0.231 0.110 0.080 1.225 1.066 0.773 1.066 0.851 0.524 HIGH 4.138 1.420 0.414 0.276 5.821 5.545 4.924 5.545 5.104 4.247 WGHTD AVE 1.527 0.350 0.155 0.098 1.813 1.629 1.269 1.629 1.367 0.940
MARION LOW 0.301 0.034 0.030 0.048 0.260 0.193 0.096 0.193 0.119 0.037 HIGH 0.905 0.139 0.091 0.083 0.915 0.757 0.481 0.757 0.552 0.268 WGHTD AVE 0.684 0.101 0.068 0.073 0.669 0.541 0.328 0.541 0.382 0.172
MARTIN LOW 3.060 0.767 0.306 0.167 3.784 3.476 2.773 3.476 2.973 2.071 HIGH 5.863 1.910 0.586 0.361 8.093 7.682 6.741 7.682 7.018 5.690 WGHTD AVE 4.220 1.214 0.424 0.243 5.540 5.179 4.372 5.179 4.605 3.517
MIAMI-DADE LOW 2.249 0.448 0.225 0.172 2.589 2.308 1.749 2.308 1.901 1.244 HIGH 12.889 4.818 1.289 0.949 19.129 18.603 17.241 18.603 17.659 15.522 WGHTD AVE 5.762 1.506 0.591 0.343 7.554 7.139 6.150 7.139 6.442 5.042
MONROE LOW 6.446 2.088 0.645 0.395 8.928 8.487 7.471 8.487 7.770 6.322 HIGH 11.597 4.414 1.160 0.858 17.250 16.750 15.479 16.750 15.866 13.890 WGHTD AVE 8.629 3.147 0.867 0.602 12.479 12.009 10.873 12.009 11.214 9.518
NASSAU LOW 0.170 0.018 0.017 0.038 0.139 0.095 0.043 0.095 0.054 0.014 HIGH 0.665 0.108 0.067 0.067 0.690 0.575 0.376 0.575 0.428 0.220 WGHTD AVE 0.376 0.052 0.038 0.050 0.350 0.274 0.157 0.274 0.186 0.077
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 194 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL -Owners -- MASONRY 0% 0% $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 0.799 0.123 0.080 0.053 0.814 0.677 0.426 0.677 0.492 0.224 HIGH 3.344 0.994 0.334 0.180 4.415 4.122 3.476 4.122 3.663 2.794 WGHTD AVE 2.053 0.514 0.206 0.110 2.519 2.289 1.811 2.289 1.944 1.347
OKEECHOBEE LOW 2.411 0.483 0.241 0.115 2.762 2.465 1.820 2.465 2.001 1.201 HIGH 3.862 0.988 0.386 0.194 4.839 4.489 3.657 4.489 3.896 2.781 WGHTD AVE 3.327 0.817 0.335 0.168 4.103 3.769 3.001 3.769 3.221 2.209
ORANGE LOW 0.723 0.102 0.072 0.058 0.681 0.539 0.304 0.539 0.363 0.142 HIGH 1.758 0.334 0.176 0.105 1.963 1.724 1.241 1.724 1.373 0.806 WGHTD AVE 1.072 0.161 0.108 0.073 1.082 0.898 0.560 0.898 0.648 0.297
OSCEOLA LOW 0.751 0.102 0.075 0.060 0.708 0.562 0.315 0.562 0.377 0.143 HIGH 1.730 0.332 0.173 0.099 1.925 1.688 1.206 1.688 1.338 0.778 WGHTD AVE 1.216 0.205 0.123 0.075 1.274 1.076 0.699 1.076 0.798 0.395
PALM BEACH LOW 3.230 0.761 0.323 0.167 3.939 3.619 2.872 3.619 3.088 2.106 HIGH 11.122 4.129 1.112 0.780 16.346 15.835 14.535 15.835 14.931 12.936 WGHTD AVE 4.718 1.261 0.494 0.268 6.116 5.727 4.833 5.727 5.093 3.868
PASCO LOW 0.671 0.115 0.067 0.056 0.685 0.569 0.367 0.569 0.419 0.213 HIGH 1.619 0.411 0.162 0.102 2.001 1.825 1.466 1.825 1.565 1.127 WGHTD AVE 0.951 0.176 0.096 0.067 1.034 0.893 0.632 0.893 0.701 0.412
PINELLAS LOW 1.002 0.205 0.100 0.071 1.127 0.985 0.719 0.985 0.791 0.487 HIGH 3.595 1.097 0.335 0.212 4.985 4.724 4.152 4.724 4.316 3.540 WGHTD AVE 1.675 0.402 0.173 0.102 2.047 1.865 1.496 1.865 1.599 1.142
POLK LOW 0.820 0.118 0.082 0.060 0.791 0.636 0.369 0.636 0.437 0.177 HIGH 1.814 0.323 0.181 0.103 1.981 1.724 1.207 1.724 1.347 0.749 WGHTD AVE 1.280 0.225 0.130 0.082 1.376 1.179 0.801 1.179 0.902 0.484
PUTNAM LOW 0.298 0.034 0.030 0.051 0.260 0.192 0.096 0.192 0.119 0.038 HIGH 0.688 0.092 0.069 0.073 0.665 0.534 0.314 0.534 0.370 0.154 WGHTD AVE 0.501 0.063 0.050 0.063 0.466 0.365 0.203 0.365 0.243 0.093
SAINT JOHNS LOW 0.239 0.028 0.024 0.041 0.192 0.136 0.060 0.136 0.077 0.020 HIGH 0.796 0.140 0.080 0.071 0.827 0.688 0.448 0.688 0.510 0.265 WGHTD AVE 0.558 0.088 0.056 0.060 0.549 0.443 0.272 0.443 0.315 0.150
SAINT LUCIE LOW 2.418 0.572 0.242 0.137 2.883 2.572 1.953 2.572 2.122 1.376 HIGH 6.279 2.109 0.628 0.385 8.775 8.346 7.353 8.346 7.645 6.247 WGHTD AVE 2.964 0.738 0.299 0.161 3.642 3.305 2.605 3.305 2.801 1.929
SANTA ROSA LOW 0.884 0.140 0.088 0.058 0.913 0.769 0.499 0.769 0.571 0.282 HIGH 4.079 1.290 0.408 0.234 5.530 5.240 4.522 5.240 4.732 3.720 WGHTD AVE 2.168 0.544 0.215 0.118 2.658 2.436 1.944 2.436 2.083 1.464
SARASOTA LOW 1.077 0.232 0.108 0.081 1.199 1.039 0.743 1.039 0.821 0.500 HIGH 3.084 0.967 0.308 0.203 4.169 3.928 3.390 3.928 3.545 2.828 WGHTD AVE 1.850 0.463 0.189 0.114 2.284 2.090 1.685 2.090 1.798 1.297
SEMINOLE LOW 0.783 0.111 0.078 0.063 0.748 0.599 0.346 0.599 0.410 0.165 HIGH 1.243 0.202 0.124 0.079 1.291 1.082 0.702 1.082 0.802 0.399 WGHTD AVE 0.965 0.141 0.097 0.070 0.962 0.790 0.487 0.790 0.566 0.255
SUMTER LOW 0.676 0.095 0.068 0.052 0.667 0.544 0.336 0.544 0.389 0.178 HIGH 0.964 0.152 0.096 0.080 0.988 0.826 0.532 0.826 0.608 0.301 WGHTD AVE 0.747 0.115 0.075 0.074 0.734 0.595 0.363 0.595 0.422 0.194
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 195 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL -Owners -- MASONRY 0% 0% $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.244 0.029 0.024 0.049 0.212 0.155 0.077 0.155 0.095 0.031 HIGH 0.343 0.044 0.034 0.054 0.312 0.240 0.131 0.240 0.157 0.060 WGHTD AVE 0.276 0.033 0.028 0.050 0.244 0.181 0.093 0.181 0.114 0.040
TAYLOR LOW 0.168 0.018 0.017 0.035 0.141 0.101 0.048 0.101 0.060 0.017 HIGH 0.367 0.053 0.037 0.049 0.353 0.282 0.166 0.282 0.195 0.084 WGHTD AVE 0.297 0.036 0.030 0.046 0.266 0.202 0.107 0.202 0.130 0.045
UNION LOW 0.234 0.025 0.023 0.065 0.201 0.144 0.070 0.144 0.087 0.027 HIGH 0.279 0.031 0.028 0.068 0.241 0.175 0.087 0.175 0.108 0.034 WGHTD AVE 0.268 0.030 0.027 0.068 0.230 0.166 0.082 0.166 0.101 0.032
VOLUSIA LOW 0.434 0.054 0.043 0.045 0.379 0.284 0.140 0.284 0.174 0.054 HIGH 2.015 0.463 0.202 0.120 2.399 2.152 1.657 2.152 1.794 1.200 WGHTD AVE 0.900 0.137 0.091 0.065 0.901 0.745 0.470 0.745 0.541 0.261
WAKULLA LOW 0.238 0.027 0.024 0.031 0.200 0.145 0.067 0.145 0.085 0.023 HIGH 0.863 0.143 0.086 0.058 0.897 0.755 0.490 0.755 0.560 0.280 WGHTD AVE 0.332 0.039 0.034 0.035 0.294 0.227 0.122 0.227 0.147 0.055
WALTON LOW 0.669 0.097 0.067 0.049 0.667 0.549 0.335 0.549 0.391 0.170 HIGH 2.941 0.887 0.294 0.172 3.860 3.578 2.976 3.578 3.147 2.364 WGHTD AVE 1.654 0.397 0.163 0.093 1.970 1.764 1.354 1.764 1.466 0.978
WASHINGTON LOW 0.627 0.089 0.063 0.047 0.616 0.504 0.303 0.504 0.355 0.150 HIGH 0.847 0.130 0.085 0.057 0.865 0.722 0.455 0.722 0.525 0.241 WGHTD AVE 0.699 0.104 0.070 0.050 0.699 0.576 0.355 0.576 0.413 0.184
Statewide LOW 0.153 0.016 0.015 0.030 0.124 0.083 0.036 0.083 0.046 0.012 HIGH 12.889 4.818 1.289 0.949 19.129 18.603 17.241 18.603 17.659 15.522 WGHTD AVE 2.618 0.595 0.268 0.145 3.174 2.921 2.382 2.921 2.534 1.845
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 196 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - MOBILE HOMES $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 1.693 0.088 0.169 0.090 1.685 1.490 1.117 1.685 1.490 1.117 HIGH 2.736 0.190 0.274 0.149 2.892 2.631 2.095 2.892 2.631 2.095 WGHTD AVE 2.097 0.127 0.210 0.112 2.153 1.932 1.497 2.153 1.932 1.497
BAKER LOW 0.934 0.035 0.093 0.069 0.832 0.688 0.459 0.832 0.688 0.459 HIGH 1.334 0.057 0.133 0.085 1.256 1.077 0.767 1.256 1.077 0.767 WGHTD AVE 1.170 0.048 0.117 0.079 1.081 0.916 0.638 1.081 0.916 0.638
BAY LOW 3.708 0.304 0.371 0.189 4.127 3.850 3.212 4.127 3.850 3.212 HIGH 17.146 4.152 1.715 1.308 23.328 22.725 21.097 23.328 22.725 21.097 WGHTD AVE 7.874 1.262 0.827 0.505 9.816 9.418 8.433 9.816 9.418 8.433
BRADFORD LOW 1.512 0.067 0.151 0.096 1.440 1.243 0.899 1.440 1.243 0.899 HIGH 1.680 0.082 0.168 0.106 1.625 1.414 1.036 1.625 1.414 1.036 WGHTD AVE 1.598 0.074 0.160 0.101 1.534 1.329 0.971 1.534 1.329 0.971
BREVARD LOW 6.015 0.629 0.602 0.328 6.966 6.566 5.638 6.966 6.566 5.638 HIGH 23.504 5.732 2.350 1.885 32.130 31.362 29.275 32.130 31.362 29.275 WGHTD AVE 12.650 2.321 1.283 0.897 16.278 15.724 14.309 16.278 15.724 14.309
BROWARD LOW 22.178 3.813 2.218 1.795 28.708 28.079 26.156 28.708 28.079 26.156 HIGH 34.227 8.302 3.423 3.166 46.977 46.131 43.710 46.977 46.131 43.710 WGHTD AVE 26.044 4.973 2.599 2.210 34.255 33.537 31.442 34.255 33.537 31.442
CALHOUN LOW 2.429 0.150 0.243 0.113 2.577 2.359 1.884 2.577 2.359 1.884 HIGH 3.172 0.230 0.317 0.153 3.461 3.204 2.628 3.461 3.204 2.628 WGHTD AVE 2.872 0.198 0.287 0.137 3.108 2.868 2.334 3.108 2.868 2.334
CHARLOTTE LOW 9.085 1.343 0.908 0.596 11.343 10.907 9.735 11.343 10.907 9.735 HIGH 14.452 3.305 1.445 1.143 19.487 18.954 17.568 19.487 18.954 17.568 WGHTD AVE 10.275 1.782 1.024 0.717 13.101 12.628 11.444 13.101 12.628 11.444
CITRUS LOW 2.906 0.215 0.291 0.159 3.134 2.878 2.349 3.134 2.878 2.349 HIGH 3.925 0.359 0.392 0.216 4.431 4.140 3.495 4.431 4.140 3.495 WGHTD AVE 3.442 0.308 0.345 0.190 3.862 3.599 3.019 3.862 3.599 3.019
CLAY LOW 1.491 0.067 0.149 0.082 1.420 1.225 0.887 1.420 1.225 0.887 HIGH 2.636 0.174 0.264 0.135 2.746 2.488 1.960 2.746 2.488 1.960 WGHTD AVE 1.867 0.099 0.188 0.109 1.861 1.647 1.247 1.861 1.647 1.247
COLLIER LOW 10.303 1.373 1.030 0.678 12.687 12.192 10.909 12.687 12.192 10.909 HIGH 19.693 4.615 1.969 1.603 26.734 26.086 24.334 26.734 26.086 24.334 WGHTD AVE 12.292 2.054 1.230 0.857 15.585 15.047 13.667 15.585 15.047 13.667
COLUMBIA LOW 1.143 0.046 0.114 0.079 1.047 0.882 0.607 1.047 0.882 0.607 HIGH 1.845 0.110 0.184 0.100 1.874 1.674 1.285 1.874 1.674 1.285 WGHTD AVE 1.632 0.089 0.164 0.095 1.620 1.428 1.070 1.620 1.428 1.070
DESOTO LOW 8.710 1.206 0.871 0.560 10.754 10.288 9.143 10.754 10.288 9.143 HIGH 9.373 1.337 0.937 0.594 11.486 10.992 9.781 11.486 10.992 9.781 WGHTD AVE 9.277 1.324 0.928 0.592 11.389 10.906 9.716 11.389 10.906 9.716
DIXIE LOW 1.888 0.118 0.189 0.104 1.941 1.742 1.355 1.941 1.742 1.355 HIGH 3.855 0.441 0.386 0.223 4.414 4.115 3.471 4.414 4.115 3.471 WGHTD AVE 2.084 0.147 0.210 0.112 2.181 1.972 1.559 2.181 1.972 1.559
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 197 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - MOBILE HOMES $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 1.070 0.042 0.107 0.078 0.974 0.817 0.562 0.974 0.817 0.562 HIGH 5.092 0.462 0.509 0.304 6.015 5.664 4.883 6.015 5.664 4.883 WGHTD AVE 1.861 0.111 0.182 0.099 1.900 1.703 1.320 1.900 1.703 1.320
ESCAMBIA LOW 3.509 0.281 0.351 0.182 3.911 3.653 3.062 3.911 3.653 3.062 HIGH 17.033 3.994 1.703 1.327 23.063 22.464 20.873 23.063 22.464 20.873 WGHTD AVE 8.850 1.325 0.860 0.565 10.931 10.489 9.400 10.931 10.489 9.400
FLAGLER LOW 2.441 0.141 0.244 0.125 2.522 2.276 1.780 2.522 2.276 1.780 HIGH 6.846 0.927 0.685 0.399 8.241 7.829 6.858 8.241 7.829 6.858 WGHTD AVE 4.058 0.439 0.383 0.228 4.653 4.342 3.663 4.653 4.342 3.663
FRANKLIN LOW 5.018 0.573 0.502 0.273 5.862 5.536 4.766 5.862 5.536 4.766 HIGH 12.798 2.628 1.280 0.895 16.768 16.235 14.846 16.768 16.235 14.846 WGHTD AVE 7.784 1.262 0.781 0.500 9.707 9.300 8.294 9.707 9.300 8.294
GADSDEN LOW 1.169 0.054 0.117 0.054 1.155 1.015 0.735 1.155 1.015 0.735 HIGH 1.833 0.103 0.183 0.084 1.895 1.714 1.326 1.895 1.714 1.326 WGHTD AVE 1.300 0.062 0.130 0.063 1.282 1.128 0.826 1.282 1.128 0.826
GILCHRIST LOW 2.193 0.152 0.219 0.119 2.292 2.072 1.630 2.292 2.072 1.630 HIGH 2.395 0.181 0.240 0.131 2.543 2.314 1.851 2.543 2.314 1.851 WGHTD AVE 2.329 0.172 0.232 0.127 2.461 2.235 1.778 2.461 2.235 1.778
GLADES LOW 9.861 1.078 0.986 0.574 11.728 11.225 9.931 11.728 11.225 9.931 HIGH 12.997 1.683 1.300 0.818 15.904 15.347 13.803 15.904 15.347 13.803 WGHTD AVE 12.904 1.665 1.290 0.811 15.782 15.226 13.687 15.782 15.226 13.687
GULF LOW 3.548 0.278 0.355 0.179 3.917 3.640 3.017 3.917 3.640 3.017 HIGH 10.259 2.010 1.026 0.691 13.300 12.845 11.678 13.300 12.845 11.678 WGHTD AVE 5.815 0.826 0.648 0.356 7.076 6.737 5.931 7.076 6.737 5.931
HAMILTON LOW 0.885 0.033 0.088 0.061 0.781 0.639 0.417 0.781 0.639 0.417 HIGH 1.035 0.044 0.103 0.069 0.966 0.821 0.568 0.966 0.821 0.568 WGHTD AVE 0.952 0.037 0.095 0.066 0.860 0.715 0.480 0.860 0.715 0.480
HARDEE LOW 7.381 0.814 0.738 0.426 8.695 8.262 7.208 8.695 8.262 7.208 HIGH 8.278 1.015 0.828 0.486 9.852 9.384 8.234 9.852 9.384 8.234 WGHTD AVE 7.786 0.907 0.780 0.459 9.250 8.807 7.718 9.250 8.807 7.718
HENDRY LOW 11.497 1.505 1.150 0.718 14.041 13.501 12.064 14.041 13.501 12.064 HIGH 17.631 2.677 1.763 1.203 22.212 21.566 19.621 22.212 21.566 19.621 WGHTD AVE 14.931 2.162 1.505 0.993 18.615 18.020 16.330 18.615 18.020 16.330
HERNANDO LOW 3.136 0.245 0.314 0.167 3.480 3.240 2.702 3.480 3.240 2.702 HIGH 5.035 0.628 0.504 0.310 5.968 5.647 4.912 5.968 5.647 4.912 WGHTD AVE 4.176 0.438 0.417 0.244 4.823 4.536 3.887 4.823 4.536 3.887
HIGHLANDS LOW 8.173 0.855 0.817 0.457 9.567 9.100 7.919 9.567 9.100 7.919 HIGH 11.325 1.509 1.132 0.684 13.812 13.277 11.839 13.812 13.277 11.839 WGHTD AVE 9.162 1.040 0.916 0.526 10.859 10.363 9.100 10.859 10.363 9.100
HILLSBOROUGH LOW 4.076 0.391 0.408 0.237 4.652 4.368 3.726 4.652 4.368 3.726 HIGH 9.636 1.837 0.964 0.697 12.451 12.018 10.941 12.451 12.018 10.941 WGHTD AVE 6.537 0.909 0.656 0.423 7.948 7.577 6.700 7.948 7.577 6.700
HOLMES LOW 2.537 0.174 0.254 0.124 2.730 2.513 2.034 2.730 2.513 2.034 HIGH 3.330 0.268 0.333 0.170 3.692 3.438 2.863 3.692 3.438 2.863 WGHTD AVE 3.176 0.245 0.316 0.159 3.499 3.253 2.695 3.499 3.253 2.695
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 198 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - MOBILE HOMES $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 11.010 1.434 1.101 0.670 13.405 12.858 11.449 13.405 12.858 11.449 HIGH 23.762 5.746 2.376 1.939 32.494 31.749 29.697 32.494 31.749 29.697 WGHTD AVE 15.350 2.847 1.534 1.087 19.858 19.236 17.589 19.858 19.236 17.589
JACKSON LOW 2.167 0.132 0.217 0.101 2.283 2.082 1.650 2.283 2.082 1.650 HIGH 3.239 0.267 0.324 0.165 3.592 3.345 2.780 3.592 3.345 2.780 WGHTD AVE 2.541 0.173 0.253 0.121 2.723 2.503 2.018 2.723 2.503 2.018
JEFFERSON LOW 0.859 0.034 0.086 0.049 0.788 0.664 0.448 0.788 0.664 0.448 HIGH 1.111 0.049 0.111 0.059 1.062 0.918 0.651 1.062 0.918 0.651 WGHTD AVE 0.999 0.042 0.100 0.055 0.939 0.804 0.558 0.939 0.804 0.558
LAFAYETTE LOW 1.389 0.073 0.139 0.075 1.373 1.209 0.898 1.373 1.209 0.898 HIGH 1.484 0.082 0.148 0.081 1.483 1.311 0.987 1.483 1.311 0.987 WGHTD AVE 1.484 0.082 0.148 0.081 1.482 1.311 0.986 1.482 1.311 0.986
LAKE LOW 2.781 0.159 0.278 0.142 2.883 2.610 2.049 2.883 2.610 2.049 HIGH 8.847 1.096 0.885 0.523 10.598 10.122 8.899 10.598 10.122 8.899 WGHTD AVE 5.683 0.567 0.569 0.313 6.533 6.155 5.262 6.533 6.155 5.262
LEE LOW 9.611 1.388 0.961 0.623 11.834 11.356 10.141 11.834 11.356 10.141 HIGH 22.216 5.731 1.767 1.884 30.765 30.073 28.189 30.765 30.073 28.189 WGHTD AVE 11.024 1.841 1.107 0.761 13.941 13.432 12.154 13.941 13.432 12.154
LEON LOW 1.001 0.041 0.100 0.054 0.932 0.791 0.542 0.932 0.791 0.542 HIGH 1.897 0.109 0.190 0.093 1.950 1.768 1.375 1.950 1.768 1.375 WGHTD AVE 1.524 0.080 0.152 0.071 1.539 1.374 1.039 1.539 1.374 1.039
LEVY LOW 1.545 0.087 0.154 0.078 1.580 1.407 1.077 1.580 1.407 1.077 HIGH 4.767 0.618 0.477 0.274 5.636 5.316 4.588 5.636 5.316 4.588 WGHTD AVE 3.035 0.257 0.305 0.171 3.316 3.053 2.503 3.316 3.053 2.503
LIBERTY LOW 1.443 0.071 0.144 0.066 1.448 1.288 0.966 1.448 1.288 0.966 HIGH 1.528 0.077 0.153 0.069 1.549 1.385 1.050 1.549 1.385 1.050 WGHTD AVE 1.518 0.076 0.152 0.068 1.536 1.372 1.038 1.536 1.372 1.038
MADISON LOW 0.900 0.035 0.090 0.054 0.803 0.661 0.439 0.803 0.661 0.439 HIGH 1.221 0.057 0.122 0.068 1.175 1.017 0.728 1.175 1.017 0.728 WGHTD AVE 1.061 0.047 0.106 0.062 1.002 0.858 0.602 1.002 0.858 0.602
MANATEE LOW 7.332 1.015 0.733 0.473 8.937 8.547 7.579 8.937 8.547 7.579 HIGH 16.108 4.018 1.611 1.354 22.088 21.531 20.079 22.088 21.531 20.079 WGHTD AVE 8.655 1.492 0.863 0.615 10.979 10.560 9.541 10.979 10.560 9.541
MARION LOW 1.552 0.072 0.155 0.079 1.522 1.338 0.984 1.522 1.338 0.984 HIGH 4.916 0.447 0.492 0.275 5.520 5.147 4.332 5.520 5.147 4.332 WGHTD AVE 3.677 0.301 0.368 0.203 4.024 3.718 3.064 4.024 3.718 3.064
MARTIN LOW 18.766 3.445 1.877 1.395 24.462 23.830 21.973 24.462 23.830 21.973 HIGH 27.205 6.724 2.721 2.271 37.381 36.589 34.377 37.381 36.589 34.377 WGHTD AVE 21.842 4.762 2.186 1.707 29.241 28.530 26.571 29.241 28.530 26.571
MIAMI-DADE LOW 20.876 3.258 2.088 1.702 26.673 26.065 24.241 26.673 26.065 24.241 HIGH 45.748 12.930 4.575 4.669 65.166 64.214 61.397 65.166 64.214 61.397 WGHTD AVE 27.997 5.633 2.805 2.434 37.173 36.443 34.270 37.173 36.443 34.270
MONROE LOW 28.373 7.035 2.837 2.448 39.038 38.192 35.895 39.038 38.192 35.895 HIGH 43.973 12.919 4.397 4.397 63.103 62.185 59.476 63.103 62.185 59.476 WGHTD AVE 36.447 10.012 3.644 3.447 51.375 50.496 47.998 51.375 50.496 47.998
NASSAU LOW 0.966 0.038 0.097 0.063 0.888 0.750 0.514 0.888 0.750 0.514 HIGH 3.331 0.323 0.333 0.165 3.739 3.472 2.904 3.739 3.472 2.904 WGHTD AVE 1.482 0.086 0.149 0.084 1.496 1.330 1.017 1.496 1.330 1.017
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 199 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - MOBILE HOMES $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 4.250 0.368 0.425 0.227 4.811 4.517 3.828 4.811 4.517 3.828 HIGH 15.134 3.352 1.513 1.116 20.193 19.621 18.119 20.193 19.621 18.119 WGHTD AVE 6.543 0.946 0.664 0.425 8.020 7.651 6.767 8.020 7.651 6.767
OKEECHOBEE LOW 13.307 1.860 1.331 0.851 16.457 15.890 14.317 16.457 15.890 14.317 HIGH 19.475 3.604 1.947 1.361 25.251 24.590 22.612 25.251 24.590 22.612 WGHTD AVE 18.176 3.254 1.814 1.265 23.440 22.791 20.881 23.440 22.791 20.881
ORANGE LOW 4.335 0.320 0.434 0.215 4.774 4.447 3.692 4.774 4.447 3.692 HIGH 8.636 1.081 0.864 0.496 10.319 9.836 8.635 10.319 9.836 8.635 WGHTD AVE 5.652 0.493 0.569 0.298 6.399 6.011 5.095 6.399 6.011 5.095
OSCEOLA LOW 4.554 0.321 0.455 0.226 5.001 4.658 3.866 5.001 4.658 3.866 HIGH 9.082 1.161 0.908 0.538 10.915 10.435 9.209 10.915 10.435 9.209 WGHTD AVE 7.412 0.762 0.743 0.407 8.635 8.202 7.115 8.635 8.202 7.115
PALM BEACH LOW 19.041 3.461 1.904 1.430 24.758 24.172 22.341 24.758 24.172 22.341 HIGH 36.160 8.981 3.341 3.316 50.493 49.625 47.100 50.493 49.625 47.100 WGHTD AVE 24.162 4.861 2.423 1.978 32.024 31.290 29.218 32.024 31.290 29.218
PASCO LOW 3.986 0.405 0.399 0.233 4.589 4.319 3.697 4.589 4.319 3.697 HIGH 7.271 1.310 0.727 0.494 9.244 8.874 7.980 9.244 8.874 7.980 WGHTD AVE 5.366 0.634 0.538 0.328 6.343 6.004 5.219 6.343 6.004 5.219
PINELLAS LOW 5.559 0.770 0.613 0.361 6.748 6.424 5.670 6.748 6.424 5.670 HIGH 10.961 2.394 1.096 0.854 14.556 14.115 13.002 14.556 14.115 13.002 WGHTD AVE 7.136 1.153 0.709 0.488 8.930 8.566 7.690 8.930 8.566 7.690
POLK LOW 5.095 0.414 0.509 0.262 5.763 5.407 4.563 5.763 5.407 4.563 HIGH 9.441 1.099 0.944 0.549 11.186 10.675 9.378 11.186 10.675 9.378 WGHTD AVE 7.399 0.820 0.744 0.428 8.722 8.293 7.231 8.722 8.293 7.231
PUTNAM LOW 1.569 0.073 0.157 0.087 1.534 1.345 0.991 1.534 1.345 0.991 HIGH 3.449 0.247 0.345 0.177 3.687 3.382 2.732 3.687 3.382 2.732 WGHTD AVE 2.531 0.151 0.255 0.130 2.629 2.377 1.864 2.629 2.377 1.864
SAINT JOHNS LOW 1.793 0.096 0.179 0.092 1.818 1.624 1.247 1.818 1.624 1.247 HIGH 4.679 0.508 0.468 0.254 5.409 5.077 4.343 5.409 5.077 4.343 WGHTD AVE 2.863 0.218 0.283 0.148 3.068 2.805 2.275 3.068 2.805 2.275
SAINT LUCIE LOW 16.495 2.960 1.650 1.166 21.279 20.593 18.791 21.279 20.593 18.791 HIGH 26.954 6.782 2.695 2.255 37.174 36.342 34.064 37.174 36.342 34.064 WGHTD AVE 18.687 3.738 1.867 1.398 24.589 23.878 22.001 24.589 23.878 22.001
SANTA ROSA LOW 4.461 0.392 0.446 0.239 5.054 4.754 4.036 5.054 4.754 4.036 HIGH 18.464 4.384 1.846 1.443 25.082 24.522 22.813 25.082 24.522 22.813 WGHTD AVE 8.515 1.265 0.856 0.543 10.514 10.106 9.024 10.514 10.106 9.024
SARASOTA LOW 7.675 1.162 0.768 0.524 9.526 9.162 8.212 9.526 9.162 8.212 HIGH 14.515 3.362 1.451 1.173 19.583 19.071 17.695 19.583 19.071 17.695 WGHTD AVE 9.663 1.781 0.987 0.701 12.447 12.037 10.951 12.447 12.037 10.951
SEMINOLE LOW 4.544 0.345 0.454 0.226 5.011 4.668 3.890 5.011 4.668 3.890 HIGH 6.688 0.659 0.570 0.361 7.711 7.263 6.242 7.711 7.263 6.242 WGHTD AVE 5.003 0.403 0.500 0.255 5.574 5.196 4.360 5.574 5.196 4.360
SUMTER LOW 3.554 0.270 0.355 0.202 3.866 3.567 2.936 3.866 3.567 2.936 HIGH 5.360 0.517 0.536 0.300 6.147 5.787 4.946 6.147 5.787 4.946 WGHTD AVE 4.238 0.362 0.424 0.236 4.731 4.409 3.696 4.731 4.409 3.696
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 200 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - MOBILE HOMES $0 $0 $0 DEDUCTIBLE $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE APPURTENANT ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS STRUCTURE LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 1.301 0.064 0.130 0.074 1.261 1.096 0.795 1.261 1.096 0.795 HIGH 1.861 0.116 0.186 0.101 1.899 1.699 1.307 1.899 1.699 1.307 WGHTD AVE 1.481 0.080 0.149 0.082 1.466 1.290 0.960 1.466 1.290 0.960
TAYLOR LOW 0.828 0.034 0.083 0.045 0.771 0.655 0.449 0.771 0.655 0.449 HIGH 1.866 0.145 0.187 0.094 2.009 1.840 1.483 2.009 1.840 1.483 WGHTD AVE 1.541 0.089 0.157 0.080 1.563 1.394 1.065 1.563 1.394 1.065
UNION LOW 1.209 0.049 0.121 0.083 1.118 0.947 0.661 1.118 0.947 0.661 HIGH 1.520 0.070 0.152 0.100 1.454 1.256 0.917 1.454 1.256 0.917 WGHTD AVE 1.478 0.067 0.148 0.095 1.407 1.213 0.878 1.407 1.213 0.878
VOLUSIA LOW 2.738 0.151 0.274 0.131 2.826 2.554 1.997 2.826 2.554 1.997 HIGH 9.899 1.577 0.942 0.622 12.334 11.816 10.554 12.334 11.816 10.554 WGHTD AVE 4.579 0.396 0.455 0.235 5.137 4.792 4.023 5.137 4.792 4.023
WAKULLA LOW 1.276 0.061 0.128 0.057 1.272 1.128 0.836 1.272 1.128 0.836 HIGH 4.346 0.436 0.435 0.224 4.968 4.668 3.961 4.968 4.668 3.961 WGHTD AVE 1.439 0.079 0.143 0.067 1.465 1.311 0.996 1.465 1.311 0.996
WALTON LOW 3.340 0.261 0.334 0.171 3.700 3.448 2.871 3.700 3.448 2.871 HIGH 15.936 3.600 1.594 1.179 21.350 20.751 19.168 21.350 20.751 19.168 WGHTD AVE 6.063 0.816 0.646 0.382 7.351 7.001 6.163 7.351 7.001 6.163
WASHINGTON LOW 3.103 0.228 0.310 0.154 3.399 3.153 2.602 3.399 3.153 2.602 HIGH 4.267 0.375 0.427 0.222 4.821 4.521 3.826 4.821 4.521 3.826 WGHTD AVE 3.591 0.301 0.358 0.185 4.013 3.747 3.139 4.013 3.747 3.139
Statewide LOW 0.828 0.033 0.083 0.045 0.771 0.639 0.416 0.771 0.639 0.416 HIGH 45.748 12.930 4.575 4.669 65.166 64.219 61.443 65.166 64.219 61.443 WGHTD AVE 7.877 1.195 0.814 0.507 9.734 9.327 8.343 9.734 9.327 8.343
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 201 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Renters -- FRAME $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.107 0.112 0.034 0.018 0.005 0.061 0.034 0.014 HIGH 0.181 0.135 0.080 0.048 0.018 0.122 0.080 0.039 WGHTD AVE 0.122 0.118 0.043 0.023 0.007 0.072 0.043 0.018
BAKER LOW 0.047 0.116 0.009 0.003 0.000 0.023 0.009 0.002 HIGH 0.073 0.126 0.017 0.007 0.001 0.037 0.017 0.005 WGHTD AVE 0.065 0.125 0.015 0.006 0.001 0.033 0.015 0.004
BAY LOW 0.289 0.120 0.144 0.088 0.032 0.205 0.144 0.072 HIGH 2.983 0.588 2.895 2.564 1.939 3.141 2.895 2.431 WGHTD AVE 1.196 0.252 0.990 0.818 0.550 1.136 0.990 0.756
BRADFORD LOW 0.088 0.145 0.023 0.010 0.002 0.049 0.023 0.007 HIGH 0.102 0.154 0.031 0.015 0.004 0.059 0.031 0.012 WGHTD AVE 0.091 0.146 0.025 0.011 0.002 0.050 0.025 0.008
BREVARD LOW 0.646 0.206 0.442 0.331 0.189 0.551 0.442 0.294 HIGH 4.841 0.968 4.894 4.426 3.509 5.239 4.894 4.235 WGHTD AVE 1.433 0.318 1.201 0.999 0.685 1.374 1.201 0.926
BROWARD LOW 2.370 0.624 2.146 1.770 1.137 2.450 2.146 1.626 HIGH 7.431 1.710 7.921 7.245 5.828 8.403 7.921 6.958 WGHTD AVE 5.033 0.847 5.076 4.532 3.466 5.483 5.076 4.309
CALHOUN LOW 0.202 0.098 0.082 0.045 0.013 0.130 0.082 0.035 HIGH 0.239 0.110 0.106 0.061 0.020 0.160 0.106 0.049 WGHTD AVE 0.212 0.102 0.089 0.050 0.015 0.138 0.089 0.039
CHARLOTTE LOW 0.839 0.228 0.658 0.516 0.307 0.779 0.658 0.467 HIGH 2.110 0.483 2.044 1.796 1.336 2.230 2.044 1.699 WGHTD AVE 1.428 0.324 1.255 1.060 0.735 1.414 1.255 0.987
CITRUS LOW 0.205 0.111 0.098 0.059 0.021 0.144 0.098 0.048 HIGH 0.331 0.154 0.188 0.127 0.058 0.255 0.188 0.108 WGHTD AVE 0.271 0.131 0.148 0.098 0.043 0.203 0.148 0.083
CLAY LOW 0.079 0.103 0.020 0.008 0.002 0.042 0.020 0.006 HIGH 0.172 0.139 0.066 0.037 0.014 0.108 0.066 0.030 WGHTD AVE 0.132 0.130 0.049 0.027 0.009 0.081 0.049 0.022
COLLIER LOW 0.933 0.258 0.698 0.526 0.286 0.848 0.698 0.466 HIGH 3.256 0.684 3.183 2.812 2.116 3.460 3.183 2.665 WGHTD AVE 2.275 0.452 2.130 1.848 1.344 2.349 2.130 1.738
COLUMBIA LOW 0.062 0.111 0.014 0.005 0.001 0.032 0.014 0.004 HIGH 0.113 0.150 0.040 0.022 0.007 0.067 0.040 0.018 WGHTD AVE 0.079 0.128 0.022 0.011 0.003 0.043 0.022 0.008
DESOTO LOW 0.947 0.261 0.718 0.558 0.330 0.861 0.718 0.503 HIGH 1.035 0.278 0.816 0.658 0.417 0.954 0.816 0.602 WGHTD AVE 1.028 0.276 0.794 0.626 0.381 0.945 0.794 0.567
DIXIE LOW 0.126 0.114 0.050 0.028 0.010 0.079 0.050 0.023 HIGH 0.223 0.137 0.121 0.082 0.040 0.167 0.121 0.070 WGHTD AVE 0.159 0.116 0.070 0.043 0.016 0.107 0.070 0.035
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 202 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- FRAME $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.057 0.085 0.012 0.004 0.001 0.029 0.012 0.003 HIGH 0.406 0.181 0.272 0.205 0.120 0.343 0.272 0.183 WGHTD AVE 0.148 0.114 0.062 0.037 0.014 0.096 0.062 0.030
ESCAMBIA LOW 0.290 0.120 0.152 0.096 0.040 0.215 0.152 0.080 HIGH 3.022 0.614 2.951 2.620 1.994 3.198 2.951 2.487 WGHTD AVE 1.351 0.308 1.146 0.949 0.640 1.311 1.146 0.877
FLAGLER LOW 0.157 0.117 0.056 0.029 0.008 0.094 0.056 0.022 HIGH 0.621 0.201 0.448 0.345 0.206 0.547 0.448 0.311 WGHTD AVE 0.283 0.131 0.152 0.104 0.052 0.206 0.152 0.090
FRANKLIN LOW 0.502 0.299 0.331 0.244 0.137 0.419 0.331 0.216 HIGH 1.546 0.329 1.369 1.163 0.823 1.538 1.369 1.087 WGHTD AVE 1.397 0.321 1.220 1.027 0.718 1.382 1.220 0.957
GADSDEN LOW 0.070 0.067 0.016 0.006 0.001 0.033 0.016 0.005 HIGH 0.127 0.088 0.042 0.021 0.005 0.073 0.042 0.016 WGHTD AVE 0.085 0.079 0.022 0.010 0.002 0.043 0.022 0.007
GILCHRIST LOW 0.149 0.124 0.064 0.040 0.016 0.098 0.064 0.033 HIGH 0.180 0.130 0.087 0.056 0.025 0.126 0.087 0.048 WGHTD AVE 0.175 0.129 0.083 0.054 0.024 0.121 0.083 0.045
GLADES LOW 1.339 0.324 1.005 0.764 0.423 1.219 1.005 0.680 HIGH 1.339 0.324 1.005 0.765 0.423 1.219 1.005 0.680 WGHTD AVE 1.339 0.324 1.005 0.765 0.423 1.219 1.005 0.680
GULF LOW 0.288 0.123 0.140 0.086 0.032 0.204 0.140 0.071 HIGH 1.484 0.305 1.314 1.116 0.786 1.474 1.314 1.042 WGHTD AVE 1.223 0.243 1.035 0.871 0.607 1.172 1.035 0.811
HAMILTON LOW 0.043 0.090 0.008 0.003 0.000 0.021 0.008 0.002 HIGH 0.051 0.116 0.010 0.004 0.001 0.025 0.010 0.003 WGHTD AVE 0.050 0.110 0.010 0.004 0.001 0.024 0.010 0.003
HARDEE LOW 0.694 0.216 0.463 0.335 0.170 0.588 0.463 0.293 HIGH 0.806 0.238 0.601 0.466 0.276 0.725 0.601 0.420 WGHTD AVE 0.726 0.222 0.497 0.365 0.193 0.623 0.497 0.322
HENDRY LOW 1.269 0.314 0.966 0.747 0.430 1.162 0.966 0.670 HIGH 2.005 0.457 1.664 1.334 0.816 1.939 1.664 1.212 WGHTD AVE 1.480 0.351 1.165 0.914 0.539 1.383 1.165 0.824
HERNANDO LOW 0.285 0.122 0.160 0.108 0.048 0.217 0.160 0.092 HIGH 0.468 0.166 0.321 0.241 0.136 0.400 0.321 0.214 WGHTD AVE 0.352 0.138 0.220 0.157 0.080 0.284 0.220 0.137
HIGHLANDS LOW 0.721 0.229 0.458 0.321 0.154 0.594 0.458 0.277 HIGH 1.206 0.297 0.910 0.701 0.405 1.097 0.910 0.630 WGHTD AVE 0.931 0.265 0.652 0.481 0.256 0.812 0.652 0.424
HILLSBOROUGH LOW 0.301 0.135 0.172 0.116 0.051 0.231 0.172 0.099 HIGH 1.635 0.381 1.547 1.360 1.027 1.698 1.547 1.288 WGHTD AVE 0.799 0.209 0.644 0.529 0.354 0.746 0.644 0.488
HOLMES LOW 0.217 0.101 0.095 0.053 0.016 0.146 0.095 0.042 HIGH 0.261 0.114 0.130 0.081 0.031 0.187 0.130 0.066 WGHTD AVE 0.251 0.111 0.122 0.074 0.027 0.177 0.122 0.061
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 203 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- FRAME $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 1.148 0.279 0.833 0.626 0.340 1.020 0.833 0.555 HIGH 4.245 0.870 4.221 3.767 2.897 4.558 4.221 3.584 WGHTD AVE 3.136 0.487 2.899 2.534 1.877 3.184 2.899 2.391
JACKSON LOW 0.147 0.090 0.052 0.027 0.007 0.087 0.052 0.020 HIGH 0.269 0.117 0.140 0.090 0.037 0.197 0.140 0.075 WGHTD AVE 0.190 0.102 0.080 0.046 0.015 0.124 0.080 0.037
JEFFERSON LOW 0.049 0.077 0.009 0.003 0.000 0.022 0.009 0.002 HIGH 0.066 0.088 0.015 0.006 0.001 0.032 0.015 0.004 WGHTD AVE 0.055 0.083 0.011 0.004 0.001 0.026 0.011 0.003
LAFAYETTE LOW 0.095 0.101 0.032 0.018 0.006 0.055 0.032 0.014 HIGH 0.095 0.101 0.032 0.018 0.006 0.055 0.032 0.014 WGHTD AVE 0.095 0.101 0.032 0.018 0.006 0.055 0.032 0.014
LAKE LOW 0.186 0.137 0.068 0.035 0.009 0.114 0.068 0.026 HIGH 0.899 0.259 0.644 0.486 0.270 0.792 0.644 0.433 WGHTD AVE 0.502 0.186 0.300 0.207 0.100 0.397 0.300 0.178
LEE LOW 0.821 0.238 0.599 0.452 0.248 0.730 0.599 0.402 HIGH 4.687 0.962 4.846 4.428 3.577 5.148 4.846 4.255 WGHTD AVE 1.914 0.361 1.718 1.480 1.073 1.910 1.718 1.390
LEON LOW 0.055 0.061 0.010 0.003 0.000 0.025 0.010 0.002 HIGH 0.132 0.106 0.045 0.023 0.007 0.077 0.045 0.018 WGHTD AVE 0.084 0.086 0.022 0.010 0.002 0.043 0.022 0.007
LEVY LOW 0.108 0.078 0.040 0.022 0.006 0.064 0.040 0.017 HIGH 0.524 0.178 0.385 0.305 0.195 0.465 0.385 0.278 WGHTD AVE 0.288 0.148 0.169 0.122 0.067 0.224 0.169 0.108
LIBERTY LOW 0.097 0.074 0.026 0.011 0.002 0.049 0.026 0.008 HIGH 0.100 0.080 0.028 0.012 0.002 0.053 0.028 0.009 WGHTD AVE 0.097 0.075 0.026 0.011 0.002 0.050 0.026 0.008
MADISON LOW 0.050 0.085 0.010 0.004 0.001 0.024 0.010 0.003 HIGH 0.070 0.095 0.018 0.008 0.002 0.036 0.018 0.006 WGHTD AVE 0.061 0.089 0.014 0.006 0.001 0.031 0.014 0.004
MANATEE LOW 0.716 0.219 0.551 0.426 0.249 0.662 0.551 0.383 HIGH 3.482 0.748 3.581 3.267 2.638 3.813 3.581 3.139 WGHTD AVE 1.265 0.307 1.130 0.964 0.687 1.267 1.130 0.902
MARION LOW 0.090 0.102 0.023 0.010 0.002 0.045 0.023 0.007 HIGH 0.406 0.195 0.232 0.165 0.085 0.310 0.232 0.144 WGHTD AVE 0.281 0.165 0.144 0.094 0.041 0.204 0.144 0.079
MARTIN LOW 2.284 0.512 1.999 1.664 1.100 2.275 1.999 1.536 HIGH 5.433 1.100 5.513 4.983 3.928 5.904 5.513 4.765 WGHTD AVE 4.022 0.757 3.921 3.479 2.642 4.258 3.921 3.302
MIAMI-DADE LOW 2.215 0.607 2.008 1.657 1.054 2.293 2.008 1.521 HIGH 10.941 2.465 11.948 11.091 9.180 12.541 11.948 10.716 WGHTD AVE 6.771 1.144 7.084 6.438 5.108 7.554 7.084 6.166
MONROE LOW 5.715 1.181 5.840 5.276 4.157 6.250 5.840 5.044 HIGH 11.898 2.538 12.979 12.139 10.203 13.567 12.979 11.763 WGHTD AVE 7.102 1.459 7.407 6.768 5.435 7.866 7.407 6.498
NASSAU LOW 0.048 0.082 0.008 0.003 0.000 0.022 0.008 0.002 HIGH 0.294 0.149 0.177 0.125 0.063 0.234 0.177 0.109 WGHTD AVE 0.193 0.118 0.097 0.063 0.028 0.138 0.097 0.053
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 204 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- FRAME $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 0.338 0.127 0.183 0.117 0.046 0.253 0.183 0.098 HIGH 2.540 0.502 2.407 2.107 1.564 2.635 2.407 1.990 WGHTD AVE 1.358 0.290 1.158 0.966 0.659 1.317 1.158 0.896
OKEECHOBEE LOW 1.372 0.327 1.044 0.801 0.452 1.255 1.044 0.716 HIGH 2.639 0.551 2.358 1.999 1.374 2.652 2.358 1.857 WGHTD AVE 2.003 0.454 1.720 1.415 0.924 1.974 1.720 1.301
ORANGE LOW 0.264 0.136 0.109 0.061 0.018 0.168 0.109 0.048 HIGH 0.736 0.236 0.504 0.372 0.204 0.632 0.504 0.329 WGHTD AVE 0.452 0.172 0.239 0.152 0.061 0.334 0.239 0.126
OSCEOLA LOW 0.284 0.140 0.119 0.065 0.018 0.185 0.119 0.050 HIGH 0.857 0.242 0.600 0.448 0.247 0.743 0.600 0.397 WGHTD AVE 0.510 0.181 0.300 0.203 0.093 0.401 0.300 0.173
PALM BEACH LOW 2.374 0.525 2.092 1.745 1.167 2.377 2.092 1.613 HIGH 7.984 1.715 8.440 7.740 6.273 8.938 8.440 7.443 WGHTD AVE 5.882 0.996 6.009 5.432 4.276 6.434 6.009 5.193
PASCO LOW 0.340 0.139 0.211 0.149 0.072 0.274 0.211 0.129 HIGH 0.838 0.220 0.703 0.586 0.408 0.807 0.703 0.546 WGHTD AVE 0.487 0.170 0.341 0.258 0.148 0.420 0.341 0.230
PINELLAS LOW 0.527 0.173 0.388 0.300 0.168 0.470 0.388 0.268 HIGH 2.675 0.528 2.700 2.445 1.945 2.889 2.700 2.342 WGHTD AVE 1.085 0.265 0.951 0.807 0.569 1.072 0.951 0.753
POLK LOW 0.360 0.150 0.176 0.106 0.037 0.255 0.176 0.086 HIGH 0.917 0.269 0.632 0.463 0.253 0.792 0.632 0.406 WGHTD AVE 0.658 0.212 0.439 0.319 0.167 0.556 0.439 0.280
PUTNAM LOW 0.096 0.119 0.026 0.011 0.002 0.052 0.026 0.008 HIGH 0.259 0.161 0.123 0.076 0.032 0.182 0.123 0.064 WGHTD AVE 0.170 0.133 0.063 0.034 0.010 0.105 0.063 0.026
SAINT JOHNS LOW 0.065 0.081 0.014 0.006 0.001 0.029 0.014 0.004 HIGH 0.400 0.168 0.254 0.184 0.100 0.326 0.254 0.162 WGHTD AVE 0.266 0.135 0.153 0.108 0.058 0.203 0.153 0.095
SAINT LUCIE LOW 1.842 0.424 1.557 1.268 0.812 1.795 1.557 1.163 HIGH 5.031 1.041 5.092 4.575 3.566 5.465 5.092 4.365 WGHTD AVE 2.672 0.543 2.419 2.061 1.453 2.701 2.419 1.926
SANTA ROSA LOW 0.383 0.142 0.220 0.147 0.070 0.297 0.220 0.125 HIGH 3.370 0.664 3.297 2.940 2.234 3.568 3.297 2.790 WGHTD AVE 1.474 0.302 1.262 1.062 0.734 1.428 1.262 0.987
SARASOTA LOW 0.687 0.213 0.532 0.412 0.240 0.637 0.532 0.370 HIGH 2.749 0.602 2.747 2.469 1.939 2.958 2.747 2.357 WGHTD AVE 1.573 0.320 1.438 1.254 0.930 1.589 1.438 1.183
SEMINOLE LOW 0.251 0.135 0.105 0.060 0.020 0.161 0.105 0.048 HIGH 0.499 0.186 0.292 0.198 0.094 0.391 0.292 0.170 WGHTD AVE 0.389 0.165 0.199 0.125 0.050 0.282 0.199 0.103
SUMTER LOW 0.265 0.125 0.133 0.084 0.033 0.192 0.133 0.070 HIGH 0.388 0.187 0.227 0.157 0.076 0.303 0.227 0.135 WGHTD AVE 0.337 0.177 0.184 0.123 0.055 0.253 0.184 0.104
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 205 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- FRAME $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.079 0.103 0.023 0.011 0.003 0.044 0.023 0.009 HIGH 0.125 0.118 0.049 0.028 0.010 0.078 0.049 0.023 WGHTD AVE 0.085 0.106 0.026 0.013 0.004 0.048 0.026 0.010
TAYLOR LOW 0.042 0.067 0.007 0.002 0.000 0.018 0.007 0.002 HIGH 0.149 0.104 0.071 0.046 0.020 0.103 0.071 0.038 WGHTD AVE 0.096 0.098 0.030 0.015 0.004 0.055 0.030 0.011
UNION LOW 0.084 0.135 0.021 0.009 0.002 0.045 0.021 0.006 HIGH 0.085 0.142 0.023 0.010 0.002 0.047 0.023 0.007 WGHTD AVE 0.085 0.140 0.022 0.010 0.002 0.046 0.022 0.007
VOLUSIA LOW 0.168 0.105 0.057 0.028 0.007 0.096 0.057 0.021 HIGH 1.103 0.293 0.892 0.726 0.475 1.040 0.892 0.667 WGHTD AVE 0.389 0.154 0.216 0.146 0.069 0.294 0.216 0.124
WAKULLA LOW 0.068 0.065 0.014 0.006 0.001 0.030 0.014 0.004 HIGH 0.406 0.141 0.246 0.174 0.091 0.324 0.246 0.151 WGHTD AVE 0.112 0.069 0.040 0.024 0.010 0.063 0.040 0.020
WALTON LOW 0.272 0.114 0.135 0.082 0.028 0.195 0.135 0.066 HIGH 2.344 0.487 2.199 1.908 1.386 2.422 2.199 1.795 WGHTD AVE 1.291 0.259 1.086 0.902 0.610 1.238 1.086 0.836
WASHINGTON LOW 0.247 0.111 0.116 0.069 0.023 0.172 0.116 0.055 HIGH 0.364 0.128 0.194 0.122 0.048 0.272 0.194 0.100 WGHTD AVE 0.293 0.119 0.151 0.095 0.037 0.214 0.151 0.079
Statewide LOW 0.042 0.061 0.007 0.002 0.000 0.018 0.007 0.002 HIGH 11.898 2.538 12.979 12.126 10.187 13.567 12.979 11.749 WGHTD AVE 1.590 0.209 1.362 1.188 0.888 1.506 1.362 1.122
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 206 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Renters -- MASONRY 0% $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.069 0.099 0.014 0.006 0.001 0.031 0.014 0.004 HIGH 0.136 0.126 0.050 0.029 0.012 0.083 0.050 0.024 WGHTD AVE 0.093 0.114 0.026 0.012 0.003 0.049 0.026 0.009
BAKER LOW 0.037 0.116 0.006 0.001 0.000 0.018 0.006 0.001 HIGH 0.056 0.126 0.010 0.003 0.000 0.028 0.010 0.002 WGHTD AVE 0.054 0.124 0.010 0.003 0.000 0.026 0.010 0.002
BAY LOW 0.205 0.102 0.081 0.045 0.014 0.128 0.081 0.036 HIGH 2.510 0.440 2.360 2.088 1.584 2.568 2.360 1.981 WGHTD AVE 1.006 0.201 0.807 0.668 0.457 0.929 0.807 0.619
BRADFORD LOW 0.067 0.142 0.013 0.005 0.001 0.034 0.013 0.003 HIGH 0.076 0.150 0.018 0.008 0.002 0.041 0.018 0.006 WGHTD AVE 0.071 0.144 0.015 0.006 0.001 0.036 0.015 0.004
BREVARD LOW 0.460 0.162 0.279 0.203 0.115 0.360 0.279 0.180 HIGH 4.079 0.725 4.007 3.621 2.877 4.299 4.007 3.466 WGHTD AVE 1.199 0.243 0.960 0.801 0.559 1.101 0.960 0.745
BROWARD LOW 1.762 0.426 1.481 1.198 0.744 1.720 1.481 1.093 HIGH 6.268 1.261 6.463 5.896 4.728 6.873 6.463 5.659 WGHTD AVE 3.021 0.566 2.766 2.389 1.717 3.065 2.766 2.242
CALHOUN LOW 0.147 0.087 0.047 0.023 0.006 0.082 0.047 0.017 HIGH 0.186 0.100 0.069 0.037 0.011 0.114 0.069 0.029 WGHTD AVE 0.164 0.094 0.057 0.030 0.008 0.096 0.057 0.023
CHARLOTTE LOW 0.740 0.180 0.542 0.419 0.249 0.657 0.542 0.378 HIGH 2.035 0.399 1.927 1.708 1.303 2.096 1.927 1.623 WGHTD AVE 0.985 0.230 0.797 0.655 0.435 0.921 0.797 0.604
CITRUS LOW 0.152 0.098 0.060 0.034 0.011 0.096 0.060 0.027 HIGH 0.231 0.142 0.112 0.074 0.034 0.159 0.112 0.063 WGHTD AVE 0.195 0.115 0.090 0.056 0.023 0.132 0.090 0.047
CLAY LOW 0.058 0.103 0.011 0.004 0.001 0.027 0.011 0.002 HIGH 0.131 0.143 0.043 0.023 0.008 0.076 0.043 0.019 WGHTD AVE 0.103 0.124 0.031 0.016 0.005 0.058 0.031 0.012
COLLIER LOW 0.676 0.192 0.444 0.324 0.169 0.558 0.444 0.285 HIGH 2.632 0.492 2.465 2.170 1.632 2.695 2.465 2.055 WGHTD AVE 1.497 0.270 1.269 1.075 0.754 1.429 1.269 1.003
COLUMBIA LOW 0.054 0.108 0.011 0.004 0.001 0.028 0.011 0.003 HIGH 0.092 0.145 0.027 0.014 0.004 0.051 0.027 0.011 WGHTD AVE 0.058 0.132 0.013 0.005 0.001 0.030 0.013 0.004
DESOTO LOW 0.504 0.169 0.319 0.231 0.121 0.405 0.319 0.203 HIGH 0.767 0.214 0.551 0.434 0.266 0.663 0.551 0.394 WGHTD AVE 0.757 0.210 0.539 0.417 0.249 0.656 0.539 0.377
DIXIE LOW 0.077 0.099 0.021 0.010 0.003 0.040 0.021 0.008 HIGH 0.118 0.107 0.042 0.023 0.007 0.071 0.042 0.018 WGHTD AVE 0.114 0.106 0.040 0.022 0.007 0.068 0.040 0.017
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 207 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- MASONRY 0% $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.044 0.087 0.007 0.002 0.000 0.022 0.007 0.001 HIGH 0.309 0.161 0.190 0.141 0.082 0.248 0.190 0.126 WGHTD AVE 0.120 0.112 0.044 0.025 0.010 0.073 0.044 0.020
ESCAMBIA LOW 0.209 0.101 0.093 0.057 0.024 0.139 0.093 0.047 HIGH 2.198 0.423 2.053 1.800 1.341 2.246 2.053 1.701 WGHTD AVE 1.112 0.245 0.912 0.755 0.516 1.049 0.912 0.699
FLAGLER LOW 0.113 0.107 0.030 0.013 0.003 0.059 0.030 0.010 HIGH 0.579 0.184 0.408 0.318 0.198 0.499 0.408 0.288 WGHTD AVE 0.173 0.116 0.070 0.042 0.018 0.106 0.070 0.035
FRANKLIN LOW 0.375 0.128 0.222 0.159 0.089 0.292 0.222 0.141 HIGH 1.254 0.250 1.062 0.897 0.635 1.203 1.062 0.838 WGHTD AVE 0.702 0.158 0.509 0.410 0.273 0.605 0.509 0.377
GADSDEN LOW 0.054 0.065 0.009 0.003 0.000 0.022 0.009 0.002 HIGH 0.084 0.085 0.020 0.008 0.001 0.041 0.020 0.006 WGHTD AVE 0.063 0.078 0.012 0.004 0.001 0.028 0.012 0.003
GILCHRIST LOW 0.123 0.122 0.047 0.028 0.011 0.077 0.047 0.023 HIGH 0.134 0.123 0.054 0.033 0.014 0.086 0.054 0.028 WGHTD AVE 0.130 0.123 0.052 0.031 0.013 0.083 0.052 0.026
GLADES LOW 0.993 0.236 0.673 0.494 0.264 0.842 0.673 0.436 HIGH 0.993 0.236 0.673 0.494 0.264 0.842 0.673 0.435 WGHTD AVE 0.993 0.236 0.673 0.494 0.264 0.842 0.673 0.435
GULF LOW 0.210 0.107 0.084 0.047 0.015 0.133 0.084 0.037 HIGH 1.256 0.236 1.074 0.913 0.652 1.210 1.074 0.854 WGHTD AVE 0.978 0.190 0.794 0.667 0.471 0.905 0.794 0.622
HAMILTON LOW 0.034 0.094 0.005 0.001 0.000 0.017 0.005 0.001 HIGH 0.045 0.118 0.008 0.003 0.000 0.021 0.008 0.002 WGHTD AVE 0.038 0.114 0.006 0.002 0.000 0.019 0.006 0.001
HARDEE LOW 0.505 0.171 0.297 0.206 0.100 0.394 0.297 0.178 HIGH 0.601 0.188 0.409 0.310 0.178 0.507 0.409 0.277 WGHTD AVE 0.540 0.177 0.330 0.234 0.119 0.430 0.330 0.204
HENDRY LOW 0.906 0.226 0.621 0.465 0.255 0.770 0.621 0.413 HIGH 1.473 0.322 1.127 0.881 0.522 1.343 1.127 0.794 WGHTD AVE 1.280 0.280 0.945 0.733 0.425 1.137 0.945 0.659
HERNANDO LOW 0.185 0.103 0.086 0.055 0.022 0.123 0.086 0.046 HIGH 0.373 0.143 0.237 0.174 0.096 0.302 0.237 0.155 WGHTD AVE 0.283 0.123 0.163 0.114 0.057 0.215 0.163 0.099
HIGHLANDS LOW 0.527 0.179 0.295 0.198 0.091 0.399 0.295 0.169 HIGH 0.897 0.223 0.615 0.461 0.257 0.764 0.615 0.409 WGHTD AVE 0.650 0.196 0.396 0.279 0.141 0.516 0.396 0.243
HILLSBOROUGH LOW 0.221 0.115 0.108 0.069 0.028 0.154 0.108 0.058 HIGH 1.309 0.288 1.192 1.043 0.786 1.314 1.192 0.988 WGHTD AVE 0.569 0.165 0.420 0.337 0.219 0.499 0.420 0.309
HOLMES LOW 0.194 0.099 0.080 0.045 0.016 0.124 0.080 0.036 HIGH 0.194 0.099 0.080 0.045 0.016 0.124 0.080 0.036 WGHTD AVE 0.194 0.099 0.080 0.045 0.016 0.124 0.080 0.036
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 208 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- MASONRY 0% $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 0.729 0.191 0.451 0.318 0.157 0.582 0.451 0.276 HIGH 3.534 0.642 3.403 3.030 2.329 3.685 3.403 2.882 WGHTD AVE 2.301 0.320 1.982 1.713 1.249 2.201 1.982 1.611
JACKSON LOW 0.097 0.082 0.025 0.011 0.002 0.048 0.025 0.008 HIGH 0.198 0.103 0.085 0.050 0.019 0.130 0.085 0.041 WGHTD AVE 0.141 0.093 0.048 0.025 0.007 0.082 0.048 0.019
JEFFERSON LOW 0.037 0.076 0.005 0.001 0.000 0.016 0.005 0.001 HIGH 0.046 0.086 0.008 0.002 0.000 0.021 0.008 0.001 WGHTD AVE 0.043 0.084 0.007 0.002 0.000 0.019 0.007 0.001
LAFAYETTE LOW 0.063 0.090 0.015 0.007 0.002 0.031 0.015 0.005 HIGH 0.063 0.090 0.015 0.007 0.002 0.031 0.015 0.005 WGHTD AVE 0.063 0.090 0.015 0.007 0.002 0.031 0.015 0.005
LAKE LOW 0.142 0.110 0.041 0.019 0.004 0.079 0.041 0.013 HIGH 0.610 0.193 0.384 0.278 0.146 0.493 0.384 0.244 WGHTD AVE 0.375 0.155 0.198 0.133 0.063 0.273 0.198 0.114
LEE LOW 0.541 0.170 0.345 0.250 0.128 0.437 0.345 0.218 HIGH 3.876 0.713 3.887 3.541 2.847 4.142 3.887 3.400 WGHTD AVE 0.941 0.219 0.718 0.576 0.366 0.844 0.718 0.526
LEON LOW 0.041 0.062 0.006 0.001 0.000 0.018 0.006 0.001 HIGH 0.097 0.101 0.026 0.011 0.003 0.050 0.026 0.008 WGHTD AVE 0.069 0.085 0.015 0.006 0.001 0.032 0.015 0.004
LEVY LOW 0.116 0.086 0.042 0.023 0.007 0.070 0.042 0.018 HIGH 0.272 0.155 0.169 0.127 0.074 0.217 0.169 0.113 WGHTD AVE 0.170 0.131 0.078 0.050 0.023 0.116 0.078 0.042
LIBERTY LOW 0.075 0.072 0.016 0.005 0.001 0.035 0.016 0.004 HIGH 0.077 0.076 0.016 0.006 0.001 0.035 0.016 0.004 WGHTD AVE 0.077 0.072 0.016 0.006 0.001 0.035 0.016 0.004
MADISON LOW 0.033 0.079 0.004 0.001 0.000 0.014 0.004 0.001 HIGH 0.056 0.116 0.012 0.004 0.001 0.028 0.012 0.003 WGHTD AVE 0.042 0.090 0.007 0.002 0.000 0.020 0.007 0.002
MANATEE LOW 0.510 0.172 0.365 0.282 0.161 0.442 0.365 0.252 HIGH 2.949 0.568 2.947 2.688 2.172 3.144 2.947 2.582 WGHTD AVE 0.811 0.211 0.660 0.547 0.372 0.760 0.660 0.507
MARION LOW 0.069 0.098 0.013 0.005 0.001 0.031 0.013 0.003 HIGH 0.298 0.173 0.147 0.095 0.044 0.212 0.147 0.081 WGHTD AVE 0.205 0.148 0.088 0.054 0.022 0.134 0.088 0.045
MARTIN LOW 1.929 0.381 1.609 1.334 0.887 1.845 1.609 1.231 HIGH 4.529 0.808 4.454 4.017 3.161 4.782 4.454 3.840 WGHTD AVE 2.795 0.503 2.568 2.242 1.652 2.826 2.568 2.115
MIAMI-DADE LOW 1.458 0.420 1.311 1.062 0.652 1.514 1.311 0.969 HIGH 10.349 2.007 11.042 10.286 8.602 11.567 11.042 9.956 WGHTD AVE 5.247 0.814 5.188 4.673 3.647 5.569 5.188 4.460
MONROE LOW 4.632 0.847 4.569 4.109 3.215 4.911 4.569 3.923 HIGH 10.051 1.892 10.669 9.947 8.319 11.177 10.669 9.631 WGHTD AVE 7.032 1.288 7.250 6.659 5.403 7.676 7.250 6.408
NASSAU LOW 0.033 0.080 0.005 0.001 0.000 0.015 0.005 0.001 HIGH 0.216 0.133 0.114 0.077 0.038 0.160 0.114 0.067 WGHTD AVE 0.146 0.108 0.063 0.039 0.017 0.095 0.063 0.032
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 209 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- MASONRY 0% $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 0.222 0.100 0.091 0.051 0.016 0.140 0.091 0.040 HIGH 2.031 0.365 1.847 1.608 1.187 2.037 1.847 1.516 WGHTD AVE 1.074 0.224 0.871 0.719 0.485 1.003 0.871 0.664
OKEECHOBEE LOW 1.040 0.240 0.723 0.541 0.297 0.893 0.723 0.480 HIGH 2.022 0.393 1.710 1.431 0.974 1.946 1.710 1.326 WGHTD AVE 1.650 0.340 1.342 1.098 0.718 1.553 1.342 1.009
ORANGE LOW 0.200 0.118 0.065 0.033 0.009 0.110 0.065 0.025 HIGH 0.524 0.189 0.319 0.229 0.122 0.417 0.319 0.201 WGHTD AVE 0.326 0.145 0.143 0.084 0.030 0.215 0.143 0.068
OSCEOLA LOW 0.203 0.120 0.065 0.031 0.007 0.113 0.065 0.023 HIGH 0.639 0.188 0.402 0.292 0.158 0.514 0.402 0.258 WGHTD AVE 0.391 0.147 0.199 0.129 0.057 0.278 0.199 0.108
PALM BEACH LOW 1.691 0.352 1.378 1.123 0.721 1.597 1.378 1.031 HIGH 9.060 1.674 9.491 8.793 7.278 9.982 9.491 8.493 WGHTD AVE 3.652 0.591 3.442 3.038 2.284 3.754 3.442 2.877
PASCO LOW 0.205 0.106 0.103 0.067 0.028 0.144 0.103 0.056 HIGH 0.763 0.189 0.643 0.547 0.392 0.729 0.643 0.512 WGHTD AVE 0.363 0.136 0.233 0.174 0.099 0.294 0.233 0.155
PINELLAS LOW 0.399 0.140 0.269 0.204 0.116 0.334 0.269 0.182 HIGH 2.203 0.435 2.155 1.948 1.544 2.313 2.155 1.865 WGHTD AVE 0.866 0.201 0.716 0.603 0.423 0.815 0.716 0.563
POLK LOW 0.243 0.120 0.092 0.050 0.015 0.146 0.092 0.039 HIGH 0.683 0.209 0.423 0.300 0.164 0.549 0.423 0.261 WGHTD AVE 0.473 0.167 0.277 0.194 0.097 0.366 0.277 0.168
PUTNAM LOW 0.072 0.112 0.015 0.005 0.001 0.036 0.015 0.004 HIGH 0.191 0.148 0.075 0.044 0.018 0.122 0.075 0.036 WGHTD AVE 0.126 0.126 0.037 0.017 0.004 0.070 0.037 0.013
SAINT JOHNS LOW 0.054 0.081 0.009 0.003 0.000 0.021 0.009 0.002 HIGH 0.302 0.150 0.173 0.123 0.067 0.230 0.173 0.108 WGHTD AVE 0.196 0.122 0.098 0.067 0.035 0.137 0.098 0.058
SAINT LUCIE LOW 1.203 0.285 0.940 0.740 0.438 1.109 0.940 0.669 HIGH 4.218 0.769 4.136 3.709 2.886 4.451 4.136 3.538 WGHTD AVE 1.784 0.347 1.498 1.251 0.852 1.702 1.498 1.161
SANTA ROSA LOW 0.286 0.118 0.142 0.091 0.043 0.202 0.142 0.077 HIGH 2.580 0.468 2.426 2.144 1.611 2.645 2.426 2.030 WGHTD AVE 1.401 0.261 1.195 1.019 0.724 1.344 1.195 0.953
SARASOTA LOW 0.558 0.167 0.402 0.314 0.192 0.486 0.402 0.282 HIGH 2.114 0.431 2.033 1.816 1.416 2.202 2.033 1.730 WGHTD AVE 1.163 0.240 1.008 0.869 0.634 1.126 1.008 0.817
SEMINOLE LOW 0.229 0.126 0.082 0.044 0.013 0.133 0.082 0.034 HIGH 0.445 0.164 0.236 0.155 0.073 0.326 0.236 0.132 WGHTD AVE 0.286 0.142 0.121 0.071 0.026 0.186 0.121 0.057
SUMTER LOW 0.181 0.107 0.073 0.042 0.014 0.115 0.073 0.034 HIGH 0.345 0.168 0.179 0.118 0.054 0.251 0.179 0.100 WGHTD AVE 0.262 0.157 0.125 0.080 0.035 0.182 0.125 0.067
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 210 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Renters -- MASONRY 0% $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.061 0.102 0.014 0.006 0.001 0.032 0.014 0.005 HIGH 0.094 0.115 0.030 0.016 0.005 0.054 0.030 0.012 WGHTD AVE 0.066 0.103 0.016 0.007 0.002 0.034 0.016 0.005
TAYLOR LOW 0.058 0.088 0.012 0.004 0.000 0.028 0.012 0.003 HIGH 0.080 0.100 0.021 0.009 0.002 0.043 0.021 0.007 WGHTD AVE 0.069 0.094 0.016 0.007 0.001 0.035 0.016 0.005
UNION LOW 0.063 0.133 0.012 0.004 0.001 0.031 0.012 0.003 HIGH 0.067 0.141 0.015 0.005 0.001 0.035 0.015 0.004 WGHTD AVE 0.064 0.138 0.013 0.005 0.001 0.033 0.013 0.003
VOLUSIA LOW 0.115 0.092 0.027 0.011 0.002 0.054 0.027 0.008 HIGH 0.824 0.229 0.623 0.501 0.325 0.739 0.623 0.459 WGHTD AVE 0.326 0.133 0.168 0.115 0.060 0.231 0.168 0.100
WAKULLA LOW 0.054 0.064 0.008 0.003 0.000 0.021 0.008 0.002 HIGH 0.300 0.119 0.158 0.108 0.056 0.220 0.158 0.093 WGHTD AVE 0.098 0.070 0.033 0.019 0.009 0.054 0.033 0.016
WALTON LOW 0.199 0.098 0.080 0.044 0.013 0.127 0.080 0.034 HIGH 2.195 0.391 2.014 1.761 1.311 2.213 2.014 1.663 WGHTD AVE 1.133 0.201 0.928 0.779 0.545 1.057 0.928 0.726
WASHINGTON LOW 0.181 0.096 0.069 0.037 0.011 0.112 0.069 0.028 HIGH 0.267 0.110 0.121 0.073 0.027 0.178 0.121 0.060 WGHTD AVE 0.220 0.103 0.095 0.055 0.019 0.144 0.095 0.044
Statewide LOW 0.033 0.062 0.004 0.001 0.000 0.014 0.004 0.001 HIGH 10.349 2.007 11.042 10.286 8.602 11.567 11.042 9.956 WGHTD AVE 1.942 0.279 1.681 1.465 1.085 1.858 1.681 1.382
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 211 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- FRAME $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.040 0.087 0.101 0.061 0.030 0.010 0.061 0.030 0.010 HIGH 0.067 0.172 0.134 0.151 0.093 0.047 0.151 0.093 0.047 WGHTD AVE 0.056 0.128 0.120 0.106 0.057 0.023 0.106 0.057 0.023
BAKER LOW 0.027 0.053 0.108 0.030 0.012 0.003 0.030 0.012 0.003 HIGH 0.027 0.053 0.108 0.030 0.012 0.003 0.030 0.012 0.003 WGHTD AVE 0.027 0.053 0.108 0.030 0.012 0.003 0.030 0.012 0.003
BAY LOW 0.156 0.557 0.163 0.563 0.441 0.274 0.563 0.441 0.274 HIGH 0.549 3.316 0.631 3.959 3.661 3.077 3.959 3.661 3.077 WGHTD AVE 0.385 1.879 0.391 2.252 2.025 1.619 2.252 2.025 1.619
BRADFORD LOW 0.044 0.000 0.000 0.078 0.031 0.009 0.078 0.031 0.009 HIGH 0.044 0.000 0.000 0.078 0.030 0.009 0.078 0.030 0.009 WGHTD AVE 0.044 0.000 0.000 0.078 0.030 0.009 0.078 0.030 0.009
BREVARD LOW 0.163 0.573 0.200 0.561 0.431 0.252 0.561 0.431 0.252 HIGH 0.784 4.841 0.968 5.898 5.506 4.720 5.898 5.506 4.720 WGHTD AVE 0.357 1.675 0.373 1.929 1.698 1.322 1.929 1.698 1.322
BROWARD LOW 0.299 1.104 0.452 1.317 1.088 0.700 1.317 1.088 0.700 HIGH 1.258 7.722 1.758 9.847 9.321 8.164 9.847 9.321 8.164 WGHTD AVE 0.751 3.712 0.895 4.563 4.153 3.351 4.563 4.153 3.351
CALHOUN LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
CHARLOTTE LOW 0.213 0.848 0.221 0.920 0.763 0.523 0.920 0.763 0.523 HIGH 0.453 2.585 0.549 3.119 2.873 2.414 3.119 2.873 2.414 WGHTD AVE 0.309 2.019 0.409 2.127 1.913 1.543 2.127 1.913 1.543
CITRUS LOW 0.073 0.220 0.107 0.200 0.146 0.080 0.200 0.146 0.080 HIGH 0.105 0.302 0.162 0.295 0.216 0.129 0.295 0.216 0.129 WGHTD AVE 0.097 0.273 0.127 0.262 0.184 0.101 0.262 0.184 0.101
CLAY LOW 0.044 0.079 0.120 0.055 0.024 0.007 0.055 0.024 0.007 HIGH 0.076 0.156 0.147 0.154 0.087 0.036 0.154 0.087 0.036 WGHTD AVE 0.055 0.129 0.129 0.107 0.059 0.025 0.107 0.059 0.025
COLLIER LOW 0.207 0.749 0.235 0.779 0.621 0.385 0.779 0.621 0.385 HIGH 0.583 3.328 0.695 4.021 3.696 3.072 4.021 3.696 3.072 WGHTD AVE 0.394 2.080 0.461 2.395 2.146 1.706 2.395 2.146 1.706
COLUMBIA LOW 0.038 0.077 0.116 0.067 0.026 0.008 0.067 0.026 0.008 HIGH 0.050 0.111 0.152 0.093 0.048 0.019 0.093 0.048 0.019 WGHTD AVE 0.039 0.082 0.146 0.074 0.030 0.010 0.074 0.030 0.010
DESOTO LOW 0.225 0.902 0.250 0.991 0.831 0.585 0.991 0.831 0.585 HIGH 0.270 1.035 0.278 1.135 0.942 0.656 1.135 0.942 0.656 WGHTD AVE 0.238 0.959 0.262 1.046 0.873 0.612 1.046 0.873 0.612
DIXIE LOW 0.050 0.141 0.109 0.113 0.076 0.038 0.113 0.076 0.038 HIGH 0.083 0.277 0.148 0.264 0.199 0.125 0.264 0.199 0.125 WGHTD AVE 0.063 0.189 0.120 0.168 0.121 0.070 0.168 0.121 0.070
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 212 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Condo Owners -- FRAME $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.032 0.068 0.082 0.041 0.020 0.006 0.041 0.020 0.006 HIGH 0.102 0.304 0.153 0.300 0.215 0.124 0.300 0.215 0.124 WGHTD AVE 0.056 0.140 0.109 0.118 0.071 0.033 0.118 0.071 0.033
ESCAMBIA LOW 0.110 0.302 0.244 0.285 0.196 0.098 0.285 0.196 0.098 HIGH 0.547 3.210 0.614 3.851 3.557 2.984 3.851 3.557 2.984 WGHTD AVE 0.349 1.740 0.378 1.990 1.763 1.373 1.990 1.763 1.373
FLAGLER LOW 0.097 0.250 0.131 0.229 0.144 0.067 0.229 0.144 0.067 HIGH 0.202 0.767 0.225 0.832 0.684 0.479 0.832 0.684 0.479 WGHTD AVE 0.112 0.376 0.146 0.345 0.251 0.146 0.345 0.251 0.146
FRANKLIN LOW 0.095 0.308 0.121 0.280 0.208 0.121 0.280 0.208 0.121 HIGH 0.296 1.371 0.299 1.550 1.352 1.030 1.550 1.352 1.030 WGHTD AVE 0.127 0.637 0.170 0.571 0.469 0.329 0.571 0.469 0.329
GADSDEN LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
GILCHRIST LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
GLADES LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
GULF LOW 0.233 1.151 0.264 1.292 1.131 0.855 1.292 1.131 0.855 HIGH 0.233 1.151 0.264 1.292 1.127 0.852 1.292 1.127 0.852 WGHTD AVE 0.233 1.151 0.264 1.292 1.127 0.852 1.292 1.127 0.852
HAMILTON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
HARDEE LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
HENDRY LOW 0.344 1.299 0.318 1.429 1.183 0.802 1.429 1.183 0.802 HIGH 0.494 2.005 0.457 2.301 1.975 1.405 2.301 1.975 1.405 WGHTD AVE 0.433 1.788 0.393 1.975 1.682 1.182 1.975 1.682 1.182
HERNANDO LOW 0.100 0.285 0.124 0.276 0.197 0.108 0.276 0.197 0.108 HIGH 0.141 0.479 0.169 0.502 0.395 0.266 0.502 0.395 0.266 WGHTD AVE 0.128 0.394 0.148 0.419 0.323 0.204 0.419 0.323 0.204
HIGHLANDS LOW 0.225 0.716 0.226 0.730 0.557 0.324 0.730 0.557 0.324 HIGH 0.324 1.206 0.297 1.316 1.086 0.726 1.316 1.086 0.726 WGHTD AVE 0.271 0.902 0.254 0.963 0.764 0.476 0.963 0.764 0.476
HILLSBOROUGH LOW 0.105 0.312 0.136 0.303 0.220 0.123 0.303 0.220 0.123 HIGH 0.308 1.600 0.376 1.899 1.718 1.410 1.899 1.718 1.410 WGHTD AVE 0.183 0.752 0.222 0.836 0.709 0.523 0.836 0.709 0.523
HOLMES LOW 0.077 0.194 0.104 0.171 0.107 0.047 0.171 0.107 0.047 HIGH 0.077 0.194 0.104 0.171 0.107 0.047 0.171 0.107 0.047 WGHTD AVE 0.077 0.194 0.104 0.171 0.106 0.047 0.171 0.106 0.047
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 213 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Condo Owners -- FRAME $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 0.413 1.872 0.411 2.127 1.852 1.381 2.127 1.852 1.381 HIGH 0.768 4.612 0.921 5.607 5.211 4.418 5.607 5.211 4.418 WGHTD AVE 0.541 3.074 0.606 3.518 3.192 2.592 3.518 3.192 2.592
JACKSON LOW 0.071 0.167 0.098 0.140 0.081 0.032 0.140 0.081 0.032 HIGH 0.071 0.167 0.098 0.140 0.082 0.032 0.140 0.082 0.032 WGHTD AVE 0.071 0.167 0.098 0.140 0.081 0.032 0.140 0.081 0.032
JEFFERSON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
LAFAYETTE LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
LAKE LOW 0.084 0.192 0.148 0.165 0.091 0.034 0.165 0.091 0.034 HIGH 0.213 0.689 0.220 0.707 0.544 0.355 0.707 0.544 0.355 WGHTD AVE 0.195 0.625 0.210 0.639 0.488 0.296 0.639 0.488 0.296
LEE LOW 0.184 0.677 0.219 0.700 0.559 0.351 0.700 0.559 0.351 HIGH 0.722 4.601 0.949 5.668 5.326 4.638 5.668 5.326 4.638 WGHTD AVE 0.319 2.187 0.423 2.158 1.927 1.534 2.158 1.927 1.534
LEON LOW 0.028 0.056 0.059 0.031 0.013 0.003 0.031 0.013 0.003 HIGH 0.058 0.129 0.094 0.102 0.055 0.020 0.102 0.055 0.020 WGHTD AVE 0.043 0.092 0.081 0.066 0.032 0.011 0.066 0.032 0.011
LEVY LOW 0.064 0.172 0.129 0.141 0.095 0.047 0.141 0.095 0.047 HIGH 0.119 0.431 0.159 0.444 0.354 0.242 0.444 0.354 0.242 WGHTD AVE 0.112 0.430 0.158 0.439 0.351 0.240 0.439 0.351 0.240
LIBERTY LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
MADISON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
MANATEE LOW 0.128 0.490 0.190 0.520 0.425 0.276 0.520 0.425 0.276 HIGH 0.556 3.482 0.748 4.283 4.016 3.493 4.283 4.016 3.493 WGHTD AVE 0.298 1.786 0.378 1.930 1.746 1.429 1.930 1.746 1.429
MARION LOW 0.047 0.095 0.104 0.075 0.033 0.010 0.075 0.033 0.010 HIGH 0.142 0.415 0.198 0.409 0.292 0.163 0.409 0.292 0.163 WGHTD AVE 0.112 0.321 0.175 0.303 0.209 0.114 0.303 0.209 0.114
MARTIN LOW 0.522 2.542 0.544 2.927 2.594 1.984 2.927 2.594 1.984 HIGH 0.896 5.433 1.100 6.661 6.226 5.333 6.661 6.226 5.333 WGHTD AVE 0.729 4.057 0.835 4.953 4.568 3.813 4.953 4.568 3.813
MIAMI-DADE LOW 0.425 1.873 0.634 2.382 2.101 1.564 2.382 2.101 1.564 HIGH 1.647 11.145 2.500 14.265 13.645 12.202 14.265 13.645 12.202 WGHTD AVE 1.019 6.534 1.587 7.736 7.247 6.211 7.736 7.247 6.211
MONROE LOW 0.817 5.014 1.201 6.258 5.815 4.909 6.258 5.815 4.909 HIGH 1.608 11.286 2.435 14.327 13.734 12.336 14.327 13.734 12.336 WGHTD AVE 1.201 7.514 1.662 9.507 8.992 7.861 9.507 8.992 7.861
NASSAU LOW 0.019 0.037 0.093 0.021 0.007 0.002 0.021 0.007 0.002 HIGH 0.097 0.295 0.149 0.295 0.213 0.126 0.295 0.213 0.126 WGHTD AVE 0.080 0.229 0.130 0.216 0.148 0.080 0.216 0.148 0.080
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 214 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Condo Owners -- FRAME $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 0.093 0.275 0.126 0.240 0.166 0.080 0.240 0.166 0.080 HIGH 0.448 2.486 0.495 2.932 2.668 2.174 2.932 2.668 2.174 WGHTD AVE 0.344 1.816 0.361 2.034 1.803 1.401 2.034 1.803 1.401
OKEECHOBEE LOW 0.552 2.639 0.551 3.073 2.742 2.105 3.073 2.742 2.105 HIGH 0.552 2.639 0.551 3.073 2.744 2.114 3.073 2.744 2.114 WGHTD AVE 0.552 2.639 0.551 3.073 2.710 2.085 3.073 2.710 2.085
ORANGE LOW 0.106 0.277 0.131 0.224 0.143 0.059 0.224 0.143 0.059 HIGH 0.250 0.895 0.260 0.955 0.770 0.506 0.955 0.770 0.506 WGHTD AVE 0.156 0.448 0.174 0.416 0.291 0.145 0.416 0.291 0.145
OSCEOLA LOW 0.109 0.276 0.138 0.230 0.143 0.057 0.230 0.143 0.057 HIGH 0.230 0.814 0.235 0.844 0.671 0.425 0.844 0.671 0.425 WGHTD AVE 0.147 0.443 0.167 0.404 0.286 0.148 0.404 0.286 0.148
PALM BEACH LOW 0.395 1.738 0.493 2.022 1.746 1.246 2.022 1.746 1.246 HIGH 1.565 10.699 2.258 13.516 12.917 11.535 13.516 12.917 11.535 WGHTD AVE 0.769 4.308 0.945 5.147 4.730 3.906 5.147 4.730 3.906
PASCO LOW 0.094 0.300 0.132 0.286 0.216 0.126 0.286 0.216 0.126 HIGH 0.196 0.838 0.220 0.946 0.815 0.615 0.946 0.815 0.615 WGHTD AVE 0.143 0.512 0.174 0.530 0.422 0.279 0.530 0.422 0.279
PINELLAS LOW 0.143 0.527 0.173 0.563 0.458 0.311 0.563 0.458 0.311 HIGH 0.446 2.728 0.587 3.320 3.096 2.667 3.320 3.096 2.667 WGHTD AVE 0.239 1.381 0.317 1.471 1.313 1.049 1.471 1.313 1.049
POLK LOW 0.115 0.310 0.139 0.264 0.175 0.078 0.264 0.175 0.078 HIGH 0.270 0.923 0.266 0.975 0.773 0.484 0.975 0.773 0.484 WGHTD AVE 0.190 0.656 0.213 0.656 0.509 0.311 0.656 0.509 0.311
PUTNAM LOW 0.072 0.160 0.128 0.134 0.072 0.026 0.134 0.072 0.026 HIGH 0.092 0.230 0.157 0.213 0.133 0.063 0.213 0.133 0.063 WGHTD AVE 0.084 0.199 0.144 0.180 0.107 0.047 0.180 0.107 0.047
SAINT JOHNS LOW 0.041 0.096 0.093 0.069 0.039 0.015 0.069 0.039 0.015 HIGH 0.126 0.410 0.162 0.412 0.312 0.194 0.412 0.312 0.194 WGHTD AVE 0.096 0.299 0.151 0.294 0.214 0.130 0.294 0.214 0.130
SAINT LUCIE LOW 0.302 1.295 0.374 1.443 1.210 0.832 1.443 1.210 0.832 HIGH 0.847 5.246 1.072 6.423 5.988 5.116 6.423 5.988 5.116 WGHTD AVE 0.603 3.414 0.700 3.954 3.593 2.925 3.954 3.593 2.925
SANTA ROSA LOW 0.185 0.677 0.193 0.703 0.560 0.352 0.703 0.560 0.352 HIGH 0.583 3.439 0.673 4.127 3.832 3.201 4.127 3.832 3.201 WGHTD AVE 0.512 2.865 0.599 3.451 3.184 2.619 3.451 3.184 2.619
SARASOTA LOW 0.191 0.792 0.227 0.867 0.732 0.514 0.867 0.732 0.514 HIGH 0.466 2.695 0.593 3.280 3.043 2.578 3.280 3.043 2.578 WGHTD AVE 0.307 1.850 0.405 2.057 1.869 1.535 2.057 1.869 1.535
SEMINOLE LOW 0.110 0.289 0.142 0.244 0.155 0.067 0.244 0.155 0.067 HIGH 0.156 0.453 0.176 0.433 0.310 0.169 0.433 0.310 0.169 WGHTD AVE 0.145 0.402 0.168 0.372 0.254 0.126 0.372 0.254 0.126
SUMTER LOW 0.111 0.328 0.171 0.304 0.218 0.121 0.304 0.218 0.121 HIGH 0.126 0.373 0.190 0.357 0.255 0.143 0.357 0.255 0.143 WGHTD AVE 0.123 0.350 0.187 0.339 0.237 0.129 0.339 0.237 0.129
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 215 Output Range Loss Costs LOSS COSTS PER $1,000 Form A-6 (2007 FHCF Exposure) PERSONAL RESIDENTIAL - Condo Owners -- FRAME $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.038 0.080 0.105 0.067 0.029 0.010 0.067 0.029 0.010 HIGH 0.038 0.080 0.105 0.067 0.029 0.010 0.067 0.029 0.010 WGHTD AVE 0.038 0.080 0.105 0.067 0.029 0.010 0.067 0.029 0.010
TAYLOR LOW 0.028 0.058 0.073 0.033 0.015 0.004 0.033 0.015 0.004 HIGH 0.044 0.114 0.078 0.092 0.059 0.029 0.092 0.059 0.029 WGHTD AVE 0.033 0.107 0.074 0.062 0.036 0.016 0.062 0.036 0.016
UNION LOW 0.030 0.061 0.120 0.037 0.016 0.004 0.037 0.016 0.004 HIGH 0.030 0.061 0.120 0.037 0.016 0.004 0.037 0.016 0.004 WGHTD AVE 0.030 0.061 0.120 0.037 0.016 0.004 0.037 0.016 0.004
VOLUSIA LOW 0.083 0.187 0.116 0.157 0.085 0.030 0.157 0.085 0.030 HIGH 0.294 1.250 0.308 1.406 1.206 0.899 1.406 1.206 0.899 WGHTD AVE 0.152 0.564 0.179 0.538 0.413 0.260 0.538 0.413 0.260
WAKULLA LOW 0.041 0.082 0.071 0.060 0.026 0.007 0.060 0.026 0.007 HIGH 0.127 0.397 0.139 0.388 0.287 0.168 0.388 0.287 0.168 WGHTD AVE 0.085 0.232 0.106 0.219 0.153 0.085 0.219 0.153 0.085
WALTON LOW 0.110 0.317 0.159 0.301 0.212 0.108 0.301 0.212 0.108 HIGH 0.466 2.633 0.523 3.107 2.831 2.313 3.107 2.831 2.313 WGHTD AVE 0.383 1.849 0.405 2.210 1.978 1.568 2.210 1.978 1.568
WASHINGTON LOW 0.100 0.288 0.132 0.253 0.170 0.077 0.253 0.170 0.077 HIGH 0.120 0.358 0.132 0.344 0.246 0.130 0.344 0.246 0.130 WGHTD AVE 0.106 0.336 0.132 0.311 0.219 0.111 0.311 0.219 0.111
Statewide LOW 0.019 0.037 0.059 0.021 0.007 0.002 0.021 0.007 0.002 HIGH 1.647 11.286 2.500 14.327 13.724 12.314 14.327 13.724 12.314 WGHTD AVE 0.310 1.759 0.408 1.940 1.741 1.400 1.940 1.741 1.400
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 216 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- MASONRY $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
ALACHUA LOW 0.026 0.063 0.096 0.038 0.016 0.005 0.038 0.016 0.005 HIGH 0.050 0.137 0.126 0.115 0.062 0.027 0.115 0.062 0.027 WGHTD AVE 0.037 0.096 0.115 0.074 0.034 0.012 0.074 0.034 0.012
BAKER LOW 0.026 0.059 0.000 0.050 0.015 0.003 0.050 0.015 0.003 HIGH 0.026 0.059 0.000 0.050 0.014 0.003 0.050 0.014 0.003 WGHTD AVE 0.026 0.059 0.000 0.050 0.014 0.003 0.050 0.014 0.003
BAY LOW 0.076 0.227 0.108 0.188 0.117 0.051 0.188 0.117 0.051 HIGH 0.371 2.402 0.428 2.749 2.516 2.080 2.749 2.516 2.080 WGHTD AVE 0.256 1.525 0.292 1.687 1.508 1.201 1.687 1.508 1.201
BRADFORD LOW 0.033 0.077 0.142 0.064 0.022 0.005 0.064 0.022 0.005 HIGH 0.033 0.077 0.142 0.064 0.022 0.005 0.064 0.022 0.005 WGHTD AVE 0.033 0.077 0.142 0.064 0.022 0.005 0.064 0.022 0.005
BREVARD LOW 0.110 0.401 0.151 0.367 0.273 0.167 0.367 0.273 0.167 HIGH 0.571 3.847 0.696 4.517 4.196 3.578 4.517 4.196 3.578 WGHTD AVE 0.312 1.850 0.364 2.030 1.817 1.467 2.030 1.817 1.467
BROWARD LOW 0.330 1.474 0.425 1.685 1.446 1.026 1.685 1.446 1.026 HIGH 0.910 7.154 1.399 8.782 8.310 7.293 8.782 8.310 7.293 WGHTD AVE 0.580 3.309 0.693 3.815 3.465 2.806 3.815 3.465 2.806
CALHOUN LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
CHARLOTTE LOW 0.151 0.681 0.170 0.694 0.565 0.382 0.694 0.565 0.382 HIGH 0.297 1.820 0.371 2.101 1.913 1.579 2.101 1.913 1.579 WGHTD AVE 0.197 0.966 0.223 1.035 0.886 0.659 1.035 0.886 0.659
CITRUS LOW 0.046 0.130 0.101 0.101 0.057 0.023 0.101 0.057 0.023 HIGH 0.079 0.243 0.146 0.216 0.143 0.079 0.216 0.143 0.079 WGHTD AVE 0.068 0.208 0.112 0.184 0.121 0.062 0.184 0.121 0.062
CLAY LOW 0.027 0.067 0.106 0.042 0.016 0.004 0.042 0.016 0.004 HIGH 0.052 0.135 0.143 0.108 0.053 0.019 0.108 0.053 0.019 WGHTD AVE 0.035 0.093 0.123 0.069 0.032 0.012 0.069 0.032 0.012
COLLIER LOW 0.165 0.651 0.189 0.619 0.477 0.284 0.619 0.477 0.284 HIGH 0.435 2.671 0.499 3.097 2.829 2.333 3.097 2.829 2.333 WGHTD AVE 0.286 1.791 0.349 1.893 1.687 1.339 1.893 1.687 1.339
COLUMBIA LOW 0.025 0.057 0.130 0.051 0.015 0.004 0.051 0.015 0.004 HIGH 0.025 0.058 0.149 0.056 0.016 0.004 0.056 0.016 0.004 WGHTD AVE 0.025 0.058 0.141 0.053 0.016 0.004 0.053 0.016 0.004
DESOTO LOW 0.129 0.504 0.169 0.480 0.373 0.231 0.480 0.373 0.231 HIGH 0.175 0.714 0.205 0.723 0.580 0.391 0.723 0.580 0.391 WGHTD AVE 0.161 0.683 0.193 0.699 0.569 0.389 0.699 0.569 0.389
DIXIE LOW 0.036 0.096 0.106 0.080 0.039 0.014 0.080 0.039 0.014 HIGH 0.062 0.226 0.138 0.208 0.150 0.093 0.208 0.150 0.093 WGHTD AVE 0.043 0.159 0.111 0.122 0.082 0.046 0.122 0.082 0.046
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 217 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- MASONRY $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
DUVAL LOW 0.016 0.036 0.083 0.026 0.005 0.001 0.026 0.005 0.001 HIGH 0.106 0.433 0.183 0.445 0.349 0.244 0.445 0.349 0.244 WGHTD AVE 0.040 0.126 0.109 0.097 0.056 0.027 0.097 0.056 0.027
ESCAMBIA LOW 0.117 0.471 0.150 0.449 0.352 0.226 0.449 0.352 0.226 HIGH 0.399 2.503 0.459 2.894 2.653 2.206 2.894 2.653 2.206 WGHTD AVE 0.240 1.273 0.277 1.404 1.227 0.943 1.404 1.227 0.943
FLAGLER LOW 0.036 0.090 0.096 0.055 0.025 0.007 0.055 0.025 0.007 HIGH 0.113 0.434 0.162 0.426 0.328 0.212 0.426 0.328 0.212 WGHTD AVE 0.056 0.191 0.106 0.148 0.100 0.054 0.148 0.100 0.054
FRANKLIN LOW 0.088 0.315 0.116 0.283 0.206 0.123 0.283 0.206 0.123 HIGH 0.214 1.063 0.224 1.143 0.984 0.742 1.143 0.984 0.742 WGHTD AVE 0.164 0.954 0.200 0.957 0.816 0.608 0.957 0.816 0.608
GADSDEN LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
GILCHRIST LOW 0.044 0.124 0.122 0.106 0.058 0.027 0.106 0.058 0.027 HIGH 0.044 0.124 0.122 0.106 0.058 0.027 0.106 0.058 0.027 WGHTD AVE 0.044 0.124 0.122 0.106 0.058 0.027 0.106 0.058 0.027
GLADES LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
GULF LOW 0.176 0.891 0.181 0.940 0.807 0.595 0.940 0.807 0.595 HIGH 0.206 1.122 0.220 1.219 1.068 0.824 1.219 1.068 0.824 WGHTD AVE 0.199 1.099 0.218 1.165 1.016 0.779 1.165 1.016 0.779
HAMILTON LOW 0.017 0.039 0.115 0.036 0.008 0.002 0.036 0.008 0.002 HIGH 0.017 0.039 0.115 0.036 0.008 0.002 0.036 0.008 0.002 WGHTD AVE 0.017 0.039 0.115 0.036 0.008 0.002 0.036 0.008 0.002
HARDEE LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
HENDRY LOW 0.236 0.948 0.235 0.962 0.770 0.498 0.962 0.770 0.498 HIGH 0.338 1.439 0.318 1.543 1.288 0.880 1.543 1.288 0.880 WGHTD AVE 0.320 1.368 0.299 1.448 1.206 0.824 1.448 1.206 0.824
HERNANDO LOW 0.069 0.208 0.107 0.184 0.121 0.060 0.184 0.121 0.060 HIGH 0.098 0.378 0.140 0.379 0.298 0.200 0.379 0.298 0.200 WGHTD AVE 0.090 0.313 0.131 0.304 0.225 0.137 0.304 0.225 0.137
HIGHLANDS LOW 0.160 0.540 0.183 0.506 0.369 0.203 0.506 0.369 0.203 HIGH 0.224 0.877 0.220 0.887 0.708 0.452 0.887 0.708 0.452 WGHTD AVE 0.189 0.678 0.200 0.665 0.508 0.303 0.665 0.508 0.303
HILLSBOROUGH LOW 0.070 0.223 0.113 0.195 0.132 0.068 0.195 0.132 0.068 HIGH 0.264 1.478 0.319 1.688 1.517 1.235 1.688 1.517 1.235 WGHTD AVE 0.138 0.632 0.183 0.664 0.557 0.409 0.664 0.557 0.409
HOLMES LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 218 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- MASONRY $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
INDIAN RIVER LOW 0.236 1.123 0.262 1.175 0.988 0.693 1.175 0.988 0.693 HIGH 0.556 3.610 0.651 4.223 3.900 3.279 4.223 3.900 3.279 WGHTD AVE 0.431 2.837 0.511 3.120 2.837 2.325 3.120 2.837 2.325
JACKSON LOW 0.046 0.120 0.090 0.091 0.046 0.015 0.091 0.046 0.015 HIGH 0.057 0.159 0.096 0.127 0.072 0.028 0.127 0.072 0.028 WGHTD AVE 0.052 0.131 0.092 0.105 0.056 0.020 0.105 0.056 0.020
JEFFERSON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
LAFAYETTE LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
LAKE LOW 0.057 0.143 0.114 0.113 0.053 0.016 0.113 0.053 0.016 HIGH 0.143 0.501 0.181 0.492 0.378 0.242 0.492 0.378 0.242 WGHTD AVE 0.124 0.419 0.165 0.385 0.276 0.156 0.385 0.276 0.156
LEE LOW 0.132 0.523 0.168 0.497 0.387 0.237 0.497 0.387 0.237 HIGH 0.592 4.132 0.751 4.916 4.609 4.006 4.916 4.609 4.006 WGHTD AVE 0.213 1.269 0.261 1.244 1.076 0.816 1.244 1.076 0.816
LEON LOW 0.019 0.043 0.056 0.020 0.007 0.001 0.020 0.007 0.001 HIGH 0.040 0.099 0.091 0.071 0.033 0.010 0.071 0.033 0.010 WGHTD AVE 0.030 0.071 0.077 0.046 0.019 0.005 0.046 0.019 0.005
LEVY LOW 0.078 0.313 0.132 0.300 0.234 0.158 0.300 0.234 0.158 HIGH 0.078 0.313 0.132 0.300 0.233 0.157 0.300 0.233 0.157 WGHTD AVE 0.078 0.313 0.132 0.300 0.234 0.158 0.300 0.234 0.158
LIBERTY LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
MADISON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
MANATEE LOW 0.098 0.403 0.153 0.394 0.315 0.203 0.394 0.315 0.203 HIGH 0.414 2.839 0.553 3.371 3.150 2.731 3.371 3.150 2.731 WGHTD AVE 0.202 1.132 0.254 1.229 1.088 0.866 1.229 1.088 0.866
MARION LOW 0.032 0.073 0.122 0.054 0.019 0.004 0.054 0.019 0.004 HIGH 0.098 0.305 0.175 0.278 0.184 0.095 0.278 0.184 0.095 WGHTD AVE 0.078 0.253 0.159 0.228 0.152 0.083 0.228 0.152 0.083
MARTIN LOW 0.388 2.018 0.389 2.253 1.992 1.532 2.253 1.992 1.532 HIGH 0.675 4.440 0.797 5.248 4.884 4.166 5.248 4.884 4.166 WGHTD AVE 0.555 3.426 0.625 3.994 3.671 3.059 3.994 3.671 3.059
MIAMI-DADE LOW 0.233 0.950 0.367 1.088 0.908 0.606 1.088 0.908 0.606 HIGH 1.190 10.349 2.007 12.815 12.267 11.007 12.815 12.267 11.007 WGHTD AVE 0.816 5.749 1.195 6.873 6.439 5.535 6.873 6.439 5.535
MONROE LOW 0.711 4.740 0.867 5.622 5.225 4.431 5.622 5.225 4.431 HIGH 1.247 9.527 1.816 11.708 11.196 10.014 11.708 11.196 10.014 WGHTD AVE 0.956 7.131 1.368 8.654 8.195 7.194 8.654 8.195 7.194
NASSAU LOW 0.018 0.040 0.107 0.030 0.008 0.001 0.030 0.008 0.001 HIGH 0.055 0.182 0.121 0.159 0.106 0.057 0.159 0.106 0.057 WGHTD AVE 0.051 0.159 0.114 0.134 0.084 0.042 0.134 0.084 0.042
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 219 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- MASONRY $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
OKALOOSA LOW 0.186 0.839 0.195 0.871 0.725 0.510 0.871 0.725 0.510 HIGH 0.314 1.859 0.345 2.096 1.885 1.512 2.096 1.885 1.512 WGHTD AVE 0.245 1.316 0.261 1.431 1.248 0.948 1.431 1.248 0.948
OKEECHOBEE LOW 0.202 0.797 0.208 0.776 0.606 0.367 0.776 0.606 0.367 HIGH 0.412 2.115 0.404 2.350 2.078 1.584 2.350 2.078 1.584 WGHTD AVE 0.407 2.097 0.403 2.325 2.053 1.560 2.325 2.053 1.560
ORANGE LOW 0.073 0.203 0.117 0.141 0.081 0.030 0.141 0.081 0.030 HIGH 0.175 0.669 0.210 0.666 0.518 0.330 0.666 0.518 0.330 WGHTD AVE 0.108 0.330 0.147 0.275 0.178 0.081 0.275 0.178 0.081
OSCEOLA LOW 0.073 0.197 0.118 0.142 0.077 0.026 0.142 0.077 0.026 HIGH 0.173 0.655 0.190 0.636 0.492 0.305 0.636 0.492 0.305 WGHTD AVE 0.094 0.299 0.135 0.238 0.155 0.073 0.238 0.155 0.073
PALM BEACH LOW 0.302 1.437 0.343 1.569 1.341 0.950 1.569 1.341 0.950 HIGH 1.112 8.257 1.559 10.068 9.563 8.448 10.068 9.563 8.448 WGHTD AVE 0.585 3.728 0.735 4.231 3.875 3.197 4.231 3.875 3.197
PASCO LOW 0.067 0.230 0.113 0.199 0.144 0.080 0.199 0.144 0.080 HIGH 0.140 0.644 0.171 0.691 0.585 0.436 0.691 0.585 0.436 WGHTD AVE 0.105 0.440 0.146 0.434 0.345 0.234 0.434 0.345 0.234
PINELLAS LOW 0.105 0.420 0.144 0.424 0.336 0.223 0.424 0.336 0.223 HIGH 0.395 2.650 0.517 3.133 2.918 2.518 3.133 2.918 2.518 WGHTD AVE 0.195 1.118 0.248 1.213 1.078 0.863 1.213 1.078 0.863
POLK LOW 0.079 0.228 0.116 0.168 0.102 0.040 0.168 0.102 0.040 HIGH 0.190 0.683 0.212 0.666 0.506 0.301 0.666 0.506 0.301 WGHTD AVE 0.138 0.505 0.173 0.473 0.353 0.209 0.473 0.353 0.209
PUTNAM LOW 0.039 0.097 0.104 0.060 0.028 0.008 0.060 0.028 0.008 HIGH 0.069 0.192 0.148 0.163 0.093 0.042 0.163 0.093 0.042 WGHTD AVE 0.050 0.127 0.128 0.100 0.049 0.017 0.100 0.049 0.017
SAINT JOHNS LOW 0.031 0.081 0.093 0.058 0.028 0.010 0.058 0.028 0.010 HIGH 0.088 0.311 0.139 0.290 0.211 0.128 0.290 0.211 0.128 WGHTD AVE 0.070 0.238 0.131 0.214 0.149 0.087 0.214 0.149 0.087
SAINT LUCIE LOW 0.250 1.203 0.284 1.278 1.077 0.760 1.278 1.077 0.760 HIGH 0.628 4.218 0.769 4.973 4.614 3.918 4.973 4.614 3.918 WGHTD AVE 0.500 3.105 0.578 3.596 3.285 2.716 3.596 3.285 2.716
SANTA ROSA LOW 0.115 0.394 0.141 0.366 0.262 0.143 0.366 0.262 0.143 HIGH 0.350 2.185 0.424 2.503 2.283 1.849 2.503 2.283 1.849 WGHTD AVE 0.312 1.812 0.369 2.080 1.882 1.499 2.080 1.882 1.499
SARASOTA LOW 0.111 0.483 0.164 0.481 0.393 0.266 0.481 0.393 0.266 HIGH 0.349 2.204 0.443 2.584 2.386 2.017 2.584 2.386 2.017 WGHTD AVE 0.235 1.514 0.312 1.645 1.489 1.221 1.645 1.489 1.221
SEMINOLE LOW 0.074 0.206 0.122 0.149 0.084 0.031 0.149 0.084 0.031 HIGH 0.115 0.370 0.157 0.332 0.228 0.122 0.332 0.228 0.122 WGHTD AVE 0.099 0.294 0.143 0.244 0.153 0.068 0.244 0.153 0.068
SUMTER LOW 0.073 0.234 0.135 0.193 0.130 0.068 0.193 0.130 0.068 HIGH 0.090 0.277 0.170 0.244 0.162 0.086 0.244 0.162 0.086 WGHTD AVE 0.077 0.246 0.156 0.207 0.137 0.070 0.207 0.137 0.070
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 220 Output Range Loss Costs Form A-6 (2007 FHCF Exposure) LOSS COSTS PER $1,000 PERSONAL RESIDENTIAL - Condo Owners -- MASONRY $0 $0 $0 DEDUCTIBLE $500 $1,000 $2,500 1% 2% 5% DEDUCTIBLE DEDUCTIBLE ADDITIONAL DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE DEDUCTIBLE COUNTY LOSS COSTS STRUCTURE CONTENTS LIVING EXPENSE TOTAL* TOTAL* TOTAL* TOTAL* TOTAL* TOTAL*
SUWANNEE LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
TAYLOR LOW 0.029 0.085 0.066 0.060 0.036 0.016 0.060 0.036 0.016 HIGH 0.029 0.085 0.066 0.060 0.036 0.016 0.060 0.036 0.016 WGHTD AVE 0.029 0.085 0.066 0.060 0.035 0.016 0.060 0.035 0.016
UNION LOW 0.025 0.057 0.132 0.045 0.014 0.003 0.045 0.014 0.003 HIGH 0.025 0.057 0.132 0.045 0.014 0.003 0.045 0.014 0.003 WGHTD AVE 0.025 0.057 0.132 0.045 0.014 0.003 0.045 0.014 0.003
VOLUSIA LOW 0.044 0.112 0.091 0.068 0.032 0.009 0.068 0.032 0.009 HIGH 0.181 0.968 0.240 1.036 0.875 0.647 1.036 0.875 0.647 WGHTD AVE 0.141 0.579 0.180 0.575 0.457 0.310 0.575 0.457 0.310
WAKULLA LOW 0.090 0.059 0.066 0.038 0.013 0.003 0.038 0.013 0.003 HIGH 0.090 0.300 0.119 0.271 0.191 0.106 0.271 0.191 0.106 WGHTD AVE 0.090 0.263 0.111 0.243 0.168 0.093 0.243 0.168 0.093
WALTON LOW 0.061 0.184 0.093 0.141 0.087 0.035 0.141 0.087 0.035 HIGH 0.308 1.867 0.354 2.102 1.890 1.516 2.102 1.890 1.516 WGHTD AVE 0.272 1.511 0.294 1.703 1.515 1.196 1.703 1.515 1.196
WASHINGTON LOW 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 HIGH 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 WGHTD AVE 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
Statewide LOW 0.016 0.036 0.056 0.020 0.006 0.001 0.020 0.006 0.001 HIGH 1.247 10.349 2.007 12.815 12.267 11.007 12.815 12.267 11.007 WGHTD AVE 0.370 2.683 0.539 2.852 2.600 2.139 2.852 2.600 2.139
*Includes contents and A.L.E. Model - EQECAT Florida Hurricane Model 2011a 221 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-7: Percentage Change In Personal Residential Output Ranges
A. Provide the percentage change in the weighted average loss costs using the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe”, from the personal residential output ranges from the previously accepted submission for the following:
• statewide (overall percentage change), • by region, as defined in Figure 41 – North, Central and South, • by coastal and inland counties, as defined in Figure 42.
B. Provide this Form on CD in both an Excel format. The file name shall include the abbreviated name of the modeling organization, the standards year, and the form name. A hard copy of Form A-7 shall be included in the submission.
North
Central
South
Figure 41. State of Florida by North/Central/South Regions
222 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Inland
Coastal
Figure 42. State of Florida by Coastal/Inland Counties
The results are shown on Form A-7.
223 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-7: Percentage Change In Personal Residential Output Ranges
'HGXFWLEOH $SS $GGLWLRQDO 6WUXFWXUH &RQWHQWV XUWHQDQW /LYLQJ 'HGXFWLEOH 'HGXFWLEOH 'HGXFWLEOH 'HGXFWLEOH 'HGXFWLEOH 'HGXFWLEOH 6WUXFWXUH ([SHQVH 7RWDO 7RWDO 7RWDO 7RWDO 7RWDO 7RWDO )UDPH &RDVWDO -11.56% -19.78% -11.17% -13.41% -14.21% -15.05% -17.04% -15.05% -16.43% -19.63% 2ZQHUV ,QODQG 13.21% 19.03% 13.69% 10.64% 15.68% 17.25% 21.34% 17.25% 20.03% 27.28% 1RUWK -22.83% -34.31% -23.06% -20.76% -27.34% -29.23% -33.51% -29.23% -32.24% -38.52% &HQWUDO -0.52% -6.29% 0.11% -0.32% -2.03% -2.63% -4.37% -2.63% -3.80% -7.18% 6RXWK -4.03% -9.09% -4.64% -8.03% -5.49% -5.81% -6.76% -5.81% -6.44% -8.37% 6WDWHZLGH -8.68% -16.70% -8.40% -9.60% -11.21% -12.12% -14.33% -12.12% -13.65% -17.27% 0DVRQU\ &RDVWDO -7.29% -15.45% -7.81% -10.63% -9.88% -10.59% -12.51% -10.59% -11.89% -15.37% 2ZQHUV ,QODQG 17.30% 23.33% 17.76% 14.38% 20.43% 22.25% 26.79% 22.25% 25.39% 32.66% 1RUWK -21.69% -34.65% -21.71% -12.01% -27.12% -29.59% -34.98% -29.59% -33.39% -41.13% &HQWUDO -2.98% -10.52% -1.87% -1.97% -5.36% -6.45% -9.43% -6.45% -8.46% -13.97% 6RXWK -5.94% -13.98% -6.88% -10.51% -8.41% -9.02% -10.77% -9.02% -10.19% -13.53% 6WDWHZLGH -5.63% -13.73% -6.14% -8.16% -8.18% -8.97% -11.08% -8.97% -10.40% -14.22% 0RELOH &RDVWDO -6.33% -14.82% -5.09% -7.40% -7.60% -7.79% -8.22% -7.60% -7.79% -8.22% +RPHV ,QODQG 25.44% 44.76% 26.69% 34.41% 28.88% 29.90% 32.28% 28.88% 29.90% 32.28% 1RUWK -19.51% -35.25% -17.99% -21.68% -22.48% -23.40% -25.34% -22.48% -23.40% -25.34% &HQWUDO 8.75% 3.30% 10.68% 13.65% 8.74% 8.82% 8.92% 8.74% 8.82% 8.92% 6RXWK -0.03% -8.11% 1.10% 0.60% -1.07% -1.12% -1.22% -1.07% -1.12% -1.22% 6WDWHZLGH 1.87% -5.85% 3.56% 3.89% 1.19% 1.07% 0.80% 1.19% 1.07% 0.80% )UDPH &RDVWDO -12.77% -17.36% -15.56% -16.72% -19.03% -14.70% -15.56% -17.19% 5HQWHUV ,QODQG 16.95% 8.72% 26.01% 30.55% 35.27% 21.90% 26.01% 32.02% 1RUWK -34.96% -21.19% -42.36% -45.45% -50.20% -39.60% -42.36% -46.55% &HQWUDO -9.32% -2.10% -15.04% -18.34% -24.43% -12.60% -15.04% -19.65% 6RXWK -5.95% -10.06% -7.21% -8.21% -10.56% -6.62% -7.21% -8.65% 6WDWHZLGH -11.40% -11.62% -14.44% -15.84% -18.49% -13.42% -14.44% -16.38% 0DVRQU\ &RDVWDO -12.50% -12.99% -15.43% -17.04% -20.43% -14.34% -15.43% -17.71% 5HQWHUV ,QODQG 21.85% 13.56% 33.61% 38.34% 41.58% 28.53% 33.61% 39.57% 1RUWK -34.64% -12.81% -43.58% -46.92% -51.50% -40.17% -43.58% -48.02% &HQWUDO -11.50% -4.20% -18.34% -21.70% -27.32% -15.64% -18.34% -22.95% 6RXWK -11.24% -12.19% -13.80% -15.39% -18.83% -12.78% -13.80% -16.06% 6WDWHZLGH -11.65% -9.58% -14.79% -16.55% -20.13% -13.57% -14.79% -17.27% )UDPH &RDVWDO -9.42% -16.16% -12.17% -17.01% -18.21% -20.51% -17.01% -18.21% -20.51% &RQGRV ,QODQG 12.94% 18.53% 13.11% 21.79% 25.65% 30.90% 21.79% 25.65% 30.90% 1RUWK -19.54% -32.56% -22.45% -33.81% -35.96% -39.32% -33.81% -35.96% -39.32% &HQWUDO -4.81% -8.28% -4.88% -11.55% -13.32% -16.30% -11.55% -13.32% -16.30% 6RXWK -6.63% -11.70% -10.51% -12.97% -13.96% -16.16% -12.97% -13.96% -16.16% 6WDWHZLGH -7.82% -15.33% -10.76% -16.14% -17.49% -20.01% -16.14% -17.49% -20.01% 0DVRQU\ &RDVWDO -7.82% -12.37% -10.58% -13.97% -15.07% -17.37% -13.97% -15.07% -17.37% &RQGRV ,QODQG 17.38% 24.52% 15.66% 29.65% 35.40% 42.51% 29.65% 35.40% 42.51% 1RUWK -22.72% -31.54% -22.00% -34.17% -36.23% -39.33% -34.17% -36.23% -39.33% &HQWUDO -5.03% -7.74% -5.35% -10.25% -11.50% -13.49% -10.25% -11.50% -13.49% 6RXWK -7.43% -12.09% -10.68% -13.66% -14.74% -17.10% -13.66% -14.74% -17.10% 6WDWHZLGH -7.48% -12.23% -10.30% -13.82% -14.95% -17.30% -13.82% -14.95% -17.30%
224 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-8: Percentage Change in Personal Residential Output Ranges by County
Provide color-coded maps by county reflecting the percentage changes in the weighted average 2% deductible loss costs for frame owners, masonry owners, mobile homes, frame renters, masonry renters, frame condos, and masonry condos from the personal residential output ranges from the previously accepted submission using the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe.”
Counties with a negative percentage change (reduction in loss costs) shall be indicated with shades of blue; counties with a positive percentage change (increase in 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.
The percentage changes in the county level weighted average loss costs for a 2% deductible for the seven policy types are shown in Figures 43 to 49 below.
Figure 43. Frame Owners - % changes by county
225 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Figure 44. Masonry Owners - % changes by county
Figure 45. Mobile Homes - % changes by county
226 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Figure 46. Frame Renters - % changes by county
Figure 47. Masonry Renters - % changes by county
227 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Figure 48. Frame Condos - % changes by county
Figure 49. Masonry Condos - % changes by county
228 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Form A-9: Probable Maximum Loss for Florida
A. Provide a detailed explanation of how the Expected Annual Hurricane Losses and Return Periods are calculated.
The expected annual losses and return periods are based on the EQECAT stochastic event set of 47,315 stochastic events affecting the mainland United States, of which 25,672 affect the 2007 FHCF exposure data provided by the Commission. Each of the 25,672 hurricanes has an annual frequency defined in the model, and a modeled result for Personal Residential Zero Deductible statewide loss, and a modeled result for Personal and Commercial Residential Zero Deductible statewide loss, using the FHCF exposure data. When the 25,672 hurricanes are sorted in descending order of loss (separately for Personal Residential, and Personal and Commercial Residential), the exceedance frequency for each loss is given by the sum of all hurricane frequencies with losses at or above that level. Each row of the tables in Part A and Part C represents a range of losses. We calculated the average loss for each range as the sum of all losses (from the 25,672 hurricanes) falling within the range divided by the number of such losses (the number of losses is provided in the ‘No. of storms’ column). We calculated the expected annual hurricane loss for each range by summing the product of loss and annual frequency over all hurricanes with losses falling within the range. We calculated the return period in years for each range by first interpolating the exceedance frequency to the value corresponding to the average loss for the range (this was done linearly between the adjacent hurricane losses, from among the 25,672 hurricanes). Taking this exceedance frequency to be λ, we calculated the return period in years as 1/ (1 – exp(-λ)).
229 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
B. Complete Form A-9, Part A showing the personal residential probable maximum loss for Florida. For the Expected Annual Hurricane Losses column, provide personal residential, zero deductible statewide loss costs based on the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe.”
C. Complete Form A-9, Part C showing the personal and commercial residential probable maximum loss for Florida. For the Expected Annual Hurricane Losses column, provide personal and commercial residential, zero deductible statewide loss costs based on the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal and commercial residential exposure data found in the file named “hlpm2007c.exe.”
In the column, Return Period (Years), provide the return period associated with the average loss within the ranges indicated on a cumulative basis.
For example, if the average loss is $4,705 million for the range $4,501 million to $5,000 million, provide the return period associated with a loss that is $4,705 million or greater.
For each loss range in millions ($1,001-$1,500, $1,501-$2,000, $2,001-$2,500) the average loss within that range should be identified and then the return period associated with that loss calculated. The return period is then the reciprocal of the probability of the loss equaling or exceeding this average loss size.
The probability of equaling or exceeding the average of each range should be smaller as the ranges increase (and the average losses within the ranges increase). Therefore, the return period associated with each range and average 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 loss of $4,705 million within the $4,501-$5,000 million range should be lower than the return period for an average loss of $5,455 million associated with a $5,001- $6,000 million range.
See the completed form below. D. Provide a graphical comparison of the current submission Personal Residential Return Periods to the previously accepted submission Personal Residential Return Periods. Personal Residential Return Period (Years) shall be shown on the y-axis on a log 10 scale with Losses in Billions shown on the x-axis. The legend shall indicate the corresponding submission with a solid line representing the current year and a dotted line representing the previously accepted submission.
See Figure 50 below. E. Provide the estimated loss for each of the Personal Residential Return Periods given in Part B. Describe how the uncertainty intervals were derived.
See the completed form below. The uncertainty intervals were derived by constructing exceedance curves based on the extremes of the 95% confidence interval on each event. 230 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
F. Provide the estimated loss for each of the Personal and Commercial Residential Return Periods given in Part D.
See the completed form below. G. Provide this Form on CD in both an Excel format. The file name shall include the abbreviated name of the modeler, the Standards year, and the Form name. A hard copy of Form A-9 shall be included in the submission.
The Form A-9 results appear in the file 2009FormA9_EQECAT_28March2011.xls.
231 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Part A - Personal Residential Probable Maximum Loss for Florida
EXPECTED AVERAGE RETURN LOSS RANGE TOTAL NUMBER OF ANNUAL LOSS PERIOD (MILLIONS) LOSS HURRICANES HURRICANE (MILLIONS) (YEARS) LOSSES* $ - to $ 500 $1,078,057 $147 7,357 $51.8 2 $ 501 to $ 1,000 $1,705,337 $736 2,316 $70.9 3 $ 1,001 to $ 1,500 $2,006,205 $1,234 1,626 $83.0 3 $ 1,501 to $ 2,000 $2,056,862 $1,742 1,181 $79.5 4 $ 2,001 to $ 2,500 $2,174,267 $2,239 971 $72.5 4 $ 2,501 to $ 3,000 $2,240,442 $2,742 817 $80.3 4 $ 3,001 to $ 3,500 $2,080,900 $3,241 642 $54.8 5 $ 3,501 to $ 4,000 $2,264,493 $3,737 606 $68.8 5 $ 4,001 to $ 4,500 $2,226,238 $4,249 524 $79.3 6 $ 4,501 to $ 5,000 $2,117,810 $4,748 446 $68.0 6 $ 5,001 to $ 6,000 $4,406,082 $5,473 805 $121.8 7 $ 6,001 to $ 7,000 $4,619,001 $6,487 712 $114.9 7 $ 7,001 to $ 8,000 $4,141,616 $7,489 553 $86.3 8 $ 8,001 to $ 9,000 $4,181,541 $8,482 493 $95.0 9 $ 9,001 to $ 10,000 $4,267,509 $9,483 450 $81.2 10 $ 10,001 to $ 11,000 $3,969,659 $10,502 378 $98.3 11 $ 11,001 to $ 12,000 $3,720,048 $11,482 324 $78.8 12 $ 12,001 to $ 13,000 $3,822,253 $12,491 306 $95.8 13 $ 13,001 to $ 14,000 $4,122,688 $13,473 306 $90.8 13 $ 14,001 to $ 15,000 $3,798,811 $14,499 262 $60.0 15 $ 15,001 to $ 16,000 $3,618,347 $15,463 234 $63.9 16 $ 16,001 to $ 17,000 $3,645,794 $16,497 221 $76.6 17 $ 17,001 to $ 18,000 $3,684,568 $17,462 211 $61.0 18 $ 18,001 to $ 19,000 $3,422,251 $18,499 185 $59.2 19 $ 19,001 to $ 20,000 $3,534,486 $19,528 181 $68.1 20 $ 20,001 to $ 21,000 $3,297,064 $20,479 161 $44.1 21 $ 21,001 to $ 22,000 $3,482,139 $21,495 162 $61.3 22 $ 22,001 to $ 23,000 $3,036,985 $22,496 135 $60.9 23 $ 23,001 to $ 24,000 $2,835,286 $23,432 121 $31.6 25 $ 24,001 to $ 25,000 $3,112,668 $24,509 127 $44.9 25 $ 25,001 to $ 26,000 $3,080,969 $25,463 121 $52.2 27 $ 26,001 to $ 27,000 $3,018,253 $26,476 114 $43.7 28 $ 27,001 to $ 28,000 $2,658,644 $27,409 97 $54.5 30 $ 28,001 to $ 29,000 $3,421,357 $28,511 120 $59.4 31 $ 29,001 to $ 30,000 $2,473,987 $29,452 84 $39.6 33 $ 30,001 to $ 35,000 $14,940,496 $32,479 460 $244.5 38 $ 35,001 to $ 40,000 $12,105,734 $37,363 324 $173.2 49 $ 40,001 to $ 45,000 $10,584,110 $42,336 250 $120.7 61 $ 45,001 to $ 50,000 $10,774,910 $47,258 228 $203.4 80 $ 50,001 to $ 55,000 $9,172,268 $52,413 175 $153.6 104 $ 55,001 to $ 60,000 $7,231,995 $57,397 126 $48.2 134 $ 60,001 to $ 65,000 $7,495,482 $62,462 120 $68.7 151 $ 65,001 to $ 70,000 $7,087,374 $67,499 105 $109.1 192 $ 70,001 to $ 75,000 $6,007,264 $72,377 83 $69.4 240 $ 75,001 to $ 80,000 $4,964,122 $77,564 64 $44.6 311 $ 80,001 to $ 90,000 $7,959,605 $84,677 94 $93.2 429 $ 90,001 to $ 100,000 $7,010,970 $94,743 74 $44.8 680 $ 100,001 to $ Maximum $24,144,711 $130,512 185 $152.9 9,523 TOTAL: 25,637 $3,979.3 Personal residential zero deductible statewide loss using 2007 FHCF personal residential exposure data – file name: hlpm2007.exe.
232 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Part B - Personal Residential Probable Maximum Loss for Florida
Return Period (years) Estimated Loss (Millions) Uncertainty Interval* TopEvent N/A N/A 1000 $122,689 $36,300 to $210,082 500 $102,387 $29,908 to $167,955 250 $80,373 $23,986 to $142,184 100 $56,348 $17,896 to $103,165 50 $38,564 $12,322 to $73,996 20 $19,272 $6,625 to $38,393 10 $9,186 $3,204 to $19,236 5 $3,236 $1,107 to $7,166 *Uncertainty bounds are not a standard output of the EQECAT model.
100,000
Current submission 10,000 Previous submission
1,000
100 Return Period (Years)
10
1 $- $20 $40 $60 $80 $100 $120 2007 FHCF Loss ($Billion)
Figure 50. Current Submission Return Periods vs. Prior Year’s Submission Return Periods
233 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Part C – Personal and Commercial Residential Probable Maximum Loss for Florida
EXPECTED AVERAGE RETURN LOSS RANGE TOTAL NUMBER OF ANNUAL LOSS PERIOD (MILLIONS) LOSS HURRICANES HURRICANE (MILLIONS) (YEARS) LOSSES* $ - to $ 500 $1,033,046 $146 7,084 $49.7 2 $ 501 to $ 1,000 $1,634,027 $736 2,221 $67.2 3 $ 1,001 to $ 1,500 $1,981,403 $1,241 1,597 $82.3 3 $ 1,501 to $ 2,000 $1,961,762 $1,744 1,125 $81.8 3 $ 2,001 to $ 2,500 $2,105,247 $2,235 942 $75.5 4 $ 2,501 to $ 3,000 $2,230,331 $2,740 814 $69.4 4 $ 3,001 to $ 3,500 $2,231,990 $3,244 688 $79.5 4 $ 3,501 to $ 4,000 $2,054,184 $3,749 548 $50.9 5 $ 4,001 to $ 4,500 $2,176,263 $4,242 513 $66.1 5 $ 4,501 to $ 5,000 $2,248,431 $4,744 474 $76.4 5 $ 5,001 to $ 6,000 $4,248,248 $5,496 773 $128.2 6 $ 6,001 to $ 7,000 $4,381,164 $6,471 677 $139.3 7 $ 7,001 to $ 8,000 $4,612,621 $7,476 617 $118.4 7 $ 8,001 to $ 9,000 $4,226,283 $8,487 498 $83.6 8 $ 9,001 to $ 10,000 $3,948,246 $9,468 417 $81.9 9 $ 10,001 to $ 11,000 $4,391,870 $10,457 420 $90.9 9 $ 11,001 to $ 12,000 $3,892,675 $11,483 339 $88.8 10 $ 12,001 to $ 13,000 $4,099,089 $12,459 329 $91.6 11 $ 13,001 to $ 14,000 $3,694,176 $13,482 274 $82.8 12 $ 14,001 to $ 15,000 $4,041,184 $14,485 279 $82.0 12 $ 15,001 to $ 16,000 $3,870,183 $15,481 250 $98.1 13 $ 16,001 to $ 17,000 $3,648,826 $16,511 221 $72.2 14 $ 17,001 to $ 18,000 $3,742,964 $17,490 214 $65.1 15 $ 18,001 to $ 19,000 $3,858,737 $18,463 209 $65.2 16 $ 19,001 to $ 20,000 $3,426,385 $19,468 176 $63.0 17 $ 20,001 to $ 21,000 $3,399,137 $20,477 166 $72.7 18 $ 21,001 to $ 22,000 $3,265,556 $21,484 152 $28.0 18 $ 22,001 to $ 23,000 $3,502,197 $22,450 156 $76.0 19 $ 23,001 to $ 24,000 $3,669,252 $23,521 156 $52.8 20 $ 24,001 to $ 25,000 $3,155,769 $24,463 129 $59.0 21 $ 25,001 to $ 26,000 $3,366,957 $25,507 132 $48.1 22 $ 26,001 to $ 27,000 $2,540,431 $26,463 96 $47.4 23 $ 27,001 to $ 28,000 $3,329,797 $27,519 121 $61.7 24 $ 28,001 to $ 29,000 $3,333,501 $28,491 117 $68.4 25 $ 29,001 to $ 30,000 $2,714,222 $29,502 92 $50.3 27 $ 30,001 to $ 35,000 $13,254,848 $32,408 409 $217.7 29 $ 35,001 to $ 40,000 $15,158,149 $37,335 406 $252.0 36 $ 40,001 to $ 45,000 $11,504,647 $42,453 271 $177.2 46 $ 45,001 to $ 50,000 $11,501,697 $47,332 243 $179.9 56 $ 50,001 to $ 55,000 $9,261,137 $52,323 177 $105.5 67 $ 55,001 to $ 60,000 $10,058,558 $57,477 175 $193.3 77 $ 60,001 to $ 65,000 $9,115,478 $62,435 146 $158.7 102 $ 65,001 to $ 70,000 $6,870,287 $67,356 102 $91.2 134 $ 70,001 to $ 75,000 $6,230,615 $72,449 86 $59.8 153 $ 75,001 to $ 80,000 $7,370,541 $77,585 95 $79.8 169 $ 80,001 to $ 90,000 $10,559,450 $84,476 125 $145.0 239 $ 90,001 to $ 100,000 $9,015,697 $94,902 95 $103.2 339 $ 100,001 to $ Maximum $39,731,978 $136,536 291 $303.8 1,129 TOTAL: 25,637 $4,681.1 Personal and commercial residential zero deductible statewide loss using 2007 FHCF personal and commercial residential exposure data – file name: hlpm2007c.exe. 234 The Florida Commission on Hurricane Loss Projection Methodology Actuarial Standards
Part D - Personal and Commercial Residential Probable Maximum Loss for Florida
Return Period (years) Estimated Loss (Millions) Uncertainty Interval* Top Event N/A N/A 1000 $147,149 $44,182 to $242,538 500 $122,854 $36,719 to $203,972 250 $96,386 $29,014 to $168,583 100 $66,508 $20,953 to $122,346 50 $45,537 $15,051 to $87,288 20 $22,639 $7,945 to $44,899 10 $10,781 $3,720 to $22,224 5 $3,729 $1,277 to $8,238 *Uncertainty bounds are not a standard output of the EQECAT model.
235 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Statistical Standards
S-1 Modeled Results and Goodness-of-Fit
A. The use of historical data in developing the model shall be supported by rigorous methods published in currently accepted scientific literature.
EQECAT’s use of historical data in developing USWIND is supported by rigorous methods published in currently accepted scientific literature. B. Modeled and historical results shall reflect agreement using currently accepted scientific and statistical methods in the appropriate disciplines.
Modeled and historical results reflect agreement using currently accepted scientific and statistical methods in the appropriate disciplines.
Disclosures
1. Identify the form of the probability distributions used for each function or variable, if applicable. Identify statistical techniques used for the estimates and the specific goodness-of-fit tests applied. Describe whether the p-values associated with the fitted distributions provide a reasonable agreement with the historical data. Provide a completed Form S-3, Distribution of Stochastic Hurricane Parameters.
Radius to maximum winds, translational speed, and profile factor are modeled using lognormal distributions, the parameters of which vary smoothly along the coast. Filling rate is modeled using a normal distribution. Friction and gust factor are modeled using lognormal distributions. Chi-squared and Kolmogorov-Smirnov tests have been performed to assess the goodness-of- fit, and reasonable agreement with the historical data has been shown.
See Form S-3 at the end of this section.
2. Describe the nature and results of the tests performed to validate the wind speeds generated.
Updating a study performed by Dr. Don Friedman, who has a Doctorate in meteorology and over 35 years analyzing hurricane wind patterns and their relation to insurance claims while at the Research Department of The Travelers Insurance Company, EQECAT performed a study of USWIND- generated peak gust wind patterns with those of actual hurricanes: Actual peak gust observations were obtained for eighteen landfalls of fifteen notable hurricanes since 1960. These observations were compared with model- generated peak gust wind speeds. Scatter plots were made of observed versus modeled. Table 3 below summarizes the results, and is limited to observations with gusts above 60 mph to avoid including areas where wind
236 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
damage on the fringe of a storm would not be significant; (this level would roughly correspond to a 1-minute sustained of 45 mph).
TABLE 3. COMPARISON OF POINT LOCATION OBSERVATIONS WITH MODEL-GENERATED WINDS (Peak Gust Observations 60 mph or more) Hurricane Year #Obs #Simulated +/- 10 #Simulated +/- 15 mph mph Donna 1960 21 14 67% 15 71% Carla 1961 14 7 50% 10 71% Betsy 1965 18 13 72% 16 89% Alicia 1983 6 4 67% 5 83% Elena 1985 8 3 38% 6 75% Gloria 1985 18 11 61% 16 89% Hugo 1989 8 5 63% 6 75% Bob 1991 18 10 56% 13 72% Andrew 1992 11 6 55% 8 73% Charley 2004 7 5 71% 6 86% Frances 2004 23 12 52% 17 74% Ivan 2004 3 2 67% 3 100% Jeanne 2004 7 4 57% 6 86% Katrina 2005 13 7 54% 8 62% Wilma 2005 28 14 50% 21 75% Total 203 117 58% 156 77%
3. Provide the date of loss of the insurance company data available for validation and verification of the model.
The primary information available for validation and verification of the model is claims data from Hurricanes Alicia (1983), Elena (1985), Gloria (1985), Juan (1985), Kate (1985), Hugo (1989), Bob (1991), Andrew (1992), Iniki (1992), Erin (1995), Opal (1995), Charley (2004), Frances (2004), Ivan (2004), Jeanne (2004), Katrina (2005), Rita (2005), and Wilma (2005).
4. Provide an assessment of uncertainty in loss costs for output ranges using confidence intervals or other accepted scientific characterizations of uncertainty.
Figure 51 below compares the loss exceedance curve presented in Form S-2 with the curves that would result from adding or subtracting one standard deviation (sigma) to the total annual hurricane frequency in the model using the hypothetical data set.
237 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
140,000,000
Frequency plus one sigma 120,000,000 Mean frequency Frequency minus one sigma
100,000,000
80,000,000 Loss ($) Loss 60,000,000
40,000,000
20,000,000
0 1 10 100 1,000 10,000 Return Period (Years) Figure 51. Uncertainty Analysis for Frequency
5. Justify any differences between the historical and modeled results using current accepted scientific and statistical methods in the appropriate disciplines.
A number of tests have been performed to verify that the differences between historical and modeled results are not statistically significant. Form S-5 at the end of this section provides such tests for the historical versus modeled results for the 2007 FHCF exposures.
6. Provide graphical comparisons of modeled and historical data and goodness-of-fit tests. Examples include hurricane frequencies, tracks, intensities, and physical damage.
Figures 52 and 53 are examples of graphical comparisons of modeled and historical data.
Figure 52 compares the historical data for translational speed near Ft. Myers and Daytona Beach with the lognormal distribution used to model it. As an example of a more quantitative comparison, we performed a Kolmogorov- Smirnov test to assess the goodness-of-fit of our modeled distribution for translational speed at Ft. Myers to the historical data. The test statistic value is 0.116. The critical test value at a 5% level of significance is 0.21, for 41
238 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards data points. Hence, the modeled distribution cannot be rejected at that level of significance. Similarly, for Daytona Beach the test statistic value is 0.208, and the critical test value at a 5% level of significance is 0.27, for 23 data points; hence the modeled distribution cannot be rejected at that level of significance.
(a) (b)
Figure 52. Goodness-of-fit for Translational Speed
239 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
0.7
0.6
historical 0.5 negative binomial
0.4
probability 0.3
0.2
0.1
0.0 012345678910 or more # events per year Figure 53. Goodness-of-fit for Hurricane Frequency in Florida
Figure 53 compares the historical data for hurricane frequency in Florida with the negative binomial distribution used to model it. We performed a Kolmogorov-Smirnov test to assess the goodness-of-fit of our modeled distribution for hurricane frequency in Florida to the historical data. The test statistic value is 0.0462. The critical test value at a 5% level of significance is 0.128, hence the modeled distribution cannot be rejected at that level of significance.
7. Provide a completed Form S-1, Probability of Florida Landfalling Hurricanes per Year.
See Form S-1 at the end of this section.
8. Provide a completed Form S-2, Examples of Loss Exceedance Estimates Based on a Limited Hypothetical Data Set.
See Form S-2 at the end of this section.
240 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
S-2 Sensitivity Analysis for 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 currently accepted scientific and statistical methods in the appropriate disciplines and have taken appropriate action.
EQECAT has assessed the sensitivity of temporal and spatial outputs with respect to the simultaneous variation of input variables using currently accepted scientific and statistical methods in the appropriate disciplines, and has taken appropriate action.
Disclosures
1. Identify the most sensitive aspect of the model and the basis for making this determination. Provide a full discussion of the degree to which these sensitivities affect output results and illustrate with an example.
The most sensitive aspect of our model involves the conversion of wind speed to damage. This is due to the fact that the damage sustained by a particular structure type depends very sensitively on the wind speed experienced at the site. For example, the damage sustained by a given structure type depends approximately on the wind speed raised to some power. If the damage is proportional to the fifth power of the wind speed, then a 1% uncertainty in the wind speed will result in a 5% uncertainty in the damage calculated at that site. The origin of this uncertainty is the underlying non-linearity of the vulnerability relationship, and not in any assumptions, data or properties unique to our model.
2. Describe how other aspects of the model may have a significant impact on the sensitivities in output results and the basis for making this determination.
The results of any model depend sensitively on details of the structural characteristics and location of the insured sites. Often, this information is not provided by the insurance or underwriting agency for use by the model. Such details can potentially have a large impact on results due to the large variation in damageability among different structure classes and secondary structural configurations, and to the large variation in the wind hazard with respect to distance to coast and other factors.
3. Describe actions taken in light of the sensitivity analyses performed.
The sensitivity analyses performed during the initial development of the model were crucial in determining optimal sample sizes and the relative importance of parameters. Subsequent analyses have been used to verify that the decisions made continue to be valid.
241 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
4. Provide a completed Form S-6, Hypothetical Events for Sensitivity and Uncertainty Analysis (requirement models submitted by modeling organizations which have not previously provided the Commission with this analysis).
See Form S-6 at the end of this section.
242 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
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 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.
EQECAT has performed uncertainty analysis on the temporal and spatial outputs of the model using currently accepted scientific and statistical methods in the appropriate disciplines and has taken appropriate action. The analysis has identified and quantified the extent that input variables impact the uncertainty in model output as the input variables are simultaneously varied.
Disclosures
1. Identify the major contributors to the uncertainty in 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.
Major contributors to the uncertainty in model output include uncertainty on storm parameters, uncertainty on site parameters, and uncertainty on the vulnerability functions, as identified in our uncertainty analysis.
One such contributor is the conversion of wind speed to damage. This is due to the fact that the damage sustained by a particular structure type depends very sensitively on the of wind speed experienced at the site. For example, the damage sustained by a given structure type depends approximately on the of wind speed raised to some power. If the damage is proportional to the fifth power of the wind speed, then a 1% uncertainty in the wind speed will result in a 5% uncertainty in the damage calculated at that site. The origin of this uncertainty is the underlying non-linearity of the vulnerability relationship, and not in any assumptions, data or properties unique to our model.
2. Describe how other aspects of the model may have a significant impact on the uncertainties in output results and the basis for making this determination.
The results of any model depend sensitively on details of the structural characteristics and location of the insured sites. Often, this information is not provided by the insurance or underwriting agency for use by the model. Such details can potentially have a large impact on results due to the large variation in damageability among different structure classes and secondary structural configurations, and to the large variation in the wind hazard with respect to distance to coast and other factors.
3. Describe actions taken in light of the uncertainty analyses performed.
243 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
The uncertainty analyses performed during the initial development of the model were crucial in determining optimal sample sizes and the relative importance of parameters. Subsequent analyses have been used to verify that the decisions made continue to be valid.
4. Form S-6 disclosed under Standard S-2 will be used in the verification of Standard S-3.
See Form S-6 at the end of this section.
244 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
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.
USWIND estimates loss costs in the mainland United States from Texas to Maine on the basis of 47,315 stochastic storm simulation results. Of these, about 25,000 affect Florida. Given the high resolution of the stochastic storm database, the contribution to the error in loss cost estimates induced by the sampling process is negligible.
Disclosure
1. Describe the sampling plan used to obtain the average annual loss costs and output ranges. For a direct Monte Carlo simulation, indicate steps taken to determine sample size. For importance sampling design, describe the underpinnings of the design.
USWIND estimates loss costs using a Latin Hypercube technique. The primary storm (e.g. radius, forward speed, and filling rate) and site (e.g. friction, gust factor) parameters are all random variables in the model.
245 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
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 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.
USWIND reasonably replicates incurred losses on a sufficient body of past hurricane events, including the most current data available to EQECAT.
Disclosures
1. Describe the nature and results of the analyses performed to validate the loss projections generated by the model. Include analyses for the 2004 hurricane season.
Overall reasonability/validity checks on historical storm estimates and expected annual loss estimates are continuously conducted on portfolios received from our clients.
Some of the validation comparisons performed are summarized in Form S-4.
2. Provide a completed Form S-4, Validation Comparisons.
See Form S-4 at the end of this section.
246 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
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, due to uncertainty, between historical and modeled annual average statewide loss costs is statistically reasonable, as shown in the information provided below.
Disclosures
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.
The results of our model were validated by checking each component of the model separately. We took the following steps to validate the hazard component:
a) Ensure that the frequency of the simulated storms matches against historical landfall frequency.
b) Compare USWIND return period wind speed estimates by landfall location against other substantive research in this area.
Steps a) and b) were used as the reasonability check for the hazard frequency (number of landfalls per year) and severity (expected wind speeds to be experienced every x years).
Given reasonability of the hazard component of the model, loss estimates were compared to actual losses sustained by specific insurance companies. In addition, comparisons of statewide expected annual loss versus the average of all historical events impacting Florida in this century were compared in order to validate estimated losses.
The expected annual loss estimates produced by USWIND are further checked for reasonability against alternative methods of obtaining the same results. Such methods include Monte Carlo simulations, analyses based solely on historical storms and actuarial techniques, and alternative methods using NHRS and historical frequency rates.
Relativities of the expected annual loss estimates by geographic territory and by construction type have also been evaluated to ensure reasonableness.
247 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Convergence tests were also performed in order to ensure that USWIND produces stable results and that additional detail (i.e., simulated storms) would not significantly alter the result. The basis for our expected annual loss estimates is the modeling of 47,315 storms.
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.
There are no differences in how the model produces loss costs for specific historical events versus loss costs for events in the stochastic hurricane set.
3. Provide a completed Form S-5, Average Annual Zero Deductible Statewide Loss Costs – Historical versus Modeled.
See Form S-5 at the end of this section.
248 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Form S-1: Probability and Frequency of Florida Landfalling Hurricanes per Year
Complete the table below showing the probability and modeled frequency of landfalling Florida hurricanes per year. Modeled probability shall be rounded to four decimal places. The historical probabilities and frequencies below have been derived from the Base Hurricane Storm Set as defined in Standard M-1.
If the data are partitioned or modified, provide the historical probabilities for the applicable partition (and its complement) or modification as well as the modeled probability in additional copies of Form S-1.
Model Results Probability of Florida Landfalling Hurricanes per Year
Number Historical Modeled Historical Modeled Of Hurricanes Probabilities Probabilities Frequencies Frequencies Per Year
0 0.5872 0.5410 64 59 1 0.2569 0.3255 28 35 2 0.1193 0.1050 13 11 3 0.0275 0.0239 3 3 4 0.0092 0.0041 1 0 5 0.0000 0.0005 0 0 6 0.0000 0.0001 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
249 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Form S-2: Examples of Loss Exceedance Estimates
Provide projections of the insured loss for various probability levels using the hypothetical data set provided in the file named “FormA1Input09.xls” and using the 2007 Florida Hurricane Catastrophe Fund aggregate personal residential exposure data set provided in the file named “hlpm2007.exe” and using the 2007 Florida Hurricane Catastrophe Fund aggregate personal and commercial residential exposure data set provided in the file named “hlpm2007c.exe.” Provide the total average annual loss for the loss exceedance distribution distribution using each data set. If the methodology of your model does not allow you to produce a viable answer, please state so and why.
Part A Estimated Personal Estimated Estimated Return Probability Residential Loss Personal & Loss Time of FHCF Data Set ($) Commercial Hypothetical (years) Exceedance Residential Loss Data Set ($) FHCF Data Set ($)
Top ____N/A___ Event _ 10,000 0.01% 122,383,578 173,658,800,128 209,209,901,056 5,000 0.02% 116,674,375 161,229,815,808 194,237,988,864 2,000 0.05% 99,025,219 138,537,893,888 162,515,189,760 1,000 0.10% 84,835,586 116,398,104,576 136,171,716,608 500 0.20% 73,774,852 96,177,299,456 112,664,248,320 250 0.40% 59,089,730 72,891,580,416 87,328,374,784 100 1.00% 42,197,957 49,973,571,584 58,553,810,944 50 2.00% 29,894,953 33,204,133,888 38,514,081,792 20 5.00% 14,791,508 15,136,976,896 17,414,952,960 10 10.00% 6,695,140 6,310,277,632 7,065,320,448 5 20.00% 2,058,810 1,806,261,760 1,981,065,472
250 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Part B
Mean (Total Average Annual Loss) 2,659,362 2,851,549,696 3,279,914,496
Median 27,581 19,358,954 20,015,772
Standard Deviation 8,233,030 10,010,549,248 11,729,008,640
Interquartile Range 1,214,559 1,028,193,280 1,119,788,672
Sample Size 47,315 events 47,315 events 47,315 events
251 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Form S-3: Distributions of Stochastic Hurricane Parameters
Provide the probability distribution functional form used for each stochastic hurricane parameters in the model. Provide a summary of the rationale for each functional form selected for each general classification. Justification for Functional Form Preferred method of derivation so provide to agreement withas data historical and to extrapolate full rangeto of potential values method derivation soPreferredof provide to agreement withas data historical and to extrapolate full rangeto of potential values method derivation soPreferredof provide to agreement withas data historical and to extrapolate full rangeto of potential values Provides best fit to historical data among commonly used distributions Provides best fit to historical data among commonly used distributions Provides best fit to historical data among commonly used distributions Provides best fit to historical data among commonly used distributions Year Year Range Used 1900- 2009 1900- 2009 1900- 2009 1900- 2004 1900- 2004 1900- 2006 1963- 1967; 1992- 2008 Data Source HURDAT HURDAT HURDAT NWS 38 (to 1984), NHC TC Reports Advisories and (1985-2004) NWS 38 (to 1984), NHC TC Reports Advisories and (1985-2004) HURDAT NHC Advisories Functional Form Form Functional of Distribution Maximum Likelihood Kernel Estimation Smoothing Maximum Likelihood Kernel Estimation Smoothing Maximum Likelihood Kernel Estimation Smoothing Lognormal Lognormal Normal Lognormal Stochastic Hurricane (Function Parameter or Variable) Landfall Location Track Direction Sustained Maximum Wind Speed MaximumRadius of Winds Translational Speed Rate Filling Inland Factor Profile
252 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Form S-4: Validation Comparisons
A. Provide five validation comparisons of actual personal residential exposures and loss to modeled exposures and loss. These comparisons must be provided by line of insurance, construction type, policy coverage, county, or other level of similar detail in addition to total losses. Include 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 loss. If this is not available, use exposures for only those policies that had a 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 loss to modeled exposures and loss. Use and provide a definition of the model’s relevant commercial residential classifications
C. Provide scatter plot(s) of modeled vs. historical losses for each of the required validation comparisons. (Plot the historical losses on the x-axis and the modeled losses on the y-axis.)
Rather than using directly a specific published hurricane wind field, the winds underlying the modeled loss cost calculations must be produced by the model being evaluated and should be the same hurricane parameters as used in completing Form A-3.
Totals by Company Actual USWIND Company Event Year TIV ($M) Difference ($M) ($M) A Opal 1995 222,270.00 112.91 99.94 -11.5% B Andrew 1992 4,578.28 48.20 41.34 -14.2% C Andrew 1992 1,229.95 19.93 18.13 -9.0% D Andrew 1992 793.41 30.75 28.77 -6.4% E Andrew 1992 608.67 29.02 28.16 -3.0% F Charley 2004 221,681.89 1134.00 994.51 -12.3% F Frances 2004 221,681.89 686.19 371.04 -45.9% F Ivan 2004 221,681.89 437.67 449.66 2.7% F Jeanne 2004 221,681.89 362.76 470.45 29.7% F Wilma 2005 240,854.58 902.63 878.25 -2.7%
253 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
10000
1000
100 Modeled Loss($M)
10 10 100 1000 10000 Actual Loss ($M)
Figure 54. Historical vs. Modeled Losses for Companies A to F
254 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
(FORM S-4 CONTINUED)
Company C by Line of Business USWIND Event LOB TIV ($M) Actual ($M) Difference ($M) Andrew Mobile Homes 56.16 0.82 0.74 -10.0% Fire & Extended 11.80 0.16 0.22 40.1% Homeowners 1,017.47 17.28 15.66 -9.4% Renters/Tenants 10.99 0.13 0.09 -31.3% Landlord 74.29 1.00 0.97 -2.5% Condominiums 59.25 0.54 0.44 -18.1% Total 1,229.95 19.93 18.13 -9.0%
100
10
1
Modeled Loss ($M) Loss Modeled 0.1
0.01 0.01 0.10 1.00 10.00 100.00 Actual Loss ($M)
Figure 55. Historical vs. Modeled Losses by LOB for Company C
255 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
(FORM S-4 CONTINUED)
Company D by County
USWIND Event County TIV ($M) Actual ($M) Difference ($M) Andrew Broward 234.51 0.50 0.53 5.9% Charlotte 25.64 0.00 0.00 0.0% Collier 44.65 0.18 0.15 -18.5% Hendry 2.74 0.00 0.00 0.0% Martin 8.22 0.00 0.00 0.0% Miami-Dade 203.79 30.01 28.04 -6.6% Monroe 0.31 0.00 0.00 0.0% Total 793.41 30.75 28.72 -6.6%
100
10
1
Modeled Loss ($M) Loss Modeled 0.1
0.01 0.01 0.10 1.00 10.00 100.00 Actual Loss ($M)
Figure 56. Historical vs. Modeled Losses by County for Company D
256 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
(FORM S-4 CONTINUED)
Company E by Line of Business USWIND Event LOB TIV ($M) Actual ($M) Difference ($M) Andrew Homeowner Form 1 0.15 0.02 0.02 -23.8% Homeowner Form 3 179.08 7.34 8.27 12.7% Homeowner Form 4 8.25 0.22 0.24 8.2% Homeowner Form 5 368.84 20.82 19.02 -8.6% Homeowner Form 6 52.36 0.63 0.62 -2.2% Total 608.67 29.02 28.16 -3.0%
100
10
1
Modeled Loss ($M) Loss Modeled 0.1
0.01 0.01 0.10 1.00 10.00 100.00 Actual Loss ($M)
Figure 57. Historical vs. Modeled Losses by LOB for Company E
257 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Totals by Company – Commercial Residential USWIND Company Event Year TIV ($M) Actual ($M) Difference ($M) G Wilma 2005 10,869.45 156.34 151.61 -3.03%
Commercial residential exposures are mapped to the vulnerability functions listed in Standard V-1, including both low-rise and high-rise structure types.
1000
100 Modeled Loss ($M) Loss Modeled
10 10.00 100.00 1,000.00 Actual Loss ($M)
Figure 58. Historical vs. Modeled Losses – Commercial Residential
258 The Florida Commission on Hurricane Loss Projection Methodology Statistical Standards
Form S-5: Average Annual Zero Deductible Statewide Loss Costs – Historical versus Modeled
A. Provide the average annual zero deductible statewide personal residential loss costs produced using the list of hurricanes in the Base Hurricane Storm Set as defined in Standard M-1 based on the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal residential exposure data found in the file named “hlpm2007.exe”.
B. Provide a comparison with the statewide personal residential loss costs produced by the model on an average industry basis.
Average Annual Zero Deductible Statewide Personal Residential Loss Costs
Time Period – 2007 FHCF Historical Hurricanes Produced by Model Exposure Data Current Submission $3.26 Billion $3.99 Billion Previously Accepted $3.53 Billion $4.27 Billion Submission Second Previously $3.56 Billion $4.32 Billion Accepted Submission Percentage Change Current Submission / Previously -7.70% -6.56% Accepted Submission Percentage Change Current Submission / Second -8.56% -7.64% Previously Accepted Submission
C. Provide the 95% confidence interval on the differences between the mean of the historical and modeled personal residential loss.
Based on the historical storm set for the 110 year experience period (1900 through 2009) and using the Florida Hurricane Catastrophe Fund’s 2007 aggregate personal residential exposure data resulted in a statewide historical annual average zero deductible loss of $3.26 billion and a modeled annual average zero deductible loss of $3.99 billion.
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The difference can be shown to be statistically insignificant as follows:
Let Xi (i=1…85) represent the losses from the 85 historical events, which occurred over 110 years. Then the historical annual loss cost A is given by:
A = ¦ Xi / 110 (where i = 1…85) = $3.26 Billion
The standard error of A is given by: 2 2 S.E (A) = SQRT(A /85 + 85* Var ({Xi }) /110 ) = $0.72 Billion
where Var ({Xi }) is the variance of the historical losses (from the 85 storms). This assumes that the Xi have identical independent distributions and the frequency has a Poisson distribution. Using the t-test the two-tailed 90% confidence for the true annual loss cost interval (narrower than the 95% confidence interval) is given by the range:
A1 = A - 1.671 * S.E (A) = $2.06 Billion A2 = A + 1.671 * S.E (A) = $4.45 Billion
The modeled annual loss cost ($3.99 Billion) is within the above range, so the difference between the historical and the modeled results is not statistically significant. D. If the data are partitioned or modified, provide the average annual zero deductible statewide personal residential loss costs for the applicable partition (and its complement) or modification as well as the modeled average annual zero deductible statewide personal residential loss costs in additional copies of Form S-5.
The data are not partitioned or modified. E. Provide the average annual zero deductible statewide personal and commercial residential loss costs produced using the list of hurricanes in the Base Hurricane Storm Set as defined in Standard M-1 based on the 2007 Florida Hurricane Catastrophe Fund’s aggregate personal and commercial residential exposure data found in the file named "hlpm2007c.exe"
F. Provide a comparison with the statewide personal and commercial residential loss costs produced by the model on an average industry basis.
Average Annual Zero Deductible Statewide Personal and Commercial Residential Loss Costs
Time Period – 2007 FHCF Historical Hurricanes Produced by Model Exposure Data Current Submission $3.80 Billion $4.70 Billion
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G. Provide the 95% confidence interval on the differences between the mean of the historical and modeled personal and commercial residential loss.
Based on the historical storm set for the 110 year experience period (1900 through 2009) and using the Florida Hurricane Catastrophe Fund’s 2007 aggregate personal and commercial residential exposure data resulted in a statewide historical annual average zero deductible loss of $3.80 billion and a modeled annual average zero deductible loss of $4.70 billion. The difference can be shown to be statistically insignificant as follows:
Let Xi (i=1…85) represent the losses from the 85 historical events, which occurred over 110 years. Then the historical annual loss cost A is given by:
A = ¦ Xi / 110 (where i = 1…85) = $3.80 Billion
The standard error of A is given by: 2 2 S.E (A) = SQRT(A /85 + 85* Var ({Xi }) /110 ) = $0.85 Billion
where Var ({Xi }) is the variance of the historical losses (from the 85 storms). This assumes that the Xi have identical independent distributions and the frequency has a Poisson distribution. Using the t-test the two-tailed 90% confidence for the true annual loss cost interval (narrower than the 95% confidence interval) is given by the range:
A1 = A - 1.671 * S.E (A) = $2.37 Billion A2 = A + 1.671 * S.E (A) = $5.22 Billion
The modeled annual loss cost ($4.70 Billion) is within the above range, so the difference between the historical and the modeled results is not statistically significant.
H. If the data are partitioned or modified, provide the average annual zero deductible statewide personal and commercial residential 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 loss costs in additional copies of Form S-5.
The data are not partitioned or modified.
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Form S-6: Hypothetical Events for Sensitivity and Uncertainty Analysis
Output is provided in the following files:
2009FormS6ExpectedLossCost_EQECAT_28March2011.dat 2009FormS6ExpectedLossCost_EQECAT_28March2011.pdf 2009FormS6LossCostContour_EQECAT_28March2011.dat 2009FormS6LossCostContour_EQECAT_28March2011.pdf
A cumulative distribution of loss costs for each of hurricane categories 1, 3, and 5 is provided in Figure 59 below.
Figure 59. Cumulative Distributions of Loss Costs
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Contour plots of mean loss cost for each of hurricane categories 1, 3, and 5 are provided in Figures 60, 61, and 62, respectively, below.
Figure 60. Contour Plot of Loss Cost for a Category 1 Hurricane
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Figure 61. Contour Plot of Loss Cost for a Category 3 Hurricane
Figure 62. Contour Plot of Loss Cost for a Category 5 Hurricane
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Uncertainty and Sensitivity Analysis for Loss Cost
The modeling organization shall perform uncertainty and sensitivity analyses for expected loss cost as outlined below. The Professional Team will perform uncertainty and sensitivity analyses based on the modeling organization’s expected loss cost calculations as part of its preparation prior to reviewing the modeling organization’s internal uncertainty and sensitivity analyses (using the model’s actual damage functions) during the on-site reviews. The modeling organization shall present to the Professional Team their uncertainty and sensitivity analyses of their model using the model’s vulnerability functions.
Sensitivity analyses will be based on standardized regression coefficients (SRC) for each model input variable in the Excel input file. The calculation of the SRCs is explained on page 22 of the Professional Team Demonstration Uncertainty/Sensitivity Analysis by R.L. Iman, M.E. Johnson, and T.A. Schroeder, September 2001, available at: www.sbafla.com/methodology/pdf/meetings/ 2001/materials/demo%20ua-sa.pdf.
Loss costs used in these sensitivity analyses are based on EQECAT’s 2011 Florida Hurricane Model. If the SRC is positive for a given model input variable, then loss cost increases as the variable increases while negative SRC values indicate that loss cost decreases as the variable increases. The SRCs in these sensitivity analyses are summarized as follows: Category CP Rmax VT PF CF FFP 1 -0.4950 0.1150 0.2147 0.1666 0.4757 0.6278 3 -0.3743 0.2559 0.1373 0.1784 0.6636 0.4374 5 -0.2687 0.4090 0.1541 0.2200 0.7619 0.3133
Figure 63 presents graphs of these SRCs for all six input variables for each category of hurricane. This figure shows that the Far Field Pressure (FFP) has the most influence on the magnitude of loss cost for a Category 1 hurricane and this relationship is positive. Central Pressure (CP) has the second most influence on the magnitude of loss cost (negative) followed by Conversion Factor (CF) (positive relationship) and forward speed (VT) (positive). The model’s shape parameter (called the Profile Factor (PF)) and Radius of Maximum Winds (Rmax) had the least but still considerable influence.
The Category 3 results in Figure 63 show that CF now has the most influence on the magnitude of loss costs followed by FFP and then CP and Rmax. PF and VT again had the least influence.
The Category 5 results in Figure 63 show that CF has the most influence on the magnitude of loss costs followed by Rmax and then FFP and CP. PF and VT again had the least influence.
Over all hurricane categories, FFP, CF, and CP have the most influence on the magnitude of loss cost followed by Rmax, PF and VT.
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Figure 63. SRCs for Expected Loss Cost for all Input Variables for all Hurricane Categories
Uncertainty analyses will be based on expected percentage reduction (EPR) for each model input variable in the Excel input file. The calculation of the EPRs is explained on page 22 of the Professional Team Demonstration Uncertainty/Sensitivity Analysis by R. L. Iman, M. E. Johnson, and T. A. Schroeder, September 2001, available at: www.sbafla.com/methodology/pdf/meetings/ 2001/materials/demo%20ua-sa.pdf.
If the EPR is large for a given input variable, that variable makes a large contribution to the uncertainty in loss cost while a small EPR indicates that the variable contributes much less to the uncertainty in loss cost. The EPRs in these uncertainty analyses are summarized as follows:
Category CP Rmax VT PF CF FFP 1 24.6% 2.3% 3.0% 2.8% 25.2% 42.0% 3 9.3% 6.7% 2.1% 2.5% 40.7% 15.9% 5 10.5% 20.0% 3.4% 7.1% 68.2% 10.4%
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Figure 64 presents graphs of these EPRs for all six input variables for each category of hurricane. This figure shows that the FFP profile parameter makes the largest contribution to the uncertainty (42.0%) in loss cost for a Category 1 hurricane. CF makes the next largest contribution (25.2%) followed closely by CP (24.6%) and then VT (3.0%). PF (2.8%) and Rmax (2.3%) made very little contribution to the uncertainty in loss cost.
The Category 3 results in Figure 64 show that CF makes the largest contribution to the uncertainty (40.7%) in loss cost followed by FFP (15.9%) and CP (9.3%) while Rmax rises (6.7%). PF (2.5%) and VT (2.1%) again make very little contribution to the uncertainty in loss cost.
The Category 5 results in Figure 64 show that CF makes the largest contribution to the uncertainty (68.2%) in loss cost followed by Rmax (20.0%). CP (10.5%) and FFP (10.4%) have similar values. PF (7.1%) and VT (3.4%) again make the least contribution to the uncertainty in loss cost.
Over all hurricane categories, CF, FFP, and CP make the largest contributions to the uncertainty in loss cos. PF and VT make the least contributions to loss costs. The EPRs in the above summary do not necessarily sum to 100% unless the underlying model is linear. In this case, the sums for Category 1, 3, and 5 are 99.8%, 77.2%, and 119.5%.
Figure 64. EPRs for Expected Loss Cost for all Input Variables for all Hurricane Categories
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Computer Standards
C-1 Documentation
A. The modeling organization shall maintain a primary document binder, containing a complete set of documents specifying the model structure, detailed software description, and functionality. Development of each section shall be indicative of accepted software engineering practices.
EQECAT maintains all such documentation, and will have it available to the professional team during the on-site visit. B. All computer software (i.e., user interface, scientific, engineering, actuarial, data preparation, and validation) relevant to the submission shall be consistently documented and dated.
EQECAT maintains all such documentation, and will have it available to the professional team during the on-site visit.
C. The modeling organization shall maintain (1) a table of all changes in the model from the previously accepted submission to the initial submission this year and (2) a table of all substantive changes since this year’s initial submission.
EQECAT maintains such a table that provides all changes from the previously accepted submission to the initial submission and all substantive changes since this year’s initial submission.
D. Documentation shall be created separately from the source code.
EQECAT maintains all such documentation, and will have it available to the professional team during the on-site visit.
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C-2 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 model.
EQECAT maintains such requirements and documentation, and will have it available to the professional team during the on-site visit. EQECAT updates the relevant requirements documentation whenever changes are made to the model.
Disclosure
1. Provide a description of the documentation for interface, human factors, functionality, documentation, data, human and material resources, security, and quality assurance.
EQECAT maintains a set of documents describing the specifications and product requirements for user interfaces, database schema, client customizations, security considerations, user manuals, and references.
The above documentation will be available to the professional team during the on-site visit.
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C-3 Model Architecture and Component Design
The modeling organization shall maintain and document (1) detailed control and data flow diagrams and interface specifications for each software component, and (2) schema definitions for each database and data file. Documentation shall be to the level of components that make significant contributions to the model output.
The design levels of the software have been documented, including software components and interfaces, data files, and database elements. This documentation will be shown to the professional team during the on-site visit.
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C-4 Implementation
A. The modeling organization shall maintain a complete procedure of coding guidelines consistent with accepted software engineering practices.
EQECAT maintains such a procedure. B. The modeling organization shall maintain a complete procedure used in creating, deriving, or procuring and verifying databases or data files accessed by components.
EQECAT maintains such a procedure. C. All components shall be traceable, through explicit component identification in the flow diagrams, down to the code level.
All components are traceable in this manner. D. The modeling organization shall maintain a table of all software components affecting loss costs, 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.
This table will be available for review by the professional team. 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.
Yes, the source code is commented in this manner. Also, EQECAT maintains live intranet source code documentation for the analysis engines. The model is based upon published research modified as appropriate by EQECAT’s meteorological, engineering, and statistical personnel. System data is organized and maintained in tables, binary files, or flat files, depending upon the type of analysis. The underlying model including algorithm implementation and technical assumptions along with the procedures used for updating the system data will be available for review by the professional team during the on-site visit. The overall system design has been implemented using standard software engineering techniques. System documentation is maintained to define critical system functionality in terms of Data Flow Diagrams, Structure Charts, and the corresponding narratives which describe how each module functions. This information is available for on- site review.
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F. The modeling organization shall maintain the following documentation for all components or data modified by items identified in Standard G-1, Disclosures 5:
1. A list of all equations and formulas used in documentation of the model with definitions of all terms and variables.
This list will be available for review by the professional team. 2. A cross-referenced list of implementation source code terms and variable names corresponding to items within F.1.
This list will be available for review by the professional team.
Disclosure
1. Specify the hardware, operating system, other software, and all computer languages required to use the model.
Details regarding the required hardware, operating system, and other software are given in Standard G-1, Disclosure 2. The calculational components of the model have been developed in C++; other components have been developed in C++ and Java.
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C-5 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.
The models have been extensively tested to verify that calculated results are consistent with the intended simulation approach. A variety of methods have been employed. These include algorithm verification through comparison to independently developed software packages, hand calculations, and sensitivity analyses. Much of this verification is performed by personnel other than the original component developers. Extensive validation testing of the software generated wind fields has been performed to confirm that generated wind speeds are consistent with observations. Numerous analyses have been conducted using actual insurance portfolio data to confirm the reasonableness of resulting answers.
B. Component Testing
1. The modeling organization shall use testing software to assist in documenting and analyzing all components.
Testing software is used to assist in documenting and analyzing all components. 2. Unit tests shall be performed and documented for each component.
Unit tests have been performed and documented for each component relevant to residential hurricane loss costs in Florida. 3. Regression tests shall be performed and documented on incremental builds.
A suite of automated regression tests is regularly run on the software to ensure integrity of the various components as well as the results produced by the integrated system. Quality assurance documentation includes a description for each test case from the regression testing suite. 4. Aggregation tests shall be performed and documented to ensure the correctness of all model components. Sufficient testing shall be performed to ensure that all components have been executed at least once. 273 The Florida Commission on Hurricane Loss Projection Methodology Computer Standards
A suite of automated regression tests is regularly run on the software to ensure integrity of the various components as well as the results produced by the integrated system.
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.
Testing software is used 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.
Client data is extensively tested during the import process into the EQECAT system to confirm its accuracy. Field level validation is performed to confirm that every data element within each record falls within known ranges. Data not falling within known ranges is marked as an error or a warning in a log depending upon the severity of the problem. Child/parent and other key relationships are also checked. A summary log is displayed at the end of import process denoting the number records which have warnings or errors.
Disclosures
1. State whether two executions of the model with no changes in input data, parameters, code, and seeds of random number generators produce the same loss costs and probable maximum loss levels.
Yes, they produce the same loss costs and probable maximum loss levels.
2. Provide an overview of the component testing procedures.
A suite of automated regression tests is regularly run on the software to ensure integrity of the various components as well as the correctness and consistency of results produced by the integrated system.
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C-6 Model Maintenance and Revision
A. The modeling organization shall maintain a clearly written policy for model revision, including verification and validation of revised components, databases, and data files.
EQECAT has a clearly written policy for model revision with respect to methodologies and data, including verification and validation of revised components, databases, and data files. B. A revision to any portion of the model that results in a change in any Florida residential hurricane loss cost shall result in a new model version number.
A revision to any portion of the model that results in a change in any Florida residential hurricane loss cost results in a new model version number. C. The modeling organization shall use tracking software to identify all errors, as well as modifications to code, data, and documentation.
EQECAT uses tracking software to identify all errors, as well as modifications to code, data, and documentation. EQECAT’s policies and procedures for model revision will be made available to the professional team during the on-site visit.
D. The modeling organization shall maintain a list of all model versions since the initial submission for this year. Each model description shall have a unique version identification, and a list of additions, deletions, and changes that define that version.
EQECAT maintains such a list of all model versions since the initial submission for the year. Each model description has a unique version identification with a list of additions, deletions, and changes that define that version.
Disclosure
1. Identify procedures used to maintain code, data, and documentation.
EQECAT has a series of ISO procedures regarding the maintenance of code, data, and documentation, and these will be made available to the professional team.
2. Describe the rules underlying the model and code revision numbering system.
EQECAT produces a major release of its software (including WORLDCATenterprise and USWIND) approximately annually. Between such
275 The Florida Commission on Hurricane Loss Projection Methodology Computer Standards major releases EQECAT sometimes produces interim releases, generally to update one or more models within WORLDCATenterprise, to provide additional software functionality, or to provide other enhancements or corrections. Version numbers for major releases are of the form WORLDCATenterprise M.X and USWIND N.Y, e.g. WORLDCATenterprise 3.15 and USWIND 5.17. Version numbers for interim releases append an additional two-digit number, e.g. WORLDCATenterprise 3.15.01 and USWIND 5.17.01.
The EQECAT Florida Hurricane model is contained in both our standalone software USWIND and our client-server software WORLDCATenterprise. The Florida Hurricane model version number is included on all output reports produced by WORLDCATenterprise and USWIND. Any change in Florida residential hurricane loss costs results in a new version number of the EQECAT Florida Hurricane model.
For example, the initial submission under the 2009 standards is for the EQECAT Florida Hurricane Model 2011. The version number is designated by the year of completion. If subsequent model revisions occur, the version numbers would have a letter appended after the year (2011a, 2011b, etc.)
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C-7 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 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.
In accordance with standard industry practices, EQECAT has in place security procedures for access to code, data, and documentation, including disaster contingency, and for maintenance of anti-virus software on all machines where code and data are accessed. Procedures are also in place to ensure that licensees of the model cannot compromise the correct operation of the software. These procedures will be made available to the professional team during the on- site visit.
Disclosure
1. Describe methods used to ensure the security and integrity of the code, data, and documentation.
The model can only be used by authorized users. Authorized user accounts are created by a trusted administrator. The program files of the model are in machine code and cannot be reverse engineered or tampered with. The data files (vulnerability curves, hazard etc.) are in binary format and cannot be tampered with. The output from the model is always labeled with the analysis parameters and other information needed to repeat a particular analysis - thus, reports of the program cannot be misused or altered to present incorrect information.
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Appendix 1 - Credentials of Selected Personnel
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CREDENTIALS
Dr. James R. (Bob) Bailey has over 15 years experience as a technical consultant, researcher, and project manager. His doctoral work in Civil Engineering included an emphasis on wind engineering, specifically wind effects on buildings and components. He is experienced in subjects related to construction materials, solid mechanics, dynamics, numerical analysis, structural analysis and design. He served as a consultant to NASA by performing an on-site inspection at the Marshall Space Flight Center to assess the structural integrity of buildings subject to tornado winds. He also has performed on-site inspections of commercial high-rise buildings in Dallas to evaluate the performance of structurally-glazed window glass systems subject to extreme wind events. He is a member of the API subcommittee that is developing a new wind loading specification for drilling masts and derricks. Dr. Bailey holds a Ph.D., M.S., and B.S. in Civil Engineering from Texas Tech University.
Dr. James J. Johnson, Consultant to EQECAT, has more than 30 years of project management and civil/nuclear engineering experience, serving the insurance/reinsurance, Fortune 500, and nuclear (domestic and international) industries. From its creation in 1994 until 2000 he headed the EQECAT division, a group that provides catastrophic risk management services to the global insurance and reinsurance industries, including catastrophe modeling software, portfolio and single site analysis, risk management consulting, training, and information. In addition, Dr. Johnson has participated in the development, implementation, and teaching of seismic risk and seismic margin assessment methodologies. He has participated in seismic PRAs of over 20 nuclear power plants. His participation encompasses many aspects including hazard definition, seismic response and uncertainty determination, detailed walkdowns, and fragility assessment. Dr. Johnson has contributed to over 80 technical reports and journal articles and is a member of the Earthquake Engineering Research Institute, American Society of Civil Engineers, and other technical organizations. Dr. Johnson holds a Ph.D. and M.S. in civil engineering from the University of Illinois, and a B.C.E. in civil engineering from the University of Minnesota. He is also a licensed Civil Engineer in California.
Dr. Mahmoud Khater, Senior Vice President and Chief Technical Officer of EQECAT, has more than 20 years of engineering experience in natural hazards risk and reliability assessment; in the insurance, power, industrial, and commercial sectors; and in the behavior of structures and lifelines under seismic and wind loading. His experience includes seismic, fire, and hurricane hazard and risk assessments for single buildings, lifeline systems, and portfolios of properties. Since joining EQECAT, Dr. Khater has served as EQECAT’s project and technical manager for the development of state-of-the-art probabilistic analysis computer programs for application to civil engineering problems, seismic risk analysis and hurricane risk assessment. Responsibilities have included several earthquake and hurricane structural response analyses and portfolio analyses. Dr. Khater holds a Ph.D. in structural engineering from Cornell University, and a M.Sc. and M.Bc. in structural engineer from Cairo University in Egypt. He is an active member in the Earthquake Engineering Research Institute and the American Society of Engineers.
Dr. Omar Khemici has over 20 years of extensive professional experience in structural engineering and natural hazard risk assessment and mitigation. As a Director for EQECAT, he provides technical direction and support to a variety of key projects. He performed the QA verification of different USWIND™ modules through hand calculations, and participated in the 279 The Florida Commission on Hurricane Loss Projection Methodology Appendices development of the USWIND™ and USQUAKE™ vulnerability functions. He recently participated in the development of the USWildfire™. Dr. Khemici is project manager for jobs with the primary insurance, reinsurance companies, and financial institutions. Dr. Khemici graduated from Stanford University in 1982 and is a licensed Civil Engineer in California.
Raymond Kincaid, Senior Vice President of EQECAT, has more than 20 years of experience in natural hazards risk management. For the last 10 years he has directed the GUI portion of the development of several software products used to assess and manage insurance portfolio risk resulting from catastrophic events including hurricanes, earthquakes, high winds, and flood. Products developed under his guidance include USWIND™, USQUAKE™, UKWIND™ and UKFLOOD™. He also has extensive experience in the design and analysis of structures to resist extreme loadings including earthquakes, hurricane, blast, and nuclear weapons effects. Mr. Kincaid has directed major natural phenomena and seismic hazard analysis programs for numerous government, manufacturing and commercial clients. Representative clients include the Department of Energy, U.S. Postal Service, Allendale Insurance, Pacific Bell, Anheuser-Busch, 3M, Northrop, Unisys, General Foods, Litton, Parker-Hannifin, and Rockwell International.
Thomas I. Larsen, Senior Vice President of EQECAT, has more than 15 years of professional structural engineering, research, computer programming, and project management experience. He participated in the development of the USWIND and USQUAKE natural catastrophe financial risk assessment software programs. This includes project management for analyses for selected clients, review of the software methodology for consistency and completeness, and compilation of post-earthquake/hurricane damage and loss experience data. Prior work at EQECAT includes natural catastrophe hazard (earthquake and related perils such as tsunami and fire following, hurricane and other windstorm, and volcano) and/or risk analysis for many different regions including Australia, Chile, Iceland, Italy, New Zealand, Puerto Rico, the Sakhalin Islands, and the Caspian Sea area. Mr. Larsen holds a M.Eng. in structural engineering from the University of California in Berkeley and B.S. in structural engineering from Stanford University. He is presently a licensed civil engineer in California.
David F. Smith, Senior Vice President of EQECAT, has more than 10 years of professional experience in hurricane model design, natural hazard research, software development, and project management. He participated in the development of the USWIND and USQUAKE natural catastrophe financial risk assessment software programs. This includes development of the hazard portions of both programs, risk analyses for selected clients, and review of the software methodology for consistency and completeness. Mr. Smith also managed the development of the hazard portion of the EQECAT hurricane/typhoon models for Japan and the Caribbean. Prior work at EQECAT includes natural catastrophe hazard and/or risk analysis for many different regions including Puerto Rico, Jamaica, Costa Rica, the Philippines, and Japan. Mr. Smith holds a M.S. in geophysics from Yale University and a B.S. in mathematics from the University of Chicago.
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Appendix 2 - Independent Review
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The Engineering, Statistical, and Scientific Validity of EQECAT USWIND Modeling Software
IMPLICATIONS FOR CATASTROPHE MODELING WITHIN THE COMMERCIAL HIGHLY PROTECTED RISK PROPERTY INSURANCE INDUSTRY
Peter J. Kelly Lixin Zeng Arkwright Mutual Insurance Company
Abstract
The validity of EQECAT USWIND1 modeling software is reviewed from several perspectives. Using several external sources for hurricane data, it is found that the storm data set represents the historical and expected long term storm patterns well and generally without bias. By reviewing storm damage estimates against a theoretical understanding of the wind effects on structures as well as actual experience, it was found that the model’s damage estimates reasonably reflect the physical properties of force and damage and that the system has no systematic bias in its damage estimation logic. One minor shortcoming in damage estimation was uncovered in the manner that USWIND uses geocoding during initial data import, especially for areas with very large zip codes. The vendor has corrected this problem in subsequent versions of the software.
All in all, the EQECAT modeling package represents a very well conceived and thoroughly researched natural disaster modeling environment for hurricanes. External data and expert opinion have been incorporated into the software. Our independent experiments as well as the advice of meteorological and structural experts lead us to conclude that the systems is an excellent tool for managing the risk of natural disasters in the commercial property insurance industry.
Presented November 7, 1996 at the ACI Conference for Catastrophe Reinsurance, New York, NY. Author information: [email protected] and [email protected]
1 USWIND is a trademark of EQECAT, Incorporated, headquartered in San Francisco.
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Introduction
Use of natural disaster modeling software for windstorm exposures has increased in recent years with the advent of improved software and the increase in natural disaster-caused damage during the most recent 10 years. For insurers in the Highly Protected Risk (HPR) commercial property marketplace, these software programs represent an important advance and a significant challenge. While some insurers take the time to calibrate these systems by examining the damage estimates that come from software, few take the time to review the probabilistic and scientific content of these systems in light of recent research and advances in the scientific community. This is unfortunate because based on our experience, the damage-based error to portfolio calculations will generally be well less than one order of magnitude, but errors due to the probabilistic and scientific components of the system can be several orders of magnitude.
In this paper, we first survey the current research on the long term probabilistic characteristics of tropical cyclones conducted at governmental agencies and scientific community. The scientific basis of the USWIND tropical cyclone modeling component of the software are then assessed. Next, the design of the wind damage calculation is reviewed. Based on this assessment, the validity of the software is tested and evaluated through a series of experiments; first to validate the damage calculations and then to validate the probabilistic storm database, which because of its proprietary nature, requires a special simulation process.
The software that was used in all analysis presented in this paper is USWIND 3.07.05.
I. An assessment of current scientific research
Tropical cyclone (TC) is a generic term for hurricane, typhoon and other tropical vortices. A severe TC is the most devastating natural disaster in terms of property damage and loss of life. Studying TC activity is therefore one of the most important objectives of meteorological agencies and scientific communities around the world. For insurers' underwriting and/or reinsurance decision making, accurate long term probabilistic characteristics of TC activity is needed. Both observational and theoretical studies have been undertaken to address these issues:
Direct historical observations: the National Hurricane Center (NHC) has archived reliable observations of the North Atlantic basin (including the North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico) TC activity since 1886 and eastern Pacific observations since 1949. The data captured includes position of storm center, central pressure, and maximum sustained wind speed every six hours. Based on the data, scientists at NOAA/National Weather Service calculated the probability distributions of TC (in particular, hurricane) frequency, intensity and track parameters along the 3000 miles coast line of the eastern and southeastern United States [Ho et al., 1987; Neumann, 1987]. The results of these studies are widely used by storm-surge modelers, climate researchers, and insurers.
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General circulation model (GCM) simulations: GCM is the numerical simulation of atmospheric and oceanic circulation based on our knowledge of dynamics and physics. High speed computers and advanced observing technology (e.g. environmental satellites) have enabled researchers to study TC activity with unprecedented detail. The latest work in this area has been undertaken by scientists at Max-Plank Institute for Meteorology in Germany [Bengtsson et al. 1995]. They run their GCM on time scales from five years to multi-decades, and have successfully simulated realistic TC activity globally. 2
Observational study and GCM simulation have their respective advantages and shortcomings. The former is directly based on historical data but representativeness of the available data is uncertain and needs to be further assessed. The latter is based on physics and thus is more robust. However, GCM’s high computational demand limits its ability to fully resolve TC activity and keeps it from being widely adopted.
Bengtsson et al. [1995] compared a GCM simulation to the observations of TC experience during a period of twenty years. It was found that the GCM and observations reveal similar frequency and geographical and seasonal distributions of TC activity. This comparison serves as an independent verification to the validity of the observational data. However, detailed examination of the data set showed that the early observations are biased toward higher hurricane activity because the wind measurements were biased high prior to the 1960s. An empirical correction was designed by Landsea [1993], and is used in our investigation.
2 A GCM designed for regional climatology study is usually teamed with a nested LAM (limited area model) in order to obtain a resolution fine enough to describe the region of interest. Studies have demonstrated encouraging results of the GCM/LAM simulation of regional climate in Europe [Giorgi et al., 1990] and North America [Hewitson and Crane, 1992]. The regional distribution of important climatic variables are shown to be realistically reproduced. In particular, Giorgi et al. [1990] illustrated the ability of the GCM/LAM to provide detailed features of European winter storms.
Admittedly, no attempt has yet to be made to simulate tropical cyclones with a GCM/LAM. As Bengtsson [1995] showed that a GCM itself can simulate the TC activities with reasonable accuracy, it is our belief that future GCM/LAM work will substantially improve such simulations. We plan to work with experts in this field to initiate studies along this path. 284 The Florida Commission on Hurricane Loss Projection Methodology Appendices
II. The scientific basis of the EQECAT software USWIND
USWIND is a wind storm hazard modeling software package developed by EQECAT, Inc. for the eastern and southeastern United States, Hawaii and Puerto Rico. Given detailed location structural information and insurance policy financial information (e.g. building location, construction and content type, total insured value, deductible, reinsurance, etc.), USWIND calculates the annual expected damage in dollar amount and percentage. Additionally, it estimates non-exceedance damage at any given probability level (e.g. the 95% non-exceedance damage). This program consists of three main steps: (1) construction of an applicable probability storm data set, and (2) damage calculations based on this data set, and (3) financial analysis (which is not part of this study.)
The scientific basis for the first step stems from the study by Ho et al. [1987, see section I], which is documented in NOAA Technical Report - NWS 38. The probability distributions of landfalling hurricanes along the eastern and southeastern United States are calculated based on historical observations. Although the history of TC records is not long (about 100 years), the observational data have been proven to be reasonably representative. An example of such prove is the agreement between the observations and GCM simulation [Bengtsson et al., 1995].
The probability distributions of TC activity are then sampled by a computer simulation scheme (Latin-Hypercubic simulation with variance reduction) to create a data set including 465,000 storms. The characteristics (such as location, intensity, etc.) of these storms is stochastically assigned. These storms are then imposed on an insurance portfolio.
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III. The damage estimation component of the EQECAT software USWIND
Storm damage is determined by accumulating site specific calculations. These calculations incorporate wind field information from the probability storm data set and individual location engineering considerations (e.g. construction, roofing, and cladding.) The damage calculation itself is a function of the projected maximum wind speed, peak gusts, and storm surge. The factors are the independent variables in a model for which the dependent variable is the percent of damage that results from a storm. The functions which relate wind speed to damage are called “vulnerability” curves within the industry. EQECAT provides a set of vulnerability functions with its software. Each curve represents a vulnerability function for different structure types. Customized vulnerability functions can also be created for unique locations by creating new curves, or by combining the existing EQECAT’s curves.
The resulting site damage is adjusted for the financial structure of the insurance policy including local or policy deductible, limits, and site specific (“facultative”) reinsurance recoveries. These net amounts are then accumulated and adjusted for portfolio level (“treaty”) reinsurance recoveries.
IV. Assessing the Simulated EQECAT USWIND Damage Calculation
As a 150 year old commercial property engineering company with an insurance capacity, Arkwright has developed a process for estimating individual site wind damage which is very complex. Initially, general storm parameters are taken into consideration. These storm parameters include wind speed, storm diameter and shape, forward speed and direction, central and external barometric pressure, and rainfall. Before translating this data in localized forces, local terrain data are analyzed. This terrain information consists of elevation, distance from coast, roughness, drainage, nearby structures (as well as storage and vegetation), and local tide patterns. The final component of input to the process is the local facility structural engineering information. This structural information includes roof construction (design, geometry, flashing, and anchorage), overall building envelope design and openings, wall construction (material, design, cladding, and glass), canopies and overhangs, and contents information (amount, susceptibility to water and wind damage, and desirability to looters.)
From these inputs an Arkwright engineer can estimate the resulting forces that can be expected to be exerted upon a building during a storm. These forces include the overall wind field, number and speed of projectiles, storm and tidal surge, wind gusts (speed, pattern, and duration), and salt deposit (for corrosion damage estimation.)
For a given profile of forces exerted upon a well defined structure, an experienced property engineer can then estimate (through theory and experience) resulting damage. This part of the process begins with identification of the likely initial failure mode (roof uplift, balcony collapse, etc.) The likely failure mode is a function of the most exposed structural component. In addition to assessing what structural component will fail, the extent of failure must be estimated -- based on the forces exerted upon the structure. Next, any subsequent or resulting failure must be
286 The Florida Commission on Hurricane Loss Projection Methodology Appendices estimated in order to complete the chain of damage producing events. Lastly, based on many losses and financial guidelines3, the financial extent of the event is determined. In an ideal modeling environment, this entire process would be represented in a detailed calculation that would take place for every storm and for every structure. Based on computing power, intended use, and inherent uncertainties in other parts of the model (the probabilistic storm data set), such a detailed approach is simply not practical within an application such as USWIND.
The approach that EQECAT has chosen is to incorporate vulnerability curves for standard structure types. These vulnerability curves were developed by EQECAT using research done by Dr. Kishor Mehta (Director of the Wind Engineering Research Center) and Dr. James McDonald (Director of the Institute for Disaster Research) at Texas Tech University, where damage analysis for storms for the last 25 years has been conducted. In addition to this work, EQECAT used claims data from all the major storms of the last 30 years that is contained in the National Hurricane Research Project at Travelers. This data was analyzed by Dr. Don G. Friedman and John Mangano. Additionally, EQECAT used internal investigations of hurricanes Andrew, Iniki, Marilyn, Bob, Opal, and typhoon Angela as well as claims data from hurricanes Hugo, Andrew, Iniki, and Opal from companies that participated in the development of USWIND.
While this research record is impressive, Arkwright also has extensive and well documented loss experience. With this data in hand and since the vulnerability curves can be customized, the issue of validity testing for the vulnerability curves is not as important as it is for the mathematical and meteorological content of the system. After an extensive calibration exercise, Arkwright developed a library of customized vulnerability curves. In addition to the customized curves however, Arkwright does use some curves that come directly form the EQECAT set, so the provided vulnerability functions do warrant review.
The first test used to validate the vulnerability curves was to compare the changes in damage to the changes in the kinetic energy at different wind speeds. With all other things being equal, the damage should be proportional to the square of the velocity (wind speed) because it is closely related to the pressure that the wind exerts on a building. The well know formula for kinetic energy bears this out. The formula for kinetic energy is
K.E. = 1/2 m v2 where m = mass of air, and v = velocity (wind speed)
Since properties (especially commercial properties) withstand considerable force before any damage results, the proportionality that we wish to test is: i. D = 0 ; for vd
3 These guidelines include the standard regional costs of materials and labor as well as increased, or inflated, cost of construction after a natural disaster due to a high demand for construction materials and personnel 287 The Florida Commission on Hurricane Loss Projection Methodology Appendices
vd = velocity (wind speed) where damage ceases to be zero.
Focusing on equation ii and removing the constants (1/2, and m) which only affect the scale of the proportionality , we get: 2 D ~ (vx - vd)
To test this comparison, we ran a simple test using individual facilities of varying structure types using the scenario storm capability of USWIND and compiled damage statistics for various wind speeds. One example of these analyses is presented in figure 1 where the damage estimates for an industrial high rise building with average cladding is reviewed.
USWIND Damage Estimate Calculation For a single facility at various wind speeds Facility Damage (Axis 2) (Axis Damage Facility Sq. of Wind Speed (Axis 1) / 70 75 80 90 100 110 120 130 140 150 160 170 180 190 Wind Speed (MPH)
Square of Wind Speed USWIND Damage
Figure 1. A comparison of the USWIND estimated wind damage at a commercial facility versus the square of the difference between the wind speed and the point at which damage ceases to be zero (vd); for this example, the point vd was 70 mph. A constant or proportionality of .0018 was included for scaling.
Visually, the test for proportionality is well met. A generally well held structural engineering principle may explain the difference observed between the damage curve and the kinetic energy curve in the center of the chart. This principle relates to loss control -- mitigating factors that help to minimize the damage when a loss occurs. Loss control is especially effective in commercial properties where measures such as bracing, flashing, and protection for storage are likely to be employed. Loss control measures tend to be effective at moderate to severe wind speeds (below 150 mph, for instance) and the damage falls below that expected from a theoretical kinetic energy standpoint as the loss control measures mitigate the damage. At catastrophic wind speeds however (above 150 mph), the loss control measures cease to be as effective as the wind forces overcome the capability of the measures to withstand the energy, giving way, and allowing failure to such an extent that the damage appears far more consistent with the theoretical kinetic energy curve. 288 The Florida Commission on Hurricane Loss Projection Methodology Appendices
The next test was an analysis of actual losses to see if the damage calculations had any systematic bias. To do this, 58 Florida locations were randomly chosen and damage from hurricane Andrew from 1992 was adjusted for inflation and compared to the results from a “scenario storm” from the historical storm dataset of USWIND. When this was done, the totals were very close. The actual losses after adjusting for inflation for these locations totaled approximately $100 million and the estimate from USWIND was high by $14 million. Furthermore, of the 58 locations, 28 estimates were below the location damage and 30 were above the location damage. This data is presented graphically in figure 2. Here a 45-degree line is drawn and the distribution pattern of USWIND/actual loss points can be observed. In a system with perfect prediction, all points would lie on the line. In a system with random error, the points will not lie on the line, but there will be equal numbers and an even pattern of points above the line and below.
Hurricane Andrew Damage Comparison USWIND estimates versus actual losses
100,000,000 10,000,000 1,000,000 100,000 10,000 1,000 100 USWIND Estimates 10 1 1 100 10,000 1,000,000 100,000,000
Actual Losses
Figure 2. A comparison of actual versus USWIND modeled damage for 58 actual locations within Florida using hurricane Andrew.
Our conclusions from a damage perspective then is that USWIND properly models the physical properties of forces versus damage and that the system has no systematic bias in its damage estimation logic.
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V. EQECAT USWIND - Validity of the probabilistic storm data set
The main challenge to the evaluation of the probabilistic storm data set is that the data are not available to the user due to their proprietary nature. To alleviate this problem, a special simulation experiment is designed.
We created a uniform portfolio consisting of commercial buildings located 10 miles apart along the coast of the eastern and southeastern United States. They have the same construction type, content and insurance policy. This portfolio is used as input to USWIND, whose probabilistic calculation gives the annual expected and non-exceedance damage at these locations (Figure 3). Because the portfolio is uniform, all of the geographical variability in damage is due to the probabilistic distribution of USWIND’s storm data set, and is independent of the damage calculation. Therefore, a comparison of the damage variability with the geographical distribution of hurricane activity will independently verify whether or not the probabilistic storm data set is consistent with observations.
USWIND Damage Distribution For an evenly distributed uniform portfolio 3.5
3
2.5
2
1.5
1
Damage Percentage Damage 0.5
0 100 350 600 850 1100 1350 1550 1800 2050 2260 2510 2760 Milepost Location (every 10 miles) from Texas to Maine
mean 90th percentile
Figure 3. USWIND estimated annual Damage (%) to the uniform portfolio. There is a building every 10 nautical miles. Solid line: expected; dashed line: 90% non-exceedance.
To compare this simulated damage calculation against historical data, actual storm experience will be reviewed. The two aspects of hurricane activity most relevant to wind damage are hurricane frequency and intensity, shown in Figures 4a and 4b, respectively. Data for these graphs comes from NOAA Technical Report - NWS 38.
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US Landfalling Hurricanes Actual experience 1886-1995 20 18 16 14 12 10 8 6
Number of Hurricanes 4 2 0 130 310 490 670 850 1030 1210 1390 1570 1750 1930 2110 2290 2470 2650 3010 Milepost Location (every 60 miles) from Texas to Maine
Figure 4a. Number of landfalling hurricanes along the eastern US coast (1886-1995). Data from North Atlantic Tropical Cyclone Best Track Data from National Hurricane Center.
US Maximum Sustained 1-minute Wind Speeds Actual experience 1886-1995 100
90
80
70
60
50 Wind Speed (MPH) Speed Wind
40
30 130 310 490 670 850 1030 1210 1390 1570 1750 1930 2110 2290 2470 2650 3010 Milepost Location (every 60 miles) from Texas to Maine
Figure 4b. One-minute sustained maximum wind speed of landfalling along the eastern and southeastern US coast (during the period of 1886-1995.) Data from North Atlantic Tropical Cyclone Best Track Data from National Hurricane Center.
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These two parameters (hurricane frequency and intensity) are combined to form an estimate of wind damage based on the fact that wind damage is proportional to the square of the wind speed and the associated kinetic energy (see section IV.) This estimate is then compared with USWIND calculation (Figure 5a).
Mean Damage Comparison; USWIND vs Historical Estimate For an evenly distributed uniform portfolio 2.5
2
1.5
1
0.5 Damage Percentage Damage
0 100 350 600 850 1100 1350 1550 1800 2050 2260 2510 2760 Milepost Location (every 10 miles) from Texas to Maine
USWIND Historical
Figure 5a. Annual expected wind damage (solid line: USWIND; dashed line: independent estimate based on historical data).
The geographical distribution of their difference is shown in Figure 5b. The two estimates generally agree well along about 70% of the coast line. USWIND estimates, however, demonstrate some noticeable difference from historical data: (1) much larger than expected local variations of damage near miles post 1400 (southern Florida); (2) consistent underestimate at the eastern part of Gulf coast (mile post 100 - 600); (3) overestimate at west Florida and New England coasts.
Detailed analysis and investigation with EQECAT revealed that the cause for the difference is USWIND’s inconsistent handling of user-supplied lat/lon coordinates during portfolio data import. Specifically, USWIND sometimes incorrectly assigns zip code centroid locations to properties rather than using the user-supplied lat/lon coordinates. The problem generally occurs when street address is missing. Because of this problem, USWIND’s probabilistic storm calculation will effectively treat buildings as if they are at the center of the zip code zone in which they are located, unless users manually enter the distance to the coastline. As a result, a building in a larger zip code zone is treated as if it were farther from the coast than one in a smaller zip code zone, and consequently is expected to sustain less wind damage. For example, most of the Gulf coast states have larger zip code zones than New England states do, USWIND estimate tend to be lower in former than in the latter area. The sharp local minimums around mile post 1400 (Figure 5b) are also found to be located in large zip code zones of the Everglades.
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Mean Damage Difference; USWIND vs Historical Estimate For an evenly distributed uniform portfolio
200%
150%
100%
50%
0%
-50% Estimate Diff. (USW-Hist)/Hist Diff. Estimate -100% 100 350 600 850 1100 1350 1550 1800 2050 2260 2510 2760
Milepost Location (every 10 miles) from Texas to Maine
Figure 5b. Comparison of annual expected damage estimates by USWIND and historical data (USWIND estimates versus historical estimates; historical estimates used as the basis.)
EQECAT worked closely with Arkwright after Arkwright identified this problem to determine just how and why the problem was occurring. Based on this work, EQECAT has indicated that they have corrected the problem in version 4.0 of the software. An analysis of this correction is not included in this report, but a preliminary test of the correction performed at EQECAT’s headquarters and reviewed jointly by Arkwright and EQECAT indicates that the correction does indeed fix the problem.
VI. USWIND Summary and Implications for the Insurance Industry
Our simulation experiment confirms that the historical hurricane observations are an appropriate basis for tropical cyclone disaster modeling. These observations are indeed reflected in the USWIND probabilistic data base. Also, the damage calculations are reliable and generally without bias.
As was mentioned in section V, EQECAT has listened to, help document, and correct the one problem encountered in this study. Based on early analysis, version 4.0 will correct the problem and for the time being (until upgrade to 4.0 is done at Arkwright), Arkwright will use an empirical correction for the lat/lon zip code centroid problem.
The implications of this work for the commercial highly protected risk property insurance industry lie as much in the process of completing the work than in the conclusions. Certainly, the discovery of any systematic bias would have been worthy of discovery. Since the natural hazard modeling software is used to make multi-million dollar reinsurance decisions as well as capacity 293 The Florida Commission on Hurricane Loss Projection Methodology Appendices allocation decisions, any error or bias in the software could prove extremely costly. However, based on our work, the software is free of bias and as a result, Arkwright can confidently incorporate USWIND into decisions about capacity or reinsurance.
The day-to-day operational implications for Arkwright that stem from the lessons learned in completing this study are significant. They include the following:
(1) The software combines the expertise of structural engineering, meteorological, mathematical, statistical, and economic scientists with the expertise of finance, accounting, and insurance professionals. Apparently because of the diversity of expertise in these disciplines among their potential customers, vendors of natural disaster modeling packages invest far too little in documentation and as a result, validity assessment and damage calibration are activities that were very difficult and time consuming. Whatever the reasons behind the documentation issue, the insurer must take responsibility for creating a controlled production environment where tests can be completed and analysis can be done. An insurer should also expect to invest significant time in building expertise in using a natural disaster modeling package.
(2) Validating the software is a very worthwhile exercise because it provides a benchmark for new releases of the program. It also has the benefit of fostering a stronger relationship between the designers of the software and the scientists within the insurer’s organization. Doing this requires a significant investment in time, money, and people, but the alternative is to write insurance with less than complete understanding of the risks involved. The insight that is gained by doing such an analysis is enormous. As a result of this work, new understandings and indeed new questions arose concerning the portfolio and the reinsurance program. For Arkwright, performing this study raised as many questions about the unique characteristics of the insurance portfolio (to be addressed through subsequent research) as it settled about the software.
(3) The potential customer set for these packages is relatively small but the functionality is relatively rich. Because of this, it is very likely that a customer will encounter (because of the combinations of the structure, the storm, the policy, and the reinsurance) a situation that has never been seen in software development. In light of this, the insurer must form and maintain a strong relationship with the support organization of the vendor. A validation exercise, by its design is likely to manifest this situation. While the experience can be trying and even frustrating for both parties, the long term result is well worth the effort as the insurer gains a greater understanding of the peril and the software and the vendor gains a better understanding of the client.
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References
Bengtsson-L., Botzet-M. and Esch-M., Hurricane-type vortices in a general circulation model, Tellus, vol. 47A, no. 2, pp.175-196, Feb. 1995.
Giorgi-F., Rosaria-M. and Visconti-G., Use of a limited-area model nested in a general circulation model for regional climate simulation over Europe, Journal of Geophysical Research, vol. 95, no. D11, pp. 18413-31, 20 Oct. 1990.
Hewitson-B. and Crane-R-G., Regional climates in the GISS global circulation model: synoptic- scale circulation, Journal of Climate, vol. 5, no. 9, pp. 1002-11, Sept. 1992.
Ho-F., Su-J., Hanevich-K., Smith-R. and Richards-F., Hurricane climatology for the Atlantic and Gulf Coast of The United States, NOAA Technical Report NWS 38, April, 1987.
Landsea-C-W., A climatology of intense (or major) Atlantic hurricanes, Monthly Weather Review, vol. 121, no. 6, pp. 1703-13, June 1993.
Nuemann, C., The National Hurricane Center risk analysis program, NOAA Technical Memo NWS NHC 38, November, 1987.
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