Tropical Cyclone Intensity
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Wind Speed-Damage Correlation in Hurricane Katrina
JP 1.36 WIND SPEED-DAMAGE CORRELATION IN HURRICANE KATRINA Timothy P. Marshall* Haag Engineering Co. Dallas, Texas 1. INTRODUCTION According to Knabb et al. (2006), Hurricane Katrina Mehta et al. (1983) and Kareem (1984) utilized the was the costliest hurricane disaster in the United States to concept of wind speed-damage correlation after date. The hurricane caused widespread devastation from Hurricanes Frederic and Alicia, respectively. In essence, Florida to Louisiana to Mississippi making a total of three each building acts like an anemometer that records the landfalls before dissipating over the Ohio River Valley. wind speed. A range of failure wind speeds can be The storm damaged or destroyed many properties, determined by analyzing building damage whereas especially near the coasts. undamaged buildings can provide upper bounds to the Since the hurricane, various agencies have conducted wind speeds. In 2006, WSEC developed a wind speed- building damage assessments to estimate the wind fields damage scale entitled the EF-scale, named after the late that occurred during the storm. The National Oceanic Dr. Ted Fujita. The author served on this committee. and Atmospheric Administration (NOAA, 2005a) Wind speed-damage correlation is useful especially conducted aerial and ground surveys and published a when few ground-based wind speed measurements are wind speed map. Likewise, the Federal Emergency available. Such was the case in Hurricane Katrina when Management Agency (FEMA, 2006) conducted a similar most of the automated stations failed before the eye study and produced another wind speed map. Both reached the coast. However, mobile towers were studies used a combination of wind speed-damage deployed by Texas Tech University (TTU) at Slidell, LA correlation, actual wind measurements, as well as and Bay St. -
Homeowners Handbook to Prepare for Natural Disasters
HOMEOWNERS HANDBOOK HANDBOOK HOMEOWNERS DELAWARE HOMEOWNERS TO PREPARE FOR FOR TO PREPARE HANDBOOK TO PREPARE FOR NATURAL HAZARDSNATURAL NATURAL HAZARDS TORNADOES COASTAL STORMS SECOND EDITION SECOND Delaware Sea Grant Delaware FLOODS 50% FPO 15-0319-579-5k ACKNOWLEDGMENTS This handbook was developed as a cooperative project among the Delaware Emergency Management Agency (DEMA), the Delaware Department of Natural Resources and Environmental Control (DNREC) and the Delaware Sea Grant College Program (DESG). A key priority of this project partnership is to increase the resiliency of coastal communities to natural hazards. One major component of strong communities is enhancing individual resilience and recognizing that adjustments to day-to- day living are necessary. This book is designed to promote individual resilience, thereby creating a fortified community. The second edition of the handbook would not have been possible without the support of the following individuals who lent their valuable input and review: Mike Powell, Jennifer Pongratz, Ashley Norton, David Warga, Jesse Hayden (DNREC); Damaris Slawik (DEMA); Darrin Gordon, Austin Calaman (Lewes Board of Public Works); John Apple (Town of Bethany Beach Code Enforcement); Henry Baynum, Robin Davis (City of Lewes Building Department); John Callahan, Tina Callahan, Kevin Brinson (University of Delaware); David Christopher (Delaware Sea Grant); Kevin McLaughlin (KMD Design Inc.); Mark Jolly-Van Bodegraven, Pam Donnelly and Tammy Beeson (DESG Environmental Public Education Office). Original content from the first edition of the handbook was drafted with assistance from: Mike Powell, Greg Williams, Kim McKenna, Jennifer Wheatley, Tony Pratt, Jennifer de Mooy and Morgan Ellis (DNREC); Ed Strouse, Dave Carlson, and Don Knox (DEMA); Joe Thomas (Sussex County Emergency Operations Center); Colin Faulkner (Kent County Department of Public Safety); Dave Carpenter, Jr. -
A Study of Synoptic-Scale Tornado Regimes
Garner, J. M., 2013: A study of synoptic-scale tornado regimes. Electronic J. Severe Storms Meteor., 8 (3), 1–25. A Study of Synoptic-Scale Tornado Regimes JONATHAN M. GARNER NOAA/NWS/Storm Prediction Center, Norman, OK (Submitted 21 November 2012; in final form 06 August 2013) ABSTRACT The significant tornado parameter (STP) has been used by severe-thunderstorm forecasters since 2003 to identify environments favoring development of strong to violent tornadoes. The STP and its individual components of mixed-layer (ML) CAPE, 0–6-km bulk wind difference (BWD), 0–1-km storm-relative helicity (SRH), and ML lifted condensation level (LCL) have been calculated here using archived surface objective analysis data, and then examined during the period 2003−2010 over the central and eastern United States. These components then were compared and contrasted in order to distinguish between environmental characteristics analyzed for three different synoptic-cyclone regimes that produced significantly tornadic supercells: cold fronts, warm fronts, and drylines. Results show that MLCAPE contributes strongly to the dryline significant-tornado environment, while it was less pronounced in cold- frontal significant-tornado regimes. The 0–6-km BWD was found to contribute equally to all three significant tornado regimes, while 0–1-km SRH more strongly contributed to the cold-frontal significant- tornado environment than for the warm-frontal and dryline regimes. –––––––––––––––––––––––– 1. Background and motivation As detailed in Hobbs et al. (1996), synoptic- scale cyclones that foster tornado development Parameter-based and pattern-recognition evolve with time as they emerge over the central forecast techniques have been essential and eastern contiguous United States (hereafter, components of anticipating tornadoes in the CONUS). -
Hurricanes Katrina and Rita – Louisiana's Response And
HURRICANES KATRINA AND RITA – LOUISIANA’S RESPONSE AND RECOVERY Ray A. Mumphrey, P.E., Louisiana Department of Transportation and Development, Baton Rouge, Louisiana, and Hossein Ghara, P.E., MBA, Louisiana Department of Transportation and Development, Baton Rouge, Louisiana KEYWORDS: Louisiana Department of Transportation and Development, National Oceanic and Atmospheric Administration, Federal Emergency Management Agency, Contra flow, Inundation, Fixed and Movable Bridges, Open Water Bridges, Coastal Protection and Restoration Authority ABSTRACT: Louisiana’s transportation and hurricane protection system took a tremendous blow from two major hurricanes that struck the coast of Louisiana in 2005, hurricanes Katrina and Rita. This presentation will introduce the audience to the transportation infrastructure damage Louisiana experienced as a result of these two storms and will describe how Louisiana is responding to the disasters and our road to recovery. Figure 1 - Hurricanes that hit the coast of Louisiana since 1900 As Louisiana residents, we become accustom to the ever present threat of hurricanes. Refer to figure 1. Much like other parts of the country, which have other natural disasters such as tornados, mud slides, avalanches or earthquakes, we just prepare for the worst, minimize loss of life and property, and thank God when it’s all over. As engineers we know we can always rebuild structures, and possibly restore livelihoods, but loss of life is not replaceable. 2005 STORMS Hurricane Katrina was a category 4 storm when it made landfall on August 29, 2005, along the Louisiana – Mississippi Gulf Coast. The storm was fast moving and provided minimum time for preparation. Refer to figure 2. “Hurricane Katrina was the most destructive hurricane to ever strike the U.S.” NOAA Just as we were getting back on our feet from the impacts of Hurricane Katrina, BAM! We were faced with another storm, Rita. -
Historic Greensburg Supercell of 4 May 2007 Anatomy of a Severe Local ‘Superstorm’
Historic Greensburg Supercell of 4 May 2007 Anatomy of a Severe Local ‘Superstorm’ Mike Umscheid National Weather Service Forecast Office – Dodge City, KS In collaboration with Leslie R. Lemon University of Oklahoma/CIMMS, NOAA/NWS Warning Decision Training Branch, Norman, OK DuPage County, IL Advanced Severe Weather Seminar March 5-6, 2010 1 © Martin Kucera A Thunderstorm Spectrum Single Cell Multi-cell Multi-cell Supercell (cluster) (line) Short-lived, Longer-lived (2-4hrs), non-tornadic supercells one or two tornadic cycles Courtesy NWS Norman Severe Local “Superstorm” 6+ hrs, 2-3 significant tornadoes (or one ultra long-lived sig tor), Many other smaller ones. Widespread destruction. 9 April 1947 Woodward, OK 2 Woodward – Udall – Greensburg Udall Woodward 10:35 pm 8:42 pm ~ ¾ to 1 mile wide 82 fatalities 1.8 miles wide 107 fatalities Photos courtesy NWS ICT, NW OK Genealogical Society, Mike Theiss Times CST 11 fatalities 1.7 miles wide 8:50 pm Greensburg 3 Integrated Warning System 4 A little preview… EF5 EF3 (+) 0237 0331 EF3 (+) EF3 0347 0437 1 supercell thunderstorm – 20 tornadoes, 4 massive tornadoes spanning 5 3 hours w/ no break, farm community obliterated, very well-documented by chasers “The Big 4” Rating: EF3 (strong) Duration: 65 min. Length: 23.5 mi Mean Width: 1.5 mi St. John Max Width: 2.2 mi Macksville Damage Area: 35.4 mi2 (A5) Rating: EF3 Damage $$: 1.5 M Duration: 24 min. Length: 17.4 mi Mean Width: 0.6 mi Max Width: 0.9 mi Trousdale Damage Area: 9.7 mi2 (A4) Hopewell Fatalities: 1 Rating: EF5 Duration: 65 min. -
Tropical Cyclone Report for Hurricane Ivan
Tropical Cyclone Report Hurricane Ivan 2-24 September 2004 Stacy R. Stewart National Hurricane Center 16 December 2004 Updated 27 May 2005 to revise damage estimate Updated 11 August 2011 to revise damage estimate Ivan was a classical, long-lived Cape Verde hurricane that reached Category 5 strength three times on the Saffir-Simpson Hurricane Scale (SSHS). It was also the strongest hurricane on record that far south east of the Lesser Antilles. Ivan caused considerable damage and loss of life as it passed through the Caribbean Sea. a. Synoptic History Ivan developed from a large tropical wave that moved off the west coast of Africa on 31 August. Although the wave was accompanied by a surface pressure system and an impressive upper-level outflow pattern, associated convection was limited and not well organized. However, by early on 1 September, convective banding began to develop around the low-level center and Dvorak satellite classifications were initiated later that day. Favorable upper-level outflow and low shear environment was conducive for the formation of vigorous deep convection to develop and persist near the center, and it is estimated that a tropical depression formed around 1800 UTC 2 September. Figure 1 depicts the “best track” of the tropical cyclone’s path. The wind and pressure histories are shown in Figs. 2a and 3a, respectively. Table 1 is a listing of the best track positions and intensities. Despite a relatively low latitude (9.7o N), development continued and it is estimated that the cyclone became Tropical Storm Ivan just 12 h later at 0600 UTC 3 September. -
Hurricane Andrew and Insurance: the Enduring Impact of An
HURRICANE ANDREW AND INSURANCE: THE ENDURING IMPACT OF AN HISTORIC STORM AUGUST 2012 Lynne McChristian Florida Representative, Insurance Information Institute (813) 480-6446 [email protected] Florida Office: Insurance Information Institute, 4775 E. Fowler Avenue, Tampa, FL 33617 INTRODUCTION Hurricane Andrew hit Florida on August 24, 1992, and the tumult for the property insurance market there has not ceased in the 20 years since. Andrew was the costliest natural disaster in U.S. history in terms of insurance payouts to people whose homes, vehicles and businesses were damaged by the storm when it struck Florida and Louisiana in 1992. The insurance claims payout totaled $15.5 billion at the time ($25 billion in 2011 dollars). Even today, the storm is the second costliest natural disaster; Hurricane Katrina, which hit in 2005, is the most costly natural disaster. But the cost is only part of Andrew’s legacy. It also revealed that Florida’s vulnerability to hurricanes had been seriously underestimated. That reality was not lost on other coastal states nor on the insurance industry, which reassessed their exposure to catastrophic storm damage in the aftermath of Andrew. The event brought a harsh awakening and forced individuals, insurers, legislators, insurance regulators and state governments to come to grips with the necessity of preparing both financially and physically for unprecedented natural disasters. Many of the insurance market changes that have occurred nationally over the last two decades can be traced to the wakeup call delivered by Hurricane Andrew. These include: . More carefully managed coastal exposure. Larger role of government in insuring coastal risks. -
A Rapid Forecasting and Mapping System of Storm Surge and Coastal Flooding
AUGUST 2020 Y A N G E T A L . 1663 A Rapid Forecasting and Mapping System of Storm Surge and Coastal Flooding KUN YANG,VLADIMIR A. PARAMYGIN, AND Y. PETER SHENG Department of Civil and Coastal Engineering, University of Florida, Gainesville, Florida (Manuscript received 16 July 2019, in final form 2 March 2020) ABSTRACT A prototype of an efficient and accurate rapid forecasting and mapping system (RFMS) of storm surge is presented. Given a storm advisory from the National Hurricane Center, the RFMS can generate a coastal inundation map on a high-resolution grid in 1 min (reference system Intel Core i7–3770K). The foundation of the RFMS is a storm surge database consisting of high-resolution simulations of 490 optimal storms generated by a robust storm surge modeling system, Curvilinear-Grid Hydrodynamics in 3D (CH3D-SSMS). The RFMS uses an efficient quick kriging interpolation scheme to interpolate the surge response from the storm surge database, which considers tens of thousands of combinations of five landfall parameters of storms: central pressure deficit, radius to maximum wind, forward speed, heading direction, and landfall location. The RFMS is applied to southwest Florida using data from Hurricane Charley in 2004 and Hurricane Irma in 2017, and to the Florida Panhandle using data from Hurricane Michael in 2018 and validated with observed high water mark data. The RFMS results agree well with observation and direct simulation of the high-resolution CH3D- SSMS. The RFMS can be used for real-time forecasting during a hurricane or ‘‘what-if’’ scenarios for miti- gation planning and preparedness training, or to produce a probabilistic flood map. -
Hurricane and Tropical Storm
State of New Jersey 2014 Hazard Mitigation Plan Section 5. Risk Assessment 5.8 Hurricane and Tropical Storm 2014 Plan Update Changes The 2014 Plan Update includes tropical storms, hurricanes and storm surge in this hazard profile. In the 2011 HMP, storm surge was included in the flood hazard. The hazard profile has been significantly enhanced to include a detailed hazard description, location, extent, previous occurrences, probability of future occurrence, severity, warning time and secondary impacts. New and updated data and figures from ONJSC are incorporated. New and updated figures from other federal and state agencies are incorporated. Potential change in climate and its impacts on the flood hazard are discussed. The vulnerability assessment now directly follows the hazard profile. An exposure analysis of the population, general building stock, State-owned and leased buildings, critical facilities and infrastructure was conducted using best available SLOSH and storm surge data. Environmental impacts is a new subsection. 5.8.1 Profile Hazard Description A tropical cyclone is a rotating, organized system of clouds and thunderstorms that originates over tropical or sub-tropical waters and has a closed low-level circulation. Tropical depressions, tropical storms, and hurricanes are all considered tropical cyclones. These storms rotate counterclockwise in the northern hemisphere around the center and are accompanied by heavy rain and strong winds (National Oceanic and Atmospheric Administration [NOAA] 2013a). Almost all tropical storms and hurricanes in the Atlantic basin (which includes the Gulf of Mexico and Caribbean Sea) form between June 1 and November 30 (hurricane season). August and September are peak months for hurricane development. -
Investigation and Prediction of Hurricane Eyewall
INVESTIGATION AND PREDICTION OF HURRICANE EYEWALL REPLACEMENT CYCLES By Matthew Sitkowski A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Atmospheric and Oceanic Sciences) at the UNIVERSITY OF WISCONSIN-MADISON 2012 Date of final oral examination: 4/9/12 The dissertation is approved by the following members of the Final Oral Committee: James P. Kossin, Affiliate Professor, Atmospheric and Oceanic Sciences Daniel J. Vimont, Professor, Atmospheric and Oceanic Sciences Steven A. Ackerman, Professor, Atmospheric and Oceanic Sciences Jonathan E. Martin, Professor, Atmospheric and Oceanic Sciences Gregory J. Tripoli, Professor, Atmospheric and Oceanic Sciences i Abstract Flight-level aircraft data and microwave imagery are analyzed to investigate hurricane secondary eyewall formation and eyewall replacement cycles (ERCs). This work is motivated to provide forecasters with new guidance for predicting and better understanding the impacts of ERCs. A Bayesian probabilistic model that determines the likelihood of secondary eyewall formation and a subsequent ERC is developed. The model is based on environmental and geostationary satellite features. A climatology of secondary eyewall formation is developed; a 13% chance of secondary eyewall formation exists when a hurricane is located over water, and is also utilized by the model. The model has been installed at the National Hurricane Center and has skill in forecasting secondary eyewall formation out to 48 h. Aircraft reconnaissance data from 24 ERCs are examined to develop a climatology of flight-level structure and intensity changes associated with ERCs. Three phases are identified based on the behavior of the maximum intensity of the hurricane: intensification, weakening and reintensification. -
10R.3 the Tornado Outbreak Across the North Florida Panhandle in Association with Hurricane Ivan
10R.3 The Tornado Outbreak across the North Florida Panhandle in association with Hurricane Ivan Andrew I. Watson* Michael A. Jamski T.J. Turnage NOAA/National Weather Service Tallahassee, Florida Joshua R.Bowen Meteorology Department Florida State University Tallahassee, Florida Jason C. Kelley WJHG-TV Panama City, Florida 1. INTRODUCTION their mobile homes were destroyed near Blountstown, Florida. Hurricane Ivan made landfall early on the morning of 16 September 2004, just west of Overall, there were 24 tornadoes reported Gulf Shores, Alabama as a category 3 across the National Weather Service (NWS) hurricane on the Saffir-Simpson Hurricane Tallahassee forecast area. The office issued Scale. Approximately 117 tornadoes were 130 tornado warnings from the afternoon of 15 reported associated with Ivan across the September until just after daybreak on 16 southeast United States. Eight people were September. killed and 17 were injured by tornadoes (Storm Data 2004; Stewart 2004). The most The paper examines the convective cells significant tornadoes occurred as hurricane within the rain bands of hurricane Ivan, which Ivan approached the Florida Gulf coast on the produced these tornadoes across the Florida afternoon and evening of 15 September. Panhandle, Big Bend, and southwest Georgia. The structure of the tornadic and non-tornadic The intense outer rain bands of Ivan supercells is examined for clues on how to produced numerous supercells over portions better warn for these types of storms. This of the Florida Panhandle, Big Bend, southwest study will focus on the short-term predictability Georgia, and Gulf coastal waters. In turn, of these dangerous storms, and will these supercells spawned dozens of investigate the problem of how to reduce the tornadoes. -
The Critical Role of Cloud–Infrared Radiation Feedback in Tropical Cyclone Development
The critical role of cloud–infrared radiation feedback in tropical cyclone development James H. Ruppert Jra,b,1, Allison A. Wingc, Xiaodong Tangd, and Erika L. Durane aDepartment of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA 16802; bCenter for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, PA 16802; cDepartment of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL 32306; dKey Laboratory of Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China; and eEarth System Science Center, University of Alabama in Huntsville/NASA Short-term Prediction Research and Transition (SPoRT) Center, Huntsville, AL 35805 Edited by Kerry A. Emanuel, Massachusetts Institute of Technology, Cambridge, MA, and approved September 21, 2020 (received for review June 29, 2020) The tall clouds that comprise tropical storms, hurricanes, and within an incipient storm locally increase the atmospheric trapping typhoons—or more generally, tropical cyclones (TCs)—are highly of infrared radiation, in turn locally warming the lower–middle effective at trapping the infrared radiation welling up from the sur- troposphere relative to the storm’s surroundings (35–39). This face. This cloud–infrared radiation feedback, referred to as the mechanism is a positive feedback to the incipient storm, as it “cloud greenhouse effect,” locally warms the lower–middle tropo- promotes its thermally direct transverse circulation (38, 39) sphere relative to a TC’s surroundings through all stages of its life (Fig. 1A). Herein, we examine the role of this feedback in the cycle. Here, we show that this effect is essential to promoting and context of TC development in nature.