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The Air Severe Thunderstorm Model for the United States In 2011, six severe thunderstorms The AIR Severe generated insured losses of over USD 1 billion each. Total losses from Thunderstorm 24 separate outbreaks that year exceeded USD 26 billion. With the potential for insured losses on both an Model for the occurrence and aggregate basis this high, companies need the best tools available to assess and mitigate U.S. United States severe thunderstorm risk. THE AIR SEVERE THUNDERSTORM MODEL FOR THE UNITED STATES The AIR Severe Thunderstorm Model AIR Worldwide has developed for the United States estimates the a comprehensive Severe frequency, severity, and geographical Thunderstorm Model for the United States... The damage distribution of potential losses from functions are based on the straight-line winds, hail, and tornadoes. scientific relationship between building damage and wind The model incorporates the latest speed/hail impact energy. The scientific research into the highly model includes both the vertical fall speed [of hail] as well as the localized effects of these complex horizontal component of wind perils as well as independent research, speed to calculate impact energy. This is especially useful when post-disaster surveys, and more than estimating the amount of damage USD 40 billion in claims data. While to building exteriors such as siding and windows. severe thunderstorm is a relatively high- - Timothy Marshall, PE frequency peril, aggregate losses can Haag Engineering result in extreme volatility in financial results, making it crucial for companies to have a robust and highly granular An Innovative Way to Model Storm Occurrence The AIR U.S. severe thunderstorm model utilizes a large view of the risk. historical data set from NOAA’s Storm Prediction Center (SPC), comprising storm reports from local authorities and trained weather spotters. Despite abundant data, however, [The new model will] allow the set reflects reporting biases, which include both historical users to make better underreporting and population biases (i.e., non-reporting of decisions about their localized events, which can go unnoticed in sparsely populated exposure over a range areas). of time horizons. AIR researchers have a very To compensate for reporting bias in the historical data, AIR good understanding of “smart-smoothed” the SPC reports to physically realistic the state of the scientific locations, including areas that may not have experienced major understanding and the activity in the brief historical record. Smart-smoothing uses uncertainties of the statistical and physical methods that leverage high-resolution community’s knowledge meteorological parameters to determine when and where about severe thunderstorm conditions were favorable for severe thunderstorm formation. hazards, and have utilized This technique results in a spatially complete catalog of that knowledge in the simulated events, which gives companies a more accurate view model. of their severe thunderstorm risk. -Dr. Harold Brooks National Severe Storms Laboratory 2 THE AIR SEVERE THUNDERSTORM MODEL FOR THE UNITED STATES advanced clustering algorithms. AIR’s event footprints, whose realistic size and shape are based on historical observation rather than on an artificially imposed grid size, are the key to the model’s ability to generate robust tails of the exceedance probability curve. Daily Simulation Captures Large and Small Loss-Causing Events The AIR model simulates daily severe thunderstorm activity based on realistic historical occurrence rates and local and seasonal weather patterns. The daily simulation enables the model to capture the large outbreaks that produce insured losses in excess of USD 25 million—the ISO’s Property Claim Services® (PCS®) threshold for issuing a catastrophe serial number—and smaller events that may last only one day. The smaller events produce lower losses, but could still impact a company’s portfolio on an aggregate basis or a more rural portfolio on an occurrence basis. AIR offers 10,000-year, 50,000-year, and 100,000-year stochastic catalogs. The availability of more simulated events, particularly in the 50,000-year and 100,000-year catalogs, along with smart-smoothing, allows for a more granular view of the risk, making the model ideal for use in ratemaking and underwriting. In addition, the model has a 10,000-year “cat-only” catalog, containing only events that exceed USD 25 million in industry insured loss. Sub-Peril–Specific Damage Functions Reflect Unique Damage Mechanisms These three maps show the model’s annual spatial distributions for all tornado, straight-line wind, and hail “hits,” respectively. The key specifies Because tornadoes, hailstorms, and straight-line how many occurrences there are per year in a particular location. windstorms inflict damage differently, the model’s damage functions are sub-peril–specific to provide the most accurate estimates of loss. For both straight-line winds Accounting for Highly Localized Effects and tornadoes, damageability is modeled as a function of Supercell thunderstorms can last for several days and affect the 3-second gust wind speed. Hail damage is a function multiple states, but the individual tornadoes, hailstorms, of hail impact energy, which takes into account storm and straight-line winds (the “sub-perils”) that make up an duration, the density of individual hailstones and their outbreak may last for just minutes and affect highly localized size, the number of hailstones by diameter per cubic areas. To capture the localized effects, AIR developed high- meter, and the accompanying wind speed. resolution damage footprints specific to each sub-peril, based on SPC and radar data. Because the SPC does not provide footprint dimensions for hail and straight-line wind, the model groups events that are close in space and time into clusters using radar data and 3 THE AIR SEVERE THUNDERSTORM MODEL FOR THE UNITED STATES States, changes in building materials and construction 1.0 Hail practices, structural aging and mitigation features, as well as Tornado other factors that affect vulnerability. Straight-line Wind Other highlights of the AIR model’s vulnerability module include: – Support for 27 individual building characteristics for straight-line winds and tornadoes and 10 individual building characteristics for hail developed based on Mean Damage Ratio structural engineering analyses and building damage observations – Weighted average damage functions for buildings with 0 unknown risk characteristics that leverage AIR’s industry Intensity (3-sec gust for tornado and wind, energy for hail) exposure database Sample damage functions for a single-family home – Damage functions for complex industrial facilities for each sub-peril The model’s damage functions are based on engineering studies, lessons learned from damage surveys, as well as extensive claims data analysis, including USD 3 billion in insurance company claims and nearly USD 40 billion in claims from AIR sister company, Xactware®. Detailed analyses of these claims data also reveal that the uncertainty around the mean damage is also sub-peril– specific, a feature captured in the model. Touchstone® allows companies to analyze results for each sub-peril individually as well as for all three sub-perils combined, thereby giving further insight into a highly complex risk. Reflecting Regional and Temporal Variations in Vulnerability AIR damage functions reflect a detailed and profound understanding of the evolution of building vulnerability in the United States and take into account the specific year of construction to allow for better differentiation of Sample regional wind vulnerability map for engineered buildings with vulnerability across regions and time. The vulnerability unknown year-built. module for the AIR Severe Thunderstorm Model for the United States is informed by findings from AIR’s multi-year, peer-reviewed study of the adoption and enforcement of building codes throughout the United 4 THE AIR SEVERE THUNDERSTORM MODEL FOR THE UNITED STATES 2013 MOORE TORNADO AIR SURVEY AIR scientists and engineers have developed tornado wind profiles from which to calculate the wind speed at a particular location. These profiles depend on the tornado’s size and maximum wind speed based on the Enhanced Fujita (EF) scale. The wind speed profiles are based on detailed claims data analyses, a study done in collaboration with Texas Tech University, and AIR’s own damage surveys, including one conducted after the 2013 Moore, Oklahoma, EF-5 tornado during which Photos A through D were taken by AIR’s scientists and engineers. In general, the damage is most severe on the center line of the tornado footprint (Photo A), and decreases toward the outer edge of the footprint (Photos B through D). (A) (B) (C) (D) NASA photo of the damage swath left in the wake of the EF-5 tornado that struck Moore, Oklahoma, and adjacent areas on the afternoon of May 20, 2013. In this image, vegetation is red, water is dark blue, roads and buildings are gray and white, respectively, and bare fields are tan. 5 THE AIR SEVERE THUNDERSTORM MODEL FOR THE UNITED STATES Comprehensive Approach to Model billions of dollars of detailed insurance company claims Validation data and damage surveys conducted in the aftermath of To ensure the most robust model possible, the AIR severe severe thunderstorms, including those conducted by AIR thunderstorm model is carefully validated against actual researchers in 2008, 2011, and 2013. loss experience. However, validation is not merely limited to final model results. For example, the annual frequency Modeled losses are extensively validated against loss of individual tornado, hail, and straight-line wind events estimates issued by PCS and actual claims data provided is validated against published studies, and seasonality is by clients. In the figure, sample model losses from five validated against SPC data. The efficacy of the model’s realizations of the model’s seven marquee events are damage functions was validated through the analysis of compared to trended PCS losses. 10 PCS Total Loss 8 Model Loss Spread 6 4 2 Insured Loss (USD Billions) 0 May-2010 May-2010 Jun-2010 Oct-2010 Apr-2011 May-2011 Jun-2012 PCS 13 PCS 14 PCS 18 PCS 31 PCS 46 PCS 48 PCS 83 [incl.
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