The AIR Severe Thunderstorm Model for the United States

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1 The AIR Severe Thunderstorm Model for the United States In 2011, six severe thunderstorms generated insured losses of over USD 1 billion each. Total losses from 24 separate outbreaks that year exceeded USD 26 billion. With the potential for insured losses on both an occurrence and aggregate basis this high, companies need the best tools available to assess and mitigate U.S. severe thunderstorm risk.

2 The AIR Severe Thunderstorm Model for the United States estimates the frequency, severity, and geographical distribution of potential losses from straight-line winds, hail, and tornadoes. The model incorporates the latest scientific research into the highly localized effects of these complex perils as well as independent research, post-disaster surveys, and more than USD 40 billion in claims data. While severe thunderstorm is a relatively highfrequency peril, aggregate losses can result in extreme volatility in financial results, making it crucial for companies to have a robust and highly granular view of the risk. [The new model will] allow users to make better decisions about their exposure over a range of time horizons. AIR researchers have a very good understanding of the state of the scientific understanding and the uncertainties of the community s knowledge about severe thunderstorm hazards, and have utilized that knowledge in the model. AIR Worldwide has developed a comprehensive Severe Thunderstorm Model for the United States... The damage functions are based on the scientific relationship between building damage and wind speed/hail impact energy. The model includes both the vertical fall speed [of hail] as well as the horizontal component of wind speed to calculate impact energy. This is especially useful when estimating the amount of damage to building exteriors such as siding and windows. - Timothy Marshall, PE Haag Engineering An Innovative Way to Model Storm Occurrence The AIR U.S. severe thunderstorm model utilizes a large 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 set reflects reporting biases, which include both historical underreporting and population biases (i.e., non-reporting of localized events, which can go unnoticed in sparsely populated areas). To compensate for reporting bias in the historical data, AIR smart-smoothed the SPC reports to physically realistic locations, including areas that may not have experienced major activity in the brief historical record. Smart-smoothing uses statistical and physical methods that leverage high-resolution meteorological parameters to determine when and where conditions were favorable for severe thunderstorm formation. This technique results in a spatially complete catalog of simulated events, which gives companies a more accurate view of their severe thunderstorm risk. -Dr. Harold Brooks National Severe Storms Laboratory 2

3 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. These three maps show the model s annual spatial distributions for all tornado, straight-line wind, and hail hits, respectively. The key specifies how many occurrences there are per year in a particular location. Accounting for Highly Localized Effects Supercell thunderstorms can last for several days and affect multiple states, but the individual tornadoes, hailstorms, and straight-line winds (the sub-perils ) that make up an outbreak may last for just minutes and affect highly localized areas. To capture the localized effects, AIR developed highresolution damage footprints specific to each sub-peril, based on SPC and radar data. Sub-Peril Specific Damage Functions Reflect Unique Damage Mechanisms Because tornadoes, hailstorms, and straight-line 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 and tornadoes, damageability is modeled as a function of the 3-second gust wind speed. Hail damage is a function of hail impact energy, which takes into account storm duration, the density of individual hailstones and their size, the number of hailstones by diameter per cubic meter, and the accompanying wind speed. 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

4 1.0 Mean Damage Ratio 0 Hail Tornado Straight-line Wind Intensity (3-sec gust for tornado and wind, energy for hail) Sample damage functions for a single-family home 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 vulnerability across regions and time. The vulnerability 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 States, changes in building materials and construction practices, structural aging and mitigation features, as well as other factors that affect vulnerability. 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 structural engineering analyses and building damage observations Weighted average damage functions for buildings with unknown risk characteristics that leverage AIR s industry exposure database Damage functions for complex industrial facilities for each sub-peril Sample regional wind vulnerability map for engineered buildings with unknown year-built. 4

5 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, In this image, vegetation is red, water is dark blue, roads and buildings are gray and white, respectively, and bare fields are tan. 5

6 Comprehensive Approach to Model Validation To ensure the most robust model possible, the AIR severe thunderstorm model is carefully validated against actual loss experience. However, validation is not merely limited to final model results. For example, the annual frequency of individual tornado, hail, and straight-line wind events is validated against published studies, and seasonality is validated against SPC data. The efficacy of the model s damage functions was validated through the analysis of billions of dollars of detailed insurance company claims data and damage surveys conducted in the aftermath of severe thunderstorms, including those conducted by AIR researchers in 2008, 2011, and Modeled losses are extensively validated against loss estimates issued by PCS and actual claims data provided by clients. In the figure, sample model losses from five realizations of the model s seven marquee events are compared to trended PCS losses. 10 Insured Loss (USD Billions) PCS Total Loss Model Loss Spread 0 May-2010 PCS 13 [incl. OK tornado] May-2010 PCS 14 [incl. OK hail] Jun-2010 PCS 18 [incl. CO, NM, IL hail] Oct-2010 PCS 31 [AZ hail] Apr-2011 PCS 46 [incl. Tuscaloosa tornado] May-2011 PCS 48 [incl. Joplin tornado] Jun-2012 PCS 83 [North America derecho] Comparison of modeled and trended PCS losses for select marquee events. AIR has developed 5 realizations of each of these events that define the ranges shown by the blue bars. The variation in modeled losses for the model s seven marquee events is generally highest for those events that have greater uncertainty in model parameters, such as for hail events. For events such as tornadoes, however, for which detailed information is available, the uncertainty of event parameters is lower, resulting in a narrower band for modeled losses. 6

7 Model at a Glance Modeled Perils Model Domain Stochastic Catalogs Supported Construction and Occupancy Classes Industry Exposure Database Straight-line winds, hail, and tornadoes Continental United States 10,000-, 50,000-, and 100,000-year all-events catalogs; 10,000-year cat-only catalog 40 construction classes and 110 occupancy classes Complex industrial facilities 90-meter resolution Detailed representation of commercial and industrial building stock Model Highlights Integrates statistical modeling with the latest meteorological research Captures the highly localized effects of straight-line winds, hail, and tornadoes Daily simulation captures the impact of both large and small loss-causing events Sub-peril specific damage functions based on the latest scientific research, post-disaster damage surveys including those conducted by AIR in 2008, 2011, and 2013 and USD 3 billion in insurance company claims and nearly USD 40 billion in claims from AIR sister company, Xactware Accounts for regional and temporal variations in wind vulnerability Supports 27 individual building characteristics for straight-line winds and tornadoes and 10 individual building characteristics for hail that were developed based on structural engineering analyses and building damage observations Features sub-peril specific damage functions for complex industrial facilities Each component extensively validated against hazard, damage, and loss data from historical events Peer reviewed by leading experts Timothy Marshall, PE, of Haag Engineering, and Dr. Harold Brooks of the National Severe Storms Laboratory 7

8 ABOUT AIR WORLDWIDE AIR Worldwide (AIR) provides risk modeling solutions that make individuals, businesses, and society more resilient to extreme events. In 1987, AIR Worldwide founded the catastrophe modeling industry and today models the risk from natural catastrophes, terrorism, pandemics, casualty catastrophes, and cyber attacks, globally. Insurance, reinsurance, financial, corporate, and government clients rely on AIR s advanced science, software, and consulting services for catastrophe risk management, insurance-linked securities, site-specific engineering analyses, and agricultural risk management. AIR Worldwide, a Verisk (Nasdaq:VRSK) business, is headquartered in Boston with additional offices in North America, Europe, and Asia. For more information, please visit AIR Worldwide A Verisk Business