AIR Extratropical Cyclone Model for Europe

Transcription

1 AIR Extratropical Cyclone Model for Europe In 2007, Kyrill roared across Europe, causing widespread damage that resulted in insured losses of more than EUR 4 billion. In 1990, a cluster of storms culminated in Daria, a large, intense storm that would cost the industry close to EUR 12 billion today. The AIR Extratropical Cyclone Model for Europe allows companies to assess their risk from winter storms in all their manifestations, including the most extreme events.

2 AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE Unlike the relatively symmetrical structure exhibited by tropical cyclones, extratropical cyclone systems are markedly more complex. From the unstable atmospheric environments in which they form, to the sophisticated processes needed to translate winds aloft to high resolution surface-level winds, to the observed clustering of storms in time and space AIR s Extratropical Cyclone Model for Europe captures the complexities that define the hazard. The model s damage functions leverage findings from AIR s detailed post-disaster surveys, comprehensive engineering studies, and the analyses of billions of euros of claims data. With expected annual losses from European extratropical cyclones second only to hurricanes in the United States, companies need a realistic, Only NWP Captures Complex 3-D Elements That Cause the Most Intense Surface Winds Because of the complex structure of extratropical cyclones and the dynamic conditions that favor their development, conventional statistical techniques for producing a catalog of potential events are not sufficient for capturing the unique wind fields associated with these storms. Realizing that this peril required a novel modeling approach, AIR introduced in 2000 the industry s first probabilistic catastrophe model to incorporate Numerical Weather Prediction (NWP). Starting with a three-dimensional snapshot of environmental conditions known collectively as initial conditions NWP predicts how the atmosphere will change over time using mathematical equations that govern fluid flow and thermodynamics. Today, AIR s fourth-generation Extratropical Cyclone Model for Europe based on NWP technology represents more than a decade of experience in modeling these complex weather systems. Robust Catalog Captures Even the Most Extreme Events To create the model s catalog of simulated events, AIR scientists utilize historical data from meteorological agencies across Europe and around the world, including complex atmospheric reanalysis data of global environmental conditions (including sea surface temperatures, air temperature, wind speed, water content and pressure) from the National Centers for Environmental Protection (NCEP) and the National Center for Atmospheric Research (NCAR). detailed model to manage the risk. Using state-of-the-art NWP technology, a historical seed storm is perturbed to create a set of realistic simulated storms. 2

3 AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE Based on NWP analysis, the physical characteristics of approximately 1,500 historical seed storms are perturbed to produce a catalog of more than 50,000 events whose wind field and track parameters reflect the complete range of potential windstorm experience across Europe. AIR s perturbation methods ensure that extreme wind events that have limited past historical precedence are realistically represented. Numerical weather prediction allows such storms to be properly separated and identified by their vortex center a critical capability for estimating occurrence losses and reflecting observed correlations of risk between countries. Representing these clusters appropriately in the stochastic catalog is also important for reinsurance contracts that cover annual aggregate losses, as well as contracts that limit losses to damage occurring within a specified time period, such as 72 hours. The AIR Extratropical Cyclone Model for Europe preserves the observed propensity for storms to occur in clusters through an advanced block bootstrapping method, which produces a more realistic temporal occurrence pattern than other, more commonly used methods based on parameterized distributions. Dublin Glasgow London Bordeaux Paris Rotterdam Brussels Zurich Oslo Berlin Munich Stockholm Copenhagen Graz The AIR model accurately identifies individual storms within spatial and temporal clusters. In 2000, three low pressure systems (from left to right: Nicole, Oratia, and an unnamed storm) swept over Europe in quick succession. Advanced Downscaling of Winds Aloft to High Resolution Surface Winds To translate the output of AIR s NWP model to highresolution surface wind speeds, AIR meteorologists use a state-of-the-art downscaling technique. Local effects are incorporated, including those from land use/land cover, surface terrain and roughness, and gustiness. Although lower resolution models may perform adequately for assessing losses at the industry level, downscaled wind fields are far more accurate for analyzing company portfolios. Statistics from hundreds of local wind stations are used to dramatically improve the resolution and realism of modeled winds at the surface. These advanced downscaling techniques result in a model with a much higher degree of fidelity, particularly in coastal and mountain regions prevalent in the Netherlands, France, the United Kingdom, and Switzerland. Explicit Modeling of Storm Clustering As history has repeatedly shown, Europe can be struck by several storms in rapid succession, and individual locations can experience relentless gale-force winds for several days. Yet an examination of wind speed observations alone might suggest that only a single, large storm swept through. ACTUAL POISSON BOOTSTRAPPED Days A block bootstrapping approach produces a more realistic temporal occurrence pattern than a Poisson distribution, capturing the tendency of storms to cluster temporally. 3

4 AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE Using advanced downscaling procedures, NWP output (left) is enhanced to 3 second gust wind speeds at approximately 1 km 1 km resolution (right). Advanced Vulnerability Module A building s response to extratropical cyclone winds can vary significantly depending on its construction type, occupancy class, and height, as well as other factors such as regional construction practices and building age. Based on meticulous literature reviews, engineering studies, post-disaster surveys after recent storms such as Erwin (2005), Kyrill (2007), Emma (2008), and Klaus (2009), and analyses of a large set of claims data, AIR engineers have developed damage functions for 34 different construction classes and 51 occupancy classes, including agriculture, greenhouses (in Denmark and the Netherlands), and forestry (in Finland, Norway, and Sweden). awnings (although walls can b damaged by flying debris). Roof tile damage and displacement is very common in residential structures. Damage at the roof edges allows wind to penetrate underneath the roof covering and membrane, creating uplift, which can result in the partial or complete removal of the roof covering. The commercial building stock displays a wider variety of construction materials. Smaller commercial structures are usually masonry construction, and their vulnerability is similar to that of residential structures. Large commercial buildings are more likely to be of reinforced concrete or steel, and mid rise and high-rise commercial buildings tend to be well engineered. Damage to engineered buildings typically occurs to nonstructural components and glazing; structural damage is extremely Roof tile damage is commonly observed in residential and small commercial structures (left) while severe roof damage (right) occurs less frequently (Source: AIR) In-Depth Understanding of the Regional Building Stock Across much of Europe, residential structures are typically of non-engineered masonry construction (the exceptions are Norway and Sweden, where wood-frame construction is predominant). When subject to typical extratropical cyclone winds, damage to these structures is usually low to moderate and limited to nonstructural elements such as roofs, windows, chimneys, balconies, parapets, and Damage to agricultural buildings and light metal industrial buildings can be severe (Source: AIR) 4

5 Forestry in Finland, Sweden, and Norway In 2005, winter storm Erwin damaged 75 million cubic meters of timber in Sweden, equal to 250 million trees, or about a year s harvest for the entire country. Timber losses cost the insurance industry approximately 2.5 billion Swedish Krona (EUR 230 million) and was a huge blow to Sweden s forestry industry, which accounts for 25% to 30% of the country s exports. An estimated half of privately owned forests in Sweden are covered by insurance. And in Finland about one-third of family-owned forests are insured. In Norway, timber products account for more than 10% of the country s exports, and forestlands cover over 20 million acres of land, about 80% of which is privately owned. AIR s forestry damage function for Finland, Sweden, and Norway take into account species, height, age, slenderness ratio, stand density, and soil characteristics as well as extensive forestry claims data from significant tree-felling storms in Scandinavia, including Anatol (1999), Erwin (2005), and Hanno (2007). AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE Forestry plays a vital role to the economies of Finland, Sweden, and Norway. AIR takes into account a wide variety of factors that affect a forest s susceptibility to wind damage. (Source: AIR) rare. However, large commercial buildings often have a substantial proportion of glass, which is very vulnerable to wind and debris. Regional Vulnerability High The AIR model also includes damage functions for warehouses, agricultural buildings, and greenhouses, which have lower resistance to wind damage than residential and commercial structures. Low Damage to the building envelope can cause damage to contents, and the level of contents damage is exacerbated in the presence of precipitation during or following a storm. The AIR model supports separate contents damage functions for residential and commercial structures, as well as business interruption damage functions that take into account such factors as construction type and occupancy class. Explicit Recognition of Regional Building Codes and Construction Practices Europe displays considerable diversity in climate and seasonal storm intensity, with certain regions subject to higher levels of wind speeds more frequently than others. Over decades, this has resulted in variations in building vulnerability across regions, as each country develops its own building codes and construction practices that reflect its historical storm experience. For example, the building Buildings in regions that frequently experience higher wind speeds tend to be less vulnerable because they are subject to more stringent building codes and local construction practices. AIR damage functions take into account variations in regional vulnerability. 5

6 AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE stock in northern parts of the United Kingdom (particularly Scotland) consistently performs better than buildings in other regions of the UK. In the southeastern UK, extreme extratropical cyclones are relatively uncommon but can cause severe damage when they do occur because the Legend Wind Gust (m/s) > 50 building stock there is considerably more vulnerable. Regional building codes in Europe are being replaced with standard structural design codes developed by the European Committee for Standardisation (European Norms, or the EN codes). Based on weather patterns and 50-year return period wind speeds, the EN codes specify the appropriate building standards for each region. The AIR model also takes into consideration the effect that regional wind hazard characteristics can have on local design levels, building code enforcement and construction practices. The AIR Industry Exposure Database for Europe: An Unparalleled Resource The AIR Extratropical Cyclone Model for Europe incorporates a robust and detailed industry exposure database (IED) based on the latest available information on risk counts and building characteristics from various government offices and statistics bureaus. Because this data can vary considerably in resolution, AIR uses a sophisticated algorithm that takes into AIR s downscaling process produces realistic wind footprints. Here, the modeled wind footprint for Klaus (2009) is compared against Météo France observations. account topography, satellite-derived land use/land cover information, and NOAA s Night Lights data to disaggregate all risk counts to a 1 km x 1 km grid. When detailed, location-specific exposure data is not available, companies can leverage the IED using Touchstone, to disaggregate their coarse resolution data to a higher resolution that accurately reflects the spatial distribution of exposure locations. This allows for consistent modeling within and between countries, which is particularly important for modeling extratropical cyclone risk in Europe. Comprehensive Approach to Model Validation To ensure the most robust and scientifically rigorous model possible, the model is carefully validated against actual loss experience. However, validation is not merely limited to final model results. Each component is independently validated against multiple sources; for example, the distribution of each storm characteristic in the stochastic catalog is carefully compared against historical storm data, and modeled wind fields are validated against wind speed observations from actual storms. Modeled losses have been validated against nearly EUR 3 billion in claims provided by 14 companies of varying sizes. The data spans 11 countries and 12 historical events from Daria (1990) to more recent storms such as Kyrill (2007), Emma (2008), and Xynthia (2010). EUR Millions 12,000 10,000 8,000 6,000 4,000 2,000 0 Capella'76 StormO'81 87J'87 Daria'90 Herta'90 Vivien'90 Wiebke'90 Verena'93 Anatol'99 Lothar'99 Martin'99 Janika'01 Jeanett'02 Erwin'05 Hanno'05 Observed Modeled Modeled losses are compared against reported losses for historical storms at an industry level (shown), as well as by company, by line of business and by coverage. Kyrill'07 Emma'07 Klaus'07 Xynthia (2010) 6

7 AIR EXTRATROPICAL CYCLONE MODEL FOR EUROPE Model at a Glance Modeled Perils Modeled Domain Extratropical cyclone winds Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France (including Monaco), Germany, Ireland, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Sweden, Switzerland, and the UK Touchstone: Country and CRESTA zone, postal code for Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France (including Monaco), Germany, Ireland, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Sweden, Switzerland, and the UK User-specified latitude/longitude for all countries CATRADER : country and CRESTA zone for Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France (including Monaco), Germany, Ireland, Latvia, Lithuania, Netherlands, Norway, Poland, Sweden, and Switzerland Supported Geographic Resolution Supported Construction Classes and Occupancies Country, CRESTA zone, and postcode for the UK Country only for Luxembourg Number of Supported Construction Classes: For all countries, the model supports 30 construction classes. Number of Supported Occupancy Classes: For all countries, the model supports 49 occupancy classes. It supports 50 occupancy classes for Denmark and the Netherlands (where the greenhouse class is added) and for Finland, Sweden, and Norway (where the forestry class is added). Unknown Damage Functions: When detailed exposure data (for example, construction type or height) is unavailable, the model applies an unknown damage function that takes into account country-specific construction characteristics. Model Highlights AIR s fourth generation model based on numerical weather prediction (NWP) ensures more realistic depiction of windstorm risk Novel storm identification technique allows for the explicit modeling of temporal and spatial clustering State-of-the-art approach to downscaling uses high resolution surface data to translate boundary layer winds to the surface Damage functions based on rigorous engineering studies, AIR post-disaster surveys, and extensive claims data Explicitly accounts for differences in regional vulnerability Supports a wide array of policy conditions including coverage limits, deductibles, loss triggers, and reinsurance conditions Losses extensively validated against more than EUR 3 billion of detailed client claims data from major storms of the last two decades Real-time ALERT service provides reliable industry loss estimates within hours of a storm, allowing clients to analyze the impact on their own portfolios 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