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Modelling Windstorm Risk
Committed To Securing Livelihoods
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Modelling Windstorm, Hailstorm, Tornado & Severe Thunderstorm Risks
Annually the US, Canada, Europe and Australia are effected by billions in losses as a consequence of severe convective storms or sub-perils of these storms. Severe windstorms, tornadoes and thunderstorms can be sub-perils triggered by a single major event or can be multiple individual events over the course of a given time period. They can no longer be viewed as attritional risks. The losses from events such tornados, hailstorms, lightning and straight-line wind that can be the onset or the result of an extreme occurrence, for example a thunderstorm outbreak or a hurricane, can be catastrophic.
Infinite Observations ZineQx Severe Storm Model provides convective
cat model solutions that simulates, assesses and manages the extreme loss volatility constituted by these extraordinarily localized peril of possible severe convective storm risk. We use a combination of historical or stochastic events data and statistical or mathematically derived data set and physical simulations to evaluate event probabilities and generate the frequency, intensity, and geographical distributed robust record of severe convective storm outbreaks with a high likelihood while implementing specific damage functions to disassociate their distinct impacts on the assets, such as building, inventory and business disruption, of our clients.


Windstorm Catastrophe Models
Modelled Regions :
Click a region to see countries or islands where courage is available.
North America
Europe
Middle East
Central America & Caribbean
Asia & Pacific
Latin America
Africa
Australia
Severe Convective Storm Risk Modelling
North America
Canada
United States
Mexico
Central America
Belize
Costa Rica
El Salvador
Honduras
Nicaragua
Panama
Caribbean
The Greater Antilles
Cuba
Puerto Rico
Jamaica
Cayman Islands
Hispaniola:
Haiti
Dominican Republic
Lucayan Archipelago
Bahamas
Turks and Caicos Islands
Lesser Antilles (Leeward Islands)
Anguilla (UK)
Saint Martin (Fr.)
Sint Maarten (Neth.)
Saint-Barthélemy (Fr.)
Saba (Neth.)
Sint Eustatius (Neth.)
Saint Kitts
Nevis
Antigua
Barbuda
Redonda
Bermuda
Montserrat (UK)
Guadeloupe (Fr.)
La Désirade (Fr.)
Marie-Galante (Fr.)
Les Saintes archipelago (Fr.)
St. Thomas (US VI)
St. John (US VI)
St. Croix (US VI)
Water Island (US VI)
Tortola (UK VI)
Virgin Gorda (UK VI)
Anegada (UK VI)
Jost Van Dyke (UK VI)
Aruba (Neth.)
Curaçao (Neth.)
Bonaire (Neth.)
La Orchila
La Tortuga
La Blanquilla
Margarita Island
Coche
Cubagua
Los Roques Archipelago
Lesser Antilles (Windward Islands)
Dominica
Martinique (Fr.)
Saint Lucia
Barbados
Saint Vincent
Grenadines
Carriacou
Petite Martinique
Grenada
Trinidad
Tobago
South America
Argentina
Bolivia
Chile
Cayman Islands
Colombia
Ecuador
Guyana
Guiana (Fr.)
Paraguay
Peru
Suriname
Uruguay
Venezuela
Europe
Andorra
Austria
Belgium
Bulgaria
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Latvia
Liechtenstein
Lithuania
Luxembourg
Malta
Monaco
Netherlands
Norway
Poland
Russia
Spain
Sweden
Switzerland
Turkey
United Kingdom
Vatican City
Asia & Pacific
East Asia
China
Hong Kong (China)
Macau (China)
Japan
North Korea
South Korea
Taiwan
South Asia
Bangladesh
India
Maldives
Sri Lanka
South Asia
Brunei
Cambodia
Indonesia
Laos
Malaysia
Myanmar
Philippines
Singapore
Thailand
Timor-Leste
Vietnam
Australasia
Australia
New Zealand
Melanesia
Fiji
New Caledonia (Fr)
Papua New Guinea
Solomon Islands
Vanuatu
Micronesia
Guam (US)
Kiribati
Marshall Islands
Nauru
Northern Mariana Islands (US)
Wake Island (US)
Polynesia
American Samoa (US)
Cook Islands (NZ)
Easter Island (Ch)
French Polynesia (Fr)
Niue (NZ)
Norfolk Island (A)
Tonga
Tuvalu
Samoa
Wallis and Futuna (Fr)

Severe Thunderstorm Models
There is abundant historical data regarding straight-line winds, hail, and tornadoes. However, these data sets reflect reporting biases because of sparse populated areas, non-reporting of localized events and occurrences that go unnoticed. To compensate for this lack of data because of non-reporting issues a smoothing technique can be applied to the data to give a more physically realistic representation and to include locations that have experienced major activity but have been left out of historical records. The smoothing techniques leverages high-resolution meteorological parameters, statistical and physical analyses to determine favorable spatial and temporal conditions for severe thunderstorm formation. The result is a complete geospatial catalogue of severe thunderstorm hazard that can be utilized to inform various organization in the industry with regard to supercell severe thunderstorm risk.
Quantifying Losses Large & Small
Major thunderstorms can last for several days at time and have an impact across multiple countries or states. However, the individual constituents of an outbreak of such a thunderstorm, tornadoes, hailstorms, and straight winds, are often very localised and last just minutes. To capture the losses from both the large and small effects Infinite Observations employs a high-resolution granular damage mapping for each specific sub-peril, based on satellite and radar data from meteorological organisation in North America, Europe and Australia along with advanced clustering analyses techniques. This yields models with exceedance probability curves that can be used to determine losses resulting from large outbreak and smaller events. (Weighed) damage functions are generated by the model for each specific sub-peril, which include factors such as gust wind velocity, impact energy, construction types, building codes, seasonality, etc. The models can be validated in its entirety or model component can be validate independently against information and research from industry sources.


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ZineQx - Infinite Observations
