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Powerful Tornado Scene

Extreme Climate Hazards

Extreme Climate Hazards: a model series designed to help organizations better understand climate risks, regardless of location. With global coverage and risk intelligence delivered through scoring, it enables more effective assessment of resilience, planning, and risk management challenges.

The models are based on established scientific methods in climatology, including extreme value analysis, return period estimation, IDF (Intensity-Duration-Frequency) curves, WASP drought indexing, and synthetic cyclone track modeling. These approaches transform historical and projected climate data into consistent, geolocated hazard scores that support informed decision-making.


This Extreme Climate Hazards series is the ideal complement to Geosapiens’ other climate risk models, particularly floods, wildfires, and hail, providing the most comprehensive and contextualized view of risks for any location.

Hurricane in City

Models in the Extreme Climate Hazards series:

Extreme Heat

Hazard based on annual maximum temperature

Extreme Cold

Hazard based on annual minimum temperature

Heatwave

Defined by minimum temperature thresholds sustained over three consecutive days

Cold wave

Defined by maximum temperature thresholds sustained over three consecutive days

Precipitation Extreme

Based on Intensity–Duration–Frequency (IDF) curves

Snow Extreme

Based on annual maximum snow water equivalent

Drought

Calculated using the Weighted Anomaly of Standardized Precipitation (WASP) index

Wind Extreme

Based on annual maximum wind speed

Cyclone

Based on maximum wind speeds derived from STORM synthetic cyclone tracks

La Terre la nuit

Geographic coverage

Geographic coverage of the Extreme Climate Hazards series is global, with modeling performed on a grid at a 10 km resolution.

Select the technological solutions to access Extreme Climate Hazards

Geosapiens’ extreme climate hazards models are available through subscription across a range of products:

Extreme climate hazards News

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