Data for climate risk modeling

Climate risk modeling estimates how floods, heat, wildfire, storms and other hazards could damage assets and portfolios, today and under future climate scenarios. Insurers, lenders and asset managers use it for pricing, capital planning and disclosure.

Climate risk data provides physical risk scores and hazard metrics by location, often under several emissions scenarios and time horizons. Weather data supplies historical observations, reanalysis and forecasts used to calibrate models and study past events. Property transaction data and building attributes connect hazards to values, which turns hazard maps into financial exposure.

A typical workflow

1. Geocode assets accurately, ideally to building level.
2. Attach hazard scores for current and future scenarios.
3. Combine with vulnerability and value data to estimate losses.
4. Aggregate to portfolio level and stress-test scenarios.

What to check before you buy

Ask about spatial resolution, which hazards are modelled, which scenarios and time horizons are used and how models were validated against historical losses. Geocoding quality matters as much as the hazard model, because a few hundred metres can change flood exposure completely.