Global climate hazard maps

_{Table: The underlying model and data for each hazard type}

_{Hazard type}

_{Hazard unit}

_{Maps resolution}

_{Underlying data and models}

_{Flood (fluvial, pluvial, and coastal)}

_{Flood depth in meters}

_{Global 10m2}

_{Hazard maps for different return periods are obtained from Moody’s global flood database [1].}

_{Tropical storm (cyclone)}

_{Max wind speed}

_{Global 11 km2}

_{Hazard maps are derived from a state-of-the-art probabilistic tropical storm database generated by a team at the Vrije University [2]. The database contains 10,000 years of synthetic cyclone activity. To statistically extend historical data to 10,000 years of cyclone data, the STORM methodology was applied – a newly developed resampling algorithm – to 38 years of cyclone data from the International Best Track Archive for Climate Stewardship (IBTrACS) project [3].}

_{Extratropical storms}

_{Global 1 km2}

_{Wind gusts are taken from the ERA5 re-analysis dataset [4], developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA5 combines vast amounts of historical atmospheric, land, and oceanic climate observations with global estimates using advanced modelling and data assimilation systems. The dataset includes hourly data since 1979. ERA5 includes several wind parameters, such as wind speed, instantaneous wind gust, and wind gust since previous post-processing.}

_{Thermal stress (heat and cold)}

_{Count of days exceeding temperature thresholds}

_{6 different thresholds: below -15°, -10°, -5°C and above 30°, 40°, 45°C}

_{Hourly data aggregated to daily maximum and minimum temperatures is derived from the ERA5 re-analysis dataset [4]. To calculate the average annual number of days the thresholds were exceeded, a 30-year period (1992–2022) was analysed.}

_{We calculated the thermal stress count for each asset based on the temperatures in the area the asset occupies.}