10.5880/pik.2017.011 Geiger, Tobias 0000-0002-8059-8270 Potsdam Institute for Climate Impact Research, Potsdam, Germany Frieler, Katja 0000-0003-4869-3013 Potsdam Institute for Climate Impact Research, Potsdam, Germany Bresch, David N. 0000-0002-8431-4263 Swiss Federal Institute of Technology, ETH: Zurich, Switzerland GFZ Data Services 2017 climate risk modeling socio-economic exposure natural disasters EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > TROPICAL CYCLONES EARTH SCIENCE > HUMAN DIMENSIONS > POPULATION EARTH SCIENCE > HUMAN DIMENSIONS > SOCIOECONOMICS environmental risk assessment Geiger, Tobias Potsdam Institute for Climate Impact Research, Potsdam, Germany Dataset 10.1175/2008MWR2395.1 10.1177/0959683609356587 10.1111/j.1466-8238.2010.00587.x 10.1175/2009BAMS2755.1 https://arxiv.org/abs/1610.09041 https://github.com/davidnbresch/climada http://www.munichre.com/ natcatservice 10.5880/pik.2017.005 10.5880/pik.2017.008 10.5194/essd-10-185-2018 10.5880/pik.2017.007 CC BY 4.0 Tropical cyclones (TCs) pose a major risk to societies worldwide. While data on observed cyclones tracks (location of the center) and wind speeds is publicly available these data sets do not contain information
on the spatial extent of the storm and people or assets exposed. Here, we provide a collection of tropical cyclone exposure data (TCE-DAT) derived with the help of spatially-explicit data on population densities
and Gross Domestic Product (GDP), also available at http://doi.org/10.5880/pik.2017.007. Up to now, this collection contains:

1) A global data set of tropical cyclone exposure accumulated to the country/event level (https://doi.org/10.5880/pik.2017.005)
2) A global data set of spatially-explicit tropical cyclone exposure available for all TC events since 1950 (https://doi.org/10.5880/pik.2017.008)

TCE-DAT is considered key information to 1) assess the contribution of climatological versus socioeconomic drivers of changes in exposure to tropical cyclones, 2) estimate changes in vulnerability from
the difference in exposure and reported damages and calibrate associated damage functions, and 3) build improved exposure-based predictors to estimate higher-level societal impacts such as long-term effects
on GDP, employment, or migration. We expect that the free availability of the underlying model and TCE-DAT will make research on tropical cyclone risks more accessible to non-experts and stakeholders.
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