2026-07-06T20:59:18Zhttp://doidb.wdc-terra.org/oaip/oaioai:doidb.wdc-terra.org:63402026-06-10T09:55:40ZDOIDBDOIDB.PIKfalse4DOIDB.PIK
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
A data collection of tropical cyclone exposure data sets (TCE-DAT)
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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