Coastal areas are urbanizing at unprecedented rates, particularly in low- and middle-income countries. Combinations of long-standing and emerging problems in these urban areas generate vulnerability for human well-being and ecosystems alike. Based on the presented data sets a spatially explicit global systematization of these problems into typical urban vulnerability profiles can be derived for the year 2000 using largely sub-national data.
We present here 11 indicator datasets for urban expansion, urban population growth, marginalization of poor populations, government effectiveness, exposures and damages to climate-related extreme events, low-lying settlement, and wetlands prevalence.
Applying a standard k-means cluster analysis to this input data reveals a global typology of seven clearly distinguishable clusters, or urban profiles of vulnerability (for results see Sterzel et. al., 2019).
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
about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind
field model to estimate the areas exposed to wind speeds above 34, 64, and 96 knots.
Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the
number of people and 2) the sum of assets exposed to wind speeds above these thresholds accounting for
temporal changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015
patterns (TCE-2015). The associated country-event level exposure data (TCE-DAT) covers the period
1950 to 2015. It 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 validate the adequateness of our methodology by comparing our
exposure estimate to estimated exposure obtained from reported wind fields available since 1988 for the
United States. 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.
Files included in the data set:
(1) TCE-DAT_historic-exposure_1950-2015.csv: Exposed population and assets by event and country using historical socio-economic exposure estimates.
(2) TCE-DAT_2015-exposure_1950-2015.csv: Exposed population and assets by event and country
using fixed socio-economic exposure at 2015 values.
(3) Data-description_TCE-DAT_2017.005.pdf: full description of the data set including information on data sources and the description of variables/ data columns
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.
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 about the spatial extent of the storm and people or assets exposed. Here, we apply a simplified wind
field model to estimate all areas (grid cells) exposed to wind speeds above 34 knots.
Based on available spatially-explicit data on population densities and Gross Domestic Product (GDP) we estimate 1) the
number of people and 2) the sum of assets exposed to above tropical storm force wind speeds for temporal
changes in historical distribution of population and assets (TCE-hist) and assuming fixed 2015 patterns
(TCE-2015).
The associated spatially-explicit exposure data (TCE-DAT) covers the period 1950 to 2015. It is considered key information to 1) assess the contribution of climatological versus socio-economic 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 validate the adequateness of our methodology by comparing our exposure
estimate to estimated exposure obtained from reported wind fields available since 1988 for the United States. 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.
Files included in the zip folder:
(1) TCE-DAT_single_events_historical.zip: Zipped archive containing 2707 files with exposed population
and assets by grid cell using historical socio-economic exposure estimates.
(2) TCE-DAT_single_events_2015.zip: Zipped archive containing 2713 files with exposed population
and assets by grid cell using fixed socio-economic exposure at 2015 values.
(3) Data-description_TCE-DAT_2017.008.pdf: full description of the data set including information on data sources and the description of variables/ data columns
Additional information on each TC event in the zipped archive (e.g. TC name, NatCatSERVICE_ID,
genesis_basin, aggregated exposure estimates by country) are available in the exposure data sets aggregated
on country-event level (see Geiger et al., 2017; http://doi.org/10.5880/pik.2017.005 for details).