Articles | Volume 12, issue 2
https://doi.org/10.5194/essd-12-817-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-817-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
09 Apr 2020
Data description paper |
| 09 Apr 2020
| 09 Apr 2020
Asset exposure data for global physical risk assessment
Institute for Environmental Decisions, ETH Zurich, Zurich, 8092,
Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss,
Zurich Airport, 8058, Switzerland
Dario Stocker
Institute for Environmental Decisions, ETH Zurich, Zurich, 8092,
Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss,
Zurich Airport, 8058, Switzerland
Thomas Röösli
Institute for Environmental Decisions, ETH Zurich, Zurich, 8092,
Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss,
Zurich Airport, 8058, Switzerland
David N. Bresch
Institute for Environmental Decisions, ETH Zurich, Zurich, 8092,
Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss,
Zurich Airport, 8058, Switzerland
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- Uncertainties and sensitivities in the quantification of future tropical cyclone risk S. Meiler et al. 10.1038/s43247-023-00998-w
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- Human populations in the world’s mountains: Spatio-temporal patterns and potential controls J. Thornton et al. 10.1371/journal.pone.0271466
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- Evaluating targeted heuristics for vulnerability assessment in flood impact model chains A. Zischg et al. 10.1111/jfr3.12736
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- A framework for building climate storylines based on downward counterfactuals: The case of the European Union Solidarity fund A. Ciullo et al. 10.1016/j.crm.2021.100349
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- Differential Fiscal Performances of Plausible Disaster Events: A Storyline Approach for the Caribbean and Central American Governments under CCRIF S. Hochrainer-Stigler et al. 10.1007/s41885-023-00126-0
- A generalized framework for designing open-source natural hazard parametric insurance C. Steinmann et al. 10.1007/s10669-023-09934-x
- Comparing an insurer's perspective on building damages with modelled damages from pan-European winter windstorm event sets: a case study from Zurich, Switzerland C. Welker et al. 10.5194/nhess-21-279-2021
- Regional tropical cyclone impact functions for globally consistent risk assessments S. Eberenz et al. 10.5194/nhess-21-393-2021
- Application of Open Data in Disaster Risk Research: A Preliminary Review Using Bibliometric Analysis J. Gao et al. 10.20965/jdr.2022.p1090
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- Impact Forecasting to Support Emergency Management of Natural Hazards B. Merz et al. 10.1029/2020RG000704
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- DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level rise N. Depsky et al. 10.5194/gmd-16-4331-2023
- Asset exposure data for global physical risk assessment S. Eberenz et al. 10.5194/essd-12-817-2020
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Short summary
The modeling of economic disaster risk on a global scale requires high-resolution maps of exposed asset values. We have developed a generic and scalable method to downscale national asset value estimates proportional to a combination of nightlight intensity and population data. Here, we present the methodology together with an evaluation of its performance for the subnational downscaling of GDP. The resulting exposure data for 224 countries and the open-source Python code are available online.
The modeling of economic disaster risk on a global scale requires high-resolution maps of...
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