Global assessment of subnational drought impact based  on the Geocoded Disasters dataset and land reanalysis

Kageyama, Yuya; Sawada, Yohei

doi:https://doi.org/10.5194/hess-26-4707-2022

Articles | Volume 26, issue 18

https://doi.org/10.5194/hess-26-4707-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-26-4707-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 18

Research article

|

27 Sep 2022

Research article |

| 27 Sep 2022

Global assessment of subnational drought impact based on the Geocoded Disasters dataset and land reanalysis

Yuya Kageyama and Yohei Sawada

Supplement

https://doi.org/10.5194/hess-26-4707-2022-supplement

Data sets

MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006, NASA EOSDIS Land Processes DAAC M. Friedl and D. Sulla-Menashe https://doi.org/10.5067/MODIS/MCD12C1.006

Average precipitation in depth FAO - Food and Agriculture Organization https://data.worldbank.org/indicator/ag.lnd.prcp.mm?msclkid=215b9959b08711ec944832810373c8aa&view=map

ERA5-Land monthly averaged data from 1981 to present J. Muñoz Sabater https://doi.org/10.24381/cds.68d2bb30

ERA5-Land monthly averaged data from 1950 to 1980 J. Muñoz Sabater https://doi.org/10.24381/cds.68d2bb30

Geocoded Disasters (GDIS) Dataset E. L. Rosvold and H. Buhaug https://doi.org/10.7927/zz3b-8y61

World by Income and Region World Bank https://datatopics.worldbank.org/world-development-indicators/the-world-by-income-and-region.html

MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006 M. Friedl and D. Sulla-Menashe https://doi.org/10.5067/MODIS/MCD12C1.006

CIESIN - Center for International Earth Science Information Network Columbia University Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 https://doi.org/10.7927/H49C6VHW

Model code and software

Drought_clusters J. E. Herrera-Estrada https://github.com/julherest/drought_clusters

Short summary

This study explores the link between hydrometeorological droughts and their socioeconomic impact at a subnational scale based on the newly developed disaster dataset with subnational location information. Hydrometeorological drought-prone areas were generally consistent with socioeconomic drought-prone areas in the disaster dataset. Our analysis clarifies the importance of the use of subnational disaster information.