Global Future Drought Layers Based on Downscaled CMIP6 Models and Multiple Socioeconomic Pathways

• Published in: Scientific data Vol. 12; no. 1; pp. 295 - 14
• Main Authors: Araujo, Diogo S. A., Enquist, Brian J., Frazier, Amy E., Merow, Cory, Roehrdanz, Patrick R., Moulatlet, Gabriel M., Zvoleff, Alex, Song, Lei, Maitner, Brian, Nikolopoulos, Efthymios I.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.02.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 704/106/694/2786; 704/242; 704/4111; Data Descriptor; Drought; Evapotranspiration; Humanities and Social Sciences; multidisciplinary; Precipitation; Science; Science (multidisciplinary)
• ISSN: 2052-4463; 2052-4463
• DOI: 10.1038/s41597-025-04612-w

Droughts are a natural hazard of growing concern as they are projected to increase in frequency and severity for many regions of the world. The identification of droughts and their future characteristics is essential to building an understanding of the geography and magnitude of potential drought change trajectories, which in turn is critical information to manage drought resilience across multiple sectors and disciplines. Adding to this effort, we developed a dataset of global historical and projected future drought indices over the 1980–2100 period based on downscaled CMIP6 models across multiple shared socioeconomic pathways (SSP). The dataset is composed of two indices: the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) for 23 downscaled global climate models (GCMs) (0.25-degree resolution), including historical (1980–2014) and future projections (2015–2100) under four climate scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The drought indices were calculated for 3-, 6- and 12-month accumulation timescales and are available as gridded spatial datasets in a regular latitude-longitude format at monthly time resolution.