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Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
854
Global Future Drought Layers Based on Downscaled CMIP6 Models and Multiple Socioeconomic Pathways
Diogo S A Araujo1, Brian J Enquist2,3, Amy E Frazier4
1Department of Civil and Environmental Engineering, Rutgers University, Piscataway, NJ, 08854, USA.
Scientific Data
|February 19, 2025
Summary
This study presents a global dataset of historical and projected drought indices (SPI and SPEI) from 1980-2100. This essential resource aids in understanding and managing future drought impacts under various climate scenarios.
Area of Science:
- Climate Science
- Environmental Science
- Data Science
Background:
- Droughts are increasing in frequency and severity globally.
- Understanding drought characteristics is crucial for resilience.
- Existing data may not fully capture future drought trajectories.
Purpose of the Study:
- To develop a comprehensive global dataset of historical and projected drought indices.
- To provide data for understanding drought change trajectories under different climate scenarios.
- To support drought resilience planning across sectors.
Main Methods:
- Utilized downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs).
- Calculated Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI).
- Generated gridded spatial datasets at 0.25-degree resolution for 1980-2100 under four Shared Socioeconomic Pathways (SSPs).
Main Results:
- A dataset of SPI and SPEI is available for 23 GCMs.
- Data covers historical (1980-2014) and future (2015-2100) periods.
- Indices are provided for 3-, 6-, and 12-month timescales at monthly resolution.
Conclusions:
- The dataset offers valuable insights into global drought patterns.
- It supports research on climate change impacts on drought.
- Facilitates improved drought risk assessment and management strategies.
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