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A high-resolution dataset for future compound hot-dry events under climate change
Yizhuo Wen1,2, Junhong Guo3, Feng Wang4
1Key Laboratory of Environmental Biotechnology, Xiamen University of Technology, Xiamen, 361024, China.
Scientific Data
|September 27, 2024
Summary
A new dataset tracks daily compound hot-dry events (CHDEs) from 1980-2100, crucial for understanding climate change impacts. Validated against real-world data, it offers reliable metrics for global and regional extreme event research.
Area of Science:
- Climate Science
- Environmental Science
- Data Science
Background:
- Global climate change is increasing compound hot-dry events (CHDEs), posing significant risks to human habitats.
- Existing meteorological data often lack the focus on extremes needed for CHDEs research.
- Accurate data is essential for analyzing the causes and effects of these impactful events.
Purpose of the Study:
- To develop a comprehensive daily compound hot-dry events (CHDEs) dataset covering 1980-2100.
- To provide a high-resolution dataset suitable for global and regional climate change impact studies.
- To validate the dataset's accuracy using observational meteorological data.
Main Methods:
- Utilized NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) data.
- Developed a dataset with 0.25-degree spatial resolution, including indicators for hot-dry extreme days (D), precipitation intensity (prI), and temperature intensity (tasI).
- Validated the dataset against observational data from China (NMIC), Europe (ERA5), and North America (ERA5).
Main Results:
- The CHDEs dataset shows strong temporal and spatial alignment with observational data.
- Predictive interval (PI) pass rates were high: D exceeded 85% (90% PI), prI was above 70%, and tasI surpassed 95%.
- The dataset's accuracy was confirmed, demonstrating its reliability for research.
Conclusions:
- The developed CHDEs dataset is a valuable resource for studying the impacts of climate change-induced extreme events.
- Its high accuracy and resolution support detailed global and regional analyses.
- The dataset facilitates research into the causes, effects, and mitigation strategies for compound hot-dry events.
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