Zhou et al. (2025) A Database of High-Resolution Meteorological Drought Comprehensive Index Across China for the 1951–2022 Period

Identification

• Journal: Data
• Year: 2025
• Date: 2025-10-28
• Authors: Xijia Zhou, Mingwei Zhang, Guicai Li, Yuanyuan Wang, Zhaodi Guo
• DOI: 10.3390/data10110171

Research Groups

• Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China
• Innovation Center for the FengYun Meteorological Satellite (FYSIC), Beijing 100081, China

Short Summary

This study developed a high-resolution (0.1 degrees) daily Meteorological Drought Comprehensive Index (MCI) dataset for China from 1951 to 2022, alongside multi-timescale Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) datasets. The MCI dataset demonstrates superior accuracy in reflecting shallow soil moisture changes in eastern China compared to single-time-scale indices, providing a robust tool for drought monitoring and analysis.

Objective

• To construct a daily multi-timescale Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Meteorological Drought Comprehensive Index (MCI) dataset for China from 1951 to 2022 at a 0.1-degree spatial resolution.
• To assess the reliability of the developed SPI and SPEI datasets by comparing them with existing drought index datasets and evaluating the underlying ERA5-Land data.
• To evaluate the characteristics and advantages of the MCI dataset in reflecting drought conditions and its correlation with daily cumulative precipitation and soil moisture content at various depths across China.
• To analyze drought variation characteristics in China since the 1950s and explore the spatiotemporal distribution of key drought events using the constructed MCI dataset.

Study Configuration

• Spatial Scale: China, with a spatial resolution of 0.1 degrees.
• Temporal Scale: Daily data covering the period from 1951 to 2022.

Methodology and Data

• Models used: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Meteorological Drought Comprehensive Index (MCI).
• Data sources:
  • ERA5-Land hourly precipitation, potential evapotranspiration, and soil moisture data (0–7 cm, 7–28 cm, 28–100 cm depths) from 1950 to 2022.
  • Verification datasets: Daily SPI and SPEI from China Meteorological Forcing Dataset (CMFD) (1979–2018) and daily global SPEI from ERA5 (1982–2021).

Main Results

• The newly generated SPI and SPEI datasets show high consistency (R² > 0.5, average biases near 0) with existing datasets in eastern China, though consistency is lower in western regions (R² < 0.3).
• The developed Meteorological Drought Comprehensive Index (MCI) dataset demonstrates superior real-time monitoring capability for shallow soil moisture (0–7 cm depth) in eastern China, with R² values often exceeding 0.7, outperforming single-time-scale SPI and SPEI.
• Analysis of drought variations from 1951 to 2022 using the MCI dataset reveals a significant expansion in the frequency and intensity of severe drought events across eastern China in the 21st century, affecting all seasons.
• The 2022 drought in eastern China, particularly in the mid-lower Yangtze Basin, was identified as severe and widespread, with some areas experiencing over 100 days of severe drought and a maximum daily affected area of 1,201,793 square kilometers.

Contributions

• Developed the first publicly available high-resolution (0.1 degrees) daily Meteorological Drought Comprehensive Index (MCI) dataset for China, covering 1951–2022, addressing limitations of existing single-time-scale drought indices.
• Demonstrated that the MCI dataset more accurately and timely reflects shallow soil moisture changes (R² > 0.7 for 0–7 cm depth) in eastern China compared to traditional SPI and SPEI, making it highly suitable for agricultural and grassland drought monitoring.
• Provided a robust tool for analyzing long-term spatiotemporal drought characteristics and identifying specific drought events across China, validated against existing literature.

Funding

• National Key R&D Program of China (Grant No. 2022YFC3002801)

Citation

@article{Zhou2025Database,
  author = {Zhou, Xijia and Zhang, Mingwei and Li, Guicai and Wang, Yuanyuan and Guo, Zhaodi},
  title = {A Database of High-Resolution Meteorological Drought Comprehensive Index Across China for the 1951–2022 Period},
  journal = {Data},
  year = {2025},
  doi = {10.3390/data10110171},
  url = {https://doi.org/10.3390/data10110171}
}