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<p>Remote sensed precipitation products (RSPPs) can provide reliable data for drought monitoring. However, using numerous RSPPs can introduce significant uncertainties due to their discrepancies. This study focuses on the Huang-Huai-Hai Plain in China, a key agricultural region sensitive to meteorological drought. Using grid precipitation interpolated by observed data from the China Meteorological Administration (CMA), we evaluated the performance of three long-term series (&gt; 30&#xa0;years) RSPPs (PERSIANN-CDR, CHIRPS, and MSWEP) in capturing the spatial and temporal characteristics of meteorological drought events. We found that (1) three RSPPs can generally reproduce the pattern of annual precipitation, but they are difficult to accurately capture the trend of CMA. (2) MSWEP performs better than the other two products in identifying drought variation and area proportions at various spatiotemporal scales, with the one-month scale (SPI1) being the optimal timescale for RSPPs to identify meteorological drought. (3) All RSPPs can reproduce the pattern of drought categories and characteristics, with their performance order of MSWEP &gt; CHIRPS &gt; PERSIANN-CDR. This indicates considerable room for improvement in depicting the drought characteristics. Our results can guide the selection of the RSPPs for meteorological drought monitoring and disaster avoidance.</p>

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Performance of remotely sensed precipitation products in capturing meteorological drought over typical agricultural planting area

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月11日

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  • Pengnian Huang,
  • Manjie Huang,
  • Aiqing Feng,
  • Yanzhong Li,
  • Kunxia Yu,
  • Yintong Guo,
  • Wenjun Yu,
  • Kang Yang

摘要

Remote sensed precipitation products (RSPPs) can provide reliable data for drought monitoring. However, using numerous RSPPs can introduce significant uncertainties due to their discrepancies. This study focuses on the Huang-Huai-Hai Plain in China, a key agricultural region sensitive to meteorological drought. Using grid precipitation interpolated by observed data from the China Meteorological Administration (CMA), we evaluated the performance of three long-term series (> 30 years) RSPPs (PERSIANN-CDR, CHIRPS, and MSWEP) in capturing the spatial and temporal characteristics of meteorological drought events. We found that (1) three RSPPs can generally reproduce the pattern of annual precipitation, but they are difficult to accurately capture the trend of CMA. (2) MSWEP performs better than the other two products in identifying drought variation and area proportions at various spatiotemporal scales, with the one-month scale (SPI1) being the optimal timescale for RSPPs to identify meteorological drought. (3) All RSPPs can reproduce the pattern of drought categories and characteristics, with their performance order of MSWEP > CHIRPS > PERSIANN-CDR. This indicates considerable room for improvement in depicting the drought characteristics. Our results can guide the selection of the RSPPs for meteorological drought monitoring and disaster avoidance.