Evaluation of multi-source precipitation products for monitoring drought across China

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Accurate precipitation data are crucial for effective drought monitoring, especially in China’s complex and diverse climatic regions. This study evaluates the performance of six multisource precipitation products-ERA5-Land, CMORPH CRT, GSMaP MVK, IMERG Late, and IMERG Final-in detecting drought across China from 2009 to 2019, using ground station observations for validation. By applying various drought and evaluation indices across various timescales, this analysis captures short and long-term climate variations, assessing each product’s accuracy across diverse regions. Spatial and temporal analyses revealed that IMERG Final closely aligns with observed precipitation, particularly in the high-rainfall areas like the Yangtze River Basin, while GSMaP MVK and ERA5 tend to overestimate precipitation in arid and semi-arid regions. Discrepancies are most pronounced in complex terrains such as the Qinghai-Tibet Plateau and southwestern mountains, where sparse observational networks exacerbate errors. Drought indices, including SPEI-3 and SPI-1, were used to measure each product’s effectiveness in detecting drought intensity, frequency, and duration. IMERG Final consistently showed the highest correlation with ground data across all drought levels (Light, Moderate, and Severe), while GSMaP MVK and ERA5 tended to overestimate drought occurrences in certain drought-prone areas. Hotspot analyses of indices such as CDD, PRCPTOT, and R95p further confirmed IMERG Final’s accuracy in identifying drought and wet event patterns, closely reflecting ground measurements, whereas ERA5 and GSMaP MVK occasionally overestimated drought frequencies. In summary, IMERG Final emerged as a relatively accurate and reliable product for drought monitoring, showing strong applicability across China’s diverse climatic regions. These findings aid in data correction, enhances understanding of regional drought variability, and integration strategies to improve water resource management and extreme event monitoring.