Assessment of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) Precipitation Products in Northwest China

This study evaluates the applicability of the IMERG satellite precipitation product in Northwest China using data from more than 6000 ground-level meteorological stations during the warm season (April–September) from 2016 to 2023. The evaluation spans climatological, annual, monthly, and daily time scales with different precipitation intensities. IMERG precipitation can well capture the spatial and temporal precipitation climatology, with precipitation decreasing from southeast to Northwest China, and peaking in August. The correlation coefficient (CC) between IMERG precipitation and ground-observed precipitation is 0.69. However, IMERG precipitation systematically overestimates precipitation at climatological, annual, and monthly scales, especially in areas with relatively low precipitation climatology. At the daily time scale, IMERG precipitation data can represent precipitation events very well, especially in the southeastern part of Northwest China. IMERG precipitation overestimates light rainfall while underestimating precipitation of other intensities. While IMERG precipitation performs well in detecting light rain events, its accuracy diminishes for heavier rainfall, highlighting limitations for monitoring extreme precipitation. The Probability of Detection (POD) for light rainfall events is consistently above 0.9, while for Torrential Rainfall events, the POD is below 0.7. These findings provide insights into the effective application of IMERG data in precipitation monitoring and forecasting in Northwest China.

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Publication Details

Journal
Remote Sensing
Published
2025-04-11
DOI
https://doi.org/10.3390/rs17081364
Citations
4
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
5.20

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article

Assessment of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) Precipitation Products in Northwest China

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4 citations
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Precipitation Measurement and Analysis
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article

Assessment of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) Precipitation Products in Northwest China

Wei Dong, Wenjing Di, Shanjun Cheng, Hongfei Xie, Wenshou Tian, Lijun Xie, Zhikun Jing
article en
4 citations

Abstract

This study evaluates the applicability of the IMERG satellite precipitation product in Northwest China using data from more than 6000 ground-level meteorological stations during the warm season (April–September) from 2016 to 2023. The evaluation spans climatological, annual, monthly, and daily time scales with different precipitation intensities. IMERG precipitation can well capture the spatial and temporal precipitation climatology, with precipitation decreasing from southeast to Northwest China, and peaking in August. The correlation coefficient (CC) between IMERG precipitation and ground-observed precipitation is 0.69. However, IMERG precipitation systematically overestimates precipitation at climatological, annual, and monthly scales, especially in areas with relatively low precipitation climatology. At the daily time scale, IMERG precipitation data can represent precipitation events very well, especially in the southeastern part of Northwest China. IMERG precipitation overestimates light rainfall while underestimating precipitation of other intensities. While IMERG precipitation performs well in detecting light rain events, its accuracy diminishes for heavier rainfall, highlighting limitations for monitoring extreme precipitation. The Probability of Detection (POD) for light rainfall events is consistently above 0.9, while for Torrential Rainfall events, the POD is below 0.7. These findings provide insights into the effective application of IMERG data in precipitation monitoring and forecasting in Northwest China.

Remote SensingVol. 17(8)
Gansu Meteorological Bureau (CN), Tianjin Meteorological Bureau (CN), Lanzhou University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Gansu Province
Openalex Percentile: Top 5%
Precipitation Measurement and Analysis
5.20
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