MIAO LEI

Dr. MIAO LEI


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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11 April 2025 in Remote Sensing
Verified
Journal Article
Open access
PDF file
DWDong WEI
Dong WEI
WDWenjing Di
Wenjing Di
WTWenshou TIAN
Wenshou TIAN
SCShanjun Cheng
Shanjun Cheng
MLMIAO LEI
MIAO LEI
ZJZhikun Jing
Zhikun Jing
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.