Back to Search
Start Over
Impact of Atmospheric Aerosols on the Accuracy of IMERG Precipitation Estimates Over Northern China
- Source :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 3956-3970 (2024)
- Publication Year :
- 2024
- Publisher :
- IEEE, 2024.
-
Abstract
- Accurate satellite precipitation estimates are vital for understanding global and large-scale regional water cycles. Among the many factors influencing satellite precipitation data quality, the detection and accuracy of precipitation products at different atmospheric aerosol concentrations are not well studied. In this study, we investigated the impact of atmospheric aerosols on the accuracy of satellite precipitation products (IMERG) over North China by comparing performance metrics such as bias, normalized root mean squared error, probability of detection (POD), and false alarm ratio (FAR) under different atmospheric aerosol conditions. The results revealed that IMERG generally exhibits poorer detectability and quantification under pollution condition. Based on the error decomposition, the estimated errors in autumn and winter were dominated by false biases, which are mainly affected by atmospheric aerosols. At the sensor level, the FARs of both infrared (IR) and passive microwave sensors show escalating trends as pollutant concentrations increase. The POD of IR sensors is affected by pollution. Pollution has a significant impact on IR detection capability. Our findings suggest that atmospheric aerosols may impact the accuracy of IMERG precipitation estimates over Northern China and need to be taken into consideration in the IMERG retrieval process and data utilization.
Details
- Language :
- English
- ISSN :
- 19391404 and 21511535
- Volume :
- 17
- Database :
- Directory of Open Access Journals
- Journal :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.146425d5f49f472787b403f4aab0d324
- Document Type :
- article
- Full Text :
- https://doi.org/10.1109/JSTARS.2024.3356256