Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm
A new quantitative precipitation estimation (QPE) method for Himawari-9 (H9) and Fengyun-4B (FY4B) satellites has been developed based on cloud top brightness temperature (TBB). The 24-hour, 6-hour, and hourly rainfall estimates of H9 and FY4B have been compared with rain gauge datasets and precipit...
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MDPI AG
2025-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/10/1703 |
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| author | Hao Chen Zifeng Yu Robert Rogers Yilin Yang |
| author_facet | Hao Chen Zifeng Yu Robert Rogers Yilin Yang |
| author_sort | Hao Chen |
| collection | DOAJ |
| description | A new quantitative precipitation estimation (QPE) method for Himawari-9 (H9) and Fengyun-4B (FY4B) satellites has been developed based on cloud top brightness temperature (TBB). The 24-hour, 6-hour, and hourly rainfall estimates of H9 and FY4B have been compared with rain gauge datasets and precipitation estimation data from the GPM IMERG V07 (IMERG) and Global Precipitation Satellite (GSMaP) products, especially based on the case study of landfalling super typhoon “Doksuri” in 2023. The results indicate that the bias-corrected QPE algorithm substantially improves precipitation estimation accuracy across multiple temporal scales and intensity categories. For extreme precipitation events (≥100 mm/day), the FY4B-based estimates exhibit markedly better performance. Furthermore, in light-to-moderate rainfall (0.1–24.9 mm/day) and heavy rain to rainstorm ranges (25.0–99.9 mm/day), its retrievals are largely comparable to those from IMERG and GSMaP, demonstrating robust consistency across varying precipitation intensities. Therefore, the new QPE retrieval algorithm in this study could largely improve the accuracy and reliability of satellite precipitation estimation for extreme weather events such as typhoons. |
| format | Article |
| id | doaj-art-a8735c2649e14a00ab9c283f36dba99c |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-a8735c2649e14a00ab9c283f36dba99c2025-08-20T03:12:12ZengMDPI AGRemote Sensing2072-42922025-05-011710170310.3390/rs17101703Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE AlgorithmHao Chen0Zifeng Yu1Robert Rogers2Yilin Yang3Asia-Pacific Typhoon Collaborative Research Center, Shanghai 201306, ChinaAsia-Pacific Typhoon Collaborative Research Center, Shanghai 201306, ChinaAsia-Pacific Typhoon Collaborative Research Center, Shanghai 201306, ChinaAsia-Pacific Typhoon Collaborative Research Center, Shanghai 201306, ChinaA new quantitative precipitation estimation (QPE) method for Himawari-9 (H9) and Fengyun-4B (FY4B) satellites has been developed based on cloud top brightness temperature (TBB). The 24-hour, 6-hour, and hourly rainfall estimates of H9 and FY4B have been compared with rain gauge datasets and precipitation estimation data from the GPM IMERG V07 (IMERG) and Global Precipitation Satellite (GSMaP) products, especially based on the case study of landfalling super typhoon “Doksuri” in 2023. The results indicate that the bias-corrected QPE algorithm substantially improves precipitation estimation accuracy across multiple temporal scales and intensity categories. For extreme precipitation events (≥100 mm/day), the FY4B-based estimates exhibit markedly better performance. Furthermore, in light-to-moderate rainfall (0.1–24.9 mm/day) and heavy rain to rainstorm ranges (25.0–99.9 mm/day), its retrievals are largely comparable to those from IMERG and GSMaP, demonstrating robust consistency across varying precipitation intensities. Therefore, the new QPE retrieval algorithm in this study could largely improve the accuracy and reliability of satellite precipitation estimation for extreme weather events such as typhoons.https://www.mdpi.com/2072-4292/17/10/1703FengYun-4BHimawari-9QPEprecipitation retrievaltyphoon |
| spellingShingle | Hao Chen Zifeng Yu Robert Rogers Yilin Yang Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm Remote Sensing FengYun-4B Himawari-9 QPE precipitation retrieval typhoon |
| title | Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm |
| title_full | Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm |
| title_fullStr | Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm |
| title_full_unstemmed | Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm |
| title_short | Precipitation Retrieval from Geostationary Satellite Data Based on a New QPE Algorithm |
| title_sort | precipitation retrieval from geostationary satellite data based on a new qpe algorithm |
| topic | FengYun-4B Himawari-9 QPE precipitation retrieval typhoon |
| url | https://www.mdpi.com/2072-4292/17/10/1703 |
| work_keys_str_mv | AT haochen precipitationretrievalfromgeostationarysatellitedatabasedonanewqpealgorithm AT zifengyu precipitationretrievalfromgeostationarysatellitedatabasedonanewqpealgorithm AT robertrogers precipitationretrievalfromgeostationarysatellitedatabasedonanewqpealgorithm AT yilinyang precipitationretrievalfromgeostationarysatellitedatabasedonanewqpealgorithm |