Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024)
This study aimed to compare and evaluate three satellite-based precipitation estimation products: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Early Run (IMERG-Early Run), Climate Prediction Center MORPHing technique Real Time (CMORPH-RT), and Precipitation Estimation f...
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MDPI AG
2025-04-01
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| Online Access: | https://www.mdpi.com/2072-4292/17/9/1598 |
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| author | Viet Duc Nguyen Nazak Rouzegari Vu Dao Fahad Almutlaq Phu Nguyen Soroosh Sorooshian |
| author_facet | Viet Duc Nguyen Nazak Rouzegari Vu Dao Fahad Almutlaq Phu Nguyen Soroosh Sorooshian |
| author_sort | Viet Duc Nguyen |
| collection | DOAJ |
| description | This study aimed to compare and evaluate three satellite-based precipitation estimation products: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Early Run (IMERG-Early Run), Climate Prediction Center MORPHing technique Real Time (CMORPH-RT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Dynamic Infrared Rain rate Now (PDIR-Now) to identify the optimal integration strategies to improve the extreme rainfall estimation during Super Typhoon Yagi (September, 2024) in Hanoi, Vietnam, using validation data from 25 ground stations. In-depth analysis of three extreme rainfall series during Typhoon Yagi (6–9 September 2024), examining 93 extreme rainfall events at the 95th percentile precipitation threshold (R95p = 21.78 mm/h), combined with statistics at lower percentile thresholds (R1p, R5p, R10p, and R90p) and upper percentile threshold (R99p), revealed IMERG-Early best captured the peak rainfall, CMORPH-RT achieved highest total rainfall accuracy, while PDIR-Now offered the best spatial analysis. However, limitations included time lags, inability to detect rainfall events above R99p (41.69 mm/hour), and low detection rates (8–12%) in areas first impacted by the typhoon. This study identified that integration strategies combining different satellite products based on their strengths at specific time scales showed potential for improved rainfall estimation: PDIR-Now with IMERG-Early (1–3 h) and IMERG-Early with CMORPH-RT (6–12 h). These integration approaches accounted for each product’s unique capabilities in capturing different aspects of extreme rainfall during super typhoon events. |
| format | Article |
| id | doaj-art-3d19a57786fd42c5a0578c7923764fc0 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-3d19a57786fd42c5a0578c7923764fc02025-08-20T01:49:28ZengMDPI AGRemote Sensing2072-42922025-04-01179159810.3390/rs17091598Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024)Viet Duc Nguyen0Nazak Rouzegari1Vu Dao2Fahad Almutlaq3Phu Nguyen4Soroosh Sorooshian5Department of Hydraulic Works and Construction (DHWC), Ministry of Agriculture and Environment (MAE), Hanoi 100000, VietnamCenter for Hydrometeorology and Remote Sensing (CHRS), Department of Civil and Environmental Engineering, University of California, Irvine (UCI), Irvine, CA 92697-2175, USACenter for Hydrometeorology and Remote Sensing (CHRS), Department of Civil and Environmental Engineering, University of California, Irvine (UCI), Irvine, CA 92697-2175, USADepartment of Geography, College of Humanities and Social Sciences, King Saud University, Riyadh 11451, Saudi ArabiaCenter for Hydrometeorology and Remote Sensing (CHRS), Department of Civil and Environmental Engineering, University of California, Irvine (UCI), Irvine, CA 92697-2175, USACenter for Hydrometeorology and Remote Sensing (CHRS), Department of Civil and Environmental Engineering, University of California, Irvine (UCI), Irvine, CA 92697-2175, USAThis study aimed to compare and evaluate three satellite-based precipitation estimation products: Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Early Run (IMERG-Early Run), Climate Prediction Center MORPHing technique Real Time (CMORPH-RT), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Dynamic Infrared Rain rate Now (PDIR-Now) to identify the optimal integration strategies to improve the extreme rainfall estimation during Super Typhoon Yagi (September, 2024) in Hanoi, Vietnam, using validation data from 25 ground stations. In-depth analysis of three extreme rainfall series during Typhoon Yagi (6–9 September 2024), examining 93 extreme rainfall events at the 95th percentile precipitation threshold (R95p = 21.78 mm/h), combined with statistics at lower percentile thresholds (R1p, R5p, R10p, and R90p) and upper percentile threshold (R99p), revealed IMERG-Early best captured the peak rainfall, CMORPH-RT achieved highest total rainfall accuracy, while PDIR-Now offered the best spatial analysis. However, limitations included time lags, inability to detect rainfall events above R99p (41.69 mm/hour), and low detection rates (8–12%) in areas first impacted by the typhoon. This study identified that integration strategies combining different satellite products based on their strengths at specific time scales showed potential for improved rainfall estimation: PDIR-Now with IMERG-Early (1–3 h) and IMERG-Early with CMORPH-RT (6–12 h). These integration approaches accounted for each product’s unique capabilities in capturing different aspects of extreme rainfall during super typhoon events.https://www.mdpi.com/2072-4292/17/9/1598remote sensingreal-time monitoringsuper typhoonYagiextreme rainfallsatellite precipitation estimation |
| spellingShingle | Viet Duc Nguyen Nazak Rouzegari Vu Dao Fahad Almutlaq Phu Nguyen Soroosh Sorooshian Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) Remote Sensing remote sensing real-time monitoring super typhoon Yagi extreme rainfall satellite precipitation estimation |
| title | Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) |
| title_full | Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) |
| title_fullStr | Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) |
| title_full_unstemmed | Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) |
| title_short | Comparative Analysis of Satellite-Based Precipitation Products During Extreme Rainfall from Super Typhoon Yagi in Hanoi, Vietnam (September 2024) |
| title_sort | comparative analysis of satellite based precipitation products during extreme rainfall from super typhoon yagi in hanoi vietnam september 2024 |
| topic | remote sensing real-time monitoring super typhoon Yagi extreme rainfall satellite precipitation estimation |
| url | https://www.mdpi.com/2072-4292/17/9/1598 |
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