Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations
This study analyzed the sensitivity of rainfall patterns in South China and the Indochina Peninsula (ICP) using statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry seasons to identify hotspots sensitive to ocean war...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/9/1458 |
| _version_ | 1797568869574901760 |
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| author | Jong-Suk Kim Phetlamphanh Xaiyaseng Lihua Xiong Sun-Kwon Yoon Taesam Lee |
| author_facet | Jong-Suk Kim Phetlamphanh Xaiyaseng Lihua Xiong Sun-Kwon Yoon Taesam Lee |
| author_sort | Jong-Suk Kim |
| collection | DOAJ |
| description | This study analyzed the sensitivity of rainfall patterns in South China and the Indochina Peninsula (ICP) using statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry seasons to identify hotspots sensitive to ocean warming in the Indo-Pacific sector. The rainfall variability was amplified by combined and/or independent effects of the El Niño–Southern Oscillation and the Indian Ocean Dipole (IOD). During the years of El Niño and a positive phase of the IOD, rainfall is less than usual in Thailand, Cambodia, southern Laos, and Vietnam. Conversely, during the years of La Niña and a negative phase of the IOD, rainfall throughout the ICP is above normal, except in parts of central Laos, northern Vietnam, and South China. This study also simulated the change of ICP rainfall in the wet and dry seasons with intentional IOD changes and verified IOD-sensitive hotspots through quantitative analysis. The results of this study provide a clear understanding both of the sensitivity of regional precipitation to the IOD and of the potential future impact of statistical changes regarding the IOD in terms of understanding regional impacts associated with precipitation in changing climates. |
| first_indexed | 2024-03-10T20:02:59Z |
| format | Article |
| id | doaj.art-f7814b932da341e3b5b9444fdd94047c |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T20:02:59Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f7814b932da341e3b5b9444fdd94047c2023-11-19T23:29:09ZengMDPI AGRemote Sensing2072-42922020-05-01129145810.3390/rs12091458Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical SimulationsJong-Suk Kim0Phetlamphanh Xaiyaseng1Lihua Xiong2Sun-Kwon Yoon3Taesam Lee4State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaState Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaDepartment of Safety and Disaster Prevention Research, Seoul Institute of Technology, Seoul 03909, KoreaDepartment of Civil Engineering, ERI, Gyeongsang National University, 501 Jinju-daero, Jinju, Gyeongnam 660-701, KoreaThis study analyzed the sensitivity of rainfall patterns in South China and the Indochina Peninsula (ICP) using statistical simulations of observational data. Quantitative changes in rainfall patterns over the ICP were examined for both wet and dry seasons to identify hotspots sensitive to ocean warming in the Indo-Pacific sector. The rainfall variability was amplified by combined and/or independent effects of the El Niño–Southern Oscillation and the Indian Ocean Dipole (IOD). During the years of El Niño and a positive phase of the IOD, rainfall is less than usual in Thailand, Cambodia, southern Laos, and Vietnam. Conversely, during the years of La Niña and a negative phase of the IOD, rainfall throughout the ICP is above normal, except in parts of central Laos, northern Vietnam, and South China. This study also simulated the change of ICP rainfall in the wet and dry seasons with intentional IOD changes and verified IOD-sensitive hotspots through quantitative analysis. The results of this study provide a clear understanding both of the sensitivity of regional precipitation to the IOD and of the potential future impact of statistical changes regarding the IOD in terms of understanding regional impacts associated with precipitation in changing climates.https://www.mdpi.com/2072-4292/12/9/1458rainfall variabilityIndian Ocean Dipole (IOD)El Niño–Southern Oscillation (ENSO)intentional statistical simulation |
| spellingShingle | Jong-Suk Kim Phetlamphanh Xaiyaseng Lihua Xiong Sun-Kwon Yoon Taesam Lee Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations Remote Sensing rainfall variability Indian Ocean Dipole (IOD) El Niño–Southern Oscillation (ENSO) intentional statistical simulation |
| title | Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations |
| title_full | Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations |
| title_fullStr | Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations |
| title_full_unstemmed | Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations |
| title_short | Remote Sensing-Based Rainfall Variability for Warming and Cooling in Indo-Pacific Ocean with Intentional Statistical Simulations |
| title_sort | remote sensing based rainfall variability for warming and cooling in indo pacific ocean with intentional statistical simulations |
| topic | rainfall variability Indian Ocean Dipole (IOD) El Niño–Southern Oscillation (ENSO) intentional statistical simulation |
| url | https://www.mdpi.com/2072-4292/12/9/1458 |
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