Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods
Summary: Tropical cyclone (TC) genesis mechanisms remain debated, complicating predictions of climate change impacts. This study uses principal-component analysis (PCA), confidence ellipses, and correlation circles to analyze TC genesis environments across ocean basins. Results show that TC genesis...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004224029419 |
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| author | QiFeng Qian YeFeng Chen XiaoJing Jia Hao Ma Wei Dong |
| author_facet | QiFeng Qian YeFeng Chen XiaoJing Jia Hao Ma Wei Dong |
| author_sort | QiFeng Qian |
| collection | DOAJ |
| description | Summary: Tropical cyclone (TC) genesis mechanisms remain debated, complicating predictions of climate change impacts. This study uses principal-component analysis (PCA), confidence ellipses, and correlation circles to analyze TC genesis environments across ocean basins. Results show that TC genesis is basin dependent, except in the North Atlantic (NA), where absolute vorticity primarily drives differences in genesis locations. Ocean basins are categorized into three groups based on PCA, and three MaxEnt machine learning (ML) models are developed to predict TC genesis under future scenarios. The ML models consistently project robust basin-specific TC genesis trends, demonstrating their utility in such studies. A multivariate environmental similarity analysis indicates significant climate change impacts on TC genesis environments globally, with the weakest changes in the NA. These findings underscore the critical role of absolute vorticity in TC genesis and highlight basin-specific differences in future environmental changes. |
| format | Article |
| id | doaj-art-c8e573c4e0c148da997a7df8543789d3 |
| institution | Kabale University |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-c8e573c4e0c148da997a7df8543789d32025-01-24T04:45:34ZengElsevieriScience2589-00422025-02-01282111714Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methodsQiFeng Qian0YeFeng Chen1XiaoJing Jia2Hao Ma3Wei Dong4Zhejiang Institute of Meteorological Science, HangZhou, Zhejiang, China; Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, HangZhou, Zhejiang, China; Corresponding authorZhejiang Institute of Meteorological Science, HangZhou, Zhejiang, ChinaKey Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, HangZhou, Zhejiang, China; Corresponding authorZhejiang Climate Center, HangZhou, Zhejiang, ChinaKey Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, HangZhou, Zhejiang, ChinaSummary: Tropical cyclone (TC) genesis mechanisms remain debated, complicating predictions of climate change impacts. This study uses principal-component analysis (PCA), confidence ellipses, and correlation circles to analyze TC genesis environments across ocean basins. Results show that TC genesis is basin dependent, except in the North Atlantic (NA), where absolute vorticity primarily drives differences in genesis locations. Ocean basins are categorized into three groups based on PCA, and three MaxEnt machine learning (ML) models are developed to predict TC genesis under future scenarios. The ML models consistently project robust basin-specific TC genesis trends, demonstrating their utility in such studies. A multivariate environmental similarity analysis indicates significant climate change impacts on TC genesis environments globally, with the weakest changes in the NA. These findings underscore the critical role of absolute vorticity in TC genesis and highlight basin-specific differences in future environmental changes.http://www.sciencedirect.com/science/article/pii/S2589004224029419Natural sciencesEarth sciencesApplied sciences |
| spellingShingle | QiFeng Qian YeFeng Chen XiaoJing Jia Hao Ma Wei Dong Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods iScience Natural sciences Earth sciences Applied sciences |
| title | Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| title_full | Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| title_fullStr | Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| title_full_unstemmed | Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| title_short | Basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| title_sort | basin dependencies of tropical cyclone genesis environment and possible future changes revealed by machine learning methods |
| topic | Natural sciences Earth sciences Applied sciences |
| url | http://www.sciencedirect.com/science/article/pii/S2589004224029419 |
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