A Study on Tropical Cyclone Genesis Characteristics in the Northwest Pacific Based on Multidimensional Analysis Using EWM and TOPSIS Methods

Against the backdrop of global climate change and data inflation, exploring new technologies to handle the growing amount of meteorological data effectively is crucial to enhancing global disaster prevention and mitigation capabilities and advancing climate research. This study investigates seasonal and regional variations in tropical cyclone (TC) genesis in the Northwest Pacific, using a multidimensional analysis of TCs from 2022 and 2023. Using the entropy weight method (EWM) and TOPSIS method combined with five essential environmental and storm predictors, this study quantitatively assesses the potential of TC generation, i.e., the Tropical Cyclone Emergence Index (TCEI), in different regions of the northwestern Pacific Ocean. The results, such as 0.7750 and 0.4624 for other areas in May 2023, show that TC generation peaks in summer and weakens significantly in winter. It is also found that the TC emergence indices of different regions in the same month vary significantly, which indicates that the climatic conditions for TC generation are more complicated and diversified. The findings of this study not only provide a reference for improving the regional meteorological disaster warning capability and lay a foundation for further understanding the impact of climate change on TCs.

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Publication Details

Journal
Transactions on Environment Energy and Earth Sciences
Published
2024-11-26
DOI
https://doi.org/10.62051/ae6g3g18
Primary Topic
Diverse Topics in Contemporary Research
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article
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article

A Study on Tropical Cyclone Genesis Characteristics in the Northwest Pacific Based on Multidimensional Analysis Using EWM and TOPSIS Methods

Yaxing Wei, Yong Xu, Shiyu Wu
Transactions on Environment Energy and Earth Sciences
Diverse Topics in Contemporary Research
article

A Study on Tropical Cyclone Genesis Characteristics in the Northwest Pacific Based on Multidimensional Analysis Using EWM and TOPSIS Methods

Yaxing Wei, Yong Xu, Shiyu Wu
article en

Abstract

Against the backdrop of global climate change and data inflation, exploring new technologies to handle the growing amount of meteorological data effectively is crucial to enhancing global disaster prevention and mitigation capabilities and advancing climate research. This study investigates seasonal and regional variations in tropical cyclone (TC) genesis in the Northwest Pacific, using a multidimensional analysis of TCs from 2022 and 2023. Using the entropy weight method (EWM) and TOPSIS method combined with five essential environmental and storm predictors, this study quantitatively assesses the potential of TC generation, i.e., the Tropical Cyclone Emergence Index (TCEI), in different regions of the northwestern Pacific Ocean. The results, such as 0.7750 and 0.4624 for other areas in May 2023, show that TC generation peaks in summer and weakens significantly in winter. It is also found that the TC emergence indices of different regions in the same month vary significantly, which indicates that the climatic conditions for TC generation are more complicated and diversified. The findings of this study not only provide a reference for improving the regional meteorological disaster warning capability and lay a foundation for further understanding the impact of climate change on TCs.

Transactions on Environment Energy and Earth SciencesVol. 3
Shanghai Maritime University (CN)
Climate action
Openalex Percentile: Top 63%
Diverse Topics in Contemporary Research
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