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

Yaokang Xu; Yichun Wei; Shiyu Wu

doi:10.62051/ae6g3g18

Authors

Yaokang Xu
Yichun Wei
Shiyu Wu

DOI:

https://doi.org/10.62051/ae6g3g18

Keywords:

Tropical Cyclone; EWM; TOPSIS; Emergence Index; Multidimensional Analysis.

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.

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References

[1] Jia Yanhong, Bai Ying, Zhai Luxin. Risk Assessment of Heavy Rainfall and Flooding in Guangxi Based on AHP-Entropy Weight Method [J]. Mapping and spatial geographic information, 2023, 46 (10): 13 - 17.

[2] LU Yaojian, LIU Hexiang, WANG Meng. Typhoon disaster risk assessment based on combined weights and fuzzy stochastic approach [J]. Fuzzy Systems and Mathematics, 2020, 34 (02): 151 - 163.

[3] Si Shoukui, Sun Xijing. Mathematical Modeling Algorithms and Applications [M]. Beijing: Defense Industry Press, 2021.

[4] Pan Jinlan, Xu Qingjuan, Liu Hexiang. Typhoon disaster risk assessment based on AHP-TOPSIS optimal combination assignment [J]. Journal of Nanning Normal University (Natural Science Edition), 2021, 38 (01): 60 - 67.

[5] Yang Mengyang. Comprehensive evaluation of disaster resilience in typhoon disaster scenarios [D]. Nanjing University, NJU, 2019.

[6] Chao Wen, Qian Xiaotao. Typhoon Disaster Vulnerability Evaluation and Premium Determination Based on Entropy Weight-TOPSIS Method--A Case Study of Fujian Province [J]. Fujian Finance, 2023 (03): 44 - 51.

[7] Liu Sheng. Study on slope stability prediction based on combined assignment-TOPSIS modeling [J]. Transportation Technology and Management, 2024, 5 (15): 7 - 9.

[8] FENG X, KLINGAMAN N P, HODGES K I. Poleward migration of western North Pacific tropical cyclones related to changes in cyclone seasonality [J]. Nat Commun, 2021, 12 (1): 6210.

[9] ZHONG J, DU H, WU Y, et al. Westward Migration of Tropical Cyclone Activity in the Western North Pacific during 1982 – 2020: Features and Possible Causes [J]. Journal of Meteorological Research, 2024, 38 (1): 1 - 9.

[10] Nie Gaozhen, Qian Qifeng. Overview of typhoon activity in the Northwest Pacific and South China Sea in 2022 [J]. Journal of Marine Meteorology, 2023, 43 (04): 99 - 109.

[11] Chen Luishou. Typhoon forecasting and its disasters [M]. Beijing: Meteorological Publishing House, 2012.

[12] NATH S, KOTAL S D, KUNDU P K. Application of Fuzzy Clustering Technique for Analysis of North Indian Ocean Tropical Cyclone Tracks[J]. Tropical Cyclone Research and Review, 2015, 4 (3): 110 - 123.

[13] GU Y, WU L, ZHAN R, et al. Climatology of developing and non-developing disturbances for tropical cyclone genesis over the western North Pacific[J]. Terrestrial, Atmospheric and Oceanic Sciences, 2022, 33 (1).

[14] TAN C, ZHAO H, KLOTZBACH P J, et al. Interdecadal shifts in tropical sea surface temperature modulate autumn tropical cyclone genesis over the western North Pacific [J]. Atmospheric research, 2024, 306: 107473.

[15] LIU W. Diversity of the Pacific-Japan Pattern and Its Influences on Northwest Pacific Tropical Cyclone Activity [D]. North Carolina: The University of North Carolina at Chapel Hill, 2020.

[16] van WESTEN R M, DIJKSTRA H A, BLOEMENDAAL N. Mechanisms of tropical cyclone response under climate change in the community earth system model [J]. Clim Dyn, 2023, 61 (5-6): 2269 - 2284.

[17] SONG J, KLOTZBACH P J, WEI N, et al. What caused the record-low frequency of western North Pacific tropical cyclones in autumn 2023? [J]. Geoscience Letters, 2024, 11 (1).