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CLASSIFYING WESTERN NORTH PACIFIC TROPICAL CYCLONES BY PHYSICAL INDEX SYSTEM
引用本文:颜东谊,徐 奎,马 超,马满仓. CLASSIFYING WESTERN NORTH PACIFIC TROPICAL CYCLONES BY PHYSICAL INDEX SYSTEM[J]. 热带气象学报(英文版), 2018, 24(2): 142-150. DOI: 10.16555/j.1006-8775.2018.02.003
作者姓名:颜东谊  徐 奎  马 超  马满仓
摘    要:The classification of tropical cyclones (TCs) is significant to obtain their temporal and spatial variation characteristics in the context of dramatic-changing global climate. A new TCs clustering method by using K-means clustering algorithm with nine physical indexes is proposed in the paper. Each TC is quantified into an 11-dimensional vector concerning trajectory attributes, time attributes and power attributes. Two recurving clusters (cluster A and E) and three straight-moving clusters (cluster B, C and D) are categorized from the TC best-track dataset of the western North Pacific (WNP) over the period of 1949-2013, and TCs’ properties have been analyzed and compared in different aspects. The calculation results of coefficient variation (CV) and Nash-Sutcliffe efficiency (NSE) reveal a high level of intra-cluster cohesiveness and inter-cluster divergence, which means that the physical index system could serve as a feasible method of TCs classification. The clusters are then analyzed in terms of trajectory, lifespan, seasonality, trend, intensity and Power Dissipation Index (PDI). The five classified clusters show distinct features in TCs’ temporal and spatial development discipline. Moreover, each cluster has its individual motion pattern, variation trend, influence region and impact degree.

关 键 词:tropical cyclone   physical index   K-means clustering   Nash-Sutcliffe efficiency   inter-cluster divergence   intra-cluster cohesiveness   power dissipation index
修稿时间:2018-03-29

CLASSIFYING WESTERN NORTH PACIFIC TROPICAL CYCLONES BY PHYSICAL INDEX SYSTEM
YAN Dong-yi,XU Kui,MA Chao and MA Man-cang. CLASSIFYING WESTERN NORTH PACIFIC TROPICAL CYCLONES BY PHYSICAL INDEX SYSTEM[J]. Journal of Tropical Meteorology, 2018, 24(2): 142-150. DOI: 10.16555/j.1006-8775.2018.02.003
Authors:YAN Dong-yi  XU Kui  MA Chao  MA Man-cang
Abstract:The classification of tropical cyclones(TCs) is significant to obtaining their temporal and spatial variation characteristics in the context of dramatic-changing global climate. A new TCs clustering method by using K-means clustering algorithm with nine physical indexes is proposed in the paper. Each TC is quantified into an 11-dimensional vector concerning trajectory attributes, time attributes and power attributes. Two recurving clusters(cluster A and E)and three straight-moving clusters(cluster B, C and D) are categorized from the TC best-track dataset of the western North Pacific(WNP) over the period of 1949-2013, and TCs' properties have been analyzed and compared in different aspects. The calculation results of coefficient variation(CV) and Nash-Sutcliffe efficiency(NSE) reveal a high level of intra-cluster cohesiveness and inter-cluster divergence, which means that the physical index system could serve as a feasible method of TCs classification. The clusters are then analyzed in terms of trajectory, lifespan, seasonality, trend,intensity and Power Dissipation Index(PDI). The five classified clusters show distinct features in TCs' temporal and spatial development discipline. Moreover, each cluster has its individual motion pattern, variation trend, influence region and impact degree.
Keywords:tropical cyclone   physical index   K-means clustering   Nash-Sutcliffe efficiency   inter-cluster divergence   intra-cluster cohesiveness   power dissipation index
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