Characteristics and Controlling Factors of Rapid Weakening of Tropical Cyclones After Reaching Their Intensity Peaks Over the Western North Pacific

被引:4
作者
Zhou, Yanchen [1 ,2 ,3 ]
Zhan, Ruifen [1 ,2 ,4 ]
Wang, Yuqing [5 ,6 ]
Wu, Zhiwei [1 ,7 ]
Chen, Guanghua [8 ]
Wang, Lan [2 ]
机构
[1] Fudan Univ, Shanghai Frontiers Sci Ctr Atmosphere Ocean Inter, Inst Atmospher Sci, Dept Atmospher & Ocean Sci, Shanghai, Peoples R China
[2] Fujian Key Lab Severe Weather, Fuzhou, Peoples R China
[3] Shanghai Meteorol Serv Ctr, Shanghai, Peoples R China
[4] China Meteorol Adm, Shanghai Typhoon Inst, Shanghai, Peoples R China
[5] Univ Hawaii Manoa, Int Pacific Res Ctr, Honolulu, HI 96822 USA
[6] Univ Hawaii Manoa, Sch Ocean & Earth Sci & Technol, Dept Atmospher Sci, Honolulu, HI 96822 USA
[7] Fudan Univ, Big Data Inst Carbon Emiss & Environm Pollut, Shanghai, Peoples R China
[8] Chinese Acad Sci, Inst Atmospher Phys, Key Lab Cloud Precipitat Phys & Severe Storms, Beijing, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
tropical cyclone; western North Pacific; rapid weakening; growth rate; LARGE-SCALE CHARACTERISTICS; INTENSIFICATION; ATLANTIC; INITIALIZATION; PREDICTION; SCHEME; MODELS; INDEX;
D O I
10.1029/2022JD036697
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The sudden transition to rapid weakening immediately after a tropical cyclone (TC) reaches its intensity peak (hereafter TP-RW) is a challenge to operational TC intensity forecasts, but the characteristics and the controlling factors of the TP-RW have not been investigated so far. In this study, the main characteristics of the TP-RW events over the western North Pacific (WNP) and the corresponding key controlling factors and their relative importance are analyzed and quantified. Results show that about 2.5 TP-RW events occurred each year, which corresponds to about 10% of total TCs over the WNP during 1982-2018. The TP-RW events occurred in all months but peaked in fall and were the most likely to occur for TCs with intensities between 90 and 145 kt. The sea surface temperature, the TC maximum potential intensity and translational speed, the environmental vertical wind shear and relative humidity are key to the TP-RW. Four distinct clusters of the TP-RW events are identified based on their tracks using the K-means clustering algorithm. The relative contribution of each of the identified key factors to each cluster is quantified using the growth rate from the simplified dynamical system for TC intensity prediction developed by DeMaria. The reversal of the growth rate from positive to negative values is shown to be a good indicator of the TP-RW processes. Different clusters are predominantly controlled by different key factors. The findings from this study can help better understand TC intensity changes and improve TC intensity forecasts for such kind of RW.
引用
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页数:18
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