Factors Affecting the Weakening Rate of Tropical Cyclones over the Western North Pacific

被引:24
|
作者
Fei, Rong [1 ,2 ,3 ,4 ]
Xu, Jing [1 ]
Wang, Yuqing [1 ,3 ,4 ]
Yang, Chi [5 ]
机构
[1] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, China Meteorol Adm, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China
[3] Univ Hawaii Manoa, Int Pacific Res Ctr, Honolulu, HI 96822 USA
[4] Univ Hawaii Manoa, Dept Atmospher Sci, Honolulu, HI 96822 USA
[5] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, 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
VERTICAL WIND SHEAR; ENVIRONMENTAL DYNAMICAL CONTROL; HURRICANE INTENSITY; POTENTIAL INTENSITY; MAXIMUM INTENSITY; PART I; ATLANTIC; EYEWALL; INTENSIFICATION; EVOLUTION;
D O I
10.1175/MWR-D-19-0356.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
In this study, based on the 6-hourly tropical cyclone (TC) best track data and the ERA-Interim reanalysis data, statistical analyses as well as a machine learning approach, XGBoost, are used to identify and quantify factors that affect the overwater weakening rate (WR) of TCs over the western North Pacific (WNP) during 1980-2017. Statistical analyses show that the TC rapid weakening events usually occur when intense TCs cross regions with a sharp decrease in sea surface temperature (DSST) with relatively faster eastward or northward translational speeds, and move into regions with large environmental vertical wind shear (VWS) and dry conditions in the upshear-left quadrant. Results from XGBoost indicate that the relative intensity of TC (TC intensity normalized by its maximum potential intensity), DSST, and VWS are dominant factors determining TC WR, contributing 26.0%, 18.3%, and 14.9% to TC WR, and 9, 5, and 5ms(-1) day(-1) to the variability of TC WR, respectively. Relative humidity in the upshear-left quadrant of VWS, zonal translational speed, divergence at 200 hPa, and meridional translational speed contribute 12.1%, 11.8%, 8.8%, and 8.1% to TC WR, respectively, but only contribute 2-3m s(-1) day(-1) to the variability of TC WR individually. These findings suggest that the improved accurate analysis and prediction of the dominant factors may lead to substantial improvements in the prediction of TC WR.
引用
收藏
页码:3693 / 3712
页数:20
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