An Empirical Model of Tropical Cyclone Intensity Forecast in the Western North Pacific

被引:3
|
作者
Ma, Chen [1 ,2 ,5 ]
Li, Tim [2 ,3 ,4 ]
机构
[1] Jiangsu Meteorol Bur, Jiangsu Meteorol Observ, Nanjing 210019, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Key Lab Meteorol Disaster,Minist Educ KLME, Joint Int Res Lab Climate & Environm Change ILCEC, Nanjing 210044, Peoples R China
[3] Univ Hawaii, Int Pacific Res Ctr, Honolulu, HI 96822 USA
[4] Univ Hawaii, Sch Ocean & Earth Sci & Technol, Dept Atmospher Sci, Honolulu, HI 96822 USA
[5] China Meteorol Adm, Key Lab Transportat Meteorol, Nanjing 210019, Peoples R China
基金
中国国家自然科学基金; 美国海洋和大气管理局;
关键词
tropical cyclone; rapid intensification; prediction model; LARGE-SCALE CHARACTERISTICS; RAPID INTENSIFICATION; ATLANTIC;
D O I
10.1007/s13351-022-2016-3
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The relative impact of environmental parameters on tropical cyclone (TC) intensification rate (IR) was investigated through a box difference index (BDI) method, using TC best track data from Joint Typhoon Warning Center and environmental fields from the NCEP final analysis data over the western North Pacific (WNP) during 2000-2018. There are total 6307 TC samples with a 6-h interval, of which about 14% belong to rapid intensification (RI) category. The analysis shows that RI occurs more frequently with higher environmental sea surface temperature, higher oceanic heat content, and lower upper-tropospheric temperature. A moderate easterly shear is more favorable for TC intensification. TC intensification happens mostly equatorward of 20 degrees N while TC weakening happens mostly when TCs are located in the northwest of the basin. Mid-tropospheric relative humidity and vertical velocity are good indicators separating the intensification and non-intensification groups. A statistical model for TC intensity prediction was constructed based on six environmental predictors, with or without initial TC intensity. Both models are skillful based on Brier skill score (BSS) relative to climatology and in comparison with other statistical models, for both a training period (2000-2018) and an independent forecast period (2019-2020).
引用
收藏
页码:691 / 702
页数:12
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