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

作     者：Chen MA Tim LI Chen MA;Tim LI

作者机构：Jiangsu Meteorological ObservatoryJiangsu Meteorological BureauNanjing 210019China Key Laboratory of Meteorological DisasterMinistry of Education(KLME)/Joint International Research Laboratory of Climate and Environmental Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)NanjingUniversityof Information Science&TechnologyNanjing210044China International Pacific Research Center and Department of Atmospheric SciencesSchool of Ocean and Earth Science and TechnologyUniversityofHawaiiHI96822USA Key Laboratory of Transportation MeteorologyChina Meteorological AdministrationNanjing 210019China 

出 版 物：《Journal of Meteorological Research》 (气象学报（英文版）)

年 卷 期：2022年第36卷第5期

页      面：691-702页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 0706[理学-大气科学] 

基　　金：Supported by the National Natural Science Foundation of China(42088101) US National Oceanic and Atmospheric Administration(NA18OAR4310298) Jiangsu Meteorological Bureau(KQ202205)。 

主　　题：tropical cyclone rapid intensification prediction model 

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°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).