Evaluation of Western North Pacific Typhoon Track Forecasts in Global and Regional Models during the 2021 Typhoon Season

被引:4
作者
Chen, Guomin [1 ,2 ,3 ]
Li, Tim [1 ,4 ]
Yang, Mengqi [2 ,3 ]
Zhang, Xiping [2 ,3 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Joint Int Res Lab Climate & Environm Change, Key Lab Meteorol Disaster,Minist Educ, Nanjing 210044, Peoples R China
[2] China Meteorol Adm, Shanghai Typhoon Inst, Shanghai 200030, Peoples R China
[3] Asia Pacific Typhoon Collaborat Res Ctr, Shanghai 200030, Peoples R China
[4] Univ Hawaii Manoa, Dept Atmospher Sci, SOEST, Honolulu, HI 96822 USA
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 direct position errors; global model; regional model; track forecast performance; TROPICAL CYCLONE FORECASTS; HURRICANE WEATHER RESEARCH;
D O I
10.3390/atmos14030499
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The track forecasts of tropical cyclones (TC) in the western North Pacific (WNP) basin during 2021 typhoon season with five global models and four regional models are evaluated here. The results show that the average direct position errors (DPEs) of the global and regional models are approximately 80, 150, 200, 300, and 400 km at 24 h, 48 h, 72 h, 96 h, and 120 h lead-times, respectively. The European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) achieved the best track forecast performance at each lead among the five global models. Among the four regional models, The China Meteorological Administration Tropical Regional Atmosphere Model for the South China Sea (CMA-TRAMS) attained the smallest DPEs within a 72 h lead, while The Hurricane Weather Research and Forecasting (HWRF) achieved the best track forecast performance at 96 h and 120 h leads. Most of the models produced an obvious westward systematic bias on track forecast from a 24 h to a 120 h lead. Further correlation and cluster analyses indicate that initial TC intensity and size and environmental steering flow can be regarded as good predictors for TC DPEs. TCs with a stronger initial intensity, a bigger initial size, and a larger environmental steering flow in general attain a smaller DPE, and the improvements may go up to 36% at short lead-time.
引用
收藏
页数:17
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