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Dynamical‐statistical long‐term prediction for tropical cyclone landfalls in East Asia
Author(s) -
Kim SoHee,
Ahn JoongBae,
Sun Jianqi
Publication year - 2021
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.7382
Subject(s) - landfall , climatology , typhoon , predictability , east asia , tropical cyclone , environmental science , meteorology , data assimilation , east coast , geography , china , statistics , geology , mathematics , physical geography , archaeology
This study develops a statistical‐dynamical seasonal typhoon forecast model (SDTFM) that utilizes the statistical correlation between East Asia (EA) tropical cyclone (TC) landfall and atmospheric circulation predicted by a coupled general circulation model for seasonal prediction and its predictability is verified. A total of 40 ensemble members produced through different data assimilation and time‐lag methods introduced as a way to reduce the initial condition error and model uncertainty enabled the development of the new SDTFM. According to the results, the SDTFM developed in this study showed significant predictability in TC landfall prediction when using the month of May for the initial conditions for the entire East Asia (EEA) and its three sub‐domains: Northern East Asia (NEA), Middle East Asia (MEA), and Southern East Asia (SEA). The predicted TC season is July–September (JAS), and only for SEA, including South China, the Philippines, and Vietnam, it is July–November (JASON) considering the relatively long landfall period. The models developed for each domain significantly predict the interannual variability of TC landfall at the 99% confidence level. The cross‐validated results are still significant at the 99% confidence level in NEA and SEA and the 95% confidence level in MEA and EEA.