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Seasonal prediction of accumulated tropical cyclone kinetic energy around Taiwan and the sources of the predictability
Author(s) -
Lu MongMing,
Lee ChingTeng,
Wang Bin
Publication year - 2012
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.3634
Subject(s) - climatology , typhoon , predictability , extratropical cyclone , environmental science , tropical cyclone , sea surface temperature , anomaly (physics) , subtropical ridge , monsoon , precipitation , cyclone (programming language) , rainband , geology , geography , meteorology , physics , quantum mechanics , field programmable gate array , computer science , computer hardware , condensed matter physics
Tropical cyclone ( TC ) is the most hazardous high‐impact weather system in Taiwan. TC seasonal prediction affecting the Taiwan area is extremely challenging because of the relatively small target area and highly variable TC genesis locations and tracks. This paper presents an empirical seasonal forecast model for predicting TC activity around Taiwan during the peak season (June through September). The predictand is the accumulative cyclone kinetic energy ( ACE ) of the invading TCs within the ‘influence domain’ defined as an area extending 300 km away from the coast. The predictors consist of the sea surface temperatures ( SSTs ) and their tendency over the tropical Indo‐Pacific Ocean and the sea level pressure ( SLP ) over extratropical East Asia during the spring season. The source of the predictability is rooted in the spring to summer evolution of the monsoon subtropical high‐ ENSO system in association with the evolution of the Indo‐Pacific SST anomalies. When the spring SST anomaly is warm over equatorial western Pacific, while it is cold but with a warming tendency over tropical South Indian Ocean, the coupled atmospheric and oceanic anomalies evolve into a favourable large scale condition conducive for active typhoon occurrence in the Taiwan area during the ensuing summer. The empirical prediction model presented in this paper has important implications for predicting TCs affecting a much larger area covering southeast China and the East China Sea ( r = 0.97).