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An Objective Synoptic Analysis Technique for the Identification of Tropical Cyclone Remote Precipitation in China and Its Application

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摘要 At present,the identification of tropical cyclone remote precipitation(TRP)requires subjective participation,leading to inconsistent results among different researchers despite adopting the same identification standard.Thus,establishing an objective identification method is greatly important.In this study,an objective synoptic analysis technique for TRP(OSAT_TRP)is proposed to identify TRP using daily precipitation datasets,historical tropical cyclone(TC)track data,and the ERA5 reanalysis data.This method includes three steps:first,independent rain belts are separated,and those that might relate to TCs'remote effects are distinguished according to their distance from the TCs.Second,the strong water vapor transport belt from the TC is identified using integrated horizontal water vapor transport(IVT).Third,TRP is distinguished by connecting the first two steps.The TRP obtained through this method can satisfy three criteria,as follows:1)the precipitation occurs outside the circulation of TCs,2)the precipitation is affected by TCs,and 3)a gap exists between the TRP and TC rain belt.Case diagnosis analysis,compared with subjective TRP results and backward trajectory analyses using HYSPLIT,indicates that OSAT_TRP can distinguish TRP even when multiple TCs in the Northwest Pacific are involved.Then,we applied the OSAT_TRP to select typical TRPs and obtained the synoptic-scale environments of the TRP through composite analysis.
出处 《Journal of Ocean University of China》 2025年第1期13-30,共18页 中国海洋大学学报(英文版)
基金 supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_1136) the National Natural Scientific Foundation of China(No.42275037) the Basic Research Fund of CAMS(No.2023Z016) the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202202) supported by the Jiangsu Collaborative Innovation Center for Climate Change。
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