A Potential Risk Index Dataset for Landfalling Tropical Cyclones over the Chinese Mainland(PRITC dataset V1.0)  

作　　者：Peiyan CHEN Hui YU Kevin K.W.CHEUNG Jiajie XIN Yi LU 

机构地区：[1]Shanghai Typhoon Institute,China Meteorological Administration,Shanghai 200030,China [2]Key Laboratory of Numerical Modeling for Tropical Cyclone of China Meteorological Administration,Shanghai 20030,China [3]The Joint Laboratory for Typhoon Forecasting Technique Applications between Shanghai Typhoon Institute and Wenzhou Meteorological Bureau,Wenzhou 325027,China [4]Climate and Atmospheric Science,NSW Department of Planning Industry and Environment,Sydney 2000,Australia

出　　处：《Advances in Atmospheric Sciences》2021年第10期1791-1802,共12页大气科学进展（英文版）

基　　金：This work has been supported by the National Key Research and Development Program of China(Grant No.2017YFC1501604);National Natural Science Foundations of China(Grant No.41875114);Shanghai Science&Technology Research Program(Grant No.19dz1200101);National Basic Research Program of China(Grant No.2015CB452806);Shanghai Sailing Program(Grant No.21YF1456900);Basic Research Projects of the Shanghai Typhoon Institute of the China Meteorological Administra-tion(Grant Nos.2020JB06,and 2021JB06).

摘　　要：A dataset entitled“A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland”(PRITC dataset V1.0)is described in this paper,as are some basic statistical analyses.Estimating the severity of the impacts of tropical cyclones(TCs)that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study,including an index combining TC-induced precipitation and wind(IPWT)and further information,such as the corresponding category level(CAT_IPWT),an index of TC-induced wind(IWT),and an index of TC-induced precipitation(IPT).The current version of the dataset includes TCs that made landfall from 1949-2018;the dataset will be extended each year.Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased,as embodied by the annual mean IPWT values,and increases in TC-induced precipitation are the main contributor to this increase.TC Winnie(1997)and TC Bilis(2006)were the two TCs with the highest IPWT and IPT values,respectively.The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.

关 键 词：tropical cyclone RISK DATASET China 

分 类 号：P444[天文地球—大气科学及气象学]