Abstract
This paper describes the access to, and the content, characteristics, and potential applications of the tropical cyclone (TC) database that is maintained and actively developed by the China Meteorological Administration, with the aim of facilitating its use in scientific research and operational services. This database records data relating to all TCs that have passed through the western North Pacific (WNP) and South China Sea (SCS) since 1949. TC data collection has expanded over recent decades via continuous TC monitoring using remote sensing and specialized field detection techniques, allowing collation of a multi-source TC database for the WNP and SCS that covers a long period, with wide coverage and many observational elements. This database now comprises a wide variety of information related to TCs, such as historical or real-time locations (i.e., best track and landfall), intensity, dynamic and thermal structures, wind strengths, precipitation amounts, and frequency. This database will support ongoing research into the processes and patterns associated with TC climatic activity and TC forecasting.
Highlights
Tropical cyclones (TCs) are destructive weather sys- LU ET AL.tems that can generate severe natural disasters (Chen and Ding, 1979; Yu and Chen, 2019)
TC precipitation and wind dataset comprises six files containing the wind and precipitation generated by TCs between 1949 and 2018; and 3
The TC intensity category is classified into six levels [i.e., tropical depression (TD), tropical storm (TS), severe tropical storm (STS), typhoon (TY), severe typhoon (STY), and super typhoon (SuperTY)] according to the Chinese National Standard for Grade of Tropical Cyclones (Ying et al, 2014)
Summary
Since 1972, the Shanghai Typhoon Institute (STI) of the CMA has been responsible for compiling the annual TC data These datasets subsequently formed the basis for the development of a multi-source CMA TC database for the WNP including the SCS (hereafter WNP). Since 2000, many TC field experiments and TC observations have been carried out, and have increased the scope of observational data available from TCs and enriched the TC database (Zhao et al, 2009; Fang et al, 2013a, 2013b, 2015; Zhang et al, 2018, 2019) These observational data and spatial information are becoming increasingly abundant, with TC-related observational data, test data, and forecasts continuing to be accumulated. We introduce the CMA’s multisource TC database for the WNP and summarize its applications and prospects
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