主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Journal of Meteorology and Environment ›› 2016, Vol. 32 ›› Issue (6): 94-101.doi: 10.3969/j.issn.1673-503X.2016.06.012

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Integration and preliminary quality control of global surface hourly temperature and precipitation data

YU Yang1, ZHU Chen2, ZHAO Qi2, XU Wen-hui2, YANG Su2, JIANG Hui2, LI Qing-xiang2, SHEN Qiu-yu3   

  1. 1. Liaoning Meteorological Information Center, Shenyang 110016, China;
    2. National Meteorological Information Center, Beijing 100081, China;
    3. Liaoning Meteorological Office, Shenyang 110016, China
  • Received:2016-08-19 Revised:2016-11-02 Online:2016-12-31 Published:2016-12-31

Abstract: Global surface temperature and precipitation data are the foundation of research on climate change,and the hourly observational data are the important basis of climate monitoring.Based on two kinds of global surface data products such as the Integrated Surface Hourly Database (ISD)and the Global Transmission System (GTS)from U.S.National Climatic Data Center,the hourly temperature and precipitation data were integrated in real time.The integrated data were processed with preliminary quality control using methods of spatial consistency checks,internal consistency checks,boundary climate checks,and extreme climate checks,and eventually formed a real-time updated datasets of global surface hourly temperature and precipitation.The results show that the integrated surface temperature and precipitation data since 2015 contain hourly data from 11,990 stations on global that almost cover the whole world.Compared to the original data without integration,the density of stations and the amount of meteorological elements in all regions from the integrated dataset increase significantly,especially in regions of Asia,Europe,and North America.The accuracy and suspected error rate of integrated data is 94.4% and 5.6%,respectively.The data with suspected error mainly exist in the regions of northeast Europe,Asia,and China,and the internal consistency conflict and beyond the climate boundary limit value are main reasons for suspect error of data.

Key words: Hourly data, Air temperature, Precipitation, Data integration, Quality control

CLC Number: