A Daily Temperature Dataset over China and Its Application in Validating a RCM Simulation

被引:192
作者
Xu Ying [1 ]
Gao Xuejie [1 ]
Shen Yan [2 ]
Xu Chonghai [1 ]
Shi Ying [1 ]
Giorgi, F. [3 ]
机构
[1] China Meteorol Adm, Natl Climate Ctr, Beijing 100081, Peoples R China
[2] China Meteorol Adm, Natl Meteorol Informat Ctr, Beijing 100081, Peoples R China
[3] Abdus Salam Int Ctr Theoret Phys, Trieste, Italy
关键词
interpolation; temperature; regional climate model; China; SPACE-TIME CLIMATE; GAUGE OBSERVATIONS; PRECIPITATION; RESOLUTION; VARIABILITY; MODEL;
D O I
10.1007/s00376-009-9029-z
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper describes the construction of a 0.5 degrees x 0.5 degrees daily temperature dataset for the period of 1961 2005 over mainland China for the purpose of climate model validation. The dataset is based on the interpolation from 751 observing stations in China and comprises 3 variables: daily mean, minimum, and maximum temperature. The "anomaly approach" is applied in the interpolation. The gridded climatology of 1971-2000 is first calculated and then a gridded daily anomaly for 1961-2005 is added to the climatology to obtain the final dataset. Comparison of the dataset with CRU (Climatic Research Unit) observations at the monthly scale shows general agreement between the two datasets. The differences found can be largely attributed to the introduction of observations at new stations. The dataset shows similar interannual variability as does CRU data over North China and eastern part of the Tibetan Plateau, but with a slightly larger linear trend. The dataset is employed to validate the simulation of three extreme indices based on daily mean, minimum, and maximum temperature by a high-resolution regional climate model. Results show that the model reproduces these indices well. The data are available at the National Climate Center of China Meteorological Administration, and a coarser resolution (1 degrees x 1 degrees) version can be accessed via the World Wide Web.
引用
收藏
页码:763 / 772
页数:10
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