Adjusted Urbanization Bias Monthly Temperature Dataset based on the Records from the National Meteorological Stations of China (1961-2015)

WEN Kangmin1REN Guoyu1,2LI Jiao3ZHANG Aiying4REN Yuyu2SUN Xiubao5ZHOU Yaqing6

1 Department of Atmospheric Sciences，School of Environmental Studies，China University of Geosciences (Wuhan)，Wuhan 430074，China2 National Climate Center，China Meteorological Administration，Beijing 100081，China3 Tieling Meteorological Bureau，Liaoning Province，Tieling 112000，China4 Beijing Meteorological Bureau，Beijing 100089，China5 South China Sea Institute of Oceanology，Chinese Academy of Sciences，Guangzhou 510000，China6 Jinzhong Meteorological Bureau，Shanxi Province，Jinzhong 030600，China

DOI:10.3974/geodb.2019.06.08.V1

Published:Dec. 2019

Visitors：9650       Data Files Downloaded：205      
Data Downloaded：179.34 MB      Citations：

Key Words：

national stations,surface air temperature,monthly mean temperature,urbanization,1961-2015,Progress in Geography

Abstract：

The adjusted urbanization bias monthly temperature dataset was developed based on the records from 763 national meteorological stations of China (1961-2015). To adjust the data from a target station, the reference stations were used within 300 km around the target station. Among the reference stations, four were chosen where correlation coefficient between trends removed annual average temperature series of the reference stations and the target stations were the largest and passed the significance test of significance level at 0.005. Then, the square of the correlation coefficient of the annual average temperature series of each reference station and its target station was used as the weight, and the weighted average of the monthly average temperature of the reference stations was calculated as the reference sequence. And following, the difference of the trends between the city station sequence and the reference sequence was used to adjust the data at target station linearly. Finally, the inverse distance weighted interpolation method was used to interpolate the temperature data of 763 stations nationwide into grid data of 2 ° x 2 °. To test the accuracy of the dataset, Beijing, Wuhan, Yinchuan and Shenzhen were selected as the representative stations of large cities in North, Central, Northwest and South China. Their relative urbanization biases were 67.0%, 75.4%, 32.7% and 50.3% in the past 55 years, respectively. The dataset was archived in .txt data format, and each file was named according to the year and month. In each file, it is composed of a header file and 18 rows and 32 columns of average temperature (℃) data. The first 6 rows are header file, which are the number of columns, the number of rows, the longitude in the lower left corner, and the latitude in the lower left corner, missing value. The dataset consist of 660 data files with data size of 2.75 MB (Compressed to one single file with data size of 895 KB). The analysis paper based on this dataset was published at Progress in Geography, Vol.38, No.4, 2019.Browse

Foundation Item：

National Natural Science Foundation of China (41575003)

Data Citation：

WEN Kangmin, REN Guoyu, LI Jiao, ZHANG Aiying, REN Yuyu, SUN Xiubao, ZHOU Yaqing. Adjusted Urbanization Bias Monthly Temperature Dataset based on the Records from the National Meteorological Stations of China (1961-2015)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2019. https://doi.org/10.3974/geodb.2019.06.08.V1.

WEN Kangmin, REN Guoyu, LI Jiao, et al. Monthly mean surface air temperature 2°x2° grid dataset in China (1961-2015) [J]. Journal of Global Change Data & Discovery, 2021, 5(1): 27-36. https://doi.org/10.3974/geodp.2021.01.04.

Data Product: