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 ›› 2023, Vol. 39 ›› Issue (6): 61-68.doi: 10.3969/j.issn.1673-503X.2023.06.008

• Articles • Previous Articles     Next Articles

Analysis of the applicability of CLDAS wind field data in Liaoning province in 2020

Weihua LIU1,2(),Wei JIN2,3,*(),Huipin WANG4,Chunxiang SHI5,Shulin QU6,Guojing HAN3,Miao YU3   

  1. 1. Dalian Weather Modification Office, Dalian 116000, China
    2. Sate Key Laboratory of Space Weather, Chinese Academy of Sciences, Beijing 100190, China
    3. Anshan Meteorological Service, Anshan 114004, China
    4. Dalian Meteorological Information Center, Dalian 116000, China
    5. National Meteorological Information Center, Beijing 100086, China
    6. College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
  • Received:2023-03-24 Online:2023-12-28 Published:2024-01-27
  • Contact: Wei JIN E-mail:liuweihua2002@163.com;lnyk_jw@163.com

Abstract:

Using the 10 m wind field data from 286 meteorological stations in Liaoning province in 2020 and the 10 m wind field data from the Land Data Assimilation System (CLDAS) of the China Meteorological Administration, the correlation coefficient (COR), mean bias (ME), root mean square error (RMSE) and mean absolute error (MAE) between the hourly wind speed data from CLDAS interpolated to the stations and the observed wind speed data at the stations were calculated to analyze and evaluate the applicability of the CLDAS wind field data in Liaoning province. The results show that the CLDAS gridded data with a 1 km resolution is closer to the observed data than those with a 5 km resolution, and the biases of the nearest neighbor interpolation method are smaller than those of the bilinear interpolation method. For the 286 stations in Liaoning province, the hourly CLDAS wind field data has a correlation coefficient below 0.95 with the observed data for only 1.7% of the total stations. The biases between the CLDAS and the observed wind speeds are larger in the coastal low-lying areas and northern Liaoning than in other inland areas. The mean biases between the CLDAS and the observed wind speeds are negative. Among the seasons, the mean bias is smallest in autumn, followed by summer and winter, and largest in spring. For the diurnal variation, the biases are smallest at night in summer and autumn, followed by winter, and largest in spring. During the daytime, the bias is smallest in winter, followed by summer and autumn, and largest in spring. Case studies of 3 strong wind events in Liaoning province all indicate that the CLDAS wind field data has good applicability.

Key words: CLDAS, Wind speed forecast, Correlation coefficients

CLC Number: