PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (12): 2061-2072.doi: 10.18306/dlkxjz.2021.12.007

• Articles • Previous Articles     Next Articles

Comparative evaluation of the ability of GHCN-CAMS and CMFD reanalysis data to reflect regional temperature in Ningxia

YAN Weixiong1,2(), ZHAO Junfang2,*(), YANG Yang1   

  1. 1. Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions / Ningxia Key Laboratory for Meteorological Sciences / Ningxia Institute of Meteorological Sciences, Yinchuan 750002, China
    2. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • Received:2021-01-07 Revised:2021-03-04 Online:2021-12-28 Published:2021-12-24
  • Contact: ZHAO Junfang;
  • Supported by:
    Key Research and Development Program of Ningxia Hui Autonomous Region(2020BBF03009);Key Research and Development Program of Ningxia Hui Autonomous Region(2020BBF03024);Natural Science Foundation of Ningxia Hui Autonomous Region(2020AAC03467)


Due to the lack of enough in-situ observation data, there are uncertainties in geoscience research and climate research. Since the 1990s, several sets of reanalysis data have been developed, such as the NCEP/NCAR reanalysis data, ECMWF reanalysis data, and so on. These reanalysis data can effectively make up for the shortcomings of the uneven spatial and temporal distribution of observation data. However, different reanalysis data have different quality and inconsistent performance in different regions. Therefore it is of great significance to carry out the regional suitability assessment of reanalysis data for the study of geo-atmospheric process and climate analysis. Based on the monthly average temperature of 24 meteorological stations in Ningxia Hui Autonomous Region (Ningxia), the reanalysis data of GHCN-CAMS (Global Historical Climatology Network and the Climate Anomaly Monitoring System) and CMFD (China Meteorological Forcing Dataset) were evaluated for the ability to reflect the surface temperature at two spatial scales of 0.5° × 0.5° and 0.1° × 0.1° and two temporal scales of annual and monthly, using statistical indices of bias, absolute bias, root-mean-square error, and correlation coefficient. The results show that: 1) The reanalysis data of GHCN-CAMS and CMFD all have strong ability to reflect the temperature in Ningxia as a whole, the former slightly overestimates the temperature in Ningxia, and the latter slightly underestimates the temperature. 2) The reanalysis data of the two spatial scales have periodic positive and negative deviations at the annual and monthly scales, and the correlation at the annual scale is better than that at the monthly scale. 3) GHCN-CAMS and CMFD show different ability to reflect the temperature under different underlying surfaces. The temperature of farmland (gravel-mulched field) is overestimated in the cold season and underestimated in the warm season. For urban land, its temperature is overall underestimated. The temperature of grassland is underestimated by CMFD in cold season and slightly overestimated in warm season; while overestimated by GHCN-CAMS in cold season and underestimated in warm season. On the whole, CMFD have a better ability to reflect the surface temperature in Ningxia.

Key words: reanalysis data, surface temperature, GHCN-CAMS, CMFD, Ningxia