LAUSR

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Currently, several global and regional forcing data sets, such as Global Land Data Assimilation System (GLDAS), China Meteorological Administration of land data assimilation system (CLDAS) and China Meteorological Forcing Dataset (CMFD), can provide estimates of these two variables for China. In this study, precipitation and shortwave radiation from CMFD, CLDAS and GLDAS were inter-compared with one another and against ground station observations during 2008–2014. The results demonstrate that all the three forcing data sets can capture the spatial distribution characteristics of precipitation over mainland China while CMFD is closer to the observed ground data. The temporal variations of precipitation from the three forcing data sets also match in most areas of mainland China with the observation, while CMFD and GLDAS perform better than CLDAS. Compared with the precipitation observation, CMFD has a slight overestimation but its correlation coefficient reaches 0.97. CLDAS precipitation shows a significant underestimation, with a bias of 107 mm yr −1 in annual mean, while GLDAS has the closest annual mean precipitation to the observed data. As for shortwave radiation, CLDAS and GLDAS heavily overestimate shortwave radiation when compared against station data, while CMFD is consistent with observation data. Spatially, the three forcing data sets have some common distribution features. Compared with CMFD, CLDAS and GLDAS have higher radiation values in most areas of mainland China and the temporal variations difference of shortwave radiation from the three forcing data sets mainly exists the south of 34° N. In summary, precipitation estimates of CMFD and GLDAS are more credible and CMFD outperforms CLDAS and GLDAS in shortwave radiation estimation over mainland China. Findings from this study can provide guidance to communities regarding the performance of different forcing data over mainland China.