Based on European Centre for Medium-Range Weather Forecasts （ECMWF） fifth-generation global atmospheric reanalysis （ERA5） every day from May to August during 1979-2020, three land-atmosphere indexes to investigate land-atmosphere coupling processes were calculated,characteristics of land-atmosphere coupling in climatology and their difference under different dry and wetsoil conditions were analyzed over eastern and southern Asia. The results show that Northeast and North China,the Tibetan plateau, India, Yunnan Province of China and Southeast Asia,the middle latitude arid zone were strong land-atmosphere coupling zones in climatology. In the middle latitude arid zone, land-atmosphere coupling had no significant difference under different soil conditions due to the low soil moisture and its little variability. In the other strong coupling zones, the coupling strength decreased with increasing soil moisture condition because of the bigger variability of soil moisture in these regions, and this law is applicable to the coupling processes between soil moisture（SM） and evapotranspiration （ET）, between ET and water vapor condition of boundary layer, between ET and instability condition of boundary layer. The land-atmosphere couplings over South China were weak in climatology, coupling between SM and ET was significant only under dry soil conditions, while the coupling between ET and atmospheric boundary layer were not significant under all soil moisture conditions.

Based on observed total solar radiation, air temperature, relative humidity and air pressure data at representative photovoltaic power stations of Gansu Province, total solar radiation data forecasted by WRF model, and total cloud cover products from FY satellite in 2019, the correlation between total solar radiation and meteorological factors was analyzed, and the prediction ability of WRF model was evaluated, firstly. And on this basis the errors of short-time solar radiation forecast were corrected. The results show that the atmospheric transmissivity was positively correlated with air temperature, and the correlation coefficient was 0.61, while it was negatively correlated with relative humidity, air pressure and total cloud cover, and the correlation coefficients were -0.44, -0.31 and -0.81 in turn. The contribution of total cloud cover to solar radiation attenuation was the most, followed by relative humidity. The deviation of solar radiation forecasted by WRF model was bigger, and the monthly distribution of forecast errors appeared ‘single peak’ pattern, the forecast errors was the biggest in June. The root mean square error (RMSE) of solar radiation forecast was the smallest in winter (45.63 W·m ^-2) and the biggest in summer (240.4 W·m^-2). The forecast ability of WRF model was better on sunny days or partly cloudy days, while it was worse on cloudy days. The forecast errors mainly came from phase bias and system bias. The correction effect of solar radiation forecast considering cloud cover was significant, the RMSE of solar radiation forecast after correction sharply decreased by 101-216.4 W·m^-2 on cloudy days, the average absolute error decreased by 59.5-173.07 W·m^-2, and the RMSE decreased by 1.92-64.23 W·m^-2 in summer with the maximum error.