In the flood season (from June to August) of 2020, Gansu Province experienced intensive precipitation with long duration and wide ranges. The performances of three global models (ECMWF, GRAPES_GFS and NCEP_GFS) and four regional models (GRAPES_3 km, GRAPES_LZ10 km, GRAPES_LZ3 km and regional model SMS-WARMS in East China) for 24-hour accumulated precipitation forecast were evaluated in this paper. The main results are as follows: (1) The ECMWF model surpassed the other two global models in forecast performance, while among regional models, the GRAPES_3 km and the SMS-WARMS were better, and the latter was more stable. (2) The regional models had lower accuracy of rain probability forecast and TS, ETS, POD than those of global models for light and moderate rain, but for rainstorms they outperformed global models; the POD and Bias of regional models for heavy rain and rainstorms were significantly higher than those of global models. (3) According to the differences of 500 hPa circulation pattern, the precipitation in Gansu could be divided into two types including subtropical high marginal type and low trough type. Four subtropical high marginal precipitation processes and three low trough precipitation processes in flood season of 2020 were tested and evaluated. For global models and regional models, they all had better capability in predicting precipitation with different magnitudes for the former type than the latter one. The ECMWF model and regional models were better than the NCEP_GFS model and the GRAPES_GFS model in predicting heavy rain and rainstorm. Among global models, the ECMWF model had the best forecast effect for the two precipitation types, and the East China regional model had the best forecast effect for the two precipitation types among regional models. (4) All the seven models had good forecasting capability for the spatial orientation of moderate and heavy rain for both rainfall types, while the forecast effect of rainfall location for subtropical high marginal type was better than that of low-trough type, but the predicted precipitation intensity was stronger than observations, especially for the center of precipitation.

The difference of land-atmosphere energy flux caused by the heterogeneity of underlying surface properties plays an important role in affecting the occurrence of local heavy precipitation. The transition of vegetation is fast in western part of the transition zone of China’s summer monsoon, the nature of vegetation is obviously different, and the surface heterogeneity is strong, so the extreme precipitation is prone to occurrence. In order to explore the influence of underlying surface heterogeneity on strong precipitation in this area, the characteristics of underlying surface were analyzed statistically. And on this basis the sensitivity tests with three or six kinds of landuse type and control test for a typical heavy rainfall process under the influence of the western Pacific subtropical high and cold air from 28 to 29 August 2017 were carried out by using the mesoscale model of WRF3.8 and NCAR-LSM land surface model. The influences of underlying surface change on rainstorm intensity, falling area and flux parameters were studied. The results show that the underlying surface with three to six kinds distributed in transition region of summer monsoon of China. The types of underlying surface were relatively few in eastern part of Qinghai to central Gansu, the heterogeneity was weak, while there were more than six kinds in southeastern part of Northwest China and northern Sichuan, the heterogeneity was strong. The proportion of representative vegetation in a single grid in the model was not high, and the contribution rate to land-atmosphere flux was less than 50%, which indicated that it was not suitable to consider the single underlying surface in calculating land-to-air flux during the heavy rain process. The area of precipitation with different magnitudes was closer to the actual situation with the increase of underlying surface types in the model, and the heterogeneity of land feature physical quantity strengthened in main rain zones. Compared with the control test, the simulated shallow surface temperature, surface heat flux, sensible heat flux and latent heat flux by two sensitivity tests reduced during the daytime, which shrank the bias to some extent, thus decreased convective available potential energy and restrained the occurrence of convective rainfall, further reduced the positive bias of precipitation.