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.

Based on observation data of temperature and precipitation in Tianjin region during 1921-2016, the precipitation from the Global Precipitation Climatology Centre (GPCC-P) and the temperature from the Climate Research Unit (CRU-T) were evaluated and it was found that they performed well. On the basis of these results, the standardized precipitation evapotranspiration index (SPEI) was further used to analyze the temporal-spatial evolution characteristics of drought for almost a century in Tianjin region and its change trend in the future was estimated. The results are as follows: (1) Drought mainly occurred in the early 1940s, late 1990s and early 2000s, and it was dominated by mild drought and moderate drought in four seasons, and its high frequency season evolved from autumn, winter to spring and summer. (2) During six periods, climate tendency of SPEI showed “increasing and decreasing” in other seasons, but it showed “increasing, decreasing and increasing” in autumn, moreover the decreasing tendency in summer was most significant with a climate tendency of -0.3 per decade at Ninghe station during 1961-2010. (3) During 1921-1970, 1931-1980, 1941-1990, it was found that precipitation was dominating factor for the wet tendency in spring and winter, while temperature and precipitation were factors in summer and autumn; during 1951-2000, 1961-2010, 1971-2016, drought tendency in spring was affected mainly by temperature, in summer and winter it was synergistically affected by temperature and precipitation. (4) There was a negative correlation between SPEI and PDO in four seasons during 1921-2016 in Tianjin region, the correlation in spring and summer decreased from northwest to southeast, while that decreased from southeast to northwest in autumn and winter. (5) In the future, it will present drought trendency in summer in the whole region and in winter in the southwestern region, while drought trendency in spring and wet trendency in autumn will not significant.

The precipitation forecast performance of GRAPES_Meso model with 3 km spatial resolution and its cloud analysis system was investigated and compared through numerical experiments for 13 heavy rainfall cases in summer and batch forecast in July 2018 in Northwest China. The results are as follows: (1) GRAPES_Meso model with 3 km spatial resolution had a good forecasting skill and stable performance for precipitation forecast in Northwest China, it could provide favourable outputs for short-term forecasting and nowcasting business. The average threat score of light rain and above for 13 heavy rainfall cases was between 0.5 and 0.6, while the threat score of batch experiments in July was slightly worse than that of 13 heavy rainfall cases. (2) By introducing observed data of radar reflectivity, satellite TBB and CTA, the cloud analysis system could reasonably adjust cloud water, rain water and other hydrometeor content, consequently reduce spin-up time in the mesoscale model and improve the forecast ability of precipitation with different magnitudes. However, the forecast results of cyclic assimilations in cloud analysis system weren’t stable. (3) The predicted coverage of radar echo by GRAESP_Meso model and cloud analysis system was consistent with observations, while the intensity of composite reflectivity was higher than the observations.