Based on daily precipitation data from 44 national meteorological stations in the southern Xinjiang and the NCEP/NCAR reanalysis data from May to September (warm season) during 1961-2020, the spatial and temporal variation characteristics of rainstorm and large-scale circulation anomalies under different decades and climatic background (warm-dry period and warm-wet period) in the southern Xinjiang were analyzed. The results show that the cumulative rainstorm days, rainstorm stations and rainstorm rainfall in the warm season of the southern Xinjiang has been increasing since 1961, but the variation trend of rainstorm intensity and the proportion of rainstorm rainfall in total precipitation was not obvious. The cumulative rainstorm days, rainstorm stations and rainstorm rainfall in the warm-wet period in the southern Xinjiang were significantly more than those in the warm-dry period, and the rainstorm intensity and the proportion of rainstorm rainfall in the total precipitation had little difference in the warm-wet period and the warm-dry period. After entering the warm-wet period, the rainstorm days and rainstorm rainfall amount increased in most stations in the southern Xinjiang (the most obvious increase was at southwest stations), but the increase extent in mountain area was smaller than that in plain. The central Asian trough, central Asian vortex and Tarim easterly low level jet were the main influencing systems for the heavy rain in the warm season in the southern Xinjiang. The heavy rain in the warm season in the southern Xinjiang was dominated by low vortex type in the warm-dry periods, and low trough type in the warm-wet periods. The easterly flow 850 hPa extended westward more obviously in the low vortex rainstorm than in the low trough rainstorm. In the circulation difference field between the warm-wet periods and the warm-dry period, the circulation anomaly in the high latitude area of the low trough rainstorm and the low vortex rainstorm showed reverse change characteristics.

Based on the observation data of daily maximum temperature from 105 national meteorological stations in Xinjiang and the NCEP/NCAR reanalysis data from May to September during 1981-2019, the spatial and temporal characteristics and circulation types of regional high temperature weather processes in Xinjiang were analyzed. The results are as follows: (1) During 1981-2019, there were 100 regional high temperature weather processes in Xinjiang, concentrating in the Yili valley plain, the southern edge of Junggar basin in northern Xinjiang, Tarim basin in southern Xinjiang and the plain area in eastern Xinjiang, which mainly occurred from June to August, with the most in July, the second in August and the least in June. (2) Since the 21st century, the number of high temperature weather processes showed an increasing trend and the intensity of the processes obviously enhanced. The start time of the processes showed an advance trend, while the end time pushed. In addition, the duration days of the processes showed a phased trend of “increase, decrease, increase”. (3) The circulation situation at 500 hPa geopotential height field causing the regional high temperature weather processes in Xinjiang could be divided into four types, namely the eastward extension of Iranian subtropical high type (accounting for 54.0%), the superposition type (accounting for 32.0%), the Xinjiang high pressure ridge type (accounting for 12.0%), and the westward extension of western Pacific subtropical high type (accounting for 2.0%).

Statistical downscaling forecasting of precipitation and 2 m air temperature was obtained based on ECMWF model forecast data from March to November 2018. The interpolated precipitation was corrected using the frequency matching method firstly and then the threshold method, the interpolated temperature was corrected by using the Kalman filter-type decreasing average statistical downscaling technique, finally the hourly precipitation and temperature prediction were obtained. The results are as follows: (1) For the accuracy of rain probability forecast, it was obviously improved by using the frequency matching method and the threshold method for most forecasting time, and the maximum improvement range was more than 20% for the former. For the relative error, the threshold method had reduced the occurrence of false alarms considerably. For the short-term heavy rainfall with 1 h rainfall greater than or equal to 20 mm, the TS score was also improved significantly after using the frequency matching method. For the Typhoon “Amby” event in 2018, in addition to the above improvement effects, the frequency matching method improved the prediction capacity of the model about the amount and patterns of rainfalls, and the threshold method corrected false-alarm station completely. (2) For the test of temperature forecast of ECMWF model, the absolute error was the largest in March for almost forecast time. After using the Kalman filter-type decreasing average statistical downscaling technique, the absolute error of temperature in different months decreased to varying degrees. In general, the absolute error curve after correction still had the periodic fluctuation with the extension of forecast period, and the position of wave peak and trough was basically the same as those before correction, and the greater the absolute error, the greater the correction range was. For the temperature case, the accuracy of the spatial distribution of temperature prediction was retained, and the absolute error decreased significantly after correction.