It is difficult to forecast heavy precipitation under complex terrain in mountainous areas， which formation mechanism is complicated， and often brings serious geological disasters. Based on conventional observation data， European Centre for MediumRange Weather Forecasts ERA5 reanalysis data， FY-4A satellite cloud imagery， Doppler radar data and forecast products from various models， the factors contributing and model forecasting performance of local short-time heavy precipitation process in the Hanjiang Basin of southern Shaanxi from the night on 3 to the early morning on 4 June 2022 were examined and analyzed. The results are as follows：（1） This process is a short-time heavy precipitation triggered by the front in the Hanjiang Basin of southern Shaanxi. Due to shallow convection instability and weak vertical wind shear， the heavy precipitation exhibited localized characteristics with significant intensity. The accumulated precipitation in 12 hours exceeds 50 mm in many stations， with a maximum of 104. 8 mm. （2） The two ends of the front are blocked by the topography and move slowly and are difficult to cross the high mountains. Consequently， convection is continuously triggered within the basin， generating heavy precipitation， and the secondary circulation formed in the surface layer of the basin can enhance convective activity. （3） A cold pool formed in the front of front continuously triggers the backward propagation of new convective cells within the basin to form a train effect. Meanwhile， the intense radar reflectivity factor， exceeding 50 dBZ， is located below the 0 ℃ isotherm level， which has high precipitation efficiency and prolonged duration， thus bringing a short-time heavy precipitation with a maximum of 62. 6 mm·h-1 . （4） Global models displayed limited capability in forecasting this process， while mesoscale regional models can reflect the characteristics of frontal convection and precipitation， especially CMA-TRAM and CMA-GD models can reflect the triggering and development trend of local strong convection well. However， the intensity and organization of the convective system induced by the frontal cold pool of the front still have substantial forecast deviations.

Convective turbulent dust emission (CTDE) is a new dust emission mechanism that thermal convective turbulent directly entrains dust particles into the atmosphere. Due to frequent occurrence, the long-term contribution of CTDE cannot be ignored. In the light of the previous research, the mechanism and influencing factors of CTDE are summarized, the parameterization schemes of CTDE are introduced, and the similarities and differences between CTDE and saltation-bombardment and/or aggregation-disintegration dust emission as well as dust devil are compared in terms of occurrence condition and dust emission flux. Finally this paper provides a reference for studying on CTDE and gives suggestions on field observation and improvement of parameterization for CTDE, including measuring CTDE events in potentially active areas, comparing the characteristics of CTDE between different dust sources, and building further correction functions of soil moisture and vegetation cover to improve the model performance.

Based on the Ji'nan S-band dual-polarization Doppler weather radar (CINRAD/SA-D) data, combined with automatic weather station data and conventional observation data, comparative analysis of the environmental conditions are made, and emphasis is laid on the analysis of dual-polarization signatures for the Wangzhuangji storm and Da'an storm, which are short for the two extreme rainfall storms separately occurring at Wangzhuangji county of Shenxian and Da'an county of Yanzhou, Shandong on 5 and 6 August 2020. The results show that: the two extreme heavy rain occurred in the conditions of high K index, large convective available potential energy (CAPE), deep wet layer, and moderately weak vertical wind shear. In contrast, the storm relative helicity (SRH) is evidently larger for the extreme rainfall event on 6 in August. The flow structures of the storms are significantly different: the Wangzhuangji storm tilts upward and intensively diverges at high-level inducing higher storm top and specific differential phase K_DP column, while Da'an storm performs as cyclonic rotation with weaker high-level divergence. The microphysical structure varies at different levels: for the both two storms, there are high concentration of solid (liquid) particles separately above (below) -10 ℃ layer. But Wangzhuangji storm has more abundant graupels above -10 ℃ layer, a few element of liquid particles from -20 ℃ to -10 ℃ layer, and a certain amount of ice particles below -10 ℃ layer. The two storms exhibit comparable dual-polarization characteristics with moderate differential reflectivity Z_DR, bigger K_DP and correlation coefficient (CC) at low-level, which indicate that the rainfall storms constructed with abundant moderate particle size liquid raindrops are rich of water favorable for extreme rainfall.

Based on winter mean temperature observation data in Xinjiang and Arctic Oscillation (AO) index and atmospheric circulation data, the relation and variation between mean temperature in Xinjiang and AO in winter were studied, the conceptual model of winter mean temperature prediction in Xinjiang due to AO influence under the climate warming background was established. The results show that in the process of climate warming, the relation between mean temperature in Xinjiang and AO in winter not only came from global warming, but also depended on AO change in the same period. Overall, the positive (negative) anomaly of temperature in Xinjiang in winter corresponded to AO positive (negative) anomaly. Since the global climate warming, the impact of AO on mean temperature in Xinjiang in winter was asymmetric. When the winter AO index was in positive phase, the corresponding air temperature in Xinjiang was higher than normal, the anomalous change of temperature in Xinjiang matched to AO anomaly in winter. However, when the winter AO index was in negative phase, the positive and negative anomaly of winter air temperature in Xinjiang depended on the intensity of the Polar vortex in northeastern Hemisphere and geopotential height anomaly in the east of 70°E longitude and middle latitude.

Based on the daily precipitation data of 66 meteorological stations in Fujian Province, NCEP/NCAR reanalysis data and NOAA daily OLR data, the large-scale circulation characteristics and it’s variation of drought events in Fujian Province from March to June 2018 were analyzed. The results show that less precipitation in every month, less rainstorm days and weakness of persistent rainstorm process led to severe meteorological drought in Fujian Province from March to June 2018. Affected by the La Niña event, Fujian was in the center of downdraft. The blocking highs were weaker, the West Pacific subtropical high was weaker and moving to the south and the east than usual, Fujian Province was in the anomalous center of water vapor flux divergence, which was the circulation background of drought. The variation of circulation showed that the blocking highs, the subtropical high and the northward propagation of tropical convection were not active in the earlier period, leading to less rainstorm days and drought development. In the later period, the circulation presented the characteristics of periodic oscillation, and the effective cooperation of the north and south system provided favorable circulation conditions for occurrence of persistent rainstorm, which alleviated the drought.

Evaluating the accuracy and uncertainty of regional meteorological data sets were very important for the simulation of land surface process and analysis of climate change. Based on the sites observation data, the simulation accuracy of air temperature and precipitation of the China meteorological forcing dataset (CMFD), the atmospheric forcing data from 2000 to 2015 in the Heihe River Basin (WRFOUT) and the simulated forcing dataset of 3 km/6-hour in the Heihe River Basin (SFD) under different underlying surface types were evaluated, and uncertainty of  three reanalysis data sets were evaulated through three cornered hat (TCH) method. The results were as follows:(1) For temperature data, the WRFOUT data set had the highest accuracy in grassland, shrub land, desert bare land and wet ground surface, while the accuracy of CMFD data set was relatively high under the cropland, and among the five underlying surfaces, the temperature values of the three sets of reanalysis data had the highest accuracy in the shrub. For precipitation data, the accuracy of the CMFD data set under the five underlying surface types was higher, SFD datasets were overestimated in grassland, shrub land and desert bare land, while WRFOUT datasets were overestimated in grassland, farmland and wetland. (2) Through the TCH method, the uncertainty of temperature data in CMFD and WRFOUT data sets was lower, while the uncertainty of SFD data set was relatively large. The uncertainty of precipitation data of the three data sets was larger, and it was higher in the area with complex vegetation types and elevations.

Based on the daily mumps cases，meteorological data from 2005 to 2011 in Yinchuan，the epidemic characteristics of the mumps cases and relations with the meteorological factors were analyzed by using the methods of climatic inclination rate and the correlation analysis． The results show that the number of mumps cases presented increasing trend，the crowd from the age of 1 to 20 with mumps cases accounted for 93． 7% of the total mumps cases in Yinchuan，and they were the main easy infected crowd，while the crowd from the age of 6 to 7 was the key crowd of prevention and control． The monthly variation of mumps cases presented increase trend from February to May and September to December，while decline trend in summer and winter．The number of mumps cases accounted for 44． 4% and 5． 0% of the total number in Xingqing and Lingwu，respectively． The correlations were significant between the number of mumps cases and the weekly mean pressure，weekly mean temperature，weekly maxium temperature difference，mean relative humidity，weekly minimum relative humidity and weekly sunshine hours． The number of mumps cases was obviously affected by the meteorological factors of the first one to fourth weeks，so mumps cases could be forecasted by using the preceding meteorological factors．