Based on the SRTM (shuttle radar topography mission)data, the ground clutter and other clutters around Tianshui radar station were filtered, then the Z-I function with localized parameters was established on the basis of six precipitation processes with three types in Southeast Gansu after filtering the ground clutter and other clutters of radar data, and at last the reflectivity factor of Xifeng new generation weather radar in Qingyang was compared with the one in Tianshui within the coincidence range. The results show that SRTM data can well simulate the distribution of ground clutter; radar reflectivity is ahead of precipitation; the Z-I function with localized parameters in Tianshui, which had a smaller A and bigger b, is significantly different to common ones; Tianshui new generation weather radar may have a systematic problem of low echo intensity.

 Based on the radial data stream transmission mode of weather radar, and unchanged original monitoring terminal and product terminal, the remote realtime display system of weather radar was developed using the C/S architecture. The system was consisted of the remote transmission server software (RTS) and the remote transmission client software (RTC), which realized the functions of remote control, monitoring and echo realtime display of weather radar across routes. Practice proved that remote users could monitor weather processes and control radar operation status at any node of the network, bringing users a real sense of realtime network monitoring and the experience of using radars. It also provided a good foundation for management department to monitor multiple radars in real time and observe weather processes in the future.

Based on observation data and numerical forecast data at ZDLYFP photovoltaic power station from March 2017 to February 2019, the inclined plane total solar radiation algorithm was improved, firstly. And on this basis two forecast models of short-term photovoltaic output power were established by using multiple linear regression (MLR) and empirical formula methods, then the forecast results were tested and evaluated. The results are as follows: (1) The inclined plane total solar radiation and temperature were higher correlated with photovoltaic output power in each season, the total correlation coefficients were 0.896 and 0.386, respectively, so they were introduced to forecast model based on MLR method as the predictors of photovoltaic output power. (2) The forecast effect of short-term power improved after the improvement of inclined plane solar radiation algorithm, and the relative root mean square error (RRMSE) of photovoltaic output power forecasted by two models of MLR and empirical formula methods reduced by 0.066 and 0.040, respectively. (3) The total root mean square error (RMSE) of photovoltaic output power obtained by MLR and empirical formula methods were 940.917 kW and 1147.172 kW, respectively, and total RRMSEs were 0.188 and 0.229. In addition, RMSEs and RRMSEs based on MLR method were less than those based on empirical formula method in each month, and the correlation coefficient of the former was slightly higher than that of the latter, which indicated that the forecast effect of MLR method was better and more stable in practical application. (4) The effect of photovoltaic power prediction was obviously distinct under different weather conditions, RRMSEs of two methods increased in turn for sunny weather, cloudy weather, overcast weather, rainy weather, dust weather and snow weather. In general, the effect of photovoltaic power prediction based on MLR method was better under different weather conditions.

A typical dust weather process occurring in Northwest China from 23 to 25 April 2014 was simulated by using the atmospheric/chemical full coupled WRF/Chem model coupled with the dust emission module. The influence of the weight factor γ in the formulas of dust flux of Shao 2004 parameterization scheme (Shao04 scheme) on spatial and temporal distribution of dust was analyzed. The scope of simulated dust was compared with that  monitored by FY-3C meteorological satellite remote sensing and dust mass concentration simulated by the model was compared with observations, the key parameter which was more suitable in the Shao04scheme for Northwest China was determined. The results are as follows: (1) The weight factor γ  had a significant influence on the simulation of dust scope and maximum center value of mass concentration and vertical dust flux. (2) Different γ values could simulated the variation trend of PM10 and PM2.5 mass concentration well in dust weather, but only when the value was setted as 1, that is, WRF/Chem model coupled with Shao2011 sand parameterization scheme could simulate the change of PM10 and PM2.5 mass concentration more accurately during the dust process in Northwest China.