Sandstorm is a serious natural disaster in north China. It is of great significance to carry out relevant research to improve the forecast level of this kind of catastrophic weather. Based on the RegCM-dust model, an extended period numerical prediction analysis of a typical severe sandstorm process in north China is conducted, and the results are compared with NCEP reanalysis data and other analysis results. The results show that the regions with high sediment discharge simulated by the model are mainly located in southern Xinjiang, Mongolia and western Inner Mongolia. The model has a certain forecasting ability for 10 m wind speed, but the simulated wind speed is smaller than the reanalysis data. The changes of dust column content and total sedimentation simulated by the model can reflect the characteristics of the dust storm weather process. The simulated sand-dust mixing ratio has a certain correspondence with the urban pollution index, which indicates that the model has certain forecasting ability for the pollution weather caused by sand-dust.

The ECMWF-HR cloud forecast products are verified by using the total cloud cover inversion products of FY-2G satellite from October 2019 to September 2020 and the diurnal variation characteristics of ECMWF-HR total cloud cover products in the central and eastern parts of Northwest China are diagnosed in selected key areas to provide references for the application of cloud forecasting. The results show that the total cloud forecasted by the ECMWF-HR is relatively stable and has obvious diurnal characteristics in the study area. Forecast deviation is small in the daytime and at night it increases by 10%-20%. Meanwhile, there are obviously seasonal characteristics of cloud forecast product, and it has positive deviation in summer half year and the spatial distribution of the deviation is even. It shows regional distribution characteristics in winter half year with negative deviations in the western Qilian Mountains and positive deviation in Gansu and the south part of Shanxi, and the deviation is lower in winter half year than in summer half year in other areas. In general, the cloud forecast product of ECMWF-HR is relatively reliable in the study area, but in two regions, there are significant anomalies. Total cloud forecast needs to be increased by about 10%-30% in the western Qilian Mountains and decreased by about 20%-30% in Gansu and the south part of Shanxi on the base of ECMWF-HR product. The model correction results are relatively close to the satellite inversion results, with an average absolute deviation of 4.5% and similar diurnal variation characteristics.

The northwest region of China is located in the hinterland of Eurasia, in which the source of water vapor is scarce, and drought is its main climatic feature. In recent years, with the continuous increase of regional precipitation, the warming and wetting in Northwest China has attracted great attention from all walks of life. In order to scientifically respond to social concerns, the team used multi-source data to conduct in-depth research on the phenomenon of warming and wetting in Northwest China from multi-scale and multi-dimensional perspectives, and found that the trend of wetting in Northwest China had significant and nonlinear enhancement characteristics. It is recognized that the wetting in Northwest China is expanding eastward, and the land surface evapotranspiration there has a special negative feedback mechanism on climate warming. It is estimated that the warming and wetting trend will still maintain in Northwest China in this century, and the wetting trend is driven by multi-factor comprehensive driving mechanism. The multi-aspect impacts of the warming and wetting in Northwest China are evaluated, and the technical countermeasures to deal with the warming and wetting there are put forward, and the research results of “the enhancement and eastward expansion of climate warming and humidification, formation mechanism and important environmental impacts in Northwest China” are formed. The major consultation report based on the research results has played an important decision-making support for the national strategies such as the development of the western region in the new era and the ecological protection and high-quality development of the Yellow River Basin. The research results were selected as “China's Top Ten Scientific and Technological Progress in Ecological Environment” in 2022, and have also received extensive attention from the international academic communities.

Based on the daily minimum temperature observation data in southeast of Gansu Province during 1969-2018, the variation of extreme low temperature events was analyzed, then 74 circulation characteristic quantities from National Climate Center were used to research the circulation system affecting the extreme low temperature events. The results are as follows: (1) The frequency of annual extreme low temperature events in southeast of Gansu Province reduced obviously with a rate of 2.3 d·(10 a)-1 in the last 50 years, and the reduction was most significant in summer and slowest in winter. There was an abrupt change of extreme low temperature days in 1987, after the abrupt change, the frequency of extreme low temperature events was relatively lower. (2) Compared with the climatic mean, the intensity of extreme low temperature events tended to increase, before 1987, the low temperature intensity anomaly increased with a rate of 0.2 ℃·(10 a)-1, while after 1987, the extrem low temperature intensity anomaly increased with a rate of 1.2 ℃·(10 a)-1. (3) The intensity of extreme low temperature in spring, summer, autumn and winter mainly ranged from -5.0～5.0 ℃, 10.0～15.0 ℃, -5.0～10.0 ℃, -20.0～-10.0 ℃, and the occurrence frequencies were 61.9%, 90.1%, 73.4% and 73.1%, respectively. (4) There was a positive correlation between extreme low temperature events and Eurasian meridional circulation in southeast of Gansu Province. The extreme low temperature events was related with cold air, the area index of western Pacific subtropical high and the intensity of polar vorticity center in the northern hemisphere in winter, while it was related with subtropical high northern boundary of South China sea, subtropical high northern boundary of the western Pacific and polar vorticity intensity of the Pacific in spring. The composited analysis of geopotential height fields indicated that Mongolia was a cold high pressure center on ground, and polar vorticity center was located in the eastern hemisphere from 500 hPa to 100 hPa, the westerly belt prevailed meridional circulation, and east Asian large trough in the westerly belt was deep and westward, the region of southeast of Gansu was controlled by strong northwest airflow after the trough, which was favourable to forming extreme low temperature events.

Based on 2-meter temperature data from the second generation monthly dynamic extended range forecast (DERF2.0) model, observational temperature data at 69 weather stations in Gansu Province, reanalysis data of NCEP/DOE and sea surface temperature data of NOAA，the forecast errors of January temperature in Gansu Province by DERF2.0 model from 1992 to 2013 and their relationship with external forcing were analyzed. The results are as follows: (1) The simulated effects of January temperature by DERF2.0 model in eastern Yellow River of Gansu (known as Hedong for short) were better than that in most regions of western Yellow River of Gansu (known as Hexi for short), especially  in Gannan, Linxia, Lanzhou, Dingxi, Pingliang and Qingyang, the average errors between forecast and observation were small and stable, and the linear tendency rates of forecasted temperature in January were consistent with observation from 1992 to 2013, while the average errors were bigger and unstable in most regions of Hexi, and the change trends of forecasted temperature were contrary to actual observation. (2) Although the model could well reflect the inter-annual variation and spatial distribution pattern of January temperature in Gansu, the abnormal centers and values of temperature change were significantly different from the observation. (3) The EOF1 of error field reflected consistent overestimate or underestimate to  January temperature, the EOF2 presented an opposite distribution pattern in Hedong and Hexi, while the EOF3 appeared a reverse phase distribution pattern in Gannan Plateau and other parts of Gansu Province. (4) The main modes of forecast error field were significantly correlated with circulation and sea surface temperature (SST) in key areas, which indicated that the response of model to circulation and SST anomalies was deficient. Therefore, it was partially possible to reduce forecast errors of January temperature in Gansu by adjusting the response ability of DERF2.0 model to circulation and SST in key areas.