Based on the multi-mode precipitation gridded forecast data, observation data at meteorological stations of Qinghai Province and precipitation gridded analysis product of CMA multi-source precipitation analysis system (CMPAS), the prediction performance of models to heavy precipitation cases in Qinghai Province from July to August 2020 were comparatively tested by using traditional verification method such as threat score (TS) and spatial verification method such as fraction skill score (FSS) of neighborhood method and object-oriented diagnostic evaluation method (MODE). The main conclusions are as follows: (1) The traditional TS scores of global model of European Center of Medium-range Weather Forecasts (ECMWF) and National Center for Environmental Prediction (NCEP), China Meteorological Administration global assimilation forecast system (CMA-GFS) and GRAPES regional mesoscale numerical prediction system (GRAPES-Meso) to light rain and above were higher, and the prediction performance difference of four models to light rain was little, but the models with the highest score under different verification methods were slightly different. (2) Compared with the observation, the forecasted locations of four models to moderate rain and above were generally to the west. The traditional TS scores of moderate rain and above were significantly different, but the performance score of models under different verification methods was relatively consistent. (3) Compared with the observation, the forecasted location of four models to heavy rain and above was generally to the north. The prediction ability of each model to heavy rain and above was poor, and the traditional TS scores of heavy rain and above were equal to 0, while FSS scores could effectively improve the evaluation ability to models difference, and MODE could give the specific performance of corresponding object attributes, which provides valuable reference for model application, but it was more sensitive to the selection of verification parameters.

Based on ERAinterim reanalysis data from 2009 to 2018, the spatial and temporal distribution characteristics of cloud liquid water content and cloud ice water content in Qinghai were analyzed. The results show that both cloud liquid water content and cloud ice water content increased from northwest to southeast. Cloud water resources were concentrated in the southern part of Yushu, southeastern part of Guoluo and Qilian mountain areas, where they were highest in summer and autumn and could reach 60～70 g·m-2. Cloud liquid water content and cloud ice water content increased firstly and then decreased with increasing altitude. Cloud liquid water content was concentrated at a height of 4 to 6 km, and cloud ice water content was concentrated at a height of 7 to 8 km. The altitude with the maximum cloud ice water content was higher than that with the maximum cloud liquid water content. In summer and autumn, the amplitudes of vertical variation of cloud liquid water content and cloud ice water content were biggest in Qinghai southern plateau, while they were smallest in Qaidam Basin. Cloud liquid water content and cloud ice water content in most parts of Qinghai increased from 2009 to 2018 and the increasing trend in autumn was most obvious. Cloud liquid water content and cloud ice water content was highest in September and lowest in January. The differences in monthly variations of cloud liquid water content and cloud ice water content in Qaidam Basin were smallest. The difference in monthly variations of cloud liquid water content in eastern agricultural region was biggest, while the difference in monthly variations of cloud ice water content in Qinghai southern plateau was biggest.

 Based on monthly dust data from 9 automatic weather stations in the Qaidam Basin from 1961 to 2019, the dust index was calculated, and the spatiotemporal variation characteristics and the main influence factors of dust intensity were analyzed. The results are as follows: (1) In recent 59 years, the intensity of dust showed a significant decrease trend with a deceleration of 2.05 a-1 in the Qaidam Basin. The annual variation of dust intensity showed a single peak distribution with the strongest in the 1970s. The mutation of dust index occurred in 1990 in the Qaidam Basin. The monthly average dust index also showed a single peak distribution to some extent, with the peak in April in spring and the valley in December in winter. (2) The dust intensity in the Qaidam Basin was high in the abdomen and low in the periphery as a whole, in recent 59 years, except for Lenghu, the dust intensity of other areas showed a significant weakening trend. The weakening rates of Nuomuhong and Golmud were faster and the weakening rate of dust intensity in spring was the fastest. (3) In recent 59 years, the annual average temperature increased, precipitation increased, wind speed decreased, windy days decreased in the Qaidam Basin, which was important reasons for the weakening of dust intensity.

In order to explore the relationship between natural pasture growth and meteorological conditions under the background of global warming in the ecological function area of northern shore of the Qinghai Lake, the influence of hydrothermal conditions on returning green date, growth height and yield of pasture were analyzed systematically based on meteorological and pasture observation data from 1997 to 2018. The results are as follows: (1) The influence of temperature on returning green date of pasture was significant in northern shore of the Qinghai Lake. The returning green date of pasture had significantly positive correlation with the first day of temperature higher than 0 ℃ and 3 ℃, the correlation coefficients were 0.590 and 0.567, respectively. (2) The growth rate of pasture had significant difference at different stages of growth, and the growth of pasture was the most vigorous from late June to mid-August. (3) The yield of pasture presented a significant ‘ladder’ variation characteristic in northern shore of the Qinghai Lake, and the average yield from 2010 to 2018 was 88% higher than that from 1997 to 2009. (4) The ≥0 ℃ accumulative temperature and precipitation during the growth of pasture presented an increasing trend in northern shore of the Qinghai Lake from 1997 to 2018, while the sunshine duration decreased, the warm and humid change characteristics were obvious, and the accumulative temperature of ≥0 ℃ during the growth of pasture was the key factor for the formation of pasture yield.