As the largest fixed and semifixed desert in China, the Gurbantünggüt Desert has a longperiod of snow in winter and the rapid growth of ephemeral plants in spring, presentingthe obvious seasonal changes in the underlying desert surface type, which could lead to the significantvariety in the near-surface boundary layer over this desert. To clarify the influence of the underlying surface change on the near-surface atmospheric boundary layer, gradient tower data and Eddy covariance data in 2017 were analyzed. The results were as follows: the wind profile can be divided into the nocturnal stable boundary layer and the daytime unstable boundary in spring, summer, and autumn, while the wind profile dominating nighttime stability in winter. During the study period, the four-season temperature profiles can be divided into four types: night radiation type, morning transition type, daylight solar radiation type, and evening transition type, and the temperature difference between spring and summer is more than that of autumn and winter. The vertical temperature lapse rate can reach 4.5°C/100 m in spring and summer, while the vertical temperature lapse rate is 0.5°C/100 m in winter. The special humidity value in summer and spring is greater than autumn and winter. The profile is almost in the inverse humidity state at almost all periods in winter. The inverse humidity phenomenon occurred on the autumn night. Besides, the specific humidity is closely related to the temperature and the near-surface wind speed. The “rapid change” of the underlying surface of the spring desert region affects the surface energy budget, which affects the turbulent energy and the stability of the near-surface layer, thus affecting the changes in temperature, humidity, and wind profile.

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Solar radiation is the most important source of energy on the Earth. The Gobi area in the eastern Xinjiang region, due to its geographic location and climate characteristics, has abundant solar energy resources. In order to provide detailed scientific data supporting solar energy development in this area, we used ground-based data to evaluate the applicability of the five reanalysis data sources: the Clouds and the Earth’s Radiant Energy System (CERES), the European Center for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the Japanese 55-year Reanalysis (JRA-55). Our results indicated that the CERES data show underestimated short-wave radiation and overestimated long-wave radiation. The correlation coefficients (r) between the ERA5 dataset and the net long-wave and short-wave radiation in observation were 0.92 and 0.91, respectively, and the r between the MERRA2 dataset and the net long-wave and short-wave radiation in observation were both 0.88. The JRA-55 dataset overestimated the long-wave radiation flux and underestimated the short-wave radiation flux. The clearness index (kt) of all datasets was poor during autumn and winter, the ERA5 estimates were cloudy when the actual condition was sunny, while the JRA-55 estimates were sunny when the actual condition was cloudy. Overall, the radiation flux in the ERA5 dataset had the highest applicability in the Gobi region.

As the largest fixed and semi-fixed desert in China, the Gurbantünggüt Desert undergoes a long period of snow cover in the winter and the rapid growth of ephemeral plants in the spring, presenting obvious seasonal changes in the underlying desert surface type, which can lead to variation in the turbulence of the nearsurface boundary layer turbulence over the desert. In this study, gradient tower data and eddy covariance data from 2017 were analysed to investigate the turbulence characteristics of the different surface boundary layers in the hinterland of the Gurbantünggüt Desert. The results indicate that stable atmospheric conditions in

Synthesized X-band dual-polarization Doppler radar data and the ambient temperature are used to explore the correlation between the microphysical properties and lightning activity of thunderclouds. After pre-processing of the radar data via the Z H-K DP correction, fuzzy logic-based classification of hydrometeors is conducted in a typical thunderstorm process in Sichuan basin, China. The results are combined with the cloud-to-ground (CG) lightning observation for a comprehensive analysis, which show significant correspondence between lightning flash and the solid microphysical particles. In low levels below the freezing level, the CG lightning activity corresponds with heavy rainfall, while it displays graupel or mixed ice-phase particles above the freezing level. The size of graupel echo coincides with the CG lightning activity largely. The CG lightning occurrence is strongly correlated with the convective intensity of thunderclouds, especially the ice-phase particles being dominated by graupel. The strong echo indicates the intensive CG lightning activity very well above the freezing level. Strong CG lightning activity often corresponds to a high cloud top and a large graupel area in the thunderclouds. Consequently, the region of mixed ice-phase particles, especially the region of mixed dry and wet graupel, can be regarded as an important spatio-temporal indicator of the CG lightning activity. Significant linkage between the microphysical properties and lightning activity is revealed above the freezing level in convective clouds in Sichuan basin, which provides a valuable indicator of lightning disasters for numerical weather prediction.