The USGS (United States Geological Survey) land-use data used in the Weather Research and Forecasting (WRF) model have become obsolete as they are unable to accurately represent actual underlying surface features. Therefore, this study developed a new multi-satellite remote-sensing land-use dataset based on the latest GLC2015 (Global Land Cover, 2015) land-use data, which had 300 m spatial resolution. The new data were used to update the default USGS land-use dataset. Based on observational data from national meteorological observing stations in Xinjiang, northwest China, a comparison of the old USGS and new GLC2015 land-use datasets in the WRF model was performed for July 2018, where the simulated variables included the sensible heat flux (SHF), latent heat flux (LHF), surface skin temperature (Tsk), two-meter air temperature (T2), wind speed (Winds), specific humidity (Q2) and relative humidity (RH). The results indicated that there were significant differences between the two datasets. For example, our statistical verification results found via in situ observations made by the MET (model evaluation tools) illustrated that the bias of T2 decreased by 2.54%, the root mean square error (RMSE) decreased by 1.48%, the bias of Winds decreased by 10.46%, and the RMSE decreased by 6.77% when using the new dataset, and the new parameter values performed a net positive effect on land–atmosphere interactions. These results suggested that the GLC2015 land-use dataset developed in this study was useful in terms of improving the performance of the WRF model in the summer months.

The deep convective boundary layer (CBL) in the Taklimakan Desert plays an important role in the climate system in East Asia. Based on the observation experiment and large‐eddy simulation, turbulent mechanisms for its formation were revealed in this study. This explained why the daily maximum CBL depth was independent of surface heating. In the late‐morning, there was a weak temperature inversion and a near‐neutral residual layer (RL) above the CBL. With the development of the CBL, stronger convection could penetrate the RL and even overshoot the top of the RL. The distinctive boundary‐layer process entrained free‐tropospheric air to warm the RL and then promoted the entrainment of the warmed air in the RL into the CBL. This extra energy supply effectively contributed to the growth of the CBL. With further positive feedback between the CBL and RL depths, a deeper CBL would form in consecutive fair‐weather conditions.

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.

Based on observations from the Unmanned Aerial Vehicle (UAV) together with an environmental particulate matter analyzer (Grimm-180) and Global Positioning System (GPS) sounding balloons, the vertical structure of dust with different particle sizes was explored over the Taklimakan Desert (TD) during an intensive observation from 1 July 2021 to 31 July 2021. The power functions were fitted between the particle counts and particle sizes, indicating negative correlations with an R² higher than 0.99 under different dust pollution conditions in Tazhong (TZ). The dust concentrations show a sharp vertical increase over the TD during dust pollution; however, more particles with larger sizes are entrained into the air in TZ compared with Minfeng (MF). The total solar radiation during dust pollution days is significantly weakened, accompanied by major modifications in the temperature stratification, which were characterized by low-level cooling (with −2.71 K mean intensity) and high-level heating (with +0.70 K mean intensity). On clear days, the average convective boundary layer (CBL) heights at the TZ and MF are approximately 3.94 and 2.84 km, respectively, and the average stable boundary layer (SBL) height at the TZ and MF are approximately 0.19 and 0.14 km, respectively. With the increasing dust pollution level, the CBL height decreases rapidly while the SBL height shows the opposite trend. The unique ultra-high atmospheric boundary layer structure in daytime provides beneficial conditions for the suspension and vertical transportation of dust over TD. Moreover, a negative correlation between the CBL height and near-surface PM₁₀/PM_2.5/PM_1.0 concentration in TD is revealed by power function fittings.

This study evaluated the Noah land-surface model performance to simulate the land-surface process during different weather conditions in the hinterland of the Taklimakan Desert. This study is based on observation data from the Taklimakan Desert Meteorology Field Experiment Station in 2014. The results illustrated that the energy-exchange process between the land surface and the atmosphere in the drifting desert can be simulated by Noah effectively. However, the effects of soil moisture and latent heat flux were very poor. For sunny days, the soil temperature and heat flux were underestimated significantly in the nighttime and overestimated in the daytime. The simulation results are very good in sand-dust weather. The simulation of heat flux and net radiation is very consistent with the observation during cloudy days. For rainy days, the model can successfully model the diurnal variation of soil moisture, but it has obvious deviations in the net radiation, heat flux, and soil heat flux.