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The atmospheric boundary layer is a crucial transitional region connecting the surface with the free atmosphere, playing a bridging role in land-sea-air interactions and the interactions between different atmospheric layers. This study utilizes rotary-wing UAVs, high-resolution lidar, and WRF simulation data to analyze the vertical distribution characteristics of temperature, humidity, wind speed, and wind direction boundary layer over the Mount Si'e region in 4–6 April 2024. The results indicate that the boundary layer temperature decreases with increasing altitude, reaching up to 18°C, while humidity decreases with height, dropping to as low as 35%. Daytime wind speeds range from 4 to 8 m/s, decreasing to 2 to 4 m/s at night. The boundary layer height can reach up to 900 m during the day and drops to 100–200 m at night, showing distinct diurnal variation characteristics. UAV observations are in good agreement with lidar and WRF simulation results, highlighting the application value of UAVs in high temporal and spatial resolution boundary layer studies. The study also reveals the significant impact of complex terrain on boundary layer characteristics, providing scientific insights into the dynamic and thermal processes of the boundary layer and offering reference value for improving regional weather forecasting and numerical simulations. [ABSTRACT FROM AUTHOR]

The atmospheric boundary layer is a key region for human activities and the interaction of various layers and is an important channel for the transportation of momentum, heat, and various substances between the free atmosphere and the surface, which has a significant impact on the development of weather and climate change. During the Second Tibetan Plateau Scientific Expedition and Research Program (STEP) in June 2022, utilizing the comprehensive stereoscopic observation experiment of the "Plateau Low Vortex Network", this study analyzed the variation characteristics and influencing factors of the atmospheric boundary layer height (ABLH) at three stations with different underlying surface types on the Qinghai–Tibet Plateau (QTP): Qumalai Station (grassland), Southeast Tibet Observation and Research Station for the Alpine Environment (SETORS, forest), and Sieshan Station (cropland). The analysis utilized sounding observation data, microwave radiometer data, and ERA5 reanalysis data. The results revealed that the temperature differences between the sounding observation data and microwave radiometer data were minor at the three stations, with a notable temperature inversion phenomenon observed at Sieshan Station. Regarding water vapor density, the differences between the sounding observation data and microwave radiometer data were relatively small at Sieshan Station. The relative humidity increased with height at Sieshan Station, whereas it increased and then decreased with height at SETORS and Qumalai Station. The ABLH at all sites reached its maximum value around noon, approximately 1500 m, and exhibited mostly convective boundary layer (CBL) characteristics. During the night, the ABLH mostly showed a stable boundary layer (SBL) pattern, with heights around 250 m. In summer, latent heat flux (LE) and sensible heat flux (H) in the eastern plateau were generally lower than those in the western plateau except at 20:00, where they were higher. Vertical velocity (w) in the eastern plateau was greater than in the western plateau. Among Sieshan Station and SETORS, LE, and H had the most significant impact on ABLH, while at Qumalai Station, ABLH was more influenced by surface long-wave radiation (Rlu). These four influencing factors showed a positive correlation with ABLH. The impact of different underlying surface types on ABLH primarily manifests in surface temperature variations, solar radiation intensity, vegetation cover, and terrain. Grasslands typically exhibit a larger range of ABLH variations, while the ABLH in forests and mountainous cropland areas is relatively stable. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the applicability of the land‐surface model CLM 4.5 in the southeastern Tibetan Plateau by utilizing field observation data from Kabu and Pailong sites. Furthermore, the study investigated the impact of night‐time precipitation changes on radiation, surface energy fluxes and soil hydrothermal characteristics in this region. Results revealed that CLM 4.5 accurately simulated upward shortwave/longwave radiation, surface energy fluxes and soil temperature in this region. However, the simulation of soil moisture exhibited a slight fluctuation of the simulated value during precipitation, resulting in poorer performance during heavy precipitation and a failure to simulate the rapid change of latent heat flux and soil moisture. Sensitivity experiments demonstrated that night‐time precipitation significantly influenced upward shortwave/longwave radiation, energy budge and soil hydrothermal processes, with each element changing considerably with changes in precipitation. Surface energy fluxes and hydrothermal characteristics were found to be more sensitive to increased precipitation than decreased precipitation. Additionally, soil moisture was found to play a crucial role in the impact of precipitation changes on surface energy fluxes and hydrothermal characteristics. Furthermore, the study also found that changes in precipitation had a more pronounced effect on relatively dry areas and seasons than already extremely wet areas and seasons. Finally, the variation in soil moisture was found to be restricted by the original soil moisture. In conclusion, this study highlighted the significant influence of night‐time precipitation on surface hydrothermal characteristics and surface energy budget in the southeastern Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The Qinghai–Tibet Plateau (QTP) is a crucial component of the global climate system, influencing the regional and global climate through complex thermal and dynamic mechanisms. The high-altitude region, which is the largest part of the extra-polar cryosphere, encompasses extensive mountain glaciers, permafrost, and seasonally frozen land, making it highly sensitive to global climate change. However, the challenging environmental conditions, such as the harsh terrain and high altitude, coupled with sparse weather station distribution and weak observatory representation, make it difficult to accurately quantify the atmospheric conditions and land–atmosphere coupling systems and their effects on the surrounding areas. To address these challenges, we utilized the Weather Research and Forecasting (WRF) model and a three-dimensional variational (3DVAR) assimilation method to create a high-resolution assimilated dataset (HRAD). The QTP-HRAD, covering the spatial range of 70 to 110°E and 25 to 40°N, was validated using both surface weather station observations and the European Center for Medium-Range Weather Forecasts Reanalysis V5, and can now be utilized for further studies on land–atmosphere interactions, water cycling and radiation energy transfer processes, and extreme weather events in the region. [ABSTRACT FROM AUTHOR]