Changes in soil temperature (ST) and soil moisture (SM) are essential for climate change and ecosystem assessments. Previous investigations on the ST and SM on the Tibetan Plateau (TP) are mainly based on the situ observation and the satellite products. In this study, the improved Community Land Model version 4.5 (CLM4.5), with proper parameter optimization and surface datasets update, is used to estimate the response of ST and SM in the TP to climate change in the long‐term time series from 1961 to 2010. After validating the reasonability of the simulated results using the observations, the spatial distribution of changes in ST and SM in annual and seasonal time series since 1960s, 1980s, 1990s, are investigated respectively and the changes of precipitation (Pr) and surface evaporation (Ev) are also analysed to understand the cause of changes objectively. As a whole, the soil was warming and wetting at the maximum value of 0.31°C/decade and 0.77%/decade since the 1960s. However, the warming process in soil mainly occurred in the 1980s while the wetting tendency is detected since the 1990s extensively. Except for the influence of air warming, the enhanced Pr and Ev might also be indispensable factors that caused the intensive wetting process but damped warming process in soil. Summer is the favourable season for the thermal and hydraulic variation since the 1980s. There exists the striking warmer and drier trend in the eastern TP since 1980s while the colder and wetter condition in the western TP since the 1990s. The magnitude of variation in soil is magnified from 1990s under the continuing impact of climate change.

The BCC-CSM2 model is the second generation of the Beijing Climate Center Climate System Model developed by the National Center of China Meteorological Administration. Using the outputs of two versions of the BCC-CSM2 model with different resolutions, namely: BCC-CSM2-MR and BCC-CSM2-HR, their performance in simulating the climate characteristics of Northwest China was compared. The BCC-CSM2-HR had a better ability to simulate the detailed distribution of the average temperature and precipitation in Northwest China, and could delineate the influence of the topography in detail. The extreme events in Northwest China were evaluated further using the BCC-CSM2-HR and the observation data from China Meteorological Data Center. The BCC-CSM2-HR provided a good simulation of the spatial distribution of extreme climate events in Northwest China, and the spatial distribution of TXx, TNx, TXn, and TNn in Northwest China show closer proximity to the observation than that of TX90p, TN90p, TX10p, and TN10p, even in the case of extreme heavy precipitation. This case study of the extreme weather events showed that the BCC-CSM2-HR model had the best simulation performance for extreme high temperature events in Northwest China, followed by extreme low temperature events, and had the worst simulation ability for extreme precipitation events.

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.

Cloud microphysical processes significantly impact the time variation and intensity of precipitation. However, due to the high altitude of the Tibetan Plateau (TP) and the lack of observational data, the understanding of cloud microphysical processes on the TP is relatively insufficient, affecting the accuracy of precipitation simulations around the TP. To further reveal the characteristics of convective precipitation and cloud microphysical structure over the TP, the mesoscale numerical model, WRF, and various observational data were used to simulate and evaluate typical convective precipitation in the Yushu area, which was recorded from 11 to 12 August 2020. The results showed that the combination of the Lin scheme in the WRF model could effectively reproduce this case’s characteristics and evolution process. In the simulation process, the particles of each phase were distributed at different altitudes, and their mass and density over time reflected the characteristics of surface precipitation changes. Among the particles mentioned above, rainwater contributed the most to the initiation and growth of graupel particles. Further research established that the initiation of graupel was mainly affected by the freezing effect of rainwater and cloud ice, while the growth of graupel was influenced primarily by the collision of graupel particles and rainwater. On the whole, from the evolution characteristics of microphysical processes over time, it was found that the ice phase process plays an essential role in this typical convective precipitation.