Satellite precipitation products have been one of the most important technologies with wide coverage more suitable for areas without data. However, their performance cannot fully meet the harsh requirement of the high resolution and precision precipitation data in recent years. It is very necessary to downscale and then integrate the satellite products with the ground observation data for better data quality. In this study, the Lantsang River Basin in the southern Tibetan Plateau was taken as an example, particularly considering topographic, geographic and vegetational elements. The geographically weighted regression (GWR) model was established with the spatial downscaling data of the tropical rainfall measurement mission (TRMM) satellite and the precipitation estimation from remotely sensed information using artificial neural networks-climate data record (PERSIANN-CDR). The GWR downscaling model was supposed to improve the correlation accuracy between satellite products and ground observation precipitation data. After that, the ensemble Kalman filter was used to take the inverse distance weighted (IDW) interpolated data of the ground meteorological station as the observed values of the fusion and then fused the downscaling TRMM and PERSIANN-CDR data to further improve the accuracy of precipitation data. The results show that: 1) The mean value of determination coefficient（R²） of PERSIANN-CDR monthly precipitation increased from 0.35 to 0.75 after GWR downscaling. At the same time, the root mean square error (RMSE) and mean absolute error (MAE) decreased by 13.98 and 10.13 mm, respectively. There was a significant increase in the correlation degree of the PERSIANN-CDR satellite precipitation product in all months after GWR downscaling. Meanwhile, the R² of TRMM monthly precipitation increased from 0.53 to 0.85, and the RMSE and MAE decreased by 11.49 and 15.50 mm, respectively. A significant improvement was achieved in the months with the low correlation degree for the surface meteorological stations before downscaling, such as May, June, and December, where the R² reached 0.67 or above after downscaling. In addition, the two types of products presented the more significant effects on the accuracy evaluation in the dry season (from November to April), compared with the rainy season (from May to October). It infers that the GWR greatly improved the monitoring performance of these two types of satellite precipitation products on precipitation in the dry season. 2) The accuracy was improved better than before after the data integration and downscaling from the ground stations. Furthermore, the ensemble Kalman filter was used for the data fusion of down-scaled products. The overestimation of precipitation was enhanced at ground meteorological stations by satellite products, especially with the less uncertainty of the data after fusion, indicating the high precision fusion. In summary, the downscaling and fusion can be expected to increase the spatial resolution and accuracy of data. The high spatial resolution of satellite products was also achieved in the high correlation with the precipitation data observed on the ground.

In the context of global climate change and intensified human activities, the Qingzang plateau, known as the "Asian Water Tower" and the "Third Pole of the Earth", plays an increasingly significant role in regulating regional and global climate systems through its land-atmosphere interactions. Numerical simulations, as an effective tool for understanding the complex climatic processes on the Qingzang plateau, have played an irreplaceable role in exploring the physical mechanisms behind the land-atmosphere systems on the Qingzang plateau and their weather and climate effects. In this paper systematically reviews the research progresses of numerical simulations on four major land-atmosphere interaction processes on the Qingzang plateau, including land-surface-atmospheric processes (boundary layer processes), cloud precipitation physics processes, regional water cycle processes, and tropospheric processes, and focuses on discussing how these processes manifest at different temporal and spatial scales and their impacts on regional weather systems, monsoon circulations, and global climate. Finally, this paper outlines future research directions by proposing a need to enhance model accuracy, optimize parameterization schemes and integrate multiple observational data sources to further reveal the unique role of the Qingzang plateau in global climate system dynamics and provide scientific basis for addressing challenges posed by climate change.

Characterized by high elevation and strong radiation, the Qingzang plateau transports huge amounts of heat and water vapor from the surface to the atmosphere, regulating the development of atmosphere boundary layer and cloud precipitation processes. The sensible heat pump effect has a significant impact on the weather, climate and atmospheric circulation over Qingzang plateau and its surrounding regions. The current conditions of the harsh environment and the lack of comprehensive observation stations seriously hinder people's understanding of land-atmosphere interaction process and its regional weather and climate effects over the Qingzang plateau. Since the 1980s, numerous large-scale field observation experiments have been conducted to study the processes of land-atmosphere interaction, atmospheric boundary layer, cloud & precipitation, and Qingzang plateau's weather and climate effects, and fruitful research results have been achieved. In particular, the National Science and Technology Special Project "the Second Qingzang Plateau Scientific Expedition and Research" was launched in 2017, and a large number of comprehensive integrated observation experiments have been carried out on the basis of previous observational projects. This article will systematically review and summarize relevant observational research progress on the land-atmosphere interaction process, atmospheric boundary layer process, cloud precipitation process, and Qingzang plateau's weather and climate effects from the perspective of in situ measurements over the past five years.

Surface energy budget components (such as net radiation flux, sensible heat flux, latent heat flux and soil heat flux) at multiple temporal scales have significant meaning for understanding the energy and water cycle over the Tibetan Plateau (TP). In the framework of ESA-MOST Dragon Programme 4, the surface energy balance system (SEBS) was tested and used to derive surface heat fluxes at different temporal scales over the TP by a combination use of geostationary satellite (FY-2C) data, polar orbiting satellite (SPOT/VGT, Terra/MODIS) data and ITPCAS forcing data. The validation results show there is a good agreement between derived heat fluxes and in situ measurements from Third Pole Environment Observation and Research Platform (TPEORP), which means the feasibility to derive surface heat fluxes over heterogeneous landscapes by a combination use of geostationary and polar orbiting satellite data in SEBS. The diurnal, seasonal and inter-annual variation characteristics were also clearly identified through analyses of derived turbulent fluxes.