The Third Pole experiences accelerated glacier retreating particularly in the eastern‐Himalaya, coinciding with a decrease of monsoon‐precipitation in the early 21st century. The extent to which the vanishing abundant maritime glaciers buffer the declining precipitation‐runoff remains unclear. Here, with a state‐of‐the‐art enthalpy‐based distributed cryosphere‐hydrology model and first‐hand hydrometeorology observations at Motuo (latest accessible Chinese county), we carefully examine the Yarlung Zangbo basin along Himalayas. We find that during 1998–2019, the rising downstream runoff (lower Nuxia; +6.40 × 10⁸ m³/yr) offsets the dropping upstream runoff (upper Nuxia; −6.89 × 10⁸ m³/yr); however, only the marginal contribution from the vanishing eastern‐Himalaya and Nyainqêntanglha glaciers. During 1998–2019, dry upstream illustrates limited glacier melt (15.7 mm/yr) with dominated snow melt (78.8 mm/yr); while much larger at humid downstream (144.8 mm/yr for glacier melt and 219.1 mm/yr for snow melt). From 1981 to 2019, we observe glacier‐to‐snow melt transition in both upstream and downstream due to glacier degradation and growing nonmonsoon‐season precipitation.

Lapse rate (LR) of near‐surface (2 m) air temperature is essential for determining spatially distributed and gridded air temperature interpolated from in situ observational sites. However, due to the limitation of sparse observational networks, high‐resolution LRs are not usually available on regional scales, especially in mountainous regions. The purpose of this study is to estimate LRs for the entire Tibetan Plateau (TP) using observed air temperature and moderate‐resolution imaging spectroradiometer (MODIS) night‐time land surface temperatures (LSTs) and to analyse the spatio‐temporal changes of the estimated LRs. First, diurnal cycles of LRs derived from in situ observations in three subregions of the TP were analysed, which shows that the LRs in the western and northeastern regions were shallow in the cold season and steep in the warm season, whereas the southeastern region exhibited a different pattern. Further comparisons revealed that the LRs for night‐time air temperatures better represented the LRs for daily mean air temperatures than the daytime ones, and the night‐time MODIS LSTs correlated well with the night‐time air temperatures, especially for the MODIS Terra data sets. Therefore, the night‐time MODIS LSTs from the Terra data sets were used to estimate high‐resolution (10 km) LRs for the daily mean temperatures over the entire TP. Estimated LRs over most areas of the TP were shallower than the commonly used environmental LR (−6.5 K/km). The LRs in the southeastern region were steeper than those in the northeastern region, while steeper LR values occurred in the northwestern region with lower temperatures and less humidity.

As the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin (also called “Yarlung Zangbo” in Chinese) has profound impacts on the water security of local and downstream inhabitants. Precipitation in the basin is mainly controlled by the Indian summer monsoon and westerly and is the key to understanding the water resources available in the basin; however, due to sparse observational data constrained by a harsh environment and complex topography, there remains a lack of reliable information on basin-wide precipitation (there are only nine national meteorological stations with continuous observations). To improve the accuracy of basin-wide precipitation data, we integrate various gauge, satellite, and reanalysis precipitation datasets, including GLDAS, ITP-Forcing, MERRA2, TRMM, and CMA datasets, to develop a new precipitation product for the 1981–2016 period over the upper Brahmaputra River basin, at 3 h and 5 km resolution. The new product has been rigorously validated at different temporal scales (e.g., extreme events, daily to monthly variability, and long-term trends) and spatial scales (point and basin scale) with gauge precipitation observations, showing much improved accuracies compared to previous products. An improved hydrological simulation has been achieved (low relative bias: −5.94 %; highest Nash–Sutcliffe coefficient of efficiency (NSE): 0.643) with the new precipitation inputs, showing reliability and potential for multidisciplinary studies. This new precipitation product is openly accessible at https://doi.org/10.5281/zenodo.3711155 (Wang et al., 2020) and additionally at the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn, last access: 10 July 2020, login required).

Upper Brahmaputra (UB) is the largest (∼240,000 km²) river basin of the Tibetan Plateau, where hydrological processes are highly sensitive to climate change. However, constrained by difficult access and sparse in situ observations, the variations in precipitation, glaciers, frozen ground, and vegetation across the UB basin remain largely unknown, and consequently the impacts of climate change on streamflow cannot be accurately assessed. To fill this gap, this project aims to establish a basinwide, large-scale observational network (that includes hydrometeorology, glacier, frozen ground, and vegetation observations), which helps quantify the UB runoff processes under climate–cryosphere–vegetation changes. At present, a multisphere observational network has been established throughout the catchment: 1) 12 stations with custom-built weighing automatic rain/snow meters and temperature probes to obtain elevation-dependent gradients; 2) 9 stations with soil moisture/temperature observations at four layers (10, 40, 80, 120 cm) covering Alpine meadow, grasslands, shrub, and forest to measure vegetation (biomass and vegetation types) and soil (physical properties) simultaneously; 3) 34 sets of probes to monitor frozen ground temperatures from 4,500 to 5,200 m elevation (100-m intervals), and two observation systems to monitor water and heat transfer processes in frozen ground at Xuegela (5,278 m) and Mayoumula (5,256 m) Mountains, for improved mapping of permafrost and active layer characteristics; 4) 5 sets of altimetry discharge observations along ungauged cross sections to supplement existing operational gauges; 5) high-precision glacier boundary and ice-surface elevation observations at Namunani Mountain with differential GPS, to supplement existing glacier observations for validating satellite imagery. This network provides an excellent opportunity to monitor UB catchment processes in great detail.