The performance of 24 GCMs available in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) is evaluated over the eastern Tibetan Plateau (TP) by comparing the model outputs with ground observations for the period 1961–2005. The twenty-first century trends of precipitation and temperature based on the GCMs’ projections over the TP are also analyzed. The results suggest that for temperature most GCMs reasonably capture the climatological patterns and spatial variations of the observed climate. However, the majority of the models have cold biases, with a mean underestimation of 1.1°–2.5°C for the months December–May, and less than 1°C for June–October. For precipitation, the simulations of all models overestimate the observations in climatological annual means by 62.0%–183.0%, and only half of the 24 GCMs are able to reproduce the observed seasonal pattern, which demonstrates a critical need to improve precipitation-related processes in these models. All models produce a warming trend in the twenty-first century under the Representative Concentration Pathway 8.5 (rcp8.5) scenario; in contrast, the rcp2.6 scenario predicts a lower average warming rate for the near term, and a small cooling trend in the long-term period with the decreasing radiative forcing. In the near term, the projected precipitation change is about 3.2% higher than the 1961–2005 annual mean, whereas in the long term the precipitation is projected to increase 6.0% under rcp2.6 and 12.0% under the rcp8.5 scenario. Relative to the 1961–2005 mean, the annual temperature is projected to increase by 1.2°–1.3°C in the short term; the warmings under the rcp2.6 and rcp8.5 scenarios are 1.8° and 4.1°C, respectively, for the long term.

The hydrological regimes for the major river basins in the Tibetan Plateau (TP), including the source regions of the Yellow (UYE), Yangtze (UYA), Mekong (UM), Salween (US), Brahmaputra (UB), and Indus (UI) rivers, were investigated through a land surface model and regression analyses between climate variables and runoff data. A hydrologic modeling framework was established across the TP to link the Variable Infiltration Capacity (VIC) land surface hydrology model with a degree‐day glacier‐melt scheme (VIC‐glacier model) at a 1/12° × 1/12°. The model performance was evaluated over the upper basins of the six rivers. The heterogeneity and scarcity of the meteorological stations are the major limitation for hydrological modeling over the TP. The relative contributions to streamflow from rainfall, snowmelt, and glacier melt for the six basins were quantified via the model framework and simulation. The results suggest that monsoon precipitation has a dominant role in sustaining seasonal streamflow over southeastern regions, contributing 65–78% of annual runoff among the UYE, UYA, UM, US, and UB basins. For the UI, the runoff regime is largely controlled by the glacier melt and snow cover in spring and summer. The contribution of glacier runoff is minor for the UYE and UM (less than 2% of total annual flow), and moderate for the UYA and US basins (5–7% of yearly flow), while glacier melt makes up about 12% and 48% of annual flow for the UB and UI basins, respectively.

The European Centre for Medium‐range Weather Forecasts (ECMWF) reanalysis ERA‐40, ERA‐Interim, University of Washington (UW) data, APHRODITE's Water Resources (APHRODITE), and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) precipitation estimates are compared with each other and with the corrected gauge observations over the Tibetan Plateau (TP) at both basin and plateau scales. The ERA‐40 generally can capture the broad spatial and temporal distributions in the gauge‐based precipitation estimates over the TP. However, the ERA‐40 shows little agreement with the gauge‐based precipitation in annual variations for the years before 1979. The anticipated improvements in the ERA‐Interim precipitation relative to ERA‐40 have not been realized in this study. It greatly overestimates the Corrected‐China Meteorological Administration (CMA) (by 74–290%) and other datasets, although the ERA‐Interim has a better correspondence than ERA‐40 with the Corrected‐CMA data at both annual and monthly scales among the selected basins. All the products can detect the large‐scale precipitation regime, including the monsoon‐dominated precipitation in summer and the westerly‐wind‐induced precipitation in winter. The Corrected‐CMA and APHRODITE estimates generally show decreasing trends in summer and increasing trends in spring and winter precipitation during 1961–2007 at both basin and plateau scales. However, the Corrected‐CMA shows larger values in trends and more cases with significance than the APHRODITE, suggesting the effects of the undercatch corrections on the precipitation trends. The use of precipitation derived from current reanalysis projects is less preferable for hydrology analysis than the TP observational data at basin scales. However, using gauge‐based precipitation datasets as hydrologic model forcings should be careful in the river basins where gauge station network is spare, such as in the Yarlung zangbo river basin. Satellite products still hold a great potential for providing high‐resolution precipitation information in remote regions such as the western TP, although more evaluations are needed on the feasibility of satellite precipitation products on the TP where the topography is complex and rainfall rate is highly variable.

The spatial‐temporal changes in terrestrial water storage (TWS) over the Tibetan Plateau (TP) and six selected basins during 2003–2014 were analyzed by applying the Gravity Recovery and Climate Experiment data and the extended Variable Infiltration Capacity‐glacier model, including the upstream of Yangtze (UYA), Yellow (UYE), Brahmaputra (UB), and Indus river basins and the Inner TP and the Qaidam Basin. The possible causes of TWS changes were investigated from the perspective of surface water balance and TWS components through multisource data and the Variable Infiltration Capacity‐glacier model. There was a strong spatial heterogeneity in changes of Gravity Recovery and Climate Experiment TWS in the TP—with apparent mass accumulation in central and northern TP and a sharp decreasing trend in southern and northwestern TP. The TWS changes in the TP were mostly attributed to variations in precipitation and evapotranspiration from the perspective of land‐surface water balance. Precipitation played a dominant role on the TWS accumulation in the UYA and UYE, while evapotranspiration had a more important role than precipitation in TWS depletion in the UB. From the perspective of TWS components, the TWS increase in the UYA and UYE was mainly caused by an increase in soil moisture, whereas the decrease in TWS in the UB was mostly due to glacier mass loss. TWS was accumulating from March through August in southeastern TP while from November to April/May in northwestern TP. The seasonal variations of TWS are highly modulated by the large‐scale climate system, atmospheric moisture flux, and precipitation regime over the TP.

Lake Siling Co is currently the largest endorheic lake in Tibet, and the lake surface area has expanded by about 40% since the 1970s, with a remarkable acceleration after 1999. In this study, a hydrologic modeling framework was established by linking the Variable Infiltration Capacity (VIC) land surface hydrologic model with the degree‐day glacier‐melt model over the Lake Siling Co basin, with an aim to quantify the contribution of each runoff component to changes in the lake storage. We found that glacier melt contributed to less than 10% of the total water input to the lake during 1979–2013, while precipitation‐induced runoff in nonglacierized area was responsible for about 67–75%. The mean annual water input to the lake increased by 2.15 × 10⁹ m³ yr⁻¹ in 2000–2013 relative to that in 1979–1999. The amount of precipitation over the lake surface, precipitation‐induced runoff, and glacier‐melt runoff accounted for 13%, 82%, and 5% of this total increase, respectively, suggesting that the substantial expansion of Siling Co in the 2000s was mostly due to the increase in precipitation‐induced runoff. When modeling lake level changes during 1979–2013, we found that the water level rose by 14.1 m when glacier melt was included and by only 10.5 m, a reduction of about one fourth, when glacier melt was removed. It is concluded that glacier melt played an important role in controlling the water level of Siling Co, although it only contributed less than 10% of water input to the lake during 1979–2013.