This paper compares the historical simulations and future projections of surface air temperature over the Tibetan Plateau of the updated Coupled Model Intercomparison Project phase (CMIP6) and the precedent phase of the project (CMIP5) to quantify differences in the projections under different scenarios. Model evaluation for the historical period indicates that the multi-model ensemble (MME) mean of CMIP6 outperforms CMIP5 MME in simulating spatial-temporal characteristics of surface air temperature. The temperature changes relative to 1986-2005 are projected in the near-term (2021-2040), mid-term (2041-2060), and long-term (2081-2100) future under Shared Socio-economic Pathway (SSP)2-4.5 and SSP5-8.5 of CMIP6 and Representative Concentration Pathway (RCP)4.5 and RCP8.5 of CMIP5. The projected temperature shows larger increases in the long-term compared with the near-term and mid-term under both SSPs and RCPs. CMIP6 MME projects higher temperature changes and accelerated warming trends relative to CMIP5 MME. Additionally, the temperature increases and warming rates show a signi cant elevation dependency, especially in the longterm. The uncertainty for future projections is quanti ed by the square root of error variance (SREV) method. The results record a clear reduction in the uncertainty of CMIP6 temperature relative to CMIP5 primarily concentrated at the elevation zones of over 5,000 m. The analysis of the projected temperature over the Tibetan Plateau is of great signi cance for policy-makers to make socio-economic adjustments for the future warming. This study is conducive to the credibility of future temperature projections for CMIP6 and enhances our comprehension of the uncertainty of SSP and RCP scenarios.

To better understand the mechanisms of the hydro-ecological cycle in the changing environments of the Yangtze River Basin (YZRB), it is valuable to investigate vegetation dynamics and their response to climate change. This study explored the spatial patterns of vegetation dynamics and the essential triggers of regional differences by analyzing vegetation variations in the 1982–2015 period at different time scales and the interannual variability of vegetation sensitivity to climate variability. The results showed that the normalized difference vegetation index (NDVI) increased significantly in the last three decades, but vegetation displayed great spatiotemporal variations at different time scales. The vegetation in the central part of the YZRB dominated by forests and shrublands was more sensitive to climate variability than vegetation in the source region of the YZRB, which was dominated by alpine meadows and tundra (AMT). The contribution of climate variables to the vegetation sensitivity index (VSI) had large spatial differences, but solar radiation and temperature were the dominant factors. Furthermore, 57.9% of the YZRB had increasing VSIs, especially in the south-central part. Consistent with the distributions of elevation and vegetation types, vegetation dynamics in the YZRB were divided into five spatial patterns, with the largest increasing NDVI trend in Region III and the largest VSI in Region IV. Moreover, the VSI exhibited fairly consistent dynamics in all subregions, but the contributions of climate variables to the VSI varied greatly among the different regions.

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Sensitivity analysis of hydrological model parameters is a crucial step in the calibration process of hydrological simulation. In this paper, the improved Morris method with the double-Latin hypercube sampling is proposed for global sensitivity analysis of 10 parameters of the Xin'anjiang model. In addition, the local sensitivity is analyzed based on the rate validation of the model parameters. In general, the results show those parameters about evaporation coefficient in the deep layer (C), free water storage capacity (SM), impervious area as a percentage of total watershed area (IMP), free water storage capacity curve index (EX), groundwater outflow coefficient (KG) and subsurface runoff abatement factor (KKG) are all less than 0.01, insensitive parameters; the parameters about evaporation conversion factor (K) and square times of the storage capacity curve(B) are in the range of [0.01, 0.1], less sensitive parameters; the parameter about flow out coefficient in soil (KSS) is in the range of [0.1, 0.2], a low-sensitivity parameter; the parameter abatement coefficient of mid-soil flow (KKSS) is greater than 1, a high-sensitivity parameter; the improved Morris method better reflects the existence of interactions between parameters. This research result provides a new technical approach for the sensitivity analysis of hydrological model parameters.

Reliable precipitation is crucial for hydrological studies over Tibetan Plateau (TP) basins with sparsely distributed rainfall gauges. In this study, four widely used precipitation products, including the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of the water resources (APHRODITE), the High Asia Reanalysis (HAR), and the satellite-based precipitation estimates from Global Precipitation Measurement (GPM) and Tropical Rainfall Measurement Mission (TRMM), were comprehensively evaluated by combining statistical analysis and hydrological simulation over the Upper Brahmaputra (UB) River Basin of TP during 2001–2013. In respect to the statistical assessment, the overall performances of GPM and HAR are comparable to each other, and both are superior to the other two datasets. For hydrological assessment, both daily and monthly GPM-based streamflow simulations perform the best not only at the UB outlet with very good results, but they also illustrate satisfactory results at Yangcun and Lhasa hydrological stations within the UB. Runoff simulation using HAR only performs well at the UB outlet, whereas it shows poor results at both Yangcun and Lhasa stations. The simulated results based on APHRODITE and TRMM show poor performances at UB. Generally, the GPM shows an encouraging potential for hydro-meteorological investigation over UB, although with some bias in flood simulation.

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