Summary
This study evaluates the performance of 26 CMIP6 climate models in simulating climate variables over High Mountain Asia, including the Tibetan Plateau, using observational data from 1979–2014. The models exhibit a mean cold bias of −1.9 °C, snow cover overestimation of 12%, and precipitation overestimation of 1.5 mm d⁻¹, with biases more pronounced in winter and at high elevation. Projections using 10 models to 2100 under four Shared Socioeconomic Pathways show significant inter-model variability, and no single model performs optimally across all three climate variables.
Regional applicability
This study is global in scope and addresses climate modelling uncertainties in a region of major hydrological importance (water resources for downstream Asia). The findings on model biases at high elevation are relevant to United Kingdom mountain regions (Scottish Highlands, Welsh mountains) where similar elevation-dependent climate processes occur, and may inform interpretation of UK climate projections in mountainous areas.
Key measures
Near-surface air temperature bias (°C), snow cover extent bias (%), precipitation bias (mm d⁻¹), relative biases (%), correlation between model biases and surface elevation
Outcomes reported
Assessment of 26 CMIP6 general circulation models' skill in simulating near-surface air temperature, snow cover extent, and precipitation over High Mountain Asia (1979–2014) and future projections to 2100 under four emissions scenarios. Evaluation of model biases and their relationship to surface elevation and inter-model variability.
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