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Abstract

The region of High Mountain Asia hosts the largest assemblage of glaciers outside the poles and is already subject to regional water allocation conflicts and geomorphic hazards due to increasing glacier mass loss and global warming. Despite the need for improved glacier health monitoring, in situ measurements of glaciers are sparse and focused on a few selected glaciers.This imposes limitations for the applicability of surface energy balance (SEB) models as their usage is limited to glaciers with sufficient observations to address the dependency on reliant forcing data and the need for calibrated model parameters, often extracted using previous empirical knowledge or tuned with observations. Therefore, most regional glacier mass change studies are obtained via remote-sensing based geodetic estimates or variations of the temperature-index model that do not allow for the quantification and attribution of the driving forces of glacier melt.In this study, we aim to evaluate the possibility of extending SEB simulations from local to regional scale by introducing a semi-automated model parameter calibration of the open-source COSIPY model forced with high resolution climate simulations for the period of 2010 to 2020.We do so by employing a cost-function informed Markov Chain Monte Carlo sampling algorithm which evaluates the mismatch between existing snowline and geodetic mass balance observations.The calibration results will be used to investigate the atmospheric drivers of few selected glaciers and compared to existing studies and measurements to evaluate both the feasibility of the applied framework and the uncertainty due to parameter choices.