Abstract ID: 28.7293 | Accepted as Poster | Poster | 2025-02-27 13:00 - 14:30 | Ágnes‐Heller‐Haus/Small Lecture Room

Glaciers are pivotal indicators of climate change, reacting to ambient atmospheric conditions via instantaneous surface energy- and mass exchanges at the atmosphere-glacier interface. These exchange processes are often not quantified in global glacier models, which usually rely on a variation of the temperature-index model. Instead, surface energy- and mass balance models enable the attribution of such meteorological drivers but their application is mostly limited to sites with in-situ observations to provide the requisite forcing data and calibrated model parameters. This study investigates the possibility of applying a surface energy- and mass balance model at unmonitored glaciers. To do this, we test methods to calibrate COSIPY using only satellite data of geodetic mass balances and transient snowline altitudes for Hintereisferner and force COSIPY with hourly data from 2.2-km horizontal grid spacing COSMO-CLM simulations. We apply Latin Hypercube Sampling (LHS) to systematically explore the model parameter space and investigate the possibility of a probabilistic Markov Chain Monte Carlo (MCMC) parameter calibration approach, focusing on addressing the issue of over-parameterisation. Model performance evaluated against available on-glacier data at Hintereisferner for a single sample year is unexpectedly good given that the parameter calibration is demonstrated to suffer from non-identifiability.