Leveraging remote observations for calibrating surface energy- and mass balance models: a case study on Hintereisferner

Glaciers are critical to the global socio-ecological system, providing essential ecosystem services and contributing to sea-level rise. They react to ambient atmospheric conditions via surface energy and mass exchanges at the glacier-atmosphere interface and are thus pivotal indicators of ongoing climate change. However, individual atmospheric drivers of glacier change are not well quantified in regional to global glacier modelling, which relies on variants of the temperature-index model due to their ease of use and performance and the reduced need for in-situ observations compared to surface energy balance models.

Leveraging advancements in high-resolution, convection-permitting climate model simulations and a growing body of remotely sensed glacier-specific observations, such as geodetic mass balances and transient snowline altitudes, we explore the possibility of calibrating the surface energy and mass balance model COSIPY using remote observations only as a first step towards applications in unmonitored regions.  

We force COSIPY at Hintereisferner with simulations using the COSMO-CLM model configured with 2.2-km grid spacing from 2000 to 2010 and combine a systematic assessment of the parameter space using Latin Hypercube Sampling and a probabilistic Markov Chain Monte Carlo framework to identify likely posterior parameter values and their associated uncertainties. The calibration outputs are used to assess the energy balance at Hintereisferner and are evaluated against benchmark surface energy balance simulations forced with in-situ observations. We discuss the results in light of commonly used model calibration procedures and validate our results against independent in-situ observations.