ACINN Graduate Seminar - SS 2025

2025-06-04 at 12:00 (on-line and on-site)

Harnessing satellite observations for calibrating surface energy- and mass balance models: a case study on Hintereisferner using COSIPY

Niklas Richter

ACINN, University of Innsbruck, Austria

 

Glaciers play a crucial role in the global socio-ecological system, providing essential ecosystem services and contributing to sea-level rise. They respond to ambient atmospheric conditions through surface energy and mass exchanges at the glacier-atmosphere interface, making them key indicators of ongoing climate change. However, the atmospheric drivers of glacier change beyond global warming remain poorly quantified in regional to global glacier modeling, which predominantly relies on temperature-index models due to their simplicity, strong performance, and reduced dependency on in-situ observations compared to surface energy balance models.
With the increasing availability of high-resolution, convection-permitting climate simulations and a growing body of remotely sensed glacier observations, such as geodetic mass balances and transient snowline altitudes, we explore the potential for calibrating the surface energy and mass balance model COSIPY at Hintereisferner using remote observations alone. This serves as a first step toward extending applications to unmonitored regions.
We force COSIPY with simulations from the COSMO-CLM model configured at 2.2-km grid spacing for the period 2000–2010 and downscaled to 20m elevation bands using locally derived lapse rates. The parameter space was systematically assessed using Latin Hypercube Sampling combined with a probabilistic Markov Chain Monte Carlo framework to identify likely posterior parameter values and their uncertainties. The model performance evaluated against available on-glacier data at Hintereisferner for a single sample year is unexpectedly good, given that the parameter calibration suffers from non-identifiability. The calibration results further provide insights into the energy balance at Hintereisferner and are benchmarked against surface energy balance simulations driven by in-situ observations to study possible bias cancellations.

 

 

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