Preprints
https://doi.org/10.5194/egusphere-2026-5635
https://doi.org/10.5194/egusphere-2026-5635
06 Nov 2026
 | 06 Nov 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

GLAMODAT (v1.0): a model-data comparison tool for assessing transient palaeoglacier simulations

Andreas Henz, Sarah Kamleitner, Samuel U. Nussbaumer, Tancrède P. M. Leger, Guillaume Jouvet, and Andreas Vieli

Abstract. Current glacier model-data comparison methods often lack quantitative, automated validation for reconstructing complex palaeoglaciers and palaeo ice fields over millennia. Rigorous validation and automatic evaluation is critical for improving the reliability of glacier reconstructions and their use in understanding past climate and future projections. We introduce an open-source, Python-based comparison tool (GLAMODAT version 1.0) that automatically evaluates palaeoglacier model simulations against dated constraints on glacier history. GLAMODAT successfully quantifies model-data mismatches and demonstrates robustness in both synthetic and real-world case studies. It effectively tracks multiple phases of advance and retreat periods within mountain valleys. It is designed for validating single palaeoglacier simulations or entire ensembles by integrating weighted misfit scoring and adaptive parameter space exploration. It enables advancements in palaeoglacier reconstructions, climate reconstructions, and parameter studies in glacier modelling.

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Andreas Henz, Sarah Kamleitner, Samuel U. Nussbaumer, Tancrède P. M. Leger, Guillaume Jouvet, and Andreas Vieli

Status: open (until 01 Jan 2027)

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Andreas Henz, Sarah Kamleitner, Samuel U. Nussbaumer, Tancrède P. M. Leger, Guillaume Jouvet, and Andreas Vieli
Andreas Henz, Sarah Kamleitner, Samuel U. Nussbaumer, Tancrède P. M. Leger, Guillaume Jouvet, and Andreas Vieli
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Latest update: 07 Nov 2026
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Short summary
We developed a tool to compare computer glacier simulations of ancient glaciers with real-world evidence, helping scientists refine models and better understand past climate. By matching simulated glacier behaviour to geological data, we improve accuracy in reconstructing glacier history and predicting future changes. This work bridges gaps between models and observations, offering clearer insights into glacier and climate dynamics.
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