ODINN-SciML/MassBalanceMachine
Global machine learning glacier mass balance model, capable of assimilating all sources of glaciological and remote sensing data
Leverages multi-temporal ML models (annual, seasonal, monthly) trained on in-situ stake measurements and geodetic surveys to predict mass balance across arbitrary spatial resolutions from meteorological and topographic inputs. Bridges observational data gaps by jointly assimilating heterogeneous glaciological and remote sensing sources, enabling spatially consistent reconstructions at user-defined temporal granularity.
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41
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21
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 05, 2026
Commits (30d)
0
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