ODINN-SciML/MassBalanceMachine
Global machine learning glacier mass balance model, capable of assimilating all sources of glaciological and remote sensing data
This project helps glaciologists and climate scientists understand how glaciers are changing by predicting their surface mass balance. You provide meteorological and topographical data, and it outputs predictions or fills data gaps for glacier mass balance on monthly, seasonal, or annual scales. It is designed for researchers studying glacial dynamics and climate impact.
Use this if you need to model glacier surface mass balance globally, assimilate various glaciological and remote sensing data, or fill in missing data for specific regions and timeframes.
Not ideal if your primary interest is in localized, highly detailed ice flow dynamics rather than broad-scale mass balance predictions.
Stars
41
Forks
21
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Feb 05, 2026
Commits (30d)
0
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