Welcome to the ICEBOOST viewer

A machine learning model for glaciers ice thickness

LAST PAGE UPDATE: 14-June-2025

Funding from the EU commission UNIVE UCI

The SKYNET project is funded by the European Commission, under the Marie Curie Global Fellowship scheme, grant no. 101066651.

RGI 62
RGI 70
DATA
Globe
SAT

    ICEBOOST v1.1

    ≥800 700 600 500 400 300 200 100 0
    ICE THICKNESS [m]
    ≥1500 1125 750 375 0 -125 -250 -375 ≤-500
    BED ELEV [m a.s.l]

    Model published in Geoscientific Model Development: https://gmd.copernicus.org/articles/18/2545/2025/

    ICEBOOST is a gradient boosted decision tree model. It averages equally the predictions from XGBoost and CatBoost. Both are trained independently for regression, using a l2 loss, and optimized globally.

    MODEL DOMAIN

    The model runs on all glaciers defined in the Randolph Glacier Inventory [Pfeffer and The Randolph Consortium, 2017]. The model is trained on version v.62, which includes ice bodies with direct connection to the ice sheets. The model can be deployed on v. 62 or the most recent v. 70.

    MODEL TARGET

    MODEL INPUTS