Published January 29, 2026 | Version 0.1.0
Dataset Open

Deliverable D2.4 Glacier mass balance data set

  • 1. EDMO icon University of Bristol, School of Geographical Sciences
  • 2. Technical University of Munich

Description

This dataset provides annual glacier mass balance estimates derived using an uncertainty-aware machine learning framework based on Bayesian Neural Fields. The dataset covers all glacierized regions defined in RGIv7 except Regions 19 and 20 (19: Sub-Antarctic and Antarctic Islands, 20: Antarctic Mainland). Temporal coverage spans 1979–2019. This dataset is intended as a global, consistent Bayesian prior for glacier mass balance. This is a preliminary release of pretrained outputs; it is intended to work as a prior for Bayesian ML and has not been finetuned on observations. The dataset structure is subject to significant change after finetuning on observations.

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lq_submission_v010.zip

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Additional details

Funding

European Commission
LIQUIDICE - LinkIng and QUantifying the Impacts of climate change on inlanD ICE, snow cover, and permafrost on water resources and society in vulnerable regions 101184962