Articles | Volume 17, issue 7
https://doi.org/10.5194/essd-17-3203-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-3203-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A high-resolution pan-Arctic meltwater discharge dataset from 1950 to 2021
Adam Igneczi
CORRESPONDING AUTHOR
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Jonathan Louis Bamber
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Department of Aerospace and Geodesy, Technical University of Munich, Munich, Germany
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Our study uses deep learning to produce a new high-resolution calving front dataset for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, containing 124 919 terminus traces. This dataset offers insights into understanding calving mechanisms and can help improve glacier frontal ablation estimates as a component of the integrated mass balance assessment.
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Short summary
Freshwater from Arctic land ice loss strongly affects the Arctic and North Atlantic oceans. Datasets describing this freshwater discharge have low resolution and do not cover the entire Arctic. We statistically enhanced coarse-resolution climate model data – from approximately 6 km to 250 m – and routed meltwater towards the coastlines to provide high-resolution data covering all Arctic regions. This approach has far fewer computational requirements than running climate models at high resolution.
Freshwater from Arctic land ice loss strongly affects the Arctic and North Atlantic oceans....
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