Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections

Future sea-level change projections with process-based stand-alone ice sheet models are typically driven with surface mass balance (SMB) forcing derived from climate models. In this work we address the problems arising from a mismatch of the modelled ice sheet geometry with the geometry used by the climate model. We present a method for applying SMB forcing from climate models to a wide range of Greenland ice sheet models with varying and temporally evolving geometries. In order to achieve that, we translate a given SMB anomaly field as a function of absolute location to a function of surface elevation for 25 regional drainage basins, which can then be applied to different modelled ice sheet geometries. The key feature of the approach is the non-locality of this remapping process. The method reproduces the original forcing data closely when remapped to the original geometry. When remapped to different modelled geometries it produces a physically meaningful forcing with smooth and continuous SMB anomalies across basin divides. The method considerably reduces non-physical biases that would arise by applying the SMB anomaly derived for the climate model geometry directly to a large range of modelled ice sheet model geometries.

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Related Dataset #1 : Dataset for "Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections"

Related Software #1 : hgoelzer/aSMB-remapping v1.0.0

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Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


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Publisher UCAR/NCAR - Library
Publication Date 2020-06-02T00:00:00
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Metadata Date 2025-07-11T19:18:35.923499
Metadata Record Identifier edu.ucar.opensky::articles:23415
Metadata Language eng; USA
Suggested Citation . (2020). Remapping of Greenland ice sheet surface mass balance anomalies for large ensemble sea-level change projections. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7348pmt. Accessed 26 January 2026.

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