Preprints
https://doi.org/10.5194/egusphere-2026-4690
https://doi.org/10.5194/egusphere-2026-4690
14 Oct 2026
 | 14 Oct 2026
Status: this preprint is open for discussion and under review for The Cryosphere (TC).

How well do climate models estimate the historical surface mass balance of the Antarctic ice sheet?

Clément Cherblanc, Charles Amory, Fredrik Boberg, Alexandra Gossart, Nicolaj Hansen, Marte Gé Hofsteenge, Christine Schøtt Hvidberg, Sylvain Marchi, Masashi Niwano, Florian Sauerland, Niels Souverijns, José Abraham Torres-Alavez, Baptiste Vandecrux, Christiaan van Dalum, Willem Jan van de Berg, Nicole van Lipzig, Maurice van Tiggelen, Kristiina Verro, and Ruth Mottram

Abstract. Earth System Model (ESM)-derived Surface Mass Balance (SMB) serves as input for ice sheet models and to make estimates of sea level rise. However, there are few previous studies examining the biases in ESMs when modelling SMB under the historical (1985–2014) period, which may elucidate biases in future projections. Regional Climate Models (RCMs) are often used as a computationally expensive step in improving modelled SMB at the present day and for future projections. It is also unclear whether they add value to SMB estimates on the Antarctic Ice Sheet (AIS), where the topography of the Plateau is relatively smooth. We evaluate SMB from 4 ESMs, 13 ESM-driven RCM simulations, 3 reanalyses and 13 reanalysis-driven RCM simulations, with 76003 AIS SMB observations compiled in the SUMup dataset. We find that ESMs can have consistent Antarctic-wide biases that are related to their temperature biases, and regional biases specific to each ESM. Downscaling with RCMs greatly improves the modelling of SMB relative to ESMs: they systematically increase the correlation coefficient (R; from 0.71 for ESMs to 0.86 for ESM-driven RCMs) and Perkins Skill Score (PSS; from 0.38 to 0.67), and reduce the Root-Mean-Squared Error (RMSE; from 17.90 cm to 15.60 cm). However, RCM downscaling does not systematically outperform reanalyses according to the same metrics (R from 0.88 to 0.90; PSS from 0.58 to 0.69; and RMSE from 11.45 cm to 11.22 cm). When downscaling, RCMs carry strong biases from their driving models, and performance improvement often stems from regional rather than continent-wide improvements. An important caution in interpreting our results is that observations are unevenly distributed in both time and space, hindering a truly unbiased ice sheet-wide assessment of SMB. However, we find that the density of observations is sufficient to identify the biases between models and observations in Dronning Maud Land and West Antarctica, but there are insufficient measurements in the rest of East Antarctica and the Peninsula, where high added value of RCMs is expected, suggesting that these regions should be a target for future observational campaigns.

Competing interests: At least one of the (co-)authors is a member of the editorial board of The Cryosphere.

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Clément Cherblanc, Charles Amory, Fredrik Boberg, Alexandra Gossart, Nicolaj Hansen, Marte Gé Hofsteenge, Christine Schøtt Hvidberg, Sylvain Marchi, Masashi Niwano, Florian Sauerland, Niels Souverijns, José Abraham Torres-Alavez, Baptiste Vandecrux, Christiaan van Dalum, Willem Jan van de Berg, Nicole van Lipzig, Maurice van Tiggelen, Kristiina Verro, and Ruth Mottram

Status: open (until 25 Nov 2026)

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Clément Cherblanc, Charles Amory, Fredrik Boberg, Alexandra Gossart, Nicolaj Hansen, Marte Gé Hofsteenge, Christine Schøtt Hvidberg, Sylvain Marchi, Masashi Niwano, Florian Sauerland, Niels Souverijns, José Abraham Torres-Alavez, Baptiste Vandecrux, Christiaan van Dalum, Willem Jan van de Berg, Nicole van Lipzig, Maurice van Tiggelen, Kristiina Verro, and Ruth Mottram
Clément Cherblanc, Charles Amory, Fredrik Boberg, Alexandra Gossart, Nicolaj Hansen, Marte Gé Hofsteenge, Christine Schøtt Hvidberg, Sylvain Marchi, Masashi Niwano, Florian Sauerland, Niels Souverijns, José Abraham Torres-Alavez, Baptiste Vandecrux, Christiaan van Dalum, Willem Jan van de Berg, Nicole van Lipzig, Maurice van Tiggelen, Kristiina Verro, and Ruth Mottram
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Latest update: 14 Oct 2026
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Short summary
Regional Climate Models are known to improve the modelling of meteorological variables, like snow accumulation, in mountainous areas, relative to coarser global models. It was unclear whether they also improve the modelling over the Antarctic Ice Sheet, which is mostly a nearly flat, high-elevation plateau. We find that Regional Climate Models do perform better than global models on most metrics tested, building trust in the regional models for future Antarctic projections.
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