Articles | Volume 19, issue 10
https://doi.org/10.5194/tc-19-5111-2025
© 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/tc-19-5111-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Oct 2025
Research article |
| 27 Oct 2025
| 27 Oct 2025
Combining observational data and numerical models to obtain a seamless high-temporal-resolution seasonal cycle of snow and ice mass balance at the MOSAiC Central Observatory
Norwegian Polar Institute, Tromsø, Norway
Faculty of Science and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Glen E. Liston
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
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The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
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Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
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The Cryosphere, 16, 237–257, https://doi.org/10.5194/tc-16-237-2022, https://doi.org/10.5194/tc-16-237-2022, 2022
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The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
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Short summary
A sea ice drifting observatory in 2019 and 2020 provided a year of observations of Arctic snow and sea ice, though some data were interrupted, especially during summer melt onset. We developed a data–model fusion system to produce continuous, high-resolution time series of snow and sea ice parameters. On all three analyzed ice types, snow redistribution correlated with sea ice deformation, and level ice thickness was governed by the thinnest fraction of snow cover.
A sea ice drifting observatory in 2019 and 2020 provided a year of observations of Arctic snow...
