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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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...
