Lars Kaleschke (@seaice.det.social.ap.brid.gy)

New paper: Itkin, P. and Liston, G. E.: 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, The Cryosphere, 19, 5111–5133, https://doi.org/10.5194/tc-19-5111-2025, 2025.

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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 Abstract. Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) observations span an entire annual cycle of Arctic snow and sea ice cover. However, the measurements of atmospheric and ocean forcing, as well as distributed measurements of snow and ice properties, were occasionally interrupted for logistical reasons. The most prolonged interruption happened during the onset of the summer melt season. Here we introduce and apply a novel data–model fusion system that can assimilate relevant observational data in a collection of modeling tools (SnowModel-LG and HIGHTSI) to provide continuous high-temporal-resolution (3-hourly) time series of snow and sea ice parameters over the entire annual cycle. We used this system to analyze differences between the three main ice types found in the MOSAiC Central Observatory: relatively deformed second-year ice, second-year ice with extensive smooth refrozen melt pond surfaces, and first-year ice. Since SnowModel-LG and HIGHTSI were used in a 1-D configuration, we used a sea ice dynamics term D to parameterize the redistribution of snow to newly created ridges and leads. D correlated highly with the sea ice deformation (R2 = 59 %, N=33) in the vicinity of the observatory, and deformation appears to explain as much as 15 % of all winter snow water equivalent. In addition, we show, in separate simulations for level ice, that snow bedforms with thin snow in the bedform troughs largely control the ice growth. Here, the mean snow depth minus 1 standard deviation was required to simulate realistic sea ice thickness using HIGHTSI; we surmise that this accounts for the control of relatively thin snow on local ice growth. Despite different initial sea ice thickness and freeze-up dates, the sea ice thickness of level ice across all ice types became similar by early winter. Our simulations suggest that the mean (spatially distributed) MOSAiC snowmelt onset began in late May but was interrupted by a snowfall event and was delayed by 3 weeks until mid- June. The level ice started to melt in the last week of June. Depending on the sea ice topography, the ice was snow-free by late June and early July. https://tc.copernicus.org/articles/19/5111/2025/