Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice.

The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences for the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo from Medium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, shipborne and in situ campaign data. The results show the best correlation for landfast and multiyear ice of high ice concentrations. For broadband albedo, R2 is equal to 0.85, with the RMS (root mean square) being equal to 0.068; for the melt pond fraction, R2 is equal to 0.36, with the RMS being equal to 0.065. The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to ice drift and challenging for the retrieval surface conditions. Combining all aerial observations gives a mean albedo RMS of 0.089 and a mean melt pond fraction RMS of 0.22. The in situ melt pond fraction correlation is R2 = 0.52 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol, which may contribute to the discrepancy between the satellite value and the observed value: mean R2 = 0.044, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data.

The tides in the Kitikmeot Sea, in the southern Canadian Arctic Archipelago, are found to be heavily influenced by seasonal sea‐ice formation and blocking in a strait. Data from a moored current profiler in Dease Strait exhibit strong tidal damping during wintertime seasonal sea‐ice cover, with 50%–60% reduction in tidal elevation and 65% reduction in tidal velocities. We used a 3D unstratified barotropic numerical tidal model of the region to show that the observed wintertime tidal damping likely requires both high sea‐ice friction and a partial sea‐ice blockage in Victoria Strait (VS), the eastern gateway of the Kitikmeot Sea, where tidal‐induced ridging causes thick, rough ice to accumulate over its shallow sill. Our analysis of the model shows different dynamics for the M₂ and K₁ tides. Both tidal constituents are dominated by the Atlantic tides entering through VS. Overall, ∼90% of the M₂ tidal energy entering VS does not reach Dease Strait because, in addition to dissipation in VS (∼25%), it is significantly diverted into adjoining bays and around an amphidrome in eastern Queen Maud Gulf (∼65%). In contrast, the smaller K₁ tide is less diverted into the subsidiary channels, after ∼20% dissipation in VS and only ∼25% in adjoining bays, it propagates far into the region and is amplified due to resonance in Dease Strait and Coronation Gulf, resulting in larger tidal height than the M₂ tide in Coronation Gulf.