The European Space Agency's CryoSat‐2 satellite mission provides radar altimeter data that are used to derive estimates of sea ice thickness and volume. These data are crucial to understanding recent variability and changes in Arctic sea ice. Sea ice thickness retrievals at the CryoSat‐2 frequency require accurate measurements of sea ice freeboard, assumed to be attainable when the main radar scattering horizon is at the snow/sea ice interface. Using an extensive snow thermophysical property dataset from late winter conditions in the Canadian Arctic, we examine the role of saline snow on first‐year sea ice (FYI), with respect to its effect on the location of the main radar scattering horizon, its ability to decrease radar penetration depth, and its impact on FYI thickness estimates. Based on the dielectric properties of saline snow commonly found on FYI, we quantify the vertical shift in the main scattering horizon. This is found to be approximately 0.07 m. We propose a thickness‐dependent snow salinity correction factor for FYI freeboard estimates. This significantly reduces CryoSat‐2 FYI retrieval error. Relative error reductions of ~11% are found for an ice thickness of 0.95 m and ~25% for 0.7 m. Our method also helps to close the uncertainty gap between SMOS and CryoSat‐2 thin ice thickness retrievals. Our results indicate that snow salinity should be considered for FYI freeboard estimates.

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.

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Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On firstyear sea ice (FYI), spatiotemporal variations in snow properties

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