A large retreat of sea-ice in the ‘stormy’ Atlantic Sector of the Arctic Ocean has become evident through a series of record minima for the winter maximum sea-ice extent since 2015. Results from the Norwegian young sea ICE (N-ICE2015) expedition, a five-month-long (Jan-Jun) drifting ice station in first and second year pack-ice north of Svalbard, showcase how sea-ice in this region is frequently affected by passing winter storms. Here we synthesise the interdisciplinary N-ICE2015 dataset, including independent observations of the atmosphere, snow, sea-ice, ocean, and ecosystem. We build upon recent results and illustrate the different mechanisms through which winter storms impact the coupled Arctic sea-ice system. These short-lived and episodic synoptic-scale events transport pulses of heat and moisture into the Arctic, which temporarily reduce radiative cooling and henceforth ice growth. Cumulative snowfall from each sequential storm deepens the snow pack and insulates the sea-ice, further inhibiting ice growth throughout the remaining winter season. Strong winds fracture the ice cover, enhance ocean-ice-atmosphere heat fluxes, and make the ice more susceptible to lateral melt. In conclusion, the legacy of Arctic winter storms for sea-ice and the ice-associated ecosystem in the Atlantic Sector lasts far beyond their short lifespan.

Snow is a crucial component of the Arctic sea ice system. Its thickness and thermal properties control heat conduction and radiative fluxes across the ocean, ice, and atmosphere interfaces. Hence, observations of the evolution of snow depth, density, thermal conductivity, and stratigraphy are crucial for the development of detailed snow numerical models predicting energy transfer through the snow pack. Snow depth is also a major uncertainty in predicting ice thickness using remote sensing algorithms. Here we examine the winter spatial and temporal evolution of snow physical properties on first‐year (FYI) and second‐year ice (SYI) in the Atlantic sector of the Arctic Ocean, during the Norwegian young sea ICE (N‐ICE2015) expedition (January to March 2015). During N‐ICE2015, the snow pack consisted of faceted grains (47%), depth hoar (28%), and wind slab (13%), indicating very different snow stratigraphy compared to what was observed in the Pacific sector of the Arctic Ocean during the SHEBA campaign (1997–1998). Average snow bulk density was 345 kg m−3 and it varied with ice type. Snow depth was 41 ± 19 cm in January and 56 ± 17 cm in February, which is significantly greater than earlier suggestions for this region. The snow water equivalent was 14.5 ± 5.3 cm over first‐year ice and 19 ± 5.4 cm over second‐year ice.

Snow‐depth distributions on sea ice have substantial impacts on winter ice growth and summer ice melt. There are two types of wind‐related snow distributions in this environment: snowdrifts that form around ice pressure ridges; and snow dunes and other snow bedforms that form on relatively level, undeformed ice. A snow‐evolution modeling system (SnowModel) was tested against winter snow observations collected during the Norwegian young sea ICE expedition (N‐ICE2015) north of Svalbard, with an emphasis on reproducing these two types of snow distributions. The SnowModel simulation spanned 1 year, summer 2014 through summer 2015, over a 1.5 km by 1.5 km domain, using a 1 m horizontal grid increment and 3 h time step. Existing SnowModel components, created originally for terrestrial applications, performed energy balance, snow property, snowdrift, and data assimilation calculations in response to prescribed meteorological forcings. A new SnowModel component, SnowDunes, was created to simulate snow‐bedform distributions on level, undeformed ice. Model results reproduced observed snowdrift profiles around pressure ridges and snow‐depth distributions over level, undeformed ice, resulting in physically realistic snow heterogeneity and property information. We conclude that the SnowModel toolkit contains the components required to simulate most processes driving the seasonal distribution of snow on sea ice. SnowModel can evolve snow on sea ice over local to pan‐Arctic areas, using grid increments ranging from 1 m to tens of km, and time increments of subhourly to daily.

During the Norwegian young sea ICE (N‐ICE2015) campaign in early 2015, a deep snowpack was observed, almost double the climatology for the region north of Svalbard. There were significant amounts of snow‐ice in second‐year ice (SYI), while much less in first‐year ice (FYI). Here we use a 1‐D snow/ice thermodynamic model, forced with reanalyses, to show that snow‐ice contributes to thickness growth of SYI in absence of any bottom growth, due to the thick snow. Growth of FYI is tightly controlled by the timing of growth onset relative to precipitation events. A later growth onset can be favorable for FYI growth due to less snow accumulation, which limits snow‐ice formation. We surmise these findings are related to a phenomenon in the Atlantic sector of the Arctic, where frequent storm events bring heavy precipitation during autumn and winter, in a region with a thinning ice cover.

During the N-ICE2015 drift expedition north-west of Svalbard, we observed the establishment and development of algal communities in first-year ice (FYI) ridges and at the snow-ice interface. Despite some indications of being hot spots for biological activity, ridges are under-studied largely because they are complex structures that are difficult to sample. Snow infiltration communities can grow at the snow-ice interface when flooded. They have been commonly observed in the Antarctic, but rarely in the Arctic, where flooding is less common mainly due to a lower snow-to-ice thickness ratio. Combining biomass measurements and algal community analysis with under-ice irradiance and current measurements as well as light modeling, we comprehensively describe these two algal habitats in an Arctic pack ice environment. High biomass accumulation in ridges was facilitated by complex surfaces for algal deposition and attachment, increased light availability, and protection against strong under-ice currents. Notably, specific locations within the ridges were found to host distinct ice algal communities. The pennate diatoms Nitzschia frigida and Navicula species dominated the underside and inclined walls of submerged ice blocks, while the centric diatom Shionodiscus bioculatus dominated the top surfaces of the submerged ice blocks. Higher light levels than those in and below the sea ice, low mesozooplankton grazing, and physical concentration likely contributed to the high algal biomass at the snow-ice interface. These snow infiltration communities were dominated by Phaeocystis pouchetii and chain-forming pelagic diatoms (Fragilariopsis oceanica and Chaetoceros gelidus). Ridges are likely to form more frequently in a thinner and more dynamic ice pack, while the predicted increase in Arctic precipitation in some regions in combination with the thinning Arctic icescape might lead to larger areas of sea ice with negative freeboard and subsequent flooding during the melt season. Therefore, these two habitats are likely to become increasingly important in the new Arctic with implications for carbon export and transfer in the ice-associated ecosystem.