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Processes driving changes in sea-ice seasonality and sea-ice thickness were explored for a ‘warm-shelf’ region along the West Antarctic Peninsula using vertically coupled sea-ice-ocean thermodynamic simulations, with and without assimilated satellite sea-ice observations and moored ocean temperature observations. Simulations with assimilated sea-ice observations permitted investigation of surface [thermodynamic and dynamic (e.g., wind-driven)] processes affecting sea-ice thickness and seasonality. Assimilation of quasi-weekly variability in the depth and temperature of the deep warm pycnocline permitted examination of subsurface processes affecting sea-ice. Simulations using assimilated sea-ice observations (and implied motion) always produced greater surface heat fluxes and overall thinner sea ice. Assimilating seasonal and quasi-weekly variability in the depth and temperature of the pycnocline modified the start of the sea-ice season by −23 to +1 d, and also modified the sea ice thickness/seasonality to be thinner/shorter or thicker/longer at sub-seasonal and seasonal timescales, highlighting a mechanism where a shoaling pycnocline enhanced upward deep-water heat fluxes as transient surface-induced turbulence had a greater effect on a reduced mixed layer volume. The observed interplay of surface, subsurface, and sea-ice modulation of ocean-atmosphere heat transfer underscores the importance of representing the interaction between sea-ice concentration and upper ocean variability in climate projections.

The once-contiguous Ellesmere Ice Shelf, first reported in writing by European explorers in 1876, and now almost completely disintegrated, has rolling, wave-like surface topography, the origin of which we investigate using a viscous buckling instability analysis. We show that rolls can develop during a winter season (~ 100 d) if sea-ice pressure (depth-integrated horizontal stress applied to the seaward front of the Ellesmere Ice Shelf) is sufficiently large (1 MPa m) and ice thickness sufficiently low (1–10 m). Roll wavelength initially depends only on sea-ice pressure, but evolves over time depending on amplitude growth rate. This implies that a thinner ice shelf, with its faster amplitude growth rate, will have a shorter wavelength compared to a thicker ice shelf when sea-ice pressure is equal. A drawback of the viscous buckling mechanism is that roll amplitude decays once sea-ice pressure is removed. However, non-Newtonian ice rheology, where effective viscosity, and thus roll change rate, depends on total applied stress may constrain roll decay rate to be much slower than growth rate and allow roll persistence from year to year. Whether the viscous-buckling mechanism we explore here ultimately can be confirmed as the origin of the Ellesmere Ice Shelf rolls remains for future research.

Southern Ocean sea ice can exhibit widespread flooding and subsequent snow-ice formation, due to relatively thick snow covers compared to the total ice thickness. Considerable subkilometer scale variability in snow and ice thickness causes poorly constrained uncertainties in determining the amount of flooding that occurs. Using datasets of snow depth and ice thickness acquired in the Weddell Sea during austral winter 2013 (AWECS campaign) from three floes, we demonstrate large spatial variability of a factor 10 and 5 for snow and combined snow and ice thickness, respectively. The temporal evolution after the floe visit was recorded by automatic weather station and ice mass balance buoys. Using a physics-based, multi-layer snow/sea ice model in a one-dimensional and distributed mode to simulate the thermodynamic processes, we show that the distributed simulations, modeling flooding across the entire heterogeneous floe, produced vastly different amounts of flooding than one-dimensional single point simulations. Three times the flooding is produced in the one-dimensional simulation for the buoy location than distributed (floe-averaged) simulations. The latter is in close agreement with buoy observations. The results suggest that using point observations or one-dimensional simulations to extrapolate processes on the floe-scale can overestimate the amount of flooding and snow-ice formation.

The inaugural data from the first systematic program of sea-ice observations in Kotzebue Sound, Alaska, in 2018 coincided with the first winter in living memory when the Sound was not choked with ice. The following winter of 2018–19 was even warmer and characterized by even less ice. Here we discuss the mass balance of landfast ice near Kotzebue (Qikiqtaġruk) during these two anomalously warm winters. We use in situ observations and a 1-D thermodynamic model to address three research questions developed in partnership with an Indigenous Advisory Council. In doing so, we improve our understanding of connections between landfast ice mass balance, marine mammals and subsistence hunting. Specifically, we show: (i) ice growth stopped unusually early due to strong vertical ocean heat flux, which also likely contributed to early start to bearded seal hunting; (ii) unusually thin ice contributed to widespread surface flooding. The associated snow ice formation partly offset the reduced ice growth, but the flooding likely had a negative impact on ringed seal habitat; (iii) sea ice near Kotzebue during the winters of 2017–18 and 2018–19 was likely the thinnest since at least 1945, driven by a combination of warm air temperatures and a persistent ocean heat flux.

In an effort to improve the reliability of Arctic sea-ice predictions, an ensemble-based Arctic Ice Ocean Prediction System (ArcIOPS) has been developed to meet operational demands. The system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model. A localized error subspace transform ensemble Kalman filter is used to assimilate the weekly merged CryoSat-2 and Soil Moisture and Ocean Salinity sea-ice thickness data together with the daily Advanced Microwave Scanning Radiometer 2 (AMSR2) sea-ice concentration data. The weather forecasts from the Global Forecast System of the National Centers for Environmental Prediction drive the sea ice–ocean coupled model. The ensemble mean sea-ice forecasts were used to facilitate the Chinese National Arctic Research Expedition in summer 2017. The forecasted sea-ice concentration is evaluated against AMSR2 and Special Sensor Microwave Imager/Sounder sea-ice concentration data. The forecasted sea-ice thickness is compared to the in-situ observations and the Pan-Arctic Ice-Ocean Modeling and Assimilation System. These comparisons show the promising potential of ArcIOPS for operational Arctic sea-ice forecasts. Nevertheless, the forecast bias in the Beaufort Sea calls for a delicate parameter calibration and a better design of the assimilation system.