is constrained to 10 9 satellite and in situ observations.
12• Strict adherence to conservation laws ensures all sources/sinks can be accounted 13 for, enabling application for meaningful budget analyses.
14• ASTE captures the large-scale dynamics of the Arctic ocean-sea ice system includ-15 ing variability and trends in heat and freshwater storage.
The lack of continuous spatial and temporal sampling of hydrographic measurements in large parts of the Arctic Ocean remains a major obstacle for quantifying mean state and variability of the Arctic Ocean circulation. This shortcoming motivates an assessment of the utility of Argo-type floats, the challenges of deploying such floats due to the presence of sea ice, and the implications of extended times of no surfacing on hydrographic inferences. Within the framework of an Arctic coupled ocean–sea ice state estimate that is constrained to available satellite and in situ observations, we establish metrics for quantifying the usefulness of such floats. The likelihood of float surfacing strongly correlates with the annual sea ice minimum cover. Within the float lifetime of 4–5 years, surfacing frequency ranges from 10–100 days in seasonally sea ice–covered regions to 1–3 years in multiyear sea ice–covered regions. The longer the float drifts under ice without surfacing, the larger the uncertainty in its position, which translates into larger uncertainties in hydrographic measurements. Below the mixed layer, especially in the western Arctic, normalized errors remain below 1, suggesting that measurements along a path whose only known positions are the beginning and end points can help constrain numerical models and reduce hydrographic uncertainties. The error assessment presented is a first step in the development of quantitative methods for guiding the design of observing networks. These results can and should be used to inform a float network design with suggested locations of float deployment and associated expected hydrographic uncertainties.
A number of feedbacks regulate the response of Arctic sea ice to local atmospheric warming. Using a realistic coupled ocean-sea ice model and its adjoint, we isolate a mechanism by which significant ice growth at the end of the melt season may occur as a lagged response to Arctic atmospheric warming. A series of perturbation simulations informed by adjoint model-derived sensitivity patterns reveal the enhanced ice growth to be accompanied by a reduction of snow thickness on the ice pack. Detailed analysis of ocean-ice-snow heat budgets confirms the essential role of the reduced snow thickness for persistence and delayed overshoot of ice growth. The underlying mechanism is a snow-melt-conductivity feedback, wherein atmosphere-driven snow melt leads to a larger conductive ocean heat loss through the overlying ice layer. Our results highlight the need for accurate observations of snow thickness to constrain climate models and to initialize sea ice forecasts. Plain Language Summary In this study we explore the relationship between Arctic sea ice growth and near-surface air temperature in a modeling framework. By mapping the time-and space-evolving sensitivity of the Arctic ice volume to changes in air temperature, we show that warming at the end of the melting season can lead to thicker ice at the end of the following winter. Warmer air temperatures can melt snow and remove the insulation it provides, exposing the ice surface to subfreezing air temperatures. We show that removal of this insulating snow layer is essential for enhancing sea ice growth later on, by allowing more heat to be conducted up and out of the underlying ocean, supporting seawater freezing. Our results highlight the importance of measuring snow thickness for accurately forecasting Arctic sea ice.
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