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The seasonal asymmetry in coastal temperatures on Hudson Bay was explored and evaluated as a proxy to hindcast sea ice conditions prior to 1972. Various indices of air temperature difference (∆T) between Churchill, MB and Inukjuak, QC were tested for linear correlations with spatially averaged sea ice concentration (SIC) and ice-free season length (IFS). A multiple regression equation employing a 31-day average of peak ∆T and a 61-day average of temperature during freeze-up reproduced the IFS record with an average error of 8.1 days. This equation was employed to extend the IFS record by 28 years. The resulting 68-year time series revealed a significant increasing trend most pronounced from 1985 to 2011. Hindcast data helped eliminate low-frequency climate oscillations of periodicity <68 years as a source of this trend, lending further evidence to the growing consensus of a declining sea ice being the result of anthropogenic climate forcing.

The formation and dissolution of the North Water Polynya (an area of open water surrounded by a sea-ice covered ocean) was examined to determine the spatial and temporal variability of the Smith Sound ice arch (a feature that prevents ice from covering the polynya). A passive microwave, sea ice concentration dataset was used to create an index classification algorithm that categorized the formation and dissolution of the North Water Polynya from 1979 to 2012. Multiple years were classified as atypical, with the polynya forming earlier, the ice arch not forming at Smith Sound, or the ice arch not forming at all. Secondly, we compare and contrast atmospheric factors that influenced the formation of the ice arch during a typical (2010-2011) and an atypical (2009-2010) formation year. A significant southerly wind event in 2009-2010 could have displaced the ice pack and prevented the consolidation of the ice arch. The importance of the changing ice pack in Nares Strait to the formation of the polynya is also discussed. / May 2016

Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into large-scale sea ice models, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs) carried out with first a simplified model of the Arctic sea ice pack then with NEMO-LIM2, a primitive equation ocean general circulation model coupled to LIM (Louvain-la-Neuve sea ice model). Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data also helps in improving the model results, but it has to be handled with care because of the strong link between ice concentration and ice thickness. Therefore, we show that one should conserve the ice thickness (not the ice volume) when ice concentration data are assimilated into the model. We also demonstrate that one should assimilate sea ice concentration and velocity data simultaneously. Finally, we give some concrete keys in order to choose which observational data set to assimilate.

Ice formed from seawater, called sea ice, is both an important actor in and a sensitive indicator of climate change. Covering 7% of the World Ocean, sea ice damps the atmosphere-ocean exchanges of heat, radiation and momentum in polar regions. It also affects the oceanic circulation at a global scale. Recent satellite and submarine observations systems indicate a sharp decrease in the extent and volume of Arctic sea ice over the last 30 years. In addition, climate models project drastic sea ice reductions for the next century, in both hemispheres, with potentially large consequences on climate and ecosystems. Contrary to what is commonly believed, sea ice retains about 25% of the oceanic salt when it forms. As salt cannot lock in the ice crystalline lattice, it accumulates in liquid inclusions of salty water (brine). Under a temperature change, the inclusions freeze or melt and release or absorb huge amounts of latent heat. This affects heat transfer through and storage in sea ice, which may affect the mass balance of sea ice at a global scale. This is the central hypothesis of this work. In order to address this problem, the author develops two sea ice models and assesses their ability to simulate the recent evolution of the sea ice mass balance. Then, the physics of brine uptake and drainage are included in the models and sea ice desalination is investigated. Finally, the impact of sea ice salinity variations on the global sea ice mass balance is studied. The roles of sea ice thermal properties, of ice-ocean salt / fresh water fluxes and of oceanic feedbacks are evaluated. The new salinity module improves the simulation of ice and ocean characteristics compared to observations. Including salinity variations increases ice growth, reduces vertical mixing in the ocean and the ocean-to-ice heat flux. In conclusion, salinity variations should be included in future sea ice models used for climate projections.

Data assimilation into sea ice models designed for climate studies has started about 15 years ago. In most of the studies conducted so far, it is assumed that the improvement brought by the assimilation is straightforward. However, some studies suggest this might not be true. In order to elucidate this question and to find an appropriate way to further assimilate sea ice concentration and velocity observations into large-scale sea ice models, we analyze here results from a number of twin experiments (i.e. experiments in which the assimilated data are model outputs) carried out with first a simplified model of the Arctic sea ice pack then with NEMO-LIM2, a primitive equation ocean general circulation model coupled to LIM (Louvain-la-Neuve sea ice model). Our objective is to determine to what degree the assimilation of ice velocity and/or concentration data improves the global performance of the model and, more specifically, reduces the error in the computed ice thickness. A simple scheme is used, and outputs from a control run and from perturbed experiments without and with data assimilation are thoroughly compared. Our results indicate that, under certain conditions depending on the assimilation weights and the type of model error, the assimilation of ice velocity data enhances the model performance. The assimilation of ice concentration data also helps in improving the model results, but it has to be handled with care because of the strong link between ice concentration and ice thickness. Therefore, we show that one should conserve the ice thickness (not the ice volume) when ice concentration data are assimilated into the model. We also demonstrate that one should assimilate sea ice concentration and velocity data simultaneously. Finally, we give some concrete keys in order to choose which observational data set to assimilate.

Arctic Ocean contributes to the global oceanic uptake of CO2 by about 5% to 14% in taking up from 66 to 199 TgC yr-1. However, the role of the marine cryosphere was ignored because it is considered as an impermeable barrier, impeding the gas exchanges between the ocean and the atmosphere [Bates and Mathis, 2009]. However, a growing body of evidence suggests that gases exchange could occur between sea ice and the atmosphere. In this context, two Arctic surveys were carried out in the framework of the International Polar Year (IPY). From there, we present a snapshot of the partial pressure of CO2 (pCO2) dynamics firstly during the initial sea ice growth and secondly from early spring to the beginning of the summer. We confirmed previous laboratory measurement findings that growing young sea ice acts as a source of CO2 to the atmosphere by measuring CO2 efflux from the ice (4 to 10 mmol m-2 d-1). We also confirmed the precipitation of calcium carbonate as ikaite in the frost flowers and throughout the ice and its negligible role on the effluxes of CO2. In early spring, supersaturations in CO2 (up to 1834 µatm) were observed in sea ice as consequence of concentration of solutes in brines, CaCO3 precipitation and microbial respiration. As the summer draw near, brine shifts to a marked undersaturation (down to almost 0 µatm) because of the brine dilution by ice meltwater, dissolution of CaCO3 and photosynthesis during the sympagic algal bloom. Out of the winter, soon as the ice becomes permeable, CO2 fluxes were observed: (i) from the ice to the atmosphere, as the brine were supersaturated, (ii) from the atmosphere to the ice, as brine shift to an undersaturation. Temperature appears to be the main driver of the pCO2 dynamics within sea ice. It mainly controls the saturation state of the brine (where others processes may be added, e.g., CaCO3 precipitation, primary production) and thus, the concentration gradient of CO2 between sea ice and the atmosphere. It also controls the brine volume and so the brine connectivity, allowing the gas exchanges between sea ice and the atmosphere. We also present a new analytical method to measure the pCO2 of the bulk sea ice. This method, based on equilibration between an ice sample and a standard gas, was successfully applied on both artificial and natural sea ice. However, this method is only applicable for permeable sea ice (i.e., brine volume > 5% [Golden et al., 1998; 2007]) to allow the equilibration between the ice and the standard gas.

The seasonal pattern of ice motion in response to wind forcing and potential consequences to upwelling on the Mackenzie Shelf are considered using satellite-derived ice motion data from the National Snow and Ice Data Center and the NCEP 10 m wind data. The frequency of strong upwelling-favorable alongshore ice motion is high in early winter (November and December) compared to middle and late winter (January to May).For periods when the alongshore component of the wind is upwelling-favorable, the ratio of ice drift divided by wind speed on the Mackenzie Shelf is 0.024 in November and0.008 in March; we conjecture that this ratio decreases as winter progresses because the internal ice stress becomes stronger as both ice thickness and ice concentration increase. This constitutes a possible 10-fold decrease in the seasonal transmission of wind stress to the underlying water from November to March. This ratio in May (0.015) is higher than that in March. We suggest that it is because the internal ice stress becomes weaker as ice concentration decreases on the Mackenzie Shelf in May. Hence, under the same wind forcing, the potential for winter upwelling on Mackenzie Shelf may be enhanced if climate warming results in reduced ice thickness and/or ice concentration. Numerical model results show that the stress on the shelf could be reduced because of the internal ice stress from the pack ice over the deep ocean when the ice moves like a rigid body. We found that the model results are not realistic when the ice strength is 5,000 Nm-2. When the ice strength is 27,500 Nm-2, the model results are more realistic.

Thesis (Ph. D.)--University of Washington, 1991. / Vita. Includes bibliographical references (leaves [117]-123).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 112-118).