| Arctic coastal polynyas, defined here as persistent openings in the winter sea ice pack, are significant areas for ocean-atmosphere heat exchange, high winter sea ice production with resulting brine rejection, and the dependence of local ecosystems.It is therefore critical to accurately quantify polynya dynamics to understand their spatial and temporal variability, particularly in the context of recent dramatic Arctic sea ice declines.In this study, grayscale morphology image processing techniques are applied to satellite-derived sea ice concentrations in the northern Bering Sea to investigate polynya dynamics throughout this region. Grayscale morphology allows for the estimation of sea ice extent with a defined error tolerance through removal of regions with low sea ice concentrations in the marginal ice zone. Furthermore, since polynyas are the primary source of water within the sea ice pack, the presence of water here can therefore be utilized to define the areal extent of polnynas.We utilize AMSR-E sea ice concentrations during January-April from 2003 to 2008 in the northern Bering Sea to extract daily time series of grayscale morphology-based polynya areas. These results compare well with those calculated by more traditional methods utilizing sea ice concentration thresholds.In addition, we investigate the potential driving forces (e.g. offshore wind velocity) of polynya development as well as calculate the spatial and interannual variability of heat fluxes across the ocean surface owing to polynya formation.They are studied variations of temperature and salinity in seawater under sea ice using hydrologic data taken from polynyas south of the St. Lawrence Island during Marches of 2008 and 2009.The results indicate that high-salinity water found during both cruises of 2008 and 2009 was due to the formation of polynyas.The salinity observed in 2008 was higher than that in 2009, as a result of higher salt production in 2008.The spatial distributions of high-salinity cores differed between the two Marches.In March 2008,a southeastward flow was formed under the persistent northerly wind in the observation region, which transported the high-salinity water produced by the polynyas in a southeast direction. A similar flow, however, did not exist in March 2009 because the northerly wind over the study area was interrupted by a southerly wind. Accordingly the polynyas and high-salinity produced by them existed for short time. As a result, these high-salinity water in 2009 did not spread vary far, and stayed within the polynyas.In addition, during the 2009 cruise, two repeated observations in the polynyas showed the core of high-salinity water was shifted to the southwest of the St. Lawrence Island. This result suggested that a southwestward flow might have existed in the area at the onset of the northerly wind, which was consistent with the alongshore and/or offshore flows caused by the northerly wind.To better understand various physical processes in polynyas and their role in global climate change, it is needed to implement simulation of polynyas.A Los Alamos Sea Ice Model (CICE) with a horizontal resolution of 6.37 km has been implemented to simulate a full year of sea-ice growth and decay starting on 1 November 2002 in the Bering Sea. Total sea ice areas from model results and ones from AMSR-E/Aqua satellite observations have a good consistency. Their correlation coefficient equals to 0.97.Model results show that polynyas in southern domains of east-west coasts are formed by means of southward movements of sea ice, which are mainly forced by offshore northeast wind. So the CICE allows us to reproduce some key dynamic processes of latent polynyas opening and closing events during January-April 2003.For the satellite observation data, polynyas are defined as regions covered by sea ice <75% concentration and for model results we use sea ice concentration of <70% as polynyas criterion, as our simulations show varying strength in horizontal gradients in sea ice concentration and thickness.Accordingly formation processes of polynyas are discussed in four districts of the Bearing Sea. Comparing with satellite data, most polynyas are very well simulated. The article profoundly discusses key factors, which impact simulation accuracy of polynyas.It is concluded that selecting suitable threshold and increasing the spatial and temporal resolution of atmosphere forcing are very favorable to improving the simulation precision. We need to use a full ocean model coupled to the sea ice model to solve the problem of deviations for some polynyas...
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