A coupled sea ice–ocean model is developed to quantify the sea ice response to changes in atmospheric and oceanic forcing in the Bering Sea over the period 1970–2008. The model captures much of the observed spatiotemporal variability of sea ice and sea surface temperature (SST) and the basic features of the upper-ocean circulation in the Bering Sea. Model results suggest that tides affect the spatial redistribution of ice mass by up to 0.1 m or 15% in the central-eastern Bering Sea by modifying ice motion and deformation and ocean flows.

The considerable interannual variability in the pattern and strength of winter northeasterly winds leads to southwestward ice mass advection during January–May, ranging from 0.9 x 10¹² m³ in 1996 to 1.8 x 10¹² m³ in 1976 and averaging 1.4 x 10¹² m³, which is almost twice the January–May mean total ice volume in the Bering Sea. The large-scale southward ice mass advection is constrained by warm surface waters in the south that melt 1.5 x 10¹² m³ of ice in mainly the ice-edge areas during January–May, with substantial interannual variability ranging from 0.94 x 10¹² m³ in 1996 to 2.0 x 10¹² m³ in 1976. Ice mass advection processes also enhance thermodynamic ice growth in the northern Bering Sea by increasing areas of open water and thin ice. Ice growth during January–May is 0.90 x 10¹² m³ in 1996 and 2.1 x 10¹² m³ in 1976, averaging 1.3 x 10¹² m³ over 1970–2008. Thus, the substantial interannual variability of the Bering Sea ice cover is dominated by changes in the wind-driven ice mass advection and the ocean thermal front at the ice edge.

The observed ecological regime shifts in the Bering Sea occurred with significant changes in sea ice, surface air temperature, and SST, which in turn are correlated with the Pacific decadal oscillation over 1970–2008 but not with other climate indices: Arctic Oscillation, North Pacific index, and El Nino–Southern Oscillation. This indicates that the PDO index may most effectively explain the regime shifts in the Bering Sea.

For the 1999 winter, this paper examines the behavior of the Bering Sea St. Lawrence Island polynya using a combination of Advanced Very High Resolution Radiometer (AVHRR), RADARSAT synthetic aperture radar (SAR), meteorological data, over-winter moored upward looking sonars (ULS) and SeaBird salinity/temperature sensors. We define a thermal ice thickness from the AVHRR retrieval of ice surface temperature combined with meteorological observations and a heat flux model. South of the island, we compare the ULS and thermal thicknesses for congelation and frazil ice. When the satellites observe congelation ice over the ULSs, the ULS and thermal ice thicknesses generally agree. When SAR observes Langmuir plumes over the ULSs, which indicate frazil ice formation, the ULSs show scatterers at 5–20 m depths in the water column and the seawater temperatures are either within 0.01°C of freezing or are slightly supercooled. This suggests that during frazil events, crystals either nucleate at depth or are transported to depth by the Langmuir circulation. The combination of the SAR imagery and ULS observations also allow measurement of the pack ice advection velocity, the polynya width and the downwind frazil accumulation thickness, giving widths of 10 to 30 km and thicknesses of 0.1–0.2 m. Substitution of these observed values with the heat flux into the Pease polynya model yields polynya widths that approximately agree with the observed.

Satellite data are important for providing the large-scale context of the Surface Heat Budget of the Arctic Ocean (SHEBA) station and for characterizing the spatial variability of the sea ice in its vicinity. The Canadian RADARSAT satellite collected 195 synthetic aperture radar (SAR) images of the SHEBA site over the course of the 1 year drift. The RADARSAT Geophysical Processor System (RGPS) used these images to compute the spatial pattern of ice motion within 100 km of the SHEBA station by tracking features in sequential images. From the ice motion data the divergence and shear of the pack ice are estimated. The divergence is large from November to January, followed by a gradual convergence from February through July. The character of the ice motion changes at the end of July, from piecewise rigid motion to free drift. The ice motion reverts to its winterlike character in late September. Thus the "kinematic" summer runs from late July to late September. The radar backscatter also goes through seasonal transitions, capturing the abrupt onset of melt (29 May) and freeze-up (15 August). The concentration of multiyear ice is about 94% in the fall, and its backscatter signature remains stable through spring. Multiyear and first-year ice cannot be distinguished during the summer melt season, when the mean backscatter is negatively correlated with the surface air temperature. The "thermodynamic" summer runs from late May to mid-August.

The pattern of recent surface warming observed in the Arctic exhibits both polar amplification and a strong relation with trends in the Arctic Oscillation mode of atmospheric circulation. Paleoclimate analyses indicate that Arctic surface temperatures were higher during the 20th century than during the preceding few centuries and that polar amplification is a common feature of the past. Paleoclimate evidence for Holocene variations in the Arctic Oscillation is mixed. Current understanding of physical mechanisms controlling atmospheric dynamics suggests that anthropogenic influences could have forced the recent trend in the Arctic Oscillation, but simulations with global climate models do not agree. In most simulations, the trend in the Arctic Oscillation is much weaker than observed. In addition, the simulated warming tends to be largest in autumn over the Arctic Ocean, whereas observed warming appears to be largest in winter and spring over the continents.

Scientists have argued for a number of years that the Arctic may be a sensitive indicator of global change, but prior to the 1990s, conditions there were believed to be largely static. This has changed in the last 10 years. Decadal-scale changes have occurred in the atmosphere, in the ocean, and on land [Serreze et al., 2000]. Surface atmospheric pressure has shown a declining trend over the Arctic, resulting in a clockwise spin-up of the atmospheric polar vortex. In the 1990s, the Arctic Ocean circulation took on a more cyclonic character, and the temperature of Atlantic water in the Arctic Ocean was found to be the highest in 50 years of observation [Morison et al., 2000]. Sea-ice thickness over much of the Arctic decreased 43% in 1958–1976 and 1993–1997 [Rothrock et al., 1999].

A summary is presented of the Surface Heat Budget of the Arctic Ocean (SHEBA) project, with a focus on the field experiment that was conducted from October 1997 to October 1998. The primary objective of the field work was to collect ocean, ice, and atmospheric datasets over a full annual cycle that could be used to understand the processes controlling surface heat exchanges—in particular, the ice-albedo feedback and cloud-radiation feedback. This information is being used to improve formulations of arctic ice-ocean-atmosphere processes in climate models and thereby improve simulations of present and future arctic climate. The experiment was deployed from an ice breaker that was frozen into the ice pack and allowed to drift for the duration of the experiment. This research platform allowed the use of an extensive suite of instruments that directly measured ocean, atmosphere, and ice properties from both the ship and the ice pack in the immediate vicinity of the ship. This summary describes the project goals, experimental design, instrumentation, and the resulting datasets. Examples of various data products available from the SHEBA project are presented.

Summertime solar heating of the upper ocean, and subsequent basal melting, are important factors in the ice mass and energy balance, as well as the seasonal evolution of the Arctic mixed layer. Despite relatively high ice concentrations near the SHEBA site in June, we observed a steady increase in elevation of mixed-layer temperature above freezing, indicating that heat loss to basal melting could not keep pace with insolation. Transmission of solar energy through the ice cover, particularly when melt ponds are present, is not well known, hence ocean heating during a time of large ice fraction is of special interest.

We focus on a particular period in June, (1998 year days 167-171, just prior to summer solstice), when there were continuous records of mean properties and turbulent fluxes from two instrument clusters in the upper 10 m, and extensive coverage by the SHEBA profiling CTD. Over the four days, the mixed layer was moderately turbulent, with little stratification in the upper 15-20 m. We observed continuous warming, along with a superimposed diurnal signal, with temperature maxima lagging maximum solar angle by 4-6 h. A diurnal cycle was also present in turbulent heat flux measured 4.2 and 8.2 m below the interface. At midday, turbulent heat flux was downward, reaching values < -10 W m^-2 at 8.2 m. At low sun angles, upward turbulent heat flux at 4.2 m reached 5 W m^-2, as heat was extracted by melting.

Main features of the observed behavior have been simulated using a simple one-dimensional model, initialized with T/S structure at time 167.0 and forced by surface stress obtained from observations. The enthalpy balance at the ice/ocean interface determines heat and buoyancy fluxes there, while insolation is treated as an exponentially distributed source term in the heat equation, with total strength calculated as a fraction of downwelling shortwave flux measured at the ice surface. To account for the observed warming and turbulent heat flux with plausible model parameters, preliminary results imply that 8-9% of the incoming surface shortwave radiation reached the water column.

We present a single column model (SCM) version of the Community Climate System Model (CCSM), that includes the upper 20 meters of the ocean, the sea ice, and the atmosphere. The model is forced by incoming solar radiation at the top boundary, vertical heat and salt fluxes at the bottom boundary, horizontal advection of mass, heat and moisture in the atmosphere, horizontal fluxes of heat and salt in the ocean, the ice velocity relative to the upper ocean, and the shear and divergence of the sea ice velocity field. Experiments are performed at Lagrangian horizontal coordinates that move with the sea ice. Two sets of simulation experiments are performed to study how ice-albedo feedback and cloud-radiation feedback manifest themselves in a single annual cycle, and in a climate change scenario. In the first set of experiments, model initialization and forcing data are prescribed from data sets produced by the Surface Heat Budget of the Arctic Ocean (SHEBA) and the First ISCCP Regional Arctic Cloud Experiment (FIRE-ACE) projects. These SHEBA/FIRE-ACE data sets extend over time periods up to 1 year. In the second set of experiments, stochastic forcing is prescribed by sampling random processes with realistic climatological statistics. These randomly-forced experiments extend over time periods of many decades. Feedbacks are quantified by comparing pairs of experiments in which specific variables (e.g. surface albedo) are first allowed to interact freely as part of the coupled system, and then are prescribed as time series. The results indicate similarities and differences between the feedback mechanisms evaluated on short and long time scales.

The deformation of pack ice is modeled as the discrete motion of rigid plates. A continuous and differentiable field of large-scale velocity is sampled at the center point of each plate to determine its uniform translation. Discontinuities in the ice velocity occur at the cracks separating pairs of adjacent plates. Ice deformation that is characterized by opening, ridging and sliding coefficients is computed directly by integrating the velocity jumps over the length of each crack, and summing over all cracks in a representative area. These coefficients depend on the large-scale strain rate and the geometry of the cracks. The relevant geometric parameters are the orientations of (a) the cracks with respect to the principal axis of the strain rate, and (b) the cracks with respect to the relative position vectors between the center points of adjacent plates on either side of the crack. For all tilings of uniform, equilateral diamonds (including squares) the opening and ridging are minimized, and the sliding is maximized, when an axis of symmetry of the plate coincides with the principal axis of the strain rate.

In this paper, we extend the analysis of geometry and deformation of pack ice initiated in part I by considering random isotropic geometry using the Poisson line process. The model is used to estimate opening, ridging and sliding coefficients for more realistic geometry than the idealized simple and regular geometry considered in part I. We then derive the shape of yield curves by applying minimization of the maximum shear stress to a linear combination of the estimated ridging and sliding coefficients. It is found that isotropic crack geometry results in a sine-lens shape for the yield curve if sliding makes no contribution to the energy dissipation. By contrast, when sliding contributes, the shape of the yield curve becomes teardropped. These results suggest the presence of a consistent relationship between large-scale characterization of inter-floe interactions and small-scale (crack and lead) ridging processes.