Sea ice modulates the energy exchange between the atmosphere and the ocean through its kinematics. Marginal ice zone (MIZ) dynamics are complex and are not well resolved in routine observations. Here, we investigate sea ice dynamics in the Greenland Sea MIZ using two Lagrangian drift datasets. We find evidence of tidal currents strongly affecting sub-daily sea ice motion. Velocity anomalies show abrupt transitions aligned with gradients in seafloor topography, indicating changes in ocean currents. Remote-sensed ice floe trajectories derived from moderate resolution satellite imagery provide a view of small-scale variability across the Greenland continental shelf. Ice floe trajectories reveal an west-east increasing velocity gradient imposed by the East Greenland Current, with maximum velocities aligned along the continental shelf edge. These results highlight the importance of small scale ocean variability for ice dynamics in the MIZ.

The Fram Strait is a key region for sea ice export, connecting the Arctic Ocean and the world ocean. Sea ice motion in the region is complex, with transitions from pack ice to the marginal ice zone, sharp gradients in ocean currents, and strong year-to-year variability. Characterizing ice and ocean dynamics in the Fram Strait marginal ice zone (MIZ)  is challenging. In situ observations from buoys are sparse, and low spatial correlation in ice velocity means that the observations that do exist are often not representative of nearby areas. Similarly, standard satellite-based observation methods lack the spatial resolution to resolve air-ice-ocean interactions in detail.To address this gap, we present new floe-scale observations of Lagrangian sea ice motion and rotation in the Fram Strait MIZ from 2003 to 2020 derived from moderate-resolution optical imagery using the Ice Floe Tracker algorithm. These observations enable analysis of the relationship between ice motion and the floe size distribution. We find that both the floe rotation and the velocity anomaly distributions depend on floe size, with variance for each decreasing as the floe size increases. We calculate the area-averaged total deformation using ice floe triads via the Green’s theorem method. For intermediate length scales (10-100 km), mean total deformation follows a power-law-like dependence on length scale. We apply a maximum likelihood estimator to calculate the length scale exponent, finding a steeper power law slope than has been observed in the pack ice. This is consistent with increased localization of deformation in the MIZ relative to the pack ice. Finally, using a quasi-geostrophic ocean model and the SubZero discrete element sea ice model, we investigate the role of eddies in the observed floe size dependence. Simulated ice motion in response to the model eddy field produces exponential velocity anomaly distributions and rotation rate distributions that scale with floe size, consistent with our observations. The observations and model results presented here underscore the importance of small-scale ocean and ice processes for ice motion in the Fram Strait. 

The Fram Strait is a key region for ice export, linking the Arctic with the world ocean. We present floe-scale observations of sea ice motion in the Fram Strait marginal ice zone (MIZ) derived from moderate-scale optical imagery spanning the 2003-2020 period. Tracked ice floes provide Lagrangian measures of ice motion during the spring and summer. We show that the floe size distribution affects the rotation rates and fluctuating velocities of sea ice floes. Using simulations based on a quasi-geostrophic ocean model and a discrete element sea ice model, we show that ocean eddy forcing alone can produce the distinct non-Gaussian velocity anomaly distributions seen in observations. The scale of the velocity distributions decreases with increasing floe size and with increasing distance from the ice edge. Similarly, we show that the rotation rate distribution in both observations and simulations narrows with increasing floe size. Finally, we show that the deformation rates measured from tracked MIZ ice floes reproduce the power law scaling seen in the central Arctic, with the deformation rate decreasing as the scale of observations increases. The observations presented here provide a new avenue for sea ice model development and validation in the summer MIZ.

Ice Floe Tracker is an open-source tool designed to retrieve floe-scale sea ice motion in the Arctic marginal ice zone during spring and summer.  Ice Floe Tracker enables observation of the floe size distribution, ice floe rotation rates, small-scale variation in floe velocity, and individual floe trajectories. Sea ice motion occurs on a wide range of scales, from the interaction of individual pieces of ice at sub-meter scales, the formation of linear kinematic features, and ice transport via basin-wide gyres. Most existing methods for tracking ice motion from remote sensing imagery rely on cross-correlation and are optimized for the winter season in the central Arctic. Cross-correlation-derived motion vectors estimate area-averaged motion and thus are well-suited for close-packed central Arctic ice; however, such estimates have high uncertainties in the dynamic, strongly deforming sea ice cover of the marginal ice zone. Our tool aims to fill this gap by using shape detection and feature tracking to observe floe-scale ice motion.The Ice Floe Tracker algorithm consists of a series of customizable modules. The code is structured as a modular package written in open-source languages. It includes parallel processing, unit testing, a command line interface, and thorough documentation (available on Github). Routines are provided to download imagery from the NASA Moderate Resolution Imaging Spectroradiometer. The satellite imagery is processed to enhance the contrast between liquid water and sea ice, sharpen floe boundaries, and remove atmospheric noise. The image is then segmented, and geometric features of ice floes are extracted. Finally, ice floe geometry and locations are compared to those in subsequent images and linked to form trajectories.  By making this tool open-source, we aim to encourage cross-disciplinary collaboration. Recent results from collaborations between observational oceanography and discrete-element sea ice model development will be highlighted. 

Sea ice mediates the exchange of momentum, heat, and moisture between the atmosphere and the ocean. Cyclones produce strong gradients in the wind field, imparting stress into the ice and causing the ice to deform. In turn, increased sea ice drift speeds and rapid changes in drift direction during the passage of a cyclone may result in enhanced momentum flux into the upper ocean.  During the year-long MOSAiC expedition, an array of drifting buoys was deployed surrounding the R/V Polarstern, enabling the characterization of sea ice motion and deformation across a range of spatial scales. In addition, autonomous sensors at a subset of sites measured the atmospheric and oceanic structure and vertical fluxes. Here, we examine a strong cyclone that impacted the MOSAiC site during January and February, 2020, while the MOSAiC site was near the North Pole. The cyclone track intersected the MOSAiC buoy array, providing an opportunity to examine spatial variability in sea ice motion during the storm in unprecedented detail. A key feature of the storm was the formation of a low-level jet (LLJ), first in the warm sector of the storm, then growing to eventually encircle the central low. The highest rates of ice motion and deformation coincide with effects of LLJ transitions. Analysis of deformation using the Green’s theorem approach indicates divergence and cyclonic vorticity as the LLJ enters the region, and convergence and anticyclonic vorticity as the LLJ leaves; maximum shear strain rate is enhanced throughout the LLJ’s passage. While the vorticity signal is particularly clear, floe structure and internal ice stresses result in high spatial variability in the magnitude of divergence and shear strain rates, especially at smaller scales. Increased current speed and shear in the upper layer of the ocean during the passage of the LLJ resulted from ice drag forcing the ocean mixed layer current. The results suggest an important role for cyclone-forced ocean mixing in pack ice during the Arctic winter.

Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019-2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air-ice-ocean system were collected at multiple spatial scales. Here, we present observations of a pair of strong mid-winter cyclones that impacted the MOSAiC site as it drifted in the central Arctic pack ice, with analytic emphasis on the second cyclone. The sea ice dynamical response showed spatial structure at the scale of the evolving atmospheric wind field. Internal ice stress and the ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post-cyclone inertial ringing in the ice and ocean. A structured response of sea ice motion and deformation to cyclone passage is seen, and the consequent ice motion then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low-level jet (LLJ) behind the trailing cold front. Impacts of the cyclone are prolonged through the coupled ice-ocean inertial response. The local impacts of the approximately 120 km wide LLJ occur over a 12 hour period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at smaller spatial scales and faster time scales than many satellite observations and coupled Earth system models can resolve.