Sea Ice Motion Research Articles

Influence of summer great cyclones on sea ice concentration and area in the Arctic Ocean

Summer Arctic cyclones occur frequently in the Arctic Ocean and play an important role in sea ice variability. We used a reanalysis dataset and sea ice concentration data to identify and track summer great Arctic cyclones and to quantitatively analyse the contribution of cyclones to variations in sea ice concentration and area. We further explored the process of how cyclones influence sea ice via sea surface temperature, radiation, sea ice motion and ice deformation. The results indicate that cyclones accelerate decreases in sea ice concentration and area. The higher the values of the sea ice concentration index (ratio of maximum variation in sea ice concentration change rate to the minimum value of sea ice concentration change rate caused by the cyclone) and sea ice area responsivity (ratio of sea ice area change caused by cyclones to total sea ice area change) are, the greater is the contribution of cyclones to sea ice reduction. Over time, sea ice concentration decreases, and the impacts of cyclones on sea ice concentration are enhanced. During summer great cyclones, a strong low-pressure system and wind stress lead to increases in sea ice motion, ice divergence and changes in sea surface temperature and net radiation, promoting decreases in sea ice concentration and area. This study aids in the prediction of short-term sea ice change, and is beneficial to the development of coupled atmosphere-ocean-ice models.

Large Scale Sea Ice Modeling – Problems and Perspectives.

AbstractThe visco‐plastic sea ice model based on [7] describes the movement of sea ice over large areas of several thousand square kilometers in time. This model has been considered in many publications and has been extended and adapted by numerically motivated and physically‐based approaches. The basic model for the simulation of sea ice circulation considers sea ice velocities and stresses coupled to the field quantities of sea ice thickness and concentration. Two transient advection equations describe the development of sea ice thickness and concentration coupled with sea ice velocity. Furthermore, the viscosity in the constitutive equation is dependent on the sea ice velocities in the sense of a non‐Newtonian fluid, which makes the constitutive relationship strongly nonlinear. An extension of the model is, for example, the elasto‐visco‐plastic constitutive law proposed by [10], which gives numerical stabilization. Recent research on the finite element implementation of the sea ice model is turned to formulations based on the (mixed) Galerkin variation approach, see for example [1] and [20]. Likewise, in [15], [16], and [18] solvers are proposed for the efficient solution of the problem.In this paper, we discuss the obstacles and possibilities of a sea ice model implementation, among others, within a least‐squares finite element method (LSFEM). The mixed LSFEM is well established in fluid mechanics, and a significant advantage of the method is its applicability to first‐order systems, see e.g. [12]. Thus, this method leads to stable and robust formulations for non‐self‐adjoint systems, as they are, for example, for the tracer equations. Based on the results of the Taylor least‐squares scheme and a first‐order Crank‐Nicolson time integrator scheme for the tracer equations, see [21], we discuss here possible steps towards an adequate solution strategy for the complete sea ice model.

Digital surface model generation for drifting Arctic sea ice with low-textured surfaces based on drone images

Arctic sea ice is constantly moving and covered with low-textured surfaces, making it difficult to generate reliable digital surface models (DSMs) from drone images. The movement of sea ice makes georeferencing of DSMs difficult, and the low-textured surfaces of sea ice cause the uncertainty of image matching. This paper proposes a robust method to generate high-quality DSMs for drifting sea ice. To overcome the challenges, the proposed method introduces four improvements to the object-space-based image-matching pipeline: relative georeferencing to recover the horizontality and scale of sea-ice DSMs using a terrestrial light detection and ranging (LiDAR) dataset, match inspection to verify the matched points using several matching constraints, adaptive search-window adjustment to ensure distinct texture information through simple texture analysis, and robust vertical positioning to reduce the matching uncertainty via matching-indicator modeling. Performance evaluations were conducted with drone and LiDAR datasets obtained from a sea-ice campaign using the Korean Icebreaker Research Vessel (IBRV) Araon in the summer of 2017. The experimental results indicated that the proposed method can achieve significant quality enhancements compared with the existing matching method and that all the considerations contributed significantly to the enhancements.

Higher-order statistical moments to analyse Arctic sea-ice drift patterns

AbstractGeophysical systems are often assumed to follow Gaussian probability density functions; however, deviations from Gaussian behaviour can shed light on the underlying dynamics. For the large-scale motion of the Arctic sea ice, such deviations have been interpreted as signatures of structure in dynamic flow fields. In this study, we use higher-order moments (skewness and kurtosis) to identify spatiotemporal changes in the Beaufort Gyre (BG) and the Transpolar Drift (TPD) sea-ice drift patterns. Higher-order moments of satellite-derived ice drift speeds are examined over the winter period of 2006–2017 to describe the persistence of features like the BG and TPD, and their variation over time. Index patterns indicate that the periphery of the BG can be identified by a combination of high positive skewness and high kurtosis in the ice drift time series on an annual basis.

Temporal and spatial change in the relationship between sea-ice motion and wind in the Arctic

This paper examines the temporal and spatial change in the characteristics of sea-ice motion in the Arctic. Ice motion is generally expressed by a motion at a constant ratio (wind factor) of wind speed, with a certain angle (turning angle) from the wind direction, and ocean currents. This study aimed to reveal the recent changes of the wind factor and turning angle using satellite observation data. We first prepared a daily ice-velocity data set from data for 2003–2017 collected by the satellite microwave sensor Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and its successor, AMSR2. Monthly values of the wind factor and turning angle were calculated by a least squares technique, based on the linear relationship between sea-ice velocity and geostrophic wind velocity. The daily variation of sea-ice motion was strongly correlated with that of the wind. The wind factor and turning angle changed regionally, seasonally and interannually. With regard to long-term trends, the wind factor has increased in almost all areas of the Arctic. However, the trend of increase stopped around 2010, especially around the central Arctic.

PARAMETER ESTIMATION AND MOTION TRACKING OF PACK ICE FROM FY-3/MERSI IMAGES

Abstract. A method to estimate the shape parameters and track the motion velocity of pack ice is presented. The method consists of sea ice recognition, pack ice extraction, parameters estimation and motion tracking. We try to estimate the shape parameters and track the motion velocity from FY-3/MERSI images of Fram strait, which were covered by cloud less than 30%. It found that the pack ice concentration significantly decreases faster than sea ice concentration. The two parameters indicate the distribution difference between sea ices and pack ices. The change of the perimeter and mean clamp diameter are obvious owing to they were sensitive to the edge of the pack ices. But the small change of roundness, convexity and width-height ratio indicate the shape similarity of pack ices in various size. More than 80% of the pack ices in the study region are tracked successfully by the proposed method. The resulting motion vectors in the overlapping zones are found to match well with the polar daily grid sea ice motion vectors provided by the National Snow and Ice Data Centre. The method can provide the actual motion vector of pack ices to improve the distribution and details of the grid-to-grid motion vectors.

Scientific Challenges and Present Capabilities in Underwater Robotic Vehicle Design and Navigation for Oceanographic Exploration Under-Ice

This paper reviews the scientific motivation and challenges, development, and use of underwater robotic vehicles designed for use in ice-covered waters, with special attention paid to the navigation systems employed for under-ice deployments. Scientific needs for routine access under fixed and moving ice by underwater robotic vehicles are reviewed in the contexts of geology and geophysics, biology, sea ice and climate, ice shelves, and seafloor mapping. The challenges of under-ice vehicle design and navigation are summarized. The paper reviews all known under-ice robotic vehicles and their associated navigation systems, categorizing them by vehicle type (tethered, untethered, hybrid, and glider) and by the type of ice they were designed for (fixed glacial or sea ice and moving sea ice).

Assessing the Potential of Enhanced Resolution Gridded Passive Microwave Brightness Temperatures for Retrieval of Sea Ice Parameters

A new enhanced resolution gridded passive microwave brightness temperature (TB) product is used to estimate sea ice concentration and motion. The effective resolution of the TBs is found to be roughly twice that of the standard 25 km resolution, though the gridded resolution of the distributed product is higher. Enhanced resolution sea ice concentrations from the Bootstrap algorithm show more detail in the sea ice, including relatively small open water regions within the ice pack. Sea ice motion estimates from the enhanced resolution TBs using a maximum cross-correlation method show a smoother motion circulation pattern; in comparison to buoys, RMS errors are 15–20% lower than motion estimates from the standard resolution fields and the magnitude of the bias is smaller as well. The enhanced resolution product includes other potentially beneficial characteristics, including twice-daily grids based on local time of day and a complete timeseries of data from nearly all multi-channel passive microwave radiometers since 1978. These enhanced resolution TBs are potential new source for long-term records of sea ice concentration, motion, age, melt, as well as salinity and ocean-atmosphere fluxes.

Combined pattern matching and feature tracking for Bohai Sea ice drift detection using Gaofen-4 imagery

ABSTRACT Sea ice is the main cause of winter marine disasters in the Bohai Sea, which is an important sea area in China. The sea ice in the Bohai Sea is easily deformed by strong water currents and rapid temperature changes. Consequently, low spatial and temporal resolution data cannot meet the needs of high-precision monitoring of the sea ice in the Bohai Sea. The geostationary satellite Gaofen-4 (GF-4) has the unique advantages of a high temporal resolution (20 s) and a high spatial resolution (50 m) and can be used to monitor sea ice drift in the Bohai Sea. We evaluate a new algorithm that combines the scale-invariant feature transform (SIFT) technique and the normalized cross-correlation (NCC) method to obtain accurate sea ice drift information. The interclass separability method is used to determine the optimal band combination (OBC), and the results show that the OBC for distinguishing sea ice from sea water is B2×(B1× B5)−1. The proposed method improves noise immunity and calculation efficiency and considers the characteristics of ice blocks. The proposed algorithm can also obtain more correctly matched feature points than the NCC method and approximately 10 times more correct points than the SIFT technique. The mean absolute error (MAE) of the velocity obtained with the proposed algorithm is 0.1615 m s−1 lower than those obtained with the SIFT and NCC methods, and the root mean square error of the velocity determination of the three algorithms is very small. The MAE of the ice movement direction obtained with the proposed algorithm is 0.605° lower than those obtained with the SIFT and NCC methods, and the MAE of a second data set is 12.378° better than that of the SIFT method. The motion of sea ice obtained by the proposed algorithm is close to the actual movement of the sea ice in the Bohai Sea.

Validation of remote-sensing products of sea-ice motion: a case study in the western Arctic Ocean

AbstractThe accuracy of sea-ice motion products provided by the National Snow and Ice Data Center (NSIDC) and the Ocean and Sea Ice Satellite Application Facility (OSI-SAF) was validated with data collected by ice drifters that were deployed in the western Arctic Ocean in 2014 and 2016. Data from both NSIDC and OSI-SAF products exhibited statistically significant (p< 0.001) correlation with drifter data. The OSI-SAF product tended to overestimate ice speed, while underestimation was demonstrated for the NSIDC product, especially for the melt season and the marginal ice zone. Monthly Lagrangian trajectories of ice floes were reconstructed using the products. Larger spatial variability in the deviation between NSIDC and drifter trajectories was observed than that of OSI-SAF, and seasonal variability in the deviation for NSIDC was observed. Furthermore, trajectories reconstructed using the NSIDC product were sensitive to variations in sea-ice concentration. The feasibility of using remote-sensing products to characterize sea-ice deformation was assessed by evaluating the distance between two arbitrary positions as estimated by the products. Compared with the OSI-SAF product, relative errors are lower (<11.6%), and spatial-temporal resolutions are higher in the NSIDC product, which makes it more suitable for estimating sea-ice deformation.

Annual Cycles of Sea Ice Motion and Deformation Derived From Buoy Measurements in the Western Arctic Ocean Over Two Ice Seasons

AbstractData collected by two buoy arrays that operated during the ice seasons of 2014/2015 and 2016/2017 were used to characterize annual cycles of ice motion and deformation in the western Arctic Ocean. An anomalously strong and weak Beaufort Gyre in 2014/2015 and 2016/2017 induced generally anticyclonic and cyclonic sea ice drift during 2014/2015 and 2016/2017, respectively. Cyclonic ice motion resulted in higher contributions of ice divergence to total ice deformation in 2016/2017 than in 2014/2015. In 2014, the autumn ice concentration and multiyear ice coverage were higher than in 2016; consequently, the response of ice motion to wind forcing was weak, and less ice deformation was observed in autumn 2014. During the autumn‐winter transition, the ice‐wind speed ratio, ice deformation rate and its spatial and temporal scaling exponents, and localization of ice deformation decreased markedly in both 2014/2015 and 2016/2017 as a result of freeze‐up and consolidation of ice floes. Such dynamic behavior was maintained through to spring with the further thickening of ice cover. Ice deformation increased due to weakened ice strength as summer approached. The amplitude of the annual cycle of ice deformation rate in the western Arctic Ocean in 2014/2015 and especially in 2016/2017 was larger than that observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) program in 1997/1998. We attribute this phenomenon to ice loss during the recent summers, especially of thick multiyear ice.

An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC)

Abstract. A new version of sea ice motion and age products includes several significant upgrades in processing, corrects known issues with the previous version, and updates the time series through 2018, with regular updates planned for the future. First, we provide a history of these NASA products distributed at the National Snow and Ice Data Center. Then we discuss the improvements to the algorithms, provide validation results for the new (Version 4) and older versions, and intercompare the two. While Version 4 algorithm changes were significant, the impact on the products is relatively minor, particularly for more recent years. The changes in Version 4 reduce motion biases by ∼ 0.01 to 0.02 cm s−1 and error standard deviations by ∼ 0.3 cm s−1. Overall, ice speed increased in Version 4 over Version 3 by 0.5 to 2.0 cm s−1 over most of the time series. Version 4 shows a higher positive trend for the Arctic of 0.21 cm s−1 per decade compared to 0.13 cm s−1 per decade for Version 3. The new version of ice age estimates indicates more older ice than Version 3, especially earlier in the record, but similar trends toward less multiyear ice. Changes in sea ice motion and age derived from the product show a significant shift in the Arctic ice cover, from a pack with a high concentration of older ice to a sea ice cover dominated by first-year ice, which is more susceptible to summer melt. We also observe an increase in the speed of the ice over the time series ≥ 30 years, which has been shown in other studies and is anticipated with the annual decrease in sea ice extent.

Long-Term Analysis of Sea Ice Drift in the Western Ross Sea, Antarctica, at High and Low Spatial Resolution

The Ross Sea region, including three main polynya areas in McMurdo Sound, Terra Nova Bay, and in front of the Ross Ice Shelf, has experienced a significant increase in sea ice extent in the first four decades of satellite observations. Here, we use Co-Registration of Optically Sensed Images and Correlation (COSI-Corr) to estimate 894 high-resolution sea ice motion fields of the Western Ross Sea in order to explore ice-atmosphere interactions based on sequential high-resolution Advanced Synthetic Aperture Radar (ASAR) images from the Envisat satellite acquired between 2002–2012. Validation of output motion vectors with manually drawn vectors for 24 image pairs show Pearson correlation coefficients of 0.92 ± 0.09 with a mean deviation in direction of −3.17 ± 6.48 degrees. The high-resolution vectors were also validated against the Environment and Climate Change Canada sea ice motion tracking algorithm, resulting in correlation coefficients of 0.84 ± 0.20 and the mean deviation in the direction of −0.04 ± 17.39 degrees. A total of 480 one-day separated velocity vector fields have been compared to an available NSIDC low-resolution sea ice motion vector product, showing much lower correlations and high directional differences. The high-resolution product is able to better identify short-term and spatial variations, whereas the low-resolution product underestimates the actual sea ice velocities by 47% in this important near-coastal region. The large-scale pattern of sea ice drift over the full time period is similar in both products. Improved image coverage is still desired to capture drift variations shorter than 24 h.

Experimental Study of Sea Ice Motion in Waves

Abstract To better understand the interactions between ships and ice, analyze ice–ice collisions, and provide parameters for the design of ships and offshore structures, it is important to study th...

Impacts of atmosphere–sea ice–ocean interaction on Southern Ocean deep convection in a climate system model

Deep convection in polar oceans plays a critical role in the variability of global climate. In this study, we investigate potential impacts of atmosphere–sea ice–ocean interaction on deep convection in the Southern Ocean (SO) of a climate system model (CSM) by changing sea ice–ocean stress. Sea ice–ocean stress plays a vital role in the horizontal momentum exchange between sea ice and the ocean, and can be parameterized as a function of the turning angle between sea ice and ocean velocity. Observations have shown that the turning angle is closely linked to the sea-ice intrinsic properties, including speed and roughness, and it varies spatially. However, a fixed turning angle, i.e., zero turning angle, is prescribed in most of the state-of-the-art CSMs. Thus, sensitivities of SO deep convection to zero and non-zero turning angles are discussed in this study. We show that the use of a non-zero turning angle weakens open–ocean deep convection and intensifies continental shelf slope convection. Our analyses reveal that a non-zero turning angle first induces offshore movement of sea ice transporting to the open SO, which leads to sea ice decrease in the SO coastal region and increase in the open SO. In the SO coastal region, the enhanced sea-ice divergence intensifies the formation of denser surface water descending along continental shelf by enhanced salt flux and reduced freshwater flux, combined with enhanced Ekman pumping and weakened stratification, contributing to the occurrence and intensification of continental shelf slope convection. On the other hand, the increased sea ice in the open SO weakens the westerlies, enhances sea-level pressure, and increases freshwater flux, whilst oceanic cyclonic circulation slows down, sea surface temperature and sea surface salinity decrease in the open SO response to the atmospheric changes. Thus, weakened cyclonic circulation, along with enhanced freshwater flux, reduced deep–ocean heat content, and increased stability of sea water, dampens the open–ocean deep convection in the SO, which in turn cools the sea surface temperature, increases sea-level pressure, and finally increases sea-ice concentration, providing a positive feedback. In the CSM, the use of a non-zero turning angle has the capability to reduce the SO warm bias. These results highlight the importance of an accurate representation of sea ice–ocean coupling processes in a CSM.

Interseasonal Connections between the Timing of the Stratospheric Final Warming and Arctic Sea Ice

AbstractConnections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.

Quantifying the Potential for Snow‐Ice Formation in the Arctic Ocean

AbstractWe examine the regional variations and long‐term changes of the potential for snow‐ice formation for level Arctic sea ice from 1980 to 2016. We use daily sea ice motion data and implement a 1‐D snow/ice thermodynamic model that follows the ice trajectories while forcing the simulations with Modern‐Era Retrospective analysis for Research and Applications, Version 2 and ERA‐Interim reanalyses. We find there is potential for snow‐ice formation in level ice over most of the Arctic Ocean; this is true since the 1980s. In addition, the regional variations are very strong. The largest potential is typically found in the Atlantic sector of the Arctic Ocean, particularly in the Greenland Sea, where precipitation is highest. We surmise that, in addition to the annual amount of solid precipitation, potential for snow‐ice formation is controlled by two main factors: the initial second‐year/multiyear ice thickness in the autumn and the timing of first‐year ice formation.

The Clock Keeps Ticking: Circadian Rhythms of Free-Ranging Polar Bears.

Life in the Arctic presents organisms with multiple challenges, including extreme photic conditions, cold temperatures, and annual loss and daily movement of sea ice. Polar bears (Ursus maritimus) evolved under these unique conditions, where they rely on ice to hunt their main prey, seals. However, very little is known about the dynamics of their daily and seasonal activity patterns. For many organisms, activity is synchronized (entrained) to the earth's day/night cycle, in part via an endogenous (circadian) timekeeping mechanism. The present study used collar-mounted accelerometer and global positioning system data from 122 female polar bears in the Chukchi and Southern Beaufort Seas collected over an 8-year period to characterize activity patterns over the calendar year and to determine if circadian rhythms are expressed under the constant conditions found in the Arctic. We reveal that the majority of polar bears (80%) exhibited rhythmic activity for the duration of their recordings. Collectively within the rhythmic bear cohort, circadian rhythms were detected during periods of constant daylight (June-August; 24.40 ± 1.39 h, mean ± SD) and constant darkness (23.89 ± 1.72 h). Exclusive of denning periods (November-April), the time of peak activity remained relatively stable (acrophases: ~1200-1400 h) for most of the year, suggesting either entrainment or masking. However, activity patterns shifted during the spring feeding and seal pupping season, as evidenced by an acrophase inversion to ~2400 h in April, followed by highly variable timing of activity across bears in May. Intriguingly, despite the dynamic environmental photoperiodic conditions, unpredictable daily timing of prey availability, and high between-animal variability, the average duration of activity (alpha) remained stable (11.2 ± 2.9 h) for most of the year. Together, these results reveal a high degree of behavioral plasticity in polar bears while also retaining circadian rhythmicity. Whether this degree of plasticity will benefit polar bears faced with a loss of sea ice remains to be determined.

Four Paradoxes of the User–Provider Interface: A Responsible Innovation Framework for Sea Ice Services

In the Arctic region, sea ice retreat as a decadal-scale crisis is creating a challenging environment for navigating long-term sustainability. Innovations in sea ice services can help marine users to anticipate sea ice concentration, thickness and motion, plan ahead, as well as increase the safety and sustainability of marine operations. Increasingly however, policy makers and information service providers confront paradoxical decision-making contexts in which contradictory solutions are needed to manage uncertainties across different spatial and temporal scales. This article proposes a forward-looking sea ice services framework that acknowledges four paradoxes pressuring sea ice service provision: the paradoxes of performing, contradictory functions embedded in sea ice services, contradicting desired futures and the paradox of responsible innovation. We draw on the results from a multi-year co-production process of (sub)seasonal sea ice services structured around scoping interviews, workshops and a participatory scenario process with representatives of marine sectors, fishers, hunters, metservice providers, and policy experts. Our proposed framework identifies institutionalized coproduction processes, enhanced decision support, paradoxical thinking and dimensions of responsible innovation as tactics necessary to address existing tensions in sea ice services. We highlight the role of socio-economic scenarios in implementing these tactics in support of responsible innovation in sea ice social–ecological systems. The article concludes with a discussion of questions around equity and responsibility raised by the ultimate confirmation that enhanced information, data infrastructures, and service provisions will not benefit all actors equally.

Reexamination of the Madden–Julian Oscillation Effect on Wintertime Sea Ice Concentrations in the North Pacific

In the Pacific sector of the Arctic, a noticeable dipole pattern of the sea ice concentration (SIC) between the Sea of Okhotsk and the Bering Sea has been reported on timescales of weeks to months. The dipole pattern owes its existence to the large-scale circulation variability across the North Pacific. Meanwhile, it is well known that eastward propagating tropical convection on an intraseasonal timescale, the Madden–Julian Oscillation (MJO), forms large-scale circulation anomalies in the North Pacific through the poleward-propagating Rossby waves that are stimulated by MJO-related tropical convection, which is often manifested as a Pacific–North American teleconnection pattern. Few studies, however, have focused on the lagged MJO influence on the SIC change in the high-latitude North Pacific by poleward-propagating waves. Thus, herein, we investigated the intraseasonal SIC variations associated with the MJO phases by considering the lagged circulation response. The dipole pattern in the composite daily SIC change map between the two seas becomes apparent after approximately one week of MJO phases 3 and 7. In the Bering Sea (the Sea of Okhotsk), the SIC increases after MJO phase 3 (phase 7), while it decreases in phase 7 (phase 3). The lagged anomalous circulation pattern in the North Pacific associated with the MJO leads to SIC changes primarily through the dynamic response in 10 m winds and the resultant sea ice motion.