Ice Drift Speed Research Articles

Ice Drift in the Arctic Ocean

Abstract The paper presents results of research based on analysis of historical and present studies of the Arctic ice drift. Current information about Arctic ice drift comes from the scientific expedition organized by the Alfred-Wrgener-Institut Helmholtz Centre for Polar and Marine Research (AWI) from Bremerhaven (Germany) in the Arctic Ocean, as a part of the Multidiscipli-nary drifting Observatory for the Study of Arctic Climate (MOSAiC), coming from the deck of the icebreaker RV “Polarstern”. The main purpose of the article was to collect and illustrate information on the phenomenon of ice drift in the Arctic Ocean, considering data from ongoing research during the MOSAiC expedition. The average movement speed of the icebreaker RV “Polarstern” frozen in Arctic ice during the first three legs of the expedition was over 5 Nm/day, which is characteristic of the current data relating to the speed of the Arctic ice drift in the place of research. On the other hand, the article is popular science, and presents the overall characteristics of Arctic ice drift with an indication of the general directions, and speed of its movement. Ice drift speeds in the Arctic can reach exceptionally high values under favorable conditions. The drift of sea ice reaching at its intensity/intensity values close to the limit (dangerous criterion) in these extreme cases is called the “ice river”. The speed of “ice rivers” can reach up to 1–2 knots, however, in extreme conditions up to 9 knots. Based on data from the AWI, correlation points were identified between the speed of Arctic ice drift and the speed of winds and atmospheric pressure values.

Evaluation of Arctic sea ice drift and its dependency on near-surface wind and sea ice conditions in the coupled regional climate model HIRHAM–NAOSIM

Abstract. We examine the simulated Arctic sea ice drift speed for the period 2003–2014 in the coupled Arctic regional climate model HIRHAM–NAOSIM 2.0. In particular, we evaluate the dependency of the drift speed on the near-surface wind speed and sea ice conditions. Considering the seasonal cycle of the Arctic basin averaged drift speed, the model reproduces the summer–autumn drift speed well but significantly overestimates the winter–spring drift speed, compared to satellite-derived observations. Also, the model does not capture the observed seasonal phase lag between drift and wind speed, but the simulated drift speed is more in phase with the near-surface wind. The model calculates a realistic negative correlation between drift speed and ice thickness and between drift speed and ice concentration during summer–autumn when the ice concentration is relatively low, but the correlation is weaker than observed. A daily grid-scale diagnostic indicates that the model reproduces the observed positive correlation between drift and wind speed. The strongest impact of wind changes on drift speed occurs for high and moderate wind speeds, with a low impact for rather calm conditions. The correlation under low-wind conditions is overestimated in the simulations compared to observation/reanalysis data. A sensitivity experiment demonstrates the significant effects of sea ice form drag from floe edges included by an improved parameterization of the transfer coefficients for momentum and heat over sea ice. However, this does not improve the agreement of the modeled drift speed / wind speed ratio with observations based on reanalysis data for wind and remote sensing data for sea ice drift. An improvement might be achieved by tuning parameters that are not well established by observations.

Patterns of sea ice drift and polar bear (Ursus maritimus) movement in Hudson Bay

Sea ice habitats are highly dynamic, and ice drift may affect the energy expenditure of travelling animals. Several studies in the high Arctic have reported increased ice drift speeds, and consequently, polar bears Ursus maritimus in these areas expended more energy on counter-ice movement for station-keeping. However, little is known about the spatiotemporal dynamics of ice drift in Hudson Bay (HB) and its implications for the declining Western Hudson Bay (WH) polar bear subpopulation. Using sea ice drift data from 1987-2015 and polar bear satellite telemetry location data from 2004-2015, we examined trends in drift speeds in HB, polar bear movement relative to drift, and assessed annual and individual variation. In contrast to other areas of the Arctic, we did not find an increase in ice drift speed over the period examined. However, variability in ice drift speed increased over time, which suggests reduced habitat predictability. Polar bear movement direction was not strongly counter to ice drift in any month, and ice drift speed and direction had little effect on bear movement rates and, thus, energy expenditure. On an annual scale, we found individuals varied in their exposure and response to ice drift, which may contribute to variability in body condition. However, the lack of a long-term increase in ice drift speed suggests this is unlikely to be the main factor affecting the body condition decline observed in the WH subpopulation. Our results contrast findings in other subpopulations and demonstrate the need for subpopulation-specific research and risk evaluation.

Drift of Pancake Ice Floes in the Winter Antarctic Marginal Ice Zone During Polar Cyclones

AbstractHigh temporal resolution in situ measurements of pancake ice drift are presented, from a pair of buoys deployed on floes in the Antarctic marginal ice zone during the winter sea ice expansion, over 9 days in which the region was impacted by four polar cyclones. Concomitant measurements of wave‐in‐ice activity from the buoys are used to infer that the ice remained unconsolidated, and pancake ice conditions were maintained over at least the first 7 days. Analysis of the data shows (i) the fastest reported ice drift speeds in the Southern Ocean; (ii) high correlation of drift velocities with the surface wind velocities, indicating absence of internal ice stresses >100 km from the ice edge where remotely sensed ice concentration is 100%; and (iii) presence of a strong inertial signature with a 13 hr period. A Lagrangian free drift model is developed, including a term for geostrophic currents that reproduce the 13 hr period signature in the ice motion. The calibrated model provides accurate predictions of the ice drift for up to 2 days, and the calibrated parameters provide estimates of wind and ocean drag for pancake floes under storm conditions.

High resolution modeling of western Alaskan tides and storm surge under varying sea ice conditions

A depth-integrated high resolution (down to 25–50 m) tide and storm surge model has been developed for the Alaska region with a focus on the coasts of western Alaska. The model uses the ADCIRC basin-to-channel scale unstructured grid circulation code forced with Climate Forecast System version 2 reanalysis meteorology. The tidal solution has been validated at 121 shelf and nearshore stations, with lower overall errors than a data assimilated tidal model (FES2012). The ADCIRC model shows considerable skill at simulating tide and coastal surge, and resulting overland flooding on the Yukon–Kuskokwim Delta, during both summer and winter storms. The root-mean-square-error of the model does not exceed 20 cm at any station, outperforming the Global Ocean Forecasting System (GOFS 3.1), a 1/12∘ data assimilated ocean general circulation model which is coupled to sea ice physics. The ADCIRC model incorporates the effect of sea ice through parameterizations of the wind drag coefficient, modifying the air–sea momentum transfer under ice coverage. Three large winter storms with distinctly different ice coverages along the coasts of western Alaska were chosen to exhibit the variable effect of sea ice on the resulting storm surge. Under forming coastal ice coverage, local increases in water levels due to ice is seen in coastal areas, and under predominantly dense pack ice, an increase in momentum transfer in the marginal sea ice at the shelf break leads to an increase in sea levels across the entire Bering Sea, both commensurate with observations. Under the most variable ice fields, results are mixed, in part due to uncertainties in the air–sea–ice drag parameterization such as related to the assumption that sea ice drift and wind velocities are always well correlated. Including a description of sea ice drift and current speeds explicitly in the air–sea–ice drag formulation and considering wave–surge–ice interaction should improve the description of momentum transferred to the water column and resulting simulation of surge.

Instantaneous sea ice drift speed from TanDEM-X interferometry

Abstract. The drift of sea ice is an important geophysical process with widespread implications for the ocean energy budget and ecosystems. Drifting sea ice can also threaten marine operations and present a hazard for ocean vessels and installations. Here, we evaluate single-pass along-track synthetic aperture radar (SAR) interferometry (S-ATI) as a tool to assess ice drift while discussing possible applications and inherent limitations. Initial validation shows that TanDEM-X phase-derived drift speed corresponds well with drift products from a ground-based radar at Utqiaġvik, Alaska. Joint analysis of TanDEM-X and Sentinel-1 data covering the Fram Strait demonstrates that S-ATI can help quantify the opening/closing rate of leads with possible applications for navigation. S-ATI enables an instantaneous assessment of ice drift and dynamic processes that are otherwise difficult to observe. For instance, by evaluating sea ice drift through the Vilkitsky Strait, Russia, we identified short-lived transient convergence patterns. We conclude that S-ATI enables the identification and analysis of potentially important dynamic processes (e.g., drift, rafting, and ridging). However, current limitations of S-ATI are significant (e.g., data availability and they presently only provide the cross-track vector component of the ice drift field) but may be significantly reduced with future SAR systems.

Fram Strait sea ice export affected by thinning: comparing high-resolution simulations and observations

Variability and trends of Fram Strait sea ice area and volume exports are examined for the period of 1990–2010. Simulations from a high-resolution version of the MPIOM model (STORM project) reproduce area and volume export well when compared with NSIDC and ICESat satellite data and in-situ ice thickness observations. The fluxes derived from ice thickness and drift satellite products vary considerably, indicating a high uncertainty in these estimates which we mostly assign to the drift observations. The model captures the observed average seasonal cycles and interannual variability of ice export. The simulated mean annual sea ice area export is 860 × 103 km2 a− 1 (1990–2010), and the correlation with the NSIDC-based area fluxes is r = 0.67. The simulated mean annual volume export is 3.3 × 103 km3 a− 1 (1990–2010), close to the ICESat/ULS values, with a correlation of r = 0.58. The simulated monthly area export has a significant positive trend of + 10% per decade, explained by wind forcing. The major contribution to the robust trend in area export between June and September. Fram Strait ice volume export variability is mainly controlled by ice drift with a dominant role of the Transpolar Drift and, to a lesser extent thickness variability. The area export increase reflects increasing ice-drift speed, but is balanced with a reduced thickness over time when it comes to volume export, giving no significant trend in volume export. The spatial variability of ice drift indicates that the export influences a large area upstream in the Trans-Polar Drift stream, and that high volume export events lead to a thinner thickness there. The central Arctic is well connected drift-wise to the Fram Strait via the Transpolar Drift while for thickness, the region north of Greenland is dominated and controlled by the Fram Strait ice export.

Investigation of acoustic properties of snow-covered sea ice

The paper presents results of field observations of hydroacoustic characteristics of snow-covered ice cover in shallow seas of the Arctic shelf. The purpose of the research was to determine the quantitative characteristics of the reflection and absorption coefficients of sound from the bottom of the drifting ice cover, as well as the Doppler broadening of the frequency spectrum of acoustic signals depending on the thickness of the ice, the structure of the reflecting surface, the thickness of the snow cover, and the ice drift speed. The objective of the research was to obtain the data necessary for choosing optimal parameters of specialized hydroacoustic equipment designed to monitor ice conditions in the areas of operation of offshore oil and gas platforms. Researches were conducted in areas of active construction of engineering marine constructions and carrying out the transport operations. The research methodology was based on the use of an autonomous measuring complex, which for a long period was installed on the bottom of the sea at depths of 50 to 130 m. The recording system consisted of the following components: upward looking pulse sonar of the IPS-5 type produced by the Canadian company ASL; the Doppler meter of the ice drift speed ADCP (the RDI firm); and a RSM-7 electromechanical current meter. All devices operated in continuous mode with a measurement cycle of 1s, the results were recorded in memory and processed after lifting the devices to the surface. The time delays of signals reflected from the ice cover, as well as the amplitudes and variations of the sound attenuation depending on the reflectance and absorption coefficients were recorded in the memory of the up-looking sonar. Variations of time delays were used to calculate a settlement of ice formations and to determine the shape of the reflective surface, including the angles of inclination of ice keels. Doppler shift of frequency of reflected acoustic signals and broadening of the frequency spectrum were calculated using values of the ice drift speed and changes of immersion depths of hummocks. Acoustic characteristics were measured repeatedly during several seasons of each year from 2010 to 2017. This investigation made possible to obtain statistical estimates of the distributions of the reflection coefficient of the sound and the quantitative values of broadening of the frequency spectrum of acoustic signals depending on the angle of incidence of the acoustic rays, the nature of the irregularities and the structure of the reflective surfaces of ice and snow cover thickness and the drift speed. The results obtained by this research allowed reasonable choosing and calculating the basic characteristics of the hydroacoustic equipment intended for runtime diagnostics of ice cover in zones of marine engineering structures.

Pan-arctic winter drift speeds and changing patterns of sea ice motion: 1979–2015

AbstractMonthly mean passive microwave-derived sea-ice motion maps for 36 winters (October–April) are used to examine pan-Arctic sea-ice drift speeds and patterns. The mean Arctic Ocean sea-ice motion consists of three well-known primary circulation regimes: the Beaufort Gyre (BG), transpolar drift (TPD), and a motion system from the Kara Sea (KS). The 36-year mean winter sea-ice drift pattern is used to identify the average boundaries between the circulation regimes mentioned above. Regression analyses of the ice drift speed anomalies show statistically significant positive drift speed trends in BG, TPD and KS. Non-significant trends are associated with negative trends of generally weak drift speeds north of the Canadian Arctic and over the Chukchi/East Siberian Shelf. The first three modes of Empirical Orthogonal Functions were found to explain 30.2%, 13.5% and 8.7% of the spatial variance in the mean winter ice drift patterns and highlight the large variability in the ice drift patterns.

Reassessing Sea Ice Drift and Its Relationship to Long‐Term Arctic Sea Ice Loss in Coupled Climate Models

AbstractResults of an earlier study suggest that sea ice drift in climate models is unrealistic, and this has undermined confidence in model projections of “long‐term” (i.e., secular) Arctic sea ice loss. We revisit this by analyzing 22 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). It is shown that, when consistent temporal sampling is applied, sea ice drift speed in models and observations come into closer agreement than previously suggested. There is still considerable intermodel scatter in climatological drift speed, and we show that much of this likely relates to prescribed parameters in the sea ice models. Since 1979, observations show a long‐term positive trend of annual mean Arctic average sea ice drift speed resulting primarily from sea ice thinning, and most of the CMIP5 models qualitatively reproduce this. The simulated annual mean drift speed trends reflect strong cancellation between winter trends (which are positive in most models and in good agreement with observations) and summer trends (which are negative in most models and in poor agreement with observations). Positive Arctic average drift speed trends do not consistently coincide with positive trends of Fram Strait outflow. The simulated regional relationship between sea ice strength and drift speed changes dramatically as the Arctic transitions from full to partial ice cover, and this “sea ice extent effect” likely influences simulated summer drift speed trends. Altogether, these results highlight aspects in which models show encouraging agreement with observations, while pinpointing aspects in which models require improvement.

Arctic Sea Ice Drift Measured by Shipboard Marine Radar

AbstractThis study presents Arctic sea ice drift fields measured by shipboard marine X‐band radar (MR). The measurements are based on the maximum cross correlation between two sequential MR backscatter images separated ∼1 min in time, a method that is commonly used to estimate sea ice drift from satellite products. The advantage of MR is that images in close temporal proximity are readily available. A typical MR antenna rotation period is ∼1–2 s, whereas satellite revisit times can be on the order of days. The technique is applied to ∼4 weeks of measurements taken from R/V Sikuliaq in the Beaufort Sea in the fall of 2015. The resulting sea ice velocity fields have ∼500 m and up to ∼5 min resolution, covering a maximum range of ∼4 km. The MR velocity fields are validated using the GPS‐tracked motion of Surface Wave Instrument Float with Tracking (SWIFT) drifters, wave buoys, and R/V Sikuliaq during ice stations. The comparison between MR and reference sea ice drift measurements yields root‐mean‐square errors from 0.8 to 5.6 cm s−1. The MR sea ice velocity fields near the ice edge reveal strong horizontal gradients and peak speeds > 1 m s−1. The observed submesoscale sea ice drift processes include an eddy with ∼6 km diameter and vorticities <–2 (normalized by the Coriolis frequency) as well as converging and diverging flow with normalized divergences <–2 and >1, respectively. The sea ice drift speed correlates only weakly with the wind speed (r2 = 0.34), which presents a challenge to conventional wisdom.

Impact of air-sea forcings on the southern ocean sea ice variability around the Indian Antarctic stations

A coupled ocean sea ice model is used to carry out sensitivity experiments to decipher the respective roles of wind, heat and freshwater flux forcings in changing the sea ice variability (concentration, volume, salinity, and drift speed) of the Antarctic region with special emphasis near the Indian Stations, Maitri [11.7°E; 70.7°S] and Bharati [76.1°E; 69.4°S]. The simulations are carried out in the Southern Ocean region [9°E−78°E; 58°S-71°S] during 1997–2012 at a resolution of 6–10 km. It is found that the air-sea forcings greatly impact the spatio-temporal variability of the sea ice variables. In the absence of wind and heat/freshwater flux forcing, the sea ice concentration (SIC) and sea ice volume (SIV) of the region decreases, except at higher latitudes. The effect of absence of heat and freshwater flux forcing on the seasonal variability of the SIC and SIV is more as compared to the wind forcing. Interestingly, the absence of wind and heat flux forcing exhibit opposite nature in influencing the temporal variability of SIV around the Maitri and Bharati regions. On using the climatological wind and heat/freshwater flux forcing, the SIC and SIV of the region increases. The climatological wind forcing have a greater effect in increasing the SIC and SIV of the region as compared to corresponding heat and freshwater flux forcings. The highest contribution in the SIV comes from the thick ice. The SIV of thick ice is found to be significantly increasing (4% per year). However, the interannual increase in medium thick ice and thin ice is very small (0.1% per year). The changes in the sea ice drift speed and vertical stability of ocean is studied vis-à-vis changes in air-sea forcing. The mixed layer heat budget of the region is also estimated and the effect of wind and heat flux forcing on it is investigated.

Study on Ice Parameters Affecting DP Performance of FPSO in Arctic Ocean

Recently, various efforts have been made to develop oil and gas in the Arctic Ocean. It is very important to consider the load caused by ice in designing floating structures in the area. The magnitude of the ice load and its impact on a structure should be considered. In this paper, we analyze ice parameters affecting the DP performance of FPSO with a DP-assisted mooring system. Several ice characteristics are selected, and the resulting ice load is calculated using GEM software. Numerous simulations are conducted while changing the values of the parameters, and DP capability plots are generated to visualize the effects of changing these parameters. It is shown that the ice drift speed and thickness are the major properties to be considered in DP system design. The limitations of the analysis and future work are discussed in the conclusion.

Near-field ice management tactics – Simulation and field testing

Robust near-field ice management tactics have been developed for use in Arctic floating drilling. The tactics provide high confidence that a station-keeping drilling rig can be kept within the managed ice channel throughout periods of complex changes in ice drift direction and speed, and thus effectively mitigate the potentially high economic cost of an emergency disconnection. Kinematic simulations were used to design the systematic arched racetrack tactics which were implemented and tested during the Oden Arctic Technology Research Cruise 2015 (OATRC2015) conducted in the pack ice north of Svalbard at about 82°N latitude and 16°30′E longitude. The long duration field tests, conducted over 10 days using two icebreakers, show the virtual drilling rig was maintained within the managed ice channel in complex ice drift conditions that included multiple ice drift loops, cusps, and reversals. Moreover, the field observations, including satellite and helicopter imagery, confirm the fundamental simulation methods. The field results are extended through simulations to assess the impact of icebreaker fleet configuration and capability on outlet ice conditions (floe size and brash content) and the performance of the tactics against long-term ice drift records (over 1200 days with over 18,000 km of drift). Results demonstrate the importance of systematically executing the tactics and confirm that the geostationary drilling rig is kept within the managed ice channel.

Arctic Ice‐Ocean Coupling and Gyre Equilibration Observed With Remote Sensing

AbstractModel and observational evidence has shown that ocean current speeds in the Beaufort Gyre have increased and recently stabilized. Because these currents rival ice drift speeds, we examine the potential for the Beaufort Gyre's shift from a system in which the wind drives the ice and the ice drives a passive ocean to one in which the ocean often, in the absence of high winds, drives the ice. The resultant stress exerted on the ocean by the ice and the resultant Ekman pumping are reversed, without any change in average wind stress curl. Through these curl reversals, the ice‐ocean stress provides a key feedback in Beaufort Gyre stabilization. This manuscript constitutes one of the first observational studies of ice‐ocean stress inclusive of geostrophic ocean currents, by making use of recently available remote sensing data.

Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6

Abstract. Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P*. These show that higher values of P* generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P* is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6).

Fram Strait sea ice export variability and September Arctic sea ice extent over the last 80 years

Abstract. A new long-term data record of Fram Strait sea ice area export from 1935 to 2014 is developed using a combination of satellite radar images and station observations of surface pressure across Fram Strait. This data record shows that the long-term annual mean export is about 880 000 km2, representing 10 % of the sea-ice-covered area inside the basin. The time series has large interannual and multi-decadal variability but no long-term trend. However, during the last decades, the amount of ice exported has increased, with several years having annual ice exports that exceeded 1 million km2. This increase is a result of faster southward ice drift speeds due to stronger southward geostrophic winds, largely explained by increasing surface pressure over Greenland. Evaluating the trend onwards from 1979 reveals an increase in annual ice export of about +6 % per decade, with spring and summer showing larger changes in ice export (+11 % per decade) compared to autumn and winter (+2.6 % per decade). Increased ice export during winter will generally result in new ice growth and contributes to thinning inside the Arctic Basin. Increased ice export during summer or spring will, in contrast, contribute directly to open water further north and a reduced summer sea ice extent through the ice–albedo feedback. Relatively low spring and summer export from 1950 to 1970 is thus consistent with a higher mid-September sea ice extent for these years. Our results are not sensitive to long-term change in Fram Strait sea ice concentration. We find a general moderate influence between export anomalies and the following September sea ice extent, explaining 18 % of the variance between 1935 and 2014, but with higher values since 2004.

Seasonal and interannual variability of the Arctic sea ice: A comparison between AO-FVCOM and observations

A high-resolution (up to 2 km), unstructured-grid, fully ice-sea coupled Arctic Ocean Finite-Volume Community Ocean Model (AO-FVCOM) was used to simulate the sea ice in the Arctic over the period 1978–2014. The spatial-varying horizontal model resolution was designed to better resolve both topographic and baroclinic dynamics scales over the Arctic slope and narrow straits. The model-simulated sea ice was in good agreement with available observed sea ice extent, concentration, drift velocity and thickness, not only in seasonal and interannual variability but also in spatial distribution. Compared with six other Arctic Ocean models (ECCO2, GSFC, INMOM, ORCA, NAME, and UW), the AO-FVCOM-simulated ice thickness showed a higher mean correlation coefficient of ∼0.63 and a smaller residual with observations. Model-produced ice drift speed and direction errors varied with wind speed: the speed and direction errors increased and decreased as the wind speed increased, respectively. Efforts were made to examine the influences of parameterizations of air-ice external and ice-water interfacial stresses on the model-produced bias. The ice drift direction was more sensitive to air-ice drag coefficients and turning angles than the ice drift speed. Increasing or decreasing either 10% in water-ice drag coefficient or 10° in water-ice turning angle did not show a significant influence on the ice drift velocity simulation results although the sea ice drift speed was more sensitive to these two parameters than the sea ice drift direction. Using the COARE 4.0-derived parameterization of air-water drag coefficient for wind stress did not significantly influence the ice drift velocity simulation.

Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models

We derive the terms in the Antarctic sea ice concentration budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean–sea ice coupled model with prescribed atmospheric forcing. Sea ice drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct ice drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea ice drift speed and direction in exterior sectors of the sea ice covered region tend to be systematic and consistent with those in winds. This suggests that sea ice errors in these areas are most likely wind-driven, so as errors in the simulated ice motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea ice is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea ice drift and the sea ice concentration budget gives insight on ways to categorize models with regard to errors in their ice dynamics. In exterior regions, models with seemingly too weak winds and slow ice drift consistently yield a lack of ice velocity divergence and hence a wrong wintertime sea ice growth rate. In interior sectors, too slow ice drift, presumably originating from issues in the physical representation of sea ice dynamics as much as from errors in surface winds, leads to wrong timing of the late winter ice retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the ice concentration budget–ice drift biases–wind biases relationship prevailing in the simulation of Antarctic sea ice over the last decades.

Dynamics of the Changing Near-Inertial Internal Wave Field in the Arctic Ocean

ABSTRACTThe dynamics of the wind-generated near-inertial internal wave field in the Canada Basin of the Arctic Ocean are investigated using the drifting Ice-Tethered Profiler dataset for the years 2005 to 2014, during a decade when sea ice extent and thickness decreased dramatically. This time series, with nearly 10 years of measurements and broad spatial coverage, is used to quantify a seasonal cycle and interannual trend for internal waves in the Arctic, using estimates of the amplitude of near-inertial waves derived from isopycnal displacements. The internal wave field is found to be most energetic in summer when sea ice is at a minimum, with a second maximum in early winter during the period of maximum wind speed. Amplitude distributions for the near-inertial waves are quantifiably different during summer and winter, due primarily to seasonal changes in sea ice properties that affect how the ice responds to the wind, which can be expressed through the “wind factor”—the ratio of sea ice drift speed to wind speed. A small positive interannual trend in near-inertial wave energy is linked to pronounced sea ice decline during the last decade. Overall variability in the internal wave field increases significantly over the second half of the record, with an increased probability of larger-than-average waves in both summer and winter. This change is linked to an overall increase in variability in the wind factor and sea ice drift speeds, and reflects a shift in year-round sea ice characteristics in the Arctic, with potential implications for dissipation and mixing associated with internal waves.