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Abstract Using operational sea-ice maps, we provide first insight into the seasonal evolution of fast ice in the East Siberian Sea for the period between 1999 and 2021. The fast ice season tends to start later by 4.7 d per decade and to end earlier by 9.7 d per decade. As a result, there is a trend towards a shorter length of fast ice season by 2 weeks per decade. The analysis of air temperatures indicates that onset and end of the fast ice season are largely driven by thermodynamic processes. Two spatial modes (large, L-mode and small, S-mode) of East Siberian fast ice cover which have significant areal differences were distinguished. The occurrence of L- and S-modes was linked to the polarity of the Arctic Oscillation (AO) index. Negative AO phase leads to increased sea-ice convergence in the region, which in turn favours sea-ice grounding and promotes the development of large fast ice extent (L-mode). Lower deformation rates in the region during positive AO phase does not allow the formation of grounded features which results in small fast ice extent (S-mode). An analysis of sea-ice divergence confirms that L-mode seasons are characterised by higher on-shore convergence compared with S-mode seasons.

The Arctic is warming much faster than the global average. This is known as Arctic Amplification and is caused by feedbacks in the local climate system. In this study, we explore a previously proposed hypothesis that an associated wind feedback in the Barents Sea could play an important role by increasing the warm water inflow into the Barents Sea. We find that the strong recent decrease in Barents Sea winter sea ice cover causes enhanced ocean-atmosphere heat flux and a local air temperature increase, thus a reduction in sea level pressure and a local cyclonic wind anomaly with eastward winds in the Barents Sea Opening. By investigating various reanalysis products and performing high-resolution perturbation experiments with the ocean and sea ice model FESOM2.1, we studied the impact of cyclonic atmospheric circulation changes on the warm Atlantic Water import into the Arctic via the Barents Sea and Fram Strait. We found that the observed wind changes do not significantly affect the warm water transport into the Barents Sea, which rejects the wind-feedback hypothesis. At the same time, the cyclonic wind anomalies in the Barents Sea increase the amount of Atlantic Water recirculating westwards in Fram Strait by a downslope shift of the West Spitsbergen Current, and thus reduce Atlantic Water reaching the Arctic basin via Fram Strait. The resulting warm-water anomaly in the Greenland Sea Gyre drives a local anticyclonic circulation anomaly.

Air-sea interactions play a critical role in the climate system. This study investigates wind-induced changes in the ocean surface temperature and sea ice cover feeding back onto the atmospheric circulation. This interaction was modeled in the Nordic seas, using a partial coupling method to constrain the ocean with prescribed wind forcing in an otherwise fully coupled Earth system model. This enabled the evaluation of not only the direct oceanic, but also the indirect atmospheric response to idealized forcing scenarios of perturbed winds over the Nordic seas. The results show that an anticyclonic wind anomaly forcing leads to significant surface cooling in the Greenland Sea mostly due to anomalous drift of sea ice. During winter, the cooling reduces the net surface heat flux to the atmosphere and increases sea level pressure. The pressure gradients result in anomalous geostrophic southerly winds, which locally are comparable both in direction and in velocity to the prescribed forcing anomalies, suggesting a positive feedback.

Air-sea interactions play a critical role in the climate system. This study investigates wind-induced changes in the ocean surface temperature and sea ice cover feeding back onto the atmospheric circulation. This interaction was modeled in the Nordic seas, using a partial coupling method to constrain the ocean with prescribed wind forcing in an otherwise fully coupled Earth system model. This enabled the evaluation of not only the direct oceanic, but also the indirect atmospheric response to idealized forcing scenarios of perturbed winds over the Nordic seas. The results show that an anticyclonic wind anomaly forcing leads to significant surface cooling in the Greenland Sea mostly due to anomalous drift of sea ice. During winter, the cooling reduces the net surface heat flux to the atmosphere and increases sea level pressure. The pressure gradients result in anomalous geostrophic southerly winds, which locally are comparable both in direction and in velocity to the prescribed forcing anomalies, suggesting a positive feedback.

Ocean heat transport is often thought to play a secondary role for Arctic surface warm16 ing in part because warm water which ows northward is prevented from reaching the 17 surface by a cold and stable halocline layer. However, recent observations in various re18 gions indicate that occasionally, warm water is found directly below the surface mixed 19 layer. Here we investigate Arctic Ocean surface energy uxes and the cold halocline layer 20 in climate model simulations from the Coupled Model Intercomparison Project Phase 21 5 (CMIP5). An ensemble of 15 models shows decreased sea ice formation and increased 22 ocean energy release during fall, winter, and spring for a high-emission future scenario. 23 Along the main pathways for warm water advection, this increased energy release is not 24 locally balanced by increased Arctic Ocean energy uptake in summer. Because during 25 Arctic winter, the ocean mixed layer is mainly heated from below, we analyze changes 26 of the cold halocline layer in the monthly mean CMIP5 data. Fresh water acts to sta27 bilize the upper ocean as expected based on previous studies. We �nd that in spite of 28 this stabilizing e�ect, periods in which warm water is found directly or almost directly 29 below the mixed layer and which occur mainly in winter and spring become more fre30 quent in high-emission future scenario simulations, especially along the main pathways 31 for warm water advection. This could reduce sea ice formation and surface albedo. 32 Plain Language

Air-sea interactions play a critical role in the climate system. This study investigates wind-induced changes in the ocean surface temperature and sea ice cover feeding back onto the atmospheric circulation. This interaction was modeled in the Nordic seas, using a partial coupling method to constrain the ocean with prescribed wind forcing in an otherwise fully coupled Earth system model. This enabled the evaluation of not only the direct oceanic, but also the indirect atmospheric response to idealized forcing scenarios of perturbed winds over the Nordic seas. The results show that an anticyclonic wind anomaly forcing leads to significant surface cooling in the Greenland Sea mostly due to anomalous drift of sea ice. During winter, the cooling reduces the net surface heat flux to the atmosphere and increases sea level pressure. The pressure gradients result in anomalous geostrophic southerly winds, which locally are comparable both in direction and in velocity to the prescribed forcing anomalies, suggesting a positive feedback.

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

Multi‐model Arctic Ocean ``Climate Response Function” (CRF) experiments are analyzed in order to explore the effects of anomalous wind forcing over the Greenland Sea (GS) on poleward ocean heat transport, Atlantic Water (AW) pathways, and the extent of Arctic sea ice. Particular emphasis is placed on the sensitivity of the AW circulation to anomalously strong or weak GS winds in relation to natural variability, the latter manifested as part of the North Atlantic Oscillation (NAO). We find that anomalously strong (weak) GS wind forcing, comparable in strength to a strong positive (negative) NAO index, results in an intensification (weakening) of the poleward AW flow, extending from south of the North Atlantic Subpolar Gyre, through the Nordic Seas, and all the way into the Canadian Basin. Reconstructions made utilizing the calculated CRFs explain ~50 % of the simulated AW flow variance; this is the proportion of variability that can be explained by GS wind forcing. In the Barents and Kara Seas there is a clear relationship between the wind‐driven anomalous AW inflow and the sea ice extent. Most of the anomalous AW heat is lost to the atmosphere, and loss of sea ice in the Barents Sea results in even more heat loss to the atmosphere, and thus effective ocean cooling. Release of passive tracers in a subset of the suite of models reveals differences in circulation patterns and shows that the flow of AW in the Arctic Ocean is highly dependent on the wind stress in the Nordic Seas. Plain Language Summary The North Atlantic Current is an extension of the Gulf Stream, which brings warm Atlantic Water northward as the current flows through the Nordic Seas. Eventually it enters the cold deep Arctic Ocean basins through the Barents Sea and Fram Strait. Nine different numerical ocean‐ice models have been analyzed and compared in order to investigate: (1) their ability to simulate this northward flow of Atlantic Water, (2) its dependence on wind forcing, and (3) its impact on Ar

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

The sea-ice climatology and sea-ice trends and variability are evaluated in simulations with the new version of the coupled Arctic atmosphere-ocean-sea ice model HIRHAM–NAOSIM 2.0. This version utilizes upgraded model components for the coupled subsystems, which include physical and numerical improvements and higher horizontal and vertical resolution, and a revised coupling procedure with the aid of the coupling software YAC (Yet Another Coupler). The model performance is evaluated against observationally based data sets and compared with the previous version. Ensemble simulations for the period 1979–2016 reveal that Arctic sea ice is thicker in all seasons and closer to observations than in the previous version. Wintertime biases in sea-ice extent, upper ocean temperatures, and near-surface air temperatures are reduced, while summertime biases are of similar magnitude as in the previous version. Problematic issues of the current model configuration and potential corrective measures and further developments are discussed.

Argo floats provide both hydrographic and trajectory data, affording the opportunity to investigate surface to mid-depth ocean dynamics. Here, Argo float data are used to determine the absolute geostrophic velocity field of the upper 50–2000 m of the Weddell Gyre, from which the overall circulation pattern is investigated. The Weddell Gyre plays a pivotal role in the modification of climate by advecting heat towards the Antarctic ice shelves and by modifying the water masses that feed into the lowest limb of the global ocean overturning circulation. Warm Deep Water, the source water mass that delivers heat to the Weddell Gyre, is conveniently located within the upper 2000 m domain covered by the floats; we investigate its volume transport as it circulates the gyre. Full depth volume transports are estimated by applying a quadratic function to extrapolate the relative dynamic height field component to the full ocean depth, using CTD profiles from ship-based surveys to determine an extrapolation error. Major new insights are provided by this study. There is an established double-gyre structure to the circulation, with a strong eastern cell and a weaker western cell. Regional variation of the baroclinic component of the flow field is revealed, indicating a northeast-to-southwest reduction in the baroclinic flow, along with a strong meridional gradient of baroclinic flow along the northern limb of the gyre, especially east of ∼25°W. The zonal mean gyre strength away from the shelf edge is 32 ± 5 Sv (1 Sv = 1 × 106 m3 s−1), of which 13 ± 3 Sv are associated with the advection of Warm Deep Water. There is a considerable amount of recirculation within the gyre interior, where water does not traverse the full zonal extent of the gyre. The recirculation is stronger in the eastern cell of the observed double-gyre structure. The interior circulation cells partly explain the large variations in previous gyre strength estimates. We provide an extensive review of previous estimat

We developed an objective parameter optimization system for a coupled sea ice-ocean model based on a genetic algorithm. The system is set up to optimize 15 model parameters simultaneously by minimizing a cost function composed of the model-observation misfit of three sea ice quantities (concentration, drift and thickness). The system is applied for a domain covering the entire Arctic and northern North Atlantic Ocean with an optimization window of about two decades (1990 - 2012). It successfully improves the simulated sea ice properties not only during the period of optimization but also in a validation period (2013 - 2016). We also examined the uniqueness of the optimal parameter sets by independent optimization experiments. Regardless of the striking similarity of the values of the cost function and optimized sea ice fields, the corresponding optimal parameters exhibit a large spread, showing the existence of multiple optimal solutions. The result shows that the utilized sea ice observations, even though covering more than two decades, cannot constrain the process parameters towards an unique solution. A correlation analysis shows that the optimal parameters are inter-related and covariant. A principal component analysis reveals that the first three (six) principal components explain 70% (90%) of the total variance of the optimal parameter sets, indicating a contraction of the parameter space.

Improvement and optimization of numerical sea ice models are of great relevance for understanding the role of sea ice in the climate system. They are also a prerequisite for meaningful prediction. To improve the simulated sea ice properties, we develop an objective parameter optimization system for a coupled sea ice– oceanmodel based on a genetic algorithm. To take the interrelation of dynamic and thermodynamicmodel parameters into account, the system is set up to optimize 15 model parameters simultaneously. The optimization is minimizing a cost function composed of the model–observation misfit of three sea ice quantities (concentration, drift, and thickness). The system is applied for a domain covering the entire Arctic and northern North Atlantic Ocean with an optimization window of about two decades (1990–2012). It successfully improves the simulated sea ice properties not only during the period of optimization but also in a validation period (2013–16). The similarity of the final values of the cost function and the resulting sea ice fields from a set of 11 independent optimizations suggest that the obtained sea ice fields are close to the best possible achievable by the current model setup, which allows us to identify limitations of the model formulation. The optimized parameters are applied for a simulation with a higher-resolution model to examine a portability of the parameters. The result shows good portability, while at the same time, it shows the importance of the oceanic conditions for the portability.

The uniqueness of optimal parameter sets of an Arctic sea ice simulation is investigated. A set of parameter optimization experiments is performed using an automatic parameter optimization system, which simultaneously optimizes 15 dynamic and thermodynamic process parameters. The system employs a stochastic approach (genetic algorithm) to find the global minimum of a cost function. The cost function is defined by the model–observation misfit and observational uncertainties of three sea ice properties (concentration, thickness, drift) covering the entire Arctic Ocean over more than two decades. A total of 11 independent optimizations are carried out to examine the uniqueness of the minimum of the cost function and the associated optimal parameter sets. All 11 optimizations asymptotically reduce the value of the cost functions toward an apparent global minimum and provide strikingly similar sea ice fields. The corresponding optimal parameters, however, exhibit a large spread, showing the existence of multiple optimal solutions. The result shows that the utilized sea ice observations, even though covering more than two decades, cannot constrain the process parameters toward a unique solution. A correlation analysis shows that the optimal parameters are interrelated and covariant. A principal component analysis reveals that the first three (six) principal components explain 70% (90%) of the total variance of the optimal parameter sets, indicating a contraction of the parameter space. Analysis of the associated ocean fields exhibits a large spread of these fields over the 11 optimized parameter sets, suggesting an importance of ocean properties to achieve a dynamically consistent view of the coupled sea ice–ocean system.

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.

The vertical distribution of black carbon (BC) par- ticles in the Arctic atmosphere is one of the key parameters controlling their radiative forcing and thus role in Arctic cli- mate change. This work investigates the presence and prop- erties of these light-absorbing aerosols over the High Cana- dian Arctic ( > 70 degree N). Airborne campaigns were performed as part of the NETCARE project (Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments) and provided insights into the variability of the vertical distributions of BC particles in summer 2014 and spring 2015. The observation periods covered evolutions of cyclonic disturbances at the polar front, which favoured the transport of air pollution into the High Canadian Arctic, as otherwise this boundary between the air masses largely im- pedes entrainment of pollution from lower latitudes. A total of 48 vertical profiles of refractory BC (rBC) mass concen- tration and particle size, extending from 0.1 to 5.5 km altitude were obtained with a Single-Particle Soot Photometer (SP2). Generally, the rBC mass concentration decreased from spring to summer by a factor of 10. Such depletion was as- sociated with a decrease in the mean rBC particle diameter, from approximately 200 to 130 nm at low altitude. Due to the very low number fraction, rBC particles did not substantially contribute to the total aerosol population in summer. The analysis of profiles with potential temperature as ver- tical coordinate revealed characteristic variability patterns within specific levels of the cold and stably stratified, dome- like, atmosphere over the polar region. The associated his- tory of transport trajectories into each of these levels showed that the variability was induced by changing rates and effi- ciencies of rBC import. Generally, the source areas affecting the polar dome extended southward with increasing potential temperature (i.e. altitude) level in the dome. While the lower dome was mos

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

The Weddell Gyre plays a role in the climate system by advecting heat poleward to the Antarctic ice shelves and by regulating the density of water masses that feed the lowest limb of the global ocean overturning circulation. Warm Deep Water is the water mass that delivers heat to the Weddell Gyre, which is subject to complex modification processes to form Weddell Sea Deep and Bottom Water, providing an important sink for atmospheric heat and carbon dioxide. A fleet of Argo floats drifting in the currents of the upper 2000 m of the water column have recently provided data covering more or less the entire Weddell Gyre region in the horizontal, and Warm Deep Water in the vertical. Argo float data thus provide an opportunity to investigate surface to mid-depth ocean dynamics by providing both hydrographic and trajectory data. Here, Argo float profile and trajectory data are exploited in order to produce a full gyre scale view of the Weddell Gyre’s circulation from a purely observation-based dataset, whose pertinent features include the double-cell structure, with a stronger eastern core that intensifies with depth, and a weaker western core that remains invariant with depth. Considerable recirculation occurs within the gyre interior about the eastern core, before the water is able to fully traverse the zonal extent of the gyre, which causes considerable uncertainty when determining the gyre strength using single transects as is typical with ship-based surveys. Further investigation of the causes, temporal stability and the physical consequences of the recirculation cells along the central gyre axis, is required if we are to fully identify and understand the ways in which the Weddell Gyre may be changing in a rapidly changing climate.

The Weddell Gyre plays a fundamental role in the climate system by advecting heat poleward to the Antarctic ice shelves and by regulating the density of water masses that feed the lowest limb of the global overturning circulation. Profile and trajectory data between 2002 and 2016 from a fleet of Argo floats between 50 and 2000 m are exploited in order to produce a full gyre scale view of the Weddell Gyre's circulation. The data exhibit a gradual cooling of the Warm Deep Water (WDW) as it circulates cyclonically around the gyre. A double-cell structure of the Weddell Gyre is revealed, with a stronger eastern core that intensifies with depth, and a weaker western core that remains invariant with depth. The deep outflow of Weddell Sea Deep and Bottom Water (WSDW, WSBW) at the western boundary of the gyre, formed from WDW by complex modification processes involving sea ice formation, and basal ice shelf melting, is not covered by the float observations. Using mooring array-based observations near the tip of the Antarctic Peninsula between 1989 and 1998, and between 2005 and 2014, a cooling of the WSBW plume is revealed over the observational period. This is in striking contrast to the WSDW in the interior Weddell Sea which has been undergoing a decadal warming. While the cause of the cooling of the WSBW plume is currently unclear, the mooring-based velocity observations indicate that the volume transport of the WSBW plume of 2.5 Sv has been stable over time.

An automatic parameter optimization system for a coupled ocean-sea ice model is applied to investigate uniqueness of parameter set obtained from data assimilation. We set up a parameter optimization experiment, in which 15 model parameters are optimized simultaneously using a 23-years optimization window. A series of 11 independent experiments are conducted to examine spread of objective functions, optimized sea ice fields and associated optimal parameters. The result shows sufficiently small spreads of objective functions and ice fields, whereas a significantly large spread of optimized parameters. This indicates the system gives an unique solution regarding the simulated ice fields, whereas multiple solutions regarding the associated model parameters. A correlation analysis shows the optimal parameters are inter-related and covariant. A principal component analysis (PCA) reveals that the first 3 principal components explain 70% of the variation of the optimal parameter sets, indicating a contraction of the model parameter space.

Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150–200 km in space and 100–300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

Many state-of-the-art coupled sea ice-ocean models use atmospheric and oceanic drag coefficients that are at best a function of the atmospheric stability but otherwise constant in time and space. Constant drag coefficients might lead to an incorrect representation of the ice-air and ice-ocean momentum exchange, since observations of turbulent fluxes imply high variability of drag coefficients. We compare three model runs, two with constant drag coefficients and one with drag coefficients varying as function of sea-ice characteristics. The computed drag coefficients range between 0.88 ×10−3 and 4.68 ×10−3 for the atmosphere, and between 1.28 ×10−3 and 13.68 ×10−3 for the ocean. They fall in the range of observed drag coefficients and illustrate the interplay of ice deformation and ice concentration in different seasons and regions. The introduction of variable drag coefficients improves the realism of the model simulation. In addition, using the average values of the variable drag coefficients improves simulations with constant drag coefficients. When drag coefficients depend on sea-ice characteristics, the average sea-ice drift speed in the Arctic basin increases from 6.22 cm s−1 to 6.64 cm s−1. This leads to a reduction of ice thickness in the entire Arctic and particularly in the Lincoln Sea with a mean value decreasing from 7.86 m to 6.62 m. Variable drag coefficients lead also to a deeper mixed layer in summer and to changes in surface salinity. Surface temperatures in the ocean are also affected by variable drag coefficients with differences of up to 0.06 °C in the East Siberian Sea. Small effects are visible in the ocean interior