In recent decades, global climate change has strongly affected the Arctic region, leading to a rapid decline in sea ice extent. This decline affects the interactions between sea ice, the atmosphere, and the ocean, driven by complex thermodynamic and dynamical processes. The Arctic mixed layer (ML), located in the upper ocean, plays a key role in regulating the interactions between the deep ocean, sea ice, and the atmosphere. This region is strongly affected by exchanges of mass (such as freshwater and saltwater fluxes) and momentum driven by various forces like ocean currents, tides, waves, and winds. Here, we study the ad-hoc vertical turbulent kinetic energy (TKE) mixing scheme within the NEMO-SI3 model. Specifically, we focus on the influence of surface and internal wave breaking in sea ice-covered regions. The critical parameters are the fraction of surface TKE that penetrates below the ML, the nature of the exponential TKE penetration decrease beneath the ML, and the damping effect on Langmuir and surface wave breaking beneath the ice cover. We aim to assess how these parameters affect the ML and various sea ice properties. Our findings reveal significant impacts on Arctic sea ice thickness under two scenarios: when ice cover does not affect wave dynamics and when the mixing process weakens. Stronger mixing leads to a deeper ML and reduced sea ice thickness by 30 to 40 centimeters, while weaker mixing results in a shallower ML and a moderate sea ice increase of 10 to 20 centimeters. Results also show that reduced sea ice models exhibit a larger volume of freshwater content in the ocean with consistent spatial patterns. Conversely, increased sea ice simulations reveal reduced freshwater content, although clear spatial patterns are not evident. Differences in upper ocean properties, particularly in ocean stratification, highlight the significant impact of strong sea ice attenuation in the mixing parametrization. These findings underscore the substantial influence of enhanced ocean mixing on the physical properties of ocean and sea ice.

We evaluate the vertical turbulent-kinetic-energy (TKE) mixing scheme of the NEMO-SI3 ocean-sea-ice model in sea-ice-covered regions of the Arctic Ocean. Specifically, we assess the parameters involved in TKE mixed-layer-penetration (MLP) parameterization. This ad hoc parameterization aims to capture processes that impact the ocean surface boundary layer, such as near-inertial oscillations, ocean swells, and waves, which are often not well represented in the default TKE scheme. We evaluate this parameterization for the first time in three regions of the Arctic Ocean: the Makarov, Eurasian, and Canada basins.We demonstrate the strong effect of the scaling parameter that accounts for the presence of sea ice. Our results confirm that TKE MLP must be scaled down below sea ice to avoid unrealistically deep mixed layers. The other parameters evaluated are the percentage of energy penetrating below the mixed layer and the length scale of its decay with depth. All these parameters affect mixed-layer depth and its seasonal cycle, surface temperature, and salinity, as well as underlying stratification. Shallow mixed layers are associated with stronger stratification and fresh surface anomalies, and deeper mixed layers correspond to weaker stratification and salty surface anomalies.Notably, we observe significant impacts on sea-ice thickness across the Arctic Ocean in two scenarios: when the scaling parameter due to sea ice is absent and when the TKE mixed-layer-penetration process vanishes. In the former case, we observe an increase of several meters in mixed-layer depth, along with a reduction in sea-ice thickness ranging from 30 to 40 cm, reflecting the impact of stronger mixing. Conversely, in the latter case, we notice that a shallower mixed layer is accompanied by a moderate increase in sea-ice thickness, ranging from 10 to 20 cm, as expected from weaker mixing. Additionally, interannual variability suggests that experiments incorporating a scaling parameter based on sea-ice concentration display an increased mixed-layer depth during periods of reduced sea ice, which is consistent with observed trends. These findings underscore the influence of enhanced ocean mixing, through specific parameterizations, on the physical properties of the upper ocean and sea ice.

In this study, we assess the ability of the ocean-sea ice general circulation models that participated in the Ocean Model Intercomparison Project (OMIP) to simulate the seasonal cycle of the ocean mixed layer depth in pan-Arctic seas. We focus on the central Arctic Ocean, Beaufort, Chukchi, East Siberian, Laptev, Kara, and Barents Seas. All models underestimate the mixed layer depth by about 15m on average during summertime compared to the MIMOC (Monthly Isopycnal/Mixed layer Ocean Climatology) observational data. In fall and winter, differences of several tens of meters are noticed between the models themselves, and between the models and the observational data. Some models generate too deep mixed layers, while others produce too shallow mixed layers. The magnitude of these inter-model variations differs depending on the sea under consideration.In almost all the seas, OMIP models with similar ocean stratification compared to MIMOC observational data display the best mixed layer depth at the end of the winter. Furthermore, all models simulate more or less the same sea ice mass balance and thus salt flux into the ocean during sea ice freezing. We argue that the discrepancies between models are not so much linked to the surface salt balance but rather to the accuracy with which those models reproduce the ocean stratification. To substantiate this behavior, we apply a simple conceptual model, which simulates the fall/winter month-to-month evolution of the mixed layer depth in ice-covered regions. In almost fully sea ice-covered regions such as the central Arctic Ocean, Beaufort, and Chukchi Seas, this simplified dynamics captures very well the behavior of the general circulation models, and this highlights that the main difference between the models is the ocean stratification. At the same time, in the East Siberian, Laptev, and Kara Seas, inter-model variations are not explained by the differences in ocean stratification, even though they contain a significant concentration of sea ice. In not fully sea ice-covered regions, such as the Barents Sea, the mixed layer depth dynamics is different: the retreat of the ice cover during summer is more significant than in fully covered regions, hence favoring exchanges with the atmosphere.

<p>The seasonal cycle of the Antarctic sea ice extent is largely controlled by the evolution of the insolation received at the top of the atmosphere. However, sea ice processes and feedbacks with the ocean and the atmosphere can modulate this seasonal cycle. Here, the atmospheric feedbacks are quantified in a series of idealized sensitivity experiments performed with an eddy-permitting (1/4°) NEMO-LIM3 Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM<sup>2</sup> regional atmospheric model. In these experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake/release upon sea ice growth/melt, ice dynamics and surface albedo. We show that the changes in surface heat fluxes are very different between the configurations driven by the reanalysis and those coupled to the atmosphere. Atmospheric feedbacks enhance the response of the modelled winter ice extent to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere. By contrast, the atmospheric feedbacks can damp the impact of the perturbations affecting the heat conductivity through sea ice.</p><div></div>

Non-spherical particles transported by turbulent flow have a rich dynamics that combines their translational and rotational motions. Here, the focus is on small, heavy, inertial particles with a spheroidal shape fully prescribed by their aspect ratio. Such particles undergo an anisotropic, orientation-dependent viscous drag with the carrier fluid flow whose associated torque is given by the Jeffery equations. Direct numerical simulations of homogeneous, isotropic turbulence are performed to study systematically how the translational motion of such spheroidal particles depends on their shape and size. Surprisingly, it is found that the Lagrangian statistics of both velocity and acceleration can be thoroughly described in terms of an effective Stokes number obtained as an isotropic average over angles of the particle's orientation. Corrections to the translational motion of particles due to their non-sphericity and rotation can hence be fully recast as an effective radius obtained from such a mean.

The seasonal cycle of the Antarctic sea ice extent is strongly asymmetric, with a relatively slow increase after the summer minimum followed by a more rapid decrease after the winter maximum. This cycle is intimately linked to the seasonal cycle of the insolation received at the top of the atmosphere, but sea ice processes as well as the exchanges with the atmosphere and ocean may also play a role. To quantify these contributions, a series of idealized sensitivity experiments have been performed with an eddy-permitting (1/4∘) NEMO-LIM3 (Nucleus for European Modelling of the Ocean–Louvain-la-Neuve sea ice model version 3) Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM2 regional atmospheric model. In those experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake and release upon sea ice growth and melt, ice dynamics, and surface albedo. We find that the evolution of sea ice extent during the ice advance season is largely independent of the direct effect of the perturbation and appears thus mainly controlled by initial state in summer and subsequent insolation changes. In contrast, the melting rate varies strongly between the experiments during the retreat, in particular if the surface albedo or sea ice transport are modified, demonstrating a strong contribution of those elements to the evolution of ice coverage through spring and summer. As with the advance phase, the retreat is also influenced by conditions at the beginning of the melt season in September. Atmospheric feedbacks enhance the model winter ice extent response to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere.

In this study, we assess the ability of the ocean-sea ice general circulation models that participated in the CMIP6 Ocean Model Intercomparison Project (OMIP) to simulate the seasonal cycle of the ocean mixed layer depth in the area of the Arctic Ocean covered by multiyear sea ice. During summertime, all models understimate the mixed layer depth by about 20 m compared to the MIMOC (Monthly Isopycnal/Mixed layer Ocean Climatology) observational data. The origin of this systematic bias is unclear. In fall and winter, differences of several tens of meters are noticed between the models themselves and between the models and the observational data. Some models generate too deep mixed layers, while others produce too shallow mixed layers. Since the mixed layer deepening in ice-covered regions during these seasons is largely controlled by the brine rejection associated with ice growth, the discrepancies between models might be related to differences in the modelled sea ice mass balance. However, a detailed model comparison reveals that this is not the case, all models simulating more or less the same sea ice mass balance and thus salt flux into the ocean during sea ice freezing. By applying to model outputs the analytical model developed by Martinson (1990), that allows in particular to determine the main processes responsable for maintaining stablility in polar oceans, it is finally found that most of the disagreement between models can be explained by the accuracy with which the Arctic halocline is reproduced by those models. This feature is simulated generally poorly and quite differently from one model to another, and models with less stratified halocline generally lead to deeper mixed layers. It now remains to identify the model deficiencies responsible for this situation.

The fragmentation of small, brittle, flexible, inextensible fibres is investigated in a fully developed, homogeneous, isotropic turbulent flow. Such small fibres spend most of their time fully stretched and their dynamics follows that of stiff rods. They can then break through tensile failure, i.e. when the tension is higher than a given threshold. Fibres bend when experiencing a strong compression. During these rare and intermittent buckling events, they can break under flexural failure, i.e. when the curvature exceeds a threshold. Fine-scale massive simulations of both the fluid flow and the fibre dynamics are performed to provide statistics on these two fragmentation processes. This gives ingredients for the development of accurate macroscopic models, namely the fragmentation rate and daughter-size distributions, which can be used to predict the time evolution of the fibre size distribution. Evidence is provided for the generic nature of turbulent fragmentation and of the resulting population dynamics. It is indeed shown that the statistics of break-up is fully determined by the probability distribution of Lagrangian fluid velocity gradients. This approach singles out that the only relevant dimensionless parameter is a local flexibility which balances flow stretching to the fibre elastic forces. This article is part of the theme issue 'Fluid dynamics, soft matter and complex systems: recent results and new methods'.

Small flexible fibers in a turbulent flow are found to be as straight as stiff rods most of the time. This is due to the cooperative action of flexural rigidity and fluid stretching. However, fibers might bend and buckle when they tumble and experience a strong enough local compression. Such events are similar to an activation process, where the role of temperature is played by the inverse of Young's modulus. Numerical simulations show that buckling occurs very intermittently in time. This results from unexpected long-range Lagrangian correlations of the turbulent shear.