The Arctic marginal ice zone (MIZ), where strong interactions between sea ice, ocean and atmosphere take place, is expanding as the result of ongoing sea ice retreat. Yet, state-of-the-art models exhibit significant biases in their representation of the complex ocean–sea ice interactions taking place in the MIZ. Here, we present the development of a new coupled sea ice–ocean wave model. This setup allows us to investigate some of the key processes at play in the MIZ. In particular, our coupling enables us to account for the wave radiation stress resulting from the wave attenuation by sea ice and the sea ice lateral melt resulting from the wave-induced sea ice fragmentation. We find that, locally in the MIZ, the ocean surface waves can affect the sea ice drift and melt, resulting in significant changes in sea ice concentration and thickness as well as sea surface temperature and salinity. Our results highlight the need to include wave–sea ice processes in models used to forecast sea ice conditions on short timescales. Our results also suggest that the coupling between waves and sea ice would ultimately need to be investigated in a more complex system, allowing for interactions with the ocean and the atmosphere.
Numerical models exhibit large biases in their representation of Arctic sea ice concentration and thickness, regardless of their complexity or resolution
Sea ice in the Arctic has been drastically receding over the past few decades
Several recent efforts in the modelling community have been focused on the impact of sea ice on waves
In parallel, progress has also been made regarding the inclusion of the effects of waves in coupled ocean–sea ice models. Using a very simple parameterization,
In the present study, we go beyond simply forcing a wave model with sea ice properties, or conversely forcing a sea ice model by wave properties, by proposing a full coupling between a spectral wave model and a state-of-the-art sea ice model. The coupled framework allows us to investigate the interactions between waves and sea ice in the Arctic and the impact that including these effects in a model has on the representation of the waves, ocean and sea ice properties in the Arctic MIZ. We focus in particular on two aspects of these interactions: firstly the effect of including the WRS, computed by the wave model, in the sea ice model and secondly the wave-induced sea ice fragmentation and its effects on lateral melt through the addition of an FSD in the sea ice model. The remainder of this paper is organized as follows. The different models and configurations used in this study are described in Sect. 2. Section 3 is devoted to the theoretical and practical implementation of the coupling between the two models. In Sect. 4, we compare two pan-Arctic simulations: one for which the coupling between wave and sea ice is implemented and one with the ocean–sea ice model run on its own. Our objective is to quantify the dynamical and thermodynamical impacts of the coupling on the sea ice and ocean surface properties. A summary and conclusions are given in Sect. 5.
In this study we make use of the spectral wave model WAVEWATCH III®
We also use the sea ice model LIM3
Implementation of the WRS in the idealized configuration.
In order to test and illustrate the effect of the coupling (Sect. 3), we make use of a simple idealized configuration (see Fig.
We also make use of the CREG025 configuration
Three simulations are performed. First we run a simulation based solely on NEMO-LIM3 (referred to as NOT_CPL), covering the period from 1 January 2002 to the end of 2010, in which the already-existing lateral-melt parameterization in LIM3 is activated. The first years of the simulations are allowing for the adjustment of the ocean and sea ice conditions, and we only analyse results from August and September 2010. During that period, the sea ice extent reaches its annual minimum, providing some fetch for the generation of waves, in particular in the Beaufort Sea. The model sea ice extent during the summer of 2010, and more generally the distribution of the sea ice concentration, compares reasonably well with satellite observations (not shown). Note that this period includes a drop in sea ice concentration in the central Arctic, found both in model results and in satellite observations, that has already been documented by
Finally, we run a simulation over the same period, based solely on WW3 (referred to as WAVE), in which the wave model is forced by sea ice conditions from the NOT_CPL simulation. In order to allow for some spin-up for the waves to develop and break the ice, we exclude the first 3 d from the analysis. In the following, all the results are for the 37 d period between 4 August and 9 September 2010.
Schematic summary of the exchanged information between the sea ice model LIM3 and the wave model WAVEWATCH III® in our coupled framework. The two boxes correspond to the processes accounted for in a given model, while the variables exchanged between the models are listed in the bubbles.
The objective of this section is to present the theoretical background and the practical implementation of the coupling between LIM3 and WW3. Figure
In the following, we describe in more detail the modifications that have been carried out in LIM3 and WW3 in order to couple them and how variables are exchanged between the two models. The coupling allows a new formulation for the sea ice lateral melt in LIM3 (Sect.
Waves transport momentum, and, when they are attenuated by either dissipation or reflection, this momentum is transferred to what has caused this attenuation
Once estimated by WW3, the WRS is then sent to the sea ice model and added as an additional term in the momentum equation of LIM3
Figure
As mentioned earlier, waves can break sea ice and thus impact the sea ice floe size. It is therefore necessary to exchange parameters defining the FSD between the two models. An FSD has been previously implemented in WW3 by
There is no FSD included in the standard version of LIM3. However, recent work by
In their sea ice model neXtSIM,
Now that both models include an FSD, the two models can be coupled in order to represent the effect of the wave-induced sea ice fragmentation, the occurrence of which in LIM3 is determined depending on information provided by WW3. As mentioned earlier, sea ice fragmentation in WW3 is determined by local wave properties, and fragmentation events result in an update of the maximum floe size
Floes that have never been broken by waves have no physical reason to follow this truncated power law. In practice, if we consider a discrete number
In all of our simulations, sea ice is initialized as unbroken everywhere so that
Tests with the simplified domain were also performed with different numbers and widths of floe categories to investigate the sensitivity of the results to those parameters. This sensitivity remains very small as long as the widths of the categories are smaller than 10 m and the categories cover a range of floe sizes larger than 300 m. In the following, we use A first category corresponds to the sea ice floes that are already broken but cannot be broken anymore ( There are 58 categories for which A last category represents unbroken floes (
Snapshots of
We evaluate the effect of this part of the coupling between WW3 and LIM3, as well as the robustness of the implementation of the FSD in LIM3, by looking at the same two simulations in our idealized configuration as presented in Fig.
A parameterization to account for the sea ice lateral melt is already implemented in LIM3. Its formulation follows
In the case of our coupled model, we estimate an FSD, and thus it makes sense to implement a parameterization of the lateral melt that depends explicitly on the FSD rather than on sea ice concentration. Following the work by
Lateral-melt rates (estimated as percentage of sea ice concentration lost per day) estimated by the coupled model after 72 h of simulation using the parameterization of
Temporal evolution of the sea ice volume loss due to lateral melt integrated over the whole domain for simulations similar to the one presented in Fig.
We run two simulations in which the lateral melt is estimated either from the formulation of
We find that the results are also sensitive to the choice of
Significant wave height
In this section we compare the three simulations performed with the CREG025 configuration described in Sect. 2.2 in order to quantify the impact of the coupling on wave, sea ice and ocean surface properties.
To evaluate the impact of waves in the MIZ, we first need to define the MIZ in our model. Various criteria, relying on sea ice concentration, floe size or the region where waves impact the sea ice floe size, have been previously used to delimit the MIZ
First, we examine the differences between the CPL and WAVE simulations, corresponding, respectively, to the coupled WW3–LIM3 run and a run performed with WW3 in stand-alone mode forced with sea ice properties from NOT_CPL. When looking at the differences in significant wave height
We now focus on the effect of adding a wave component on the sea ice properties by comparing results from the CPL and NOT_CPL simulations. Figure
There are also differences in sea surface properties between the two simulations (Fig.
Sea ice concentration and thickness in the CPL simulation
Given that there is no coupling between the ocean and the wave components, the difference in sea surface properties must arise from variations in sea ice conditions and in particular the sea ice melt, and we now investigate this further. Figure
SST
Figure
The total melted sea ice volume, once integrated over the MIZ, increases by 3 % between CPL and NOT_CPL, mainly due to the larger volume of sea ice melted laterally in NOT_CPL (Fig.
The differences in lateral melt between the CPL and the NOT_CPL runs cannot explain the differences in sea ice and sea surface properties seen in Figs.
The primary effect of the WRS is to push sea ice, modifying the intensity and the direction of the sea ice drift.
This impact is significant in the MIZ, where the average sea ice drift velocity increases by
In the following we investigate in further detail the wave–sea ice interactions in two regions during storms. Indeed, although the differences between the CPL and NOT_CPL run at the pan-Arctic scale remain small, it is clear that the way the waves can influence the sea ice and the ocean surface would depend on the local properties of the waves, wind, sea ice and ocean surface.
Volume of sea ice melted by lateral melt in the CPL simulation over the period between 4 August and 9 September 2010
Significant wave height and wave mean direction of propagation
We first focus on a storm event that occurred near the MIZ in the Beaufort Sea on 16–17 August 2010 (Figs.
The differences in sea ice properties around the sea ice tongue between the two runs also result in changes in SST and SSS, with increases of around 1
In our model, bottom melt arises from heat fluxes determined by two distinct processes: (i) a conductive heat flux, the intensity of which is controlled by the difference between sea ice temperature and SST, and (ii) a turbulent heat flux in the surface layer, which depends on both the SST and the shear between the sea ice and the sea surface currents. The inclusion of the WRS could in principle affect the turbulent heat flux through its effect on the sea ice drift, but it is not the case here, suggesting that the deficit of sea ice melt on the eastern side of the sea ice tongue in the CPL run is therefore due to the combination of a colder SST and sea ice reduction.
Mean sea ice drift
The storm that we just examined in the Beaufort Sea occurred on the same date as a second and stronger storm in the Barents Sea, with wave heights of up to 5 m and south-westerly winds reaching
SST
In contrast to the effects of the storm in the Beaufort Sea, the WRS in the CPL run reaches large values (Fig.
The differences in sea ice drift between the CPL and the NOT_CPL runs also result in differences in bottom melt (Fig.
The differences in SST and SSS exhibit similar patterns to the differences in heat flux (Figs.
Averaged differences between the CPL and NOT_CPL simulations of
From these two particular cases we suggest a generalization of the mechanisms by which the waves can impact the sea ice and ocean properties in the MIZ. It is based on a simple principle: if sea ice is moved towards warmer water, it tends to melt more, and vice versa. The direction of the WRS compared to the orientation of the sea ice edge is thus fundamental if we are to understand the impact of the waves. In compact sea ice, waves are quickly attenuated and the direction of the WRS is generally towards the packed ice, thus impeding part of the sea ice melt and increasing the SST and SSS (Fig.
The goal of this study was to examine the wave–sea ice interactions in the MIZ of the Arctic Ocean during the melt season as these processes are thought to be important for determining the sea ice conditions but are not accounted for in the state-of-the-art sea ice models. To that aim, we have developed a model framework, coupling the wave model WW3 with a modified version of the ocean–sea ice model NEMO-LIM3. The coupled model was then used to examine two aspects of the wave–sea ice interactions: (i) the impact of the WRS on the sea ice drift in the MIZ and (ii) the effects of using the wave-induced sea ice fragmentation to estimate lateral melt. The WRS tends to compact the ice edge and thus reduces the total sea ice melt in the MIZ. Yet, its overall impact on the MIZ sea ice area and volume remains limited (Fig.
In the MIZ, waves push sea ice as they are attenuated, locally modifying the position of the sea ice edge through a modulation of the magnitude and timing of the sea ice melt, which results in significant changes in the SST and SSS. Although the impact at the pan-Arctic scale remains limited, the case studies of storms in the Barents and Beaufort seas show how this modulation can be locally and intermittently important. Results from our simple configuration have also revealed that the WRS could strongly modulate the position of the sea ice edge. Yet, except very locally in response to strong storms, the position of the pan-Arctic sea ice edge simulated by our realistic configuration appears to be insensitive to the effect of the wave. This is likely because the position of the sea ice edge in an ocean–sea ice model
is primarily determined by the atmospheric forcing and the bulk formulae and is in particular strongly tied to the position of the sea ice edge in the atmospheric reanalysis
We have also tested two parameterizations of the lateral melt, based either on wave-induced fragmentation information or solely on a scaling between the size of the floes and the sea ice concentration, following
Regardless of the choices made for the implementation of the FSD, the effect of the lateral melt for both formulations remains limited as any change in lateral melt tends to be compensated for by an opposite change in bottom melt. The effect might however become more important if longer simulations were performed. Indeed,
Among the wave–sea ice interaction processes considered in this study, we find that the dynamical effect of the waves (the WRS) has a larger impact on sea ice conditions and sea surface properties than the modulation of lateral melt by sea ice fragmentation. Our simulations were however limited to only a few weeks during the melting season, and it is unclear if the result would hold if longer timescales were considered. In order to answer this question, we would need to implement a parameterization that accounts for the refreezing of floes, through lateral growth and welding. A first parameterization of this kind has been very recently developed by
The coupling developed in this study marks a valuable new step towards an improved representation of waves and sea ice interactions in models, which might improve the representation of the dynamics in the MIZ. Yet, our coupling relies on a number of assumptions, which are most likely leading to an underestimation of the impact of the waves on the ocean and sea ice conditions. For instance, in our coupling, the sea ice rheology is unaffected by fragmentation, which is unlikely to be the case in reality
Here we provide the details of the calculation and implementation of the FSD and in particular of the mechanical redistribution function
Assuming that, in a given grid cell, sea ice fragmentation does not induce any change in the sea ice concentration,
In the absence of a wave model to simulate the sea state,
In our coupled model, sea ice fragmentation is initially computed by WW3
As detailed in Sect.
In practice, in LIM3, we define a given number
With this choice of
If sea ice in a given grid cell has already been broken, the FSD may have deviated from the truncated power-law distribution (due to advection or melting). If fragmentation occurs again at a later model time step, we force the FSD to be reset to the power law assumed in WW3, by adjusting the fraction of each floe size category contributing to the redistribution through the value
The smallest floe size category (i.e.
This system consists in a triangular matrix in which all diagonal terms are non-zero. It is solved by carrying out
The constraint
The Drakkar forcing set is described in
GB and FA formulated the study. GB, FA, CR, CT and CL developed the coupled framework. GB and CL led the paper writing with significant input from the other authors.
The authors declare that they have no conflict of interest.
Part of this work has been carried out as part of the Copernicus Marine Environment Monitoring Service (CMEMS) ArcticMix and WIzARd projects. CMEMS is implemented by Mercator Ocean in the framework of a delegation agreement with the European Union. We thank Martin Vancoppenolle for his valuable help as well as Verena Haid and Xavier Couvelard for their significant assistance in setting up the coupled framework.
This research has been supported by the DGA, the ANR (grant nos. ANR-14-CE01-0012 MIMOSA and ANR-10-LABX-19-01), the EU-FP7 (grant no. SWARP 607476), the ONR (grant no. N0001416WX01117), and the CMEMS (grant projects ArcticMix and WIzARd).
This paper was edited by Daniel Feltham and reviewed by three anonymous referees.