We provide high-resolution in situ observations of wave-induced sea ice breakup in the natural environment. In order to obtain such data, a drone was deployed from the Canadian Coast Guard ship
The marginal ice zone (MIZ) is the ice-covered region that is affected by waves, usually found on the periphery of the polar and subpolar oceans. Reductions in the Arctic sea ice thickness and summer extent in response to global warming
By fracturing large pieces of sea ice into smaller ones, waves change the floe size distribution (FSD) locally and, thus, contribute to an increase in the total lateral sea ice surface that is in contact with water. This results in a greater total sea ice perimeter and in the exposure of water areas that were previously capped under a layer of sea ice to the atmosphere. During the melt season, both the increase in the total ice perimeter and the lower albedo caused by the exposure of darker waters can increase the melt rate
A fragmented ice cover can also have a significantly different dynamical response to external forces, as discussed by
The FSD is an undoubtedly important parameter for sea ice dynamics; hence, there have been great efforts to quantify it. However, to our knowledge, there are no observational studies that directly relate the FSD to the processes that generated it in the natural environment. Most observations come from satellite or aerial imagery of Arctic and Antarctic MIZs, where observable floes have an unknown history
Large-scale spectral wave–ice models (WIMs)
Focusing on the process of breakup itself, rather than on its influence on dynamics,
In summary, there seems to be a consensus from process-based model studies towards the fact that a preferential size is generated by wave-induced sea ice breakup and that the power law observed at a large scale cannot be explained by this process alone. However, it is still unclear what the respective contributions of sea ice rigidity and wave properties are in determining the preferential size and the shape of the FSD. The question remains as to whether these theoretical conclusions are supported by field observations.
Although there have been significant efforts to model the breakup process, only few studies have approached the problem from an observational perspective (e.g.
To date, few field studies on natural breakup have been conducted, mainly because the MIZ is an arduous area to sample directly from. It is indeed hard to be in the MIZ at the right place and at the right time, with good but not overly harsh weather conditions for breakup to happen, and with the right apparatus and available people to measure all relevant variables during a natural breakup event. Indeed, it is possible to study wave–ice interactions in the laboratory, but it is not clear if the results directly apply to the natural environment owing mostly to the complex life history of naturally grown sea ice compared with the more homogeneous growth conditions of the laboratory.
Rather than waiting for the stars to be aligned in the natural environment, we chose to create waves with a ship in order to simulate breakup events. With the help of an unmanned aerial vehicle (UAV or drone) and image processing, the breakup experiments conducted in the Gulf of St. Lawrence (GSL) and in northern Baffin Bay (NBB) allowed us to measure the outcome of small-period waves breaking naturally grown sea ice. While no apparatus measuring curvature of the ice or incident wave properties were successfully deployed, it was possible to extract information about the resulting FSD, the breakup speed and its extent. When compared to thin elastic plate theory, these results give insight on the underlying physics of wave-induced sea ice breakup.
The setup for the experiments conducted to obtain FSDs resulting from wave-induced breakup is as follows. First, a large, level ice floe with a side exposed to open water is identified. A UAV is then deployed and positioned above the ice edge to record high-resolution footage of the breakup event. Finally, the Canadian Coast Guard ship (CCGS)
The first experiment was conducted in the northwestern Gulf of St. Lawrence (GSL;
Schematic representation of the experiment conducted in the GSL. The grey shape represents the ship, and the red and blue-to-yellow lines are the UAV and ship GPS tracks, respectively. The red dot is the fixed position from which the drone filmed the breakup, and the filled blue rectangle is its field of view. The dashed blue rectangle is the area covered by the panoramic picture obtained by taking multiple pictures of the resulting broken ice (Fig.
Figure
The second experiment was conducted in northern Baffin Bay (NBB;
Schematic representation of the NBB experiment. The grey shape represents the ship, and the orange ellipse is the Zodiac. The red and blue-to-yellow lines are the UAV and ship GPS tracks, respectively. The solid and filled blue rectangles are the area of the panoramic picture selected for analysis (Fig.
Steps of the image processing algorithm used for the boundary identification of floes in the GSL experiment.
Figure
The detection of sea ice floes in each orthomosaic consists of a series of steps, which are illustrated in Fig.
Sample of the ellipses fitted on the ice floes by MATLAB. Yellow and blue lines indicate the major and minor axes of length
Here, the method that gives the best results is the watershed transform
Snapshots of the wave-induced breakup experiment at
Similarly to
Using drone footage in the GSL, it was possible to estimate the wavelength and the wave period due to favourable lighting conditions provided by the oblique sunlight. The in-ice wavelength
The speed of the breakup front is evaluated using an automated and unsupervised algorithm that identifies the furthest fracture point along each of the coloured lines in the direction of wave propagation shown in Fig.
Table
Figure
Temporal evolution of the furthest crack location relative to the floe edge at
Wave and ice parameter values measured, estimated or calculated for both experiments as well as their associated uncertainties. Values in parentheses indicate extreme values whenever they are not equidistant from the mean.
In the GSL, the ice fractured up to 60 m from the ice edge, leading to a partial breakup of the floe. In the NBB experiment, the 540 m wide floe was completely broken up by the ship-generated waves. Figure
Breakup resulting from the GSL experiment. The ship sailed along the horizontal axis of the image.
Partial view of the breakup resulting from the NBB experiment, corresponding to the green rectangle in Fig.
To quantify the morphology of sea ice floes, the floe size distribution is first computed using the number density, as has been done in most studies for decades (e.g.
The GSL NFSD exhibits a modal shape with a mean value of 2.8 m and a standard deviation of 1.2 m. The NBB NFSD, on the other hand, has a bimodal shape with a mean value of 5.9 m and a standard deviation of 3.4 m. It is interesting to see that the NBB FSD has a shape similar to what
Number-based probability density functions of floe size (NFSDs) resulting from the breakup experiments.
Let
Figure
Area-based floe size distributions (AFSDs) resulting from the breakup experiments computed with Eq. (
There are very few reports in the literature on wave-induced sea ice breakup events and even fewer that are observed at adequate time and spatial scales. The two experiments presented here, carried out under two contrasting sets of environmental conditions, shed light on multiple aspects of wave–ice interactions: (1) the floe size distribution that results from wave-induced breakup, (2) wave propagation in sea ice and (3) wave attenuation, all of which are discussed below.
The AFSDs obtained in this study (Fig.
Another quantity associated with the FSD that is often used as a state variable in wave–ice interaction modelling studies (e.g.
The first hypothesis is the one used by
Another theoretical framework that has been used in the last decade in the wave–ice interaction community (e.g.
First,
In order to compute
It is worth mentioning that
With values of
Physical quantities related to the AFSDs and comparison to
In the two experiments, ice broke up from the edge inward, with the furthest crack at a given time oriented parallel to the wave phase plane. The speed
Figure
Figure 11a shows that the measured phase speed of the wave propagating into the unbroken ice
From the video footage of the GSL experiment, we can clearly see that waves were attenuated along their propagation into the ice. As attenuation reduces the wave amplitude, it would contribute to slowing down the breakup process and, hence, lead to
The results presented here allow for a rough analysis of the wave propagation into the ice, but there is clearly a need for more experiments in which wave propagation is adequately measured. Not only would this provide data to help identify the dispersion relation of waves propagating into ice but it would also aid quantification of the respective contributions of attenuation and fatigue to the breakup speed.
Phase speed
In the GSL, the breakup extent reached 60 m from the original floe edge. In the NBB experiment, the entire floe that was approximately 540 m wide broke up. Assuming that the incident waves were similar in terms of period, wavelength and amplitude for both experiments (see Table
Results obtained from the analysis of two wave-induced sea ice breakup experiments, captured by a UAV and carried out under two contrasting sets of environmental conditions, provide direct and detailed measurements that shed light on many aspects related to wave–ice interactions. The aerial imagery of the breakup event also allowed for the characterization of wave propagation, breakup evolution and extent.
A novel way of computing the FSD – using the partial aerial concentration rather than the number density – is proposed. The AFSD allows mass conservation, as the total sea ice area can be calculated from it, which is something that cannot be achieved using the NFSD without depending on the assumed shape of the floes. Thus, we deem the AFSD to be physically more relevant than the NFSD. It is also fully coherent with numerical modelling frameworks that solve for the evolution of conserved quantities such as the ITD. The AFSD also allows one to identify the presence of a preferential floe size as a result of wave-induced breakup events. The observation of a preferential size, along with the fact that ice thickness has an effect on it, resonates with many other process-based modelling studies and anecdotal evidence reported in the literature (e.g.
Theoretical frameworks relating the position of maximal strain to the incident wavelength
The estimation of the Young's modulus of the sea ice encountered during the experiments was first made using the empirical relationships of
It was also identified that waves propagating into the unbroken ice might follow the mass loading dispersion relation, as the wavelength and the phase speed were smaller in unbroken ice than in deep water. Moreover, the breakup speed in the GSL experiment is less than or equal to the group speed of inertial-gravity waves, suggesting that attenuation played a bigger role than ice fatigue during the process. Finally, waves were attenuated much faster in the thinner ice floe. However, the lack of in situ data on sea ice properties and wave characteristics over the course of their propagation does not allow us to identify the processes at play nor to partition the contributions of the different processes expected to attenuate waves in ice.
In summary, these results show that using a ship to generate waves allows one to experiment in a controlled yet natural environment. This is a promising way to study wave-induced sea ice breakup, which advances our understanding of numerous wave–ice interactions. Collecting key in situ data to complement the UAV information would significantly improve the scientific output. This could be done by using ice-going platforms, such as an ice canoe, to deploy wave buoys and measure ice properties (e.g. thickness, temperature, salinity, snow cover), as was done by
The code required to produce the results is available at the following Git repository (
The video of the GSL experiment is available on ResearchGate at
EDL planned and conducted both experiments, developed the image processing tools, performed the data analysis, wrote the first draft of the paper, and participated in the discussion and writing. DD provided the original idea for the experiment, provided guidance on data analysis, and participated in the discussion and writing.
The contact author has declared that neither of the authors has any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The authors would like to thank Tim Williams and one anonymous reviewer for their careful reading and for sharing valuable insight that helped improved the paper. We also thank the Canadian Coast Guard crew of the icebreaker
This research has been supported by the Natural Sciences and Engineering Research Council of Canada (grant no. 676518), the Fonds de recherche du Québec – Nature et technologies (grant no. 259530), the “Physics of Seasonal Sea Ice” NSERC discovery grant to Dany Dumont (grant nos. RGPIN-2019-06563 and RGPAS-2019-00068), the Odyssée Saint-Laurent program of the Réseau Québec Maritime, and the Canadian Foundation for Innovation and Amundsen Science.
This paper was edited by Petra Heil and reviewed by Timothy Williams and two anonymous referees.