Abstract. We present WIce-FOAM 1.0, a numerical model built on OpenFOAM that couples the dynamics and thermodynamics of heterogeneous sea ice to analyse waves' response in marginal ice zone regions composed of consolidated ice floes and interstitial grease ice. The model represents prototypical conditions on the 5 km scale, where each 10 m grid cell classified as ice floe or grease ice may contain both ice types, but are predominantly occupied by one. Our model aims to study the mean shear viscosity of heterogeneous sea ice to bridge the gap with larger-scale ocean-sea ice models in which sub-grid details and wave effects are neglected. We tested the model in the Southern Ocean using a realistic sea-ice field from a SAR satellite image and complemented our analysis by idealised simulations. The thermodynamic model was coupled online to optimize the stiffness of the process scales and to explicitly account for the distinct characteristics of different ice types. We first investigated the dynamic response of sea ice to one-way wave forcing across a range of wave periods and directions. The results show that the domain-averaged sea-ice viscosity is scale invariant from approximately 800 m to 5 km and is primarily governed by the relative proportion of ice floes to grease ice, with less sensitivity to wave periods and directions. While the wave direction affects the local strain rate and viscosity, and the presence and orientation of narrow connections between the larger ice floes significantly influence the mean viscosity, these effects do not break the observed scale invariance. Finally, we demonstrate that, despite the different time scales, the mean viscosity responds nonlinearly to the inclusion of thermodynamic sea-ice growth. This model represents a first step towards a mechanistic understanding and description of heterogeneous sea ice, which is common in the Antarctic and is increasing in the warming Arctic. It can be used to design field experiments and to derive parametrisations of waves-in-ice response for large-scale sea-ice models.

Abstract The coastal polynya formed off Cape Darnley, in the Southern Ocean, is a favorable site for a secondary phytoplankton bloom in the late summer and autumn. In late February of 2018, we conducted in‐situ observations onboard an icebreaker and measured surface water chlorophyll a concentrations reaching 5.5 μg/L. Concurrently, in turbulent conditions associated with wind speeds exceeding 20 m/s, ocher‐colored newly‐formed sea ice, in the form of grease and pancake ice, spread across the polynya. Chlorophyll a concentrations measured in the grease and pancake ice were 47 times (260.0 μg/L) and 11 times (61.8 μg/L) higher than in the surrounding seawater, respectively. The corresponding sea ice algal concentration was sufficiently high to discolor the ice. Moreover, water temperatures were at or below the freezing point at depths shallower than 30 m, suggesting that suspended frazil ice came into contact with phytoplankton, which were particularly abundant in the water column during the bloom, and scavenged them. The diatom Fragilariopsis curta represented more than 83% of both total diatom cell abundance and biovolume in sea ice. Combining known algal growth rates with our results of chlorophyll a concentration in newly‐formed ice, most of the ice algae originated from phytoplankton incorporated and accumulated by frazil ice. The considerable algal concentrations measured in new ice suggest that this accumulation process could contribute to the algal standing stock in Antarctic sea ice. The abundant bloom‐forming phytoplankton incorporated into sea ice suggests that they could be a seed population for subsequent ice‐algal or ice‐edge bloom formation.

Oil spillages on a sea’s or an ocean’s surface are a threat to marine and coastal ecosystems. They are mainly caused by ship accidents, illegal discharge of oil from ships during cleaning and oil seepage from natural reservoirs. Synthetic-Aperture Radar (SAR) has proved to be a useful tool for analyzing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan’s territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan’s Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this paper, we report the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by SAR experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures.

Abstract Sea ice–wave interactions have been widely studied in the marginal ice zone, at relatively low wind speeds and wave frequencies. Here, we focus on very different conditions typical of coastal polynyas: extremely high wind speeds and locally generated, short, steep waves. We overview available parameterizations of relevant physical processes (nonlinear wave–wave interactions, energy input by wind, whitecapping and ice‐related dissipation) and discuss modifications necessary to adjust them to polynya conditions. We use satellite‐derived data and spectral modeling to analyze waves in 10 polynya events in the Terra Nova Bay, Antarctica. We estimate the wind‐input reduction factor over frazil/grease ice in the wave‐energy balance equation at 0.56. By calibrating the model to satellite observations we show that exact treatment of quadruplet wave–wave interactions (as opposed to the default Discrete Interaction Approximation) is necessary to fit the model to data, and that the power n > 4 in the sea‐ice source term Sice ∼ fn (where f denotes wave frequency) is required to reproduce the strong attenuation of high‐frequency waves observed for frazil streaks. We use a very‐high resolution satellite image of a fragment of one of the polynyas to determine whitecap fraction. We show that there are more than twofold differences in whitecap fraction over ice‐free and ice‐covered regions, and that the model produces realistic whitecap fractions without any tuning of the whitecapping source term. Finally, we estimate the polynya‐area‐integrated wind input, energy dissipation due to whitecapping, and whitecap fraction to be on average below 25%, 10% and 30%, respectively, of the corresponding open‐water values.

Small-scale computational fluid dynamics modelling of the wave induced ice floe-grease ice interaction in the Antarctic marginal ice zone

Meteorological and hydrological conditions impacting grease ice ridges formation along the southern Baltic shore

Every year situation when theArctic seas are free of ice is becoming more frequent. It allows scientists to study hard-to-reach areas using well-equipped research vessels instead of icebreakers. During the COVID-19 pandemic, the successful expedition of the research vessel “Academician Mstislav Keldysh” with more than 60 scientists from 15 countries across the four Arctic seas (Barents, Kara, Laptev, and East Siberian) on September–November 2020 seems like a real wonder. One of the expedition tasks was remote sensing of different hydrophysical processes by their manifestation on the sea surface using marine radar. This article proposes the method of generating high spatial resolution radar maps of the sea surface and algorithms of hydrophysical processes identification. This article also presents examples of registered processes, such as wind waves, ice fields with different types of ice (grease ice, pancake ice, nilas, and young ice), manifestations of internal waves observed in the Kara Gate and Vilkitsky Strait, as well as manifestations of intense methane seeps on the sea surface. This article contains quantitative estimations of the physical parameters of the observed processes underlying the effectiveness of Doppler marine radars in harsh conditions of the Arctic seas.

Wave-influenced formation of new ice: Model building and a test case

Frazil ice, consisting of loose disc-shaped ice crystals, is the first ice that forms in the annual cycle in the marginal ice zone (MIZ) of the Antarctic. A sufficient number of frazil ice crystals form the surface “grease ice” layer, playing a fundamental role in the freezing processes in the MIZ. As soon as the ocean waves are sufficiently damped by a frazil ice cover, a closed ice cover can form. In this article, we investigate the rheological properties of frazil ice, which has a crucial influence on the growth of sea ice in the MIZ. An in situ test setup for measuring temperature and rheological properties was developed. Frazil ice shows shear thinning flow behavior. The presented measurements enable real-data-founded modelling of the annual ice cycle in the MIZ.

Identification of an oil spill is essential to evaluate the potential spread and float from the source to coastal terrains, and their continued monitoring is essential for managing the environmental protection actions to confine the pollution and avoid further damage. The SAR sensor is perceived as the most significant remote sensing apparatus for the oil slick examination. One of the main aspects of oil spreading over sea surface is that it dampens the capillary waves and so, the backscatter radio waves are suppressed. As a result, oil spills are represented as black spots, while the brighter regions are usually related with unspoiled polluted sea areas. Additionally, the wide coverage that the sensor can provide is highly significant including long-range fate, as well as contextual information, such as sensitive coastal areas or vessels, which can be enclosed in the acquired image. However, oceanic natural phenomena such as low wind speed regions, weed beds and algae blooms, wave shadows behind land, grease ice, etc. can also be depicted as dark spots. These dark regions are commonly categorized as "look-Alikes and their discrimination is very challenging. Machine Learning techniques are the most appropriate choice to classify oil spills and look-Alikes. In the present work, a comparison between decision trees models and NN is performed to identify and extract the appropriate set of features characterizing an oil spill allowing effective evolution monitoring and setting up proper emergency actions.

The marginal ice zone is a highly dynamical region where sea ice and ocean waves interact. Large-scale sea ice models only compute domain-averaged responses. As the majority of the marginal ice zone consists of mobile ice floes surrounded by grease ice, finer-scale modelling is needed to resolve variations of its mechanical properties, wave-induced pressure gradients and drag forces acting on the ice floes. A novel computational fluid dynamics approach is presented that considers the heterogeneous sea ice material composition and accounts for the wave-ice interaction dynamics. Results show, after comparing three realistic sea ice layouts with similar concentration and floe diameter, that the discrepancy between the domain-averaged temporal stress and strain rate evolutions increases for decreasing wave period. Furthermore, strain rate and viscosity are mostly affected by the variability of ice floe shape and diameter.

Young sea ice composed of grease and pancake ice (GPI), as well as thin floes, considered to be the most common form of sea ice fringing Antarctica, is now becoming the “new normal” also in the Arctic. A study of the rheological properties of GPI is carried out by comparing the predictions of two viscous wave propagation models: the Keller model and the close-packing (CP) model, with the observed wave attenuation obtained by SAR image techniques. In order to fit observations, it is shown that describing GPI as a viscous medium requires the adoption of an ice viscosity which increases with the ice thickness. The consequences regarding the possibility of ice thickness retrieval from remote sensing data of wave attenuation are discussed. We provide examples of GPI thickness retrievals from a Sentinel-1 C band SAR image taken in the Beaufort Sea on 1 November 2015, and three CosmoSkyMed X band SAR images taken in the Weddell Sea on March 2019. The estimated GPI thicknesses are consistent with concurrent SMOS measurements and available local samplings.

Abstract. Frazil and grease ice forms in the ocean mixed layer (OML) during highly turbulent conditions (strong wind, large waves) accompanied by intense heat loss to the atmosphere. Three main velocity scales that shape the complex, three-dimensional (3D) OML dynamics under those conditions are the friction velocity u* at the ocean–atmosphere interface, the vertical velocity w* associated with convective motion, and the vertical velocity w*,L associated with Langmuir turbulence. The fate of buoyant particles, e.g., frazil crystals, in that dynamic environment depends primarily on their floatability, i.e., the ratio of their rising velocity wt to the characteristic vertical velocity, which is dependent on w* and w*,L. In this work, the dynamics of frazil ice is investigated numerically with the high-resolution, non-hydrostatic hydrodynamic model CROCO (Coastal and Regional Ocean COmmunity Model), extended to account for frazil transport and its interactions with surrounding water. An idealized model setup is used (a square computational domain with periodic lateral boundaries, spatially uniform atmospheric and wave forcing). The model reproduces the main features of buoyancy- and wave-forced OML circulation, including the preferential concentration of frazil particles in elongated patches at the sea surface. Two spatial patterns are identified in the distribution of frazil volume fraction at the surface: one related to individual surface convergence zones, very narrow, and oriented approximately parallel to the wind/wave direction and one in the form of wide streaks with a separation distance of a few hundred meters, oriented obliquely to the direction of the forcing. Several series of simulations are performed, differing in terms of the level of coupling between the frazil and hydrodynamic processes, from a situation when frazil has no influence on hydrodynamics (as in most models of material transport in the OML) to a situation in which frazil modifies the net density, effective viscosity, and transfer coefficients at the ocean–atmosphere interface and exerts a net drag force on the surrounding water. The role of each of those effects in shaping the bulk OML characteristics and frazil transport is assessed, and the density of the ice–water mixture is found to have the strongest influence on those characteristics.

The significant reduction of the sea ice extent in the western Arctic has been observed by the sustained satellite observations since 1979. The opening ocean is now allowing waves to evolve and propagate under the presence of the Arctic sea ice. A better understanding of the wave-ice interaction is necessary for the safe shipping over the sea ice covered Arctic Ocean and to improve the Arctic climate projection. During R/V Mirai Arctic Expedition in October 2019, two drifting wave-buoys were concurrently deployed in the open ocean and the Arctic marginal ice zone (MIZ) with grease ice and pancake ice. The wave and sea ice conditions at the time of the deployments were documented in detail. Based on the wave buoy data and the sea ice edge estimated by a Synthetic Aperture Radar (SAR) image, attenuation rates of waves under the grease ice are estimated. Good agreement in the frequency dependency of the wave attenuation rate is presented between the observational results and the theoretical prediction from the viscous model of Weber (1987). The agreement implies that the observed surface waves were attenuated by the viscous damping beneath grease ice. It is also found that the observed attenuation rates were generally lower than the previous studies. Several possible factors are discussed, such as the sea ice type, wind energy input, and uncertainties in the estimation of the attenuation rate.

Abstract Sea ice formation processes occur on subgrid scales, and the detailed physics describing the processes are therefore not generally represented in climate models. One likely consequence of this is the premature closing of areas of open water in model simulations, which may result in a misrepresentation of heat and gas exchange between the ocean and atmosphere. This work demonstrates the implementation of a more realistic model of sea ice formation, introducing grease ice as a wind and oceanic stress‐dependent intermediary state between water and new sea ice. We use the fully coupled land‐atmosphere‐ocean‐sea ice model, HadGEM3‐GC3.1 and perform a three‐member ensemble with the new grease ice scheme from 1964 to 2013. Comparing our sea ice results with the existing ensemble without grease ice formation shows an increase in sea ice thickness and volume in the Arctic. In the Antarctic, including grease ice processes results in large local changes to both simulated sea ice concentration and thickness, but no change to the total area or volume.

Abstract. We investigate a case of ocean waves through a pack ice cover captured by Sentinel-1A synthetic aperture radar (SAR) on 12 October 2015 in the Beaufort Sea. The study domain is 400 km by 300 km, adjacent to a marginal ice zone (MIZ). The wave spectra in this domain were reported in a previous study (Stopa et al., 2018b). In that study, the authors divided the domain into two regions delineated by the first appearance of leads (FAL) and reported a clear change of wave attenuation of the total energy between the two regions. In the present study, we use the same dataset to study the spectral attenuation in the domain. According to the quality of SAR-retrieved wave spectrum, we focus on a range of wave numbers corresponding to 9–15 s waves from the open-water dispersion relation. We first determine the apparent attenuation rates of each wave number by pairing the wave spectra from different locations. These attenuation rates slightly increase with increasing wave number before the FAL and become lower and more uniform against wave number in thicker ice after the FAL. The spectral attenuation due to the ice effect is then extracted from the measured apparent attenuation and used to calibrate two viscoelastic wave-in-ice models. For the Wang and Shen (2010b) model, the calibrated equivalent shear modulus and viscosity of the pack ice are roughly 1 order of magnitude greater than that in grease and pancake ice reported in Cheng et al. (2017). These parameters obtained for the extended Fox and Squire model are much greater, as found in Mosig et al. (2015) using data from the Antarctic MIZ. This study shows a promising way of using remote-sensing data with large spatial coverage to conduct model calibration for various types of ice cover.Highlights. Three key points: The spatial distribution of wave number and spectral attenuation in pack ice are analyzed from SAR-retrieved surface wave spectra. The spectral attenuation rate of 9–15 s waves varies around 10−5 m2 s−1, with lower values in thicker semicontinuous ice fields with leads. The calibrated viscoelastic parameters are greater than those found in pancake ice.

The paper presents the topography, morphology, and structure of various forms of piled ice observed at the southern coast of the Baltic Sea. The authors distinguished pressured ice, grease ice ridge, ridge ice, and hummock ice, based on the results of observations, measurements and photographic documentation that were collected by the authors in the years 1979–2019. Cross-sections of the forms were prepared based on the results of manual drilling. The recognised forms were then classified according to their structure, topography, and morphology as well as the genetic conditions of the region. The distinguished forms of piled ice differ not only in terms of the type and structure of the ice that they consist of, but also in terms of topography and the piling factor: wind, wave movements, and currents.

A laboratory experimental study conducted in a freshwater wave flume installed in a refrigerated room characterized the modifications of wave propagation along on-site manufactured ice covers. Monochromatic surface waves of various amplitudes and frequencies were generated and propagated through three types of ice covers: sheet ice, broken ice floes, and grease ice. This study characterized the spatial evolutions of wave height attenuation and phase speed changes. Wave phase speed increased significantly in sheet ice relative to open water values while no significant changes in phase speed were present with other ice covers. The modifications by sheet ice are consistent with thin plate model predictions based on the elasticity of ice, using measured mechanical properties of sheet ice. Attenuation was strongest for shorter waves in sheet ice followed by grease ice and ice floes. Attenuation under grease ice is shown to be related to the surface wave orbital velocity, similar to dissipation by bottom friction and swell dissipation. The attenuation coefficient of grease ice normalized by wavenumber is proportional to wave steepness with a coefficient varying with ice properties. This laboratory experimental study examined and characterized wave dispersion and attenuation under these different ice properties and wave characteristics, which could be useful in understanding and modeling wave-ice interaction processes in open waters.

Abstract Internal solitary waves (ISWs) propagating in a stably stratified two‐layer fluid in which the upper boundary condition changes from open water to ice are studied for grease, level, and nilas ice. The ISW‐induced current at the surface is capable of transporting the ice in the horizontal direction. In the level ice case, the transport speed of, relatively long ice floes, nondimensionalized by the wave speed is linearly dependent on the length of the ice floe nondimensionalized by the wave length. Measures of turbulent kinetic energy dissipation under the ice are comparable to those at the wave density interface. Moreover, in cases where the ice floe protrudes into the pycnocline, interaction with the ice edge can cause the ISW to break or even be destroyed by the process. The results suggest that interaction between ISWs and sea ice may be an important mechanism for dissipation of ISW energy in the Arctic Ocean.

Climate change at the Western Antarctic Peninsula (WAP) is predicted to cause major changes in phytoplankton community composition, however, detailed seasonal field data remain limited and it is largely unknown how (changes in) environmental factors influence cell size and ecosystem function. Physicochemical drivers of phytoplankton community abundance, taxonomic composition and size class were studied over two productive austral seasons in the coastal waters of the climatically sensitive WAP. Ice type (fast, grease, pack or brash ice) was important in structuring the pre-bloom phytoplankton community as well as cell size of the summer phytoplankton bloom. Maximum biomass accumulation was regulated by light and nutrient availability, which in turn were regulated by wind-driven mixing events. The proportion of larger-sized (> 20 µm) diatoms increased under prolonged summer stratification in combination with frequent and moderate-strength wind-induced mixing. Canonical correspondence analysis showed that relatively high temperature was correlated with nano-sized cryptophytes, whereas prymnesiophytes (Phaeocystis antarctica) increased in association with high irradiance and low salinities. During autumn of Season 1, a large bloom of 4.5-µm-sized diatoms occurred under conditions of seawater temperature > 0 °C and relatively high light and phosphate concentrations. This bloom was followed by a succession of larger nano-sized diatoms (11.4 µm) related to reductions in phosphate and light availability. Our results demonstrate that flow cytometry in combination with chemotaxonomy and size fractionation provides a powerful approach to monitor phytoplankton community dynamics in the rapidly warming Antarctic coastal waters.