Brief communication:Pancake ice floe size distribution during the winter expansion of the Antarctic marginal ice zone

The size distribution of pancake ice floes is calculated from images acquired during a voyage to the Antarctic marginal ice zone in the winter expansion season. Results show that 50 % of the sea ice area is made up of floes with diameters of 2.3-4 m. The floe size distribution shows two distinct slopes on either side of the 2.3-4 m range, neither of which conforms to a power law. Following a relevant recent study, it is conjectured that the growth of pancakes from frazil forms the distribution of small floes (D<2.3 m), and welding of pancakes forms the distribution of large floes (D>4 m)

Modelling attenuation of irregular wave fields by artificial ice floes in the laboratory

A summary is given on the utility of laboratory experiments for gaining understanding of wave attenuation in the marginal ice zone, as a complement to field observations, theory and numerical models. It is noted that most results to date are for regular incident waves, which, combined with the highly nonlinear wave–floe interaction phenomena observed and measured during experimental tests, implies that the attenuation of regular waves cannot necessarily be used to infer the attenuation of irregular waves. Two experiments are revisited in which irregular wave tests were conducted but not previously reported, one involving a single floe and the other a large number of floes, and the transmission coefficients for the irregular and regular wave tests are compared. The transmission spectra derived from the irregular wave tests agree with the regular wave data but are overpredicted by linear models due to nonlinear dissipative processes, regardless of floe configuration

Three-dimensional imaging of waves and floes in the marginal ice zone during a cyclone

The marginal ice zone is the dynamic interface between the open ocean and consolidated inner pack ice. Surface gravity waves regulate marginal ice zone extent and properties, and, hence, atmosphere-ocean fluxes and ice advance/retreat. Over the past decade, seminal experimental campaigns have generated much needed measurements of wave evolution in the marginal ice zone, which, notwithstanding the prominent knowledge gaps that remain, are underpinning major advances in understanding the region’s role in the climate system. Here, we report three-dimensional imaging of waves from a moving vessel and simultaneous imaging of floe sizes, with the potential to enhance the marginal ice zone database substantially. The images give the direction–frequency wave spectrum, which we combine with concurrent measurements of wind speeds and reanalysis products to reveal the complex multi-component wind-plus-swell nature of a cyclone-driven wave field, and quantify evolution of large-amplitude waves in sea ice

Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2

The Antarctic marginal ice zone (MIZ) is a highly dynamic region where sea ice interacts with ocean surface waves generated in ice-free areas of the Southern Ocean. Improved large-scale (satellite-based) estimates of MIZ extent and variability are crucial for understanding atmosphere–ice–ocean interactions and biological processes and detection of change therein. Legacy methods for defining the MIZ are typically based on sea ice concentration thresholds and do not directly relate to the fundamental physical processes driving MIZ variability. To address this, new techniques have been developed to measure the spatial extent of significant wave height attenuation in sea ice from variations in Ice, Cloud and land Elevation Satellite-2 (ICESat-2) surface heights. The poleward wave penetration limit (boundary) is defined as the location where significant wave height attenuation equals the estimated error in significant wave height. Extensive automated and manual acceptance/rejection criteria are employed to ensure confidence in along-track wave penetration width estimates due to significant cloud contamination of ICESat-2 data or where wave attenuation is not observed. Analysis of 304 ICESat-2 tracks retrieved from four months of 2019 (February, May, September and December) reveals that sea-ice-concentration-derived MIZ width estimates are far narrower (by a factor of ∼ 7 on average) than those from the new technique presented here. These results suggest that indirect methods of MIZ estimation based on sea ice concentration are insufficient for representing physical processes that define the MIZ. Improved large-scale measurements of wave attenuation in the MIZ will play an important role in increasing our understanding of this complex sea ice zone

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedi�tion (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To re�duce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between envi�ronmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shap�ing the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question

Statistics of wave orbital velocities in random directional sea states

The inclusion of at least the second order nonlinear contribution is necessary to achieve an accurate representation of ocean waves. While this is well known for the surface elevation, the importance of second order nonlinearity on the velocity potential, and hence on the wave kinematics and associated wave loads, is still unclear. To explicitly address the effect of nonlinear contribution on wave velocities Monte-Carlo simulations with a second order wave model are carried out with different initial random conditions. Results show that the statistical distribution of the horizontal components of wave orbital velocity departs substantially from Normality due to second order contributions for both unidirectional and directional wave fields

Estimation of kinetic energy dissipation from breaking waves in the wave crest region

Wave-induced turbulence due to breaking in the absence of surface shear stresses is investigated experimentally. A high-fidelity particle image velocimetry (PIV) technique is used to measure the turbulence near the water surface, inside the wave crests. The spatial velocity vector fields of the breaking waves acquired from PIV provide accurate vertical velocity profiles near the air-water interface, as well as wavenumber velocity spectra beneath the breaking waves at different depths. These velocity spectra exhibit a Kolmogorov interval at high wavenumbers, indicating the presence of isotropic turbulence and permitting an estimation of energy dissipation rates. The depth dependence of dissipation rates of the breaking waves generated in the laboratory shows a scaling similar to that found in wind-forced breaking waves in the field. A phase dependence in the dissipation rates of turbulence kinetic energy is also observed, which should be considered to improve the accuracy of the estimated and modeled wave energy dissipation

Interactions between Irregular Wave Fields and Sea Ice: A Physical Model for Wave Attenuation and Ice Breakup in an Ice Tank

Irregular, unidirectional surface water waves incident on model ice in an ice tank are used as a physical model of ocean surface wave interactions with sea ice. Results are given for an experiment consisting of three tests, starting with a continuous ice cover and in which the incident wave steepness increases between tests. The incident waves range from causing no breakup of the ice cover to breakup of the full length of ice cover. Temporal evolution of the ice edge, breaking front, and mean floe sizes are reported. Floe size distributions in the different tests are analyzed. The evolution of the wave spectrum with distance into the ice-covered water is analyzed in terms of changes of energy content, mean wave period, and spectral bandwidth relative to their incident counterparts, and pronounced differences are found between the tests. Further, an empirical attenuation coefficient is derived from the measurements and shown to have a power-law dependence on frequency comparable to that found in field measurements. Links between wave properties and ice breakup are discussed.Giulio Passerotti, Luke G. Bennetts, Franz von Bock und Polach, Alberto Alberello, Otto Puolakka, Azam Dolatshah, Jaak Monbaliu, and Alessandro Toffol