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

Parameter-free higher-order Schrödinger systems with weak dissipation and forcing

The higher-order nonlinear Schrödinger equation (NLS) (Dysthe’s equation in the context of water waves) models the time evolution of the slowly modulated amplitude of a wave packet in physical systems described by dispersive partial differential equations (PDEs). These systems, of which water waves are a canonical example, require the presence of a small-valued ordering parameter so that a multi-scale expansion can be performed. However, often the resulting system itself contains this parameter. Thus, these models are difficult to interpret from a formal asymptotics perspective. This article describes a procedure to derive a parameter-free, higher-order evolution equation for a generic infinite-dimensional dispersive PDE with weak linear damping and/or forcing. This is achieved by placing the PDE in an infinite-dimensional Hilbert space and Taylor expanding with Fréchet derivatives. An attractive feature of this procedure is that it can be used in many different physical settings, including water waves, nonlinear optics and any dispersive system with weak dissipation or forcing and does not assume any additional structure to the governing PDE, for example its Hamiltonian nature. To complement this, two specific examples with accompanying symbolic algebra code are demonstrated that can be used as a template for other physical systems

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

Observations of Rogue Seas in the Southern Ocean

We report direct observations of surface waves from a stereo camera system along with concurrent measurements of wind speed during an expedition across the Southern Ocean in the austral winter aboard the South African icebreaker S.A. Agulhas II. Records include water surface elevation across a range of wave conditions spanning from early stages of wave growth to full development. We give experimental evidence of rogue seas, i.e., sea states characterized by heavy tails of the probability density function well beyond the expectation based on bound mode theory. These conditions emerge during wave growth, where strong wind forcing and high nonlinearity drive wave dynamics. Quasiresonance wave-wave interactions, which are known to sustain the generation of large amplitude rogue waves, capture this behavior. Wave statistics return to normality as the wind forcing ceases and waves switch to a full developed condition

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

Numerical simulations of ocean surface waves along the Australian coast with a focus on the Great Barrier Reef

Numerical simulations of ocean surface waves along the Australian coast are performed with the spectral wave model WAVEWATCH III (WW3) and the state-of-the-art physics and numerics. A large-scale, high-resolution (1–15 km) unstructured mesh is designed for better resolving the extensive Australian coastline. Based on verification against altimeter and buoy observations, it is found that the WW3 simulations, with an observation-based source term package (i.e., ST6) and other relevant physical processes, perform reasonably well in predicting wave heights and periods in most regions. Nonetheless, the Great Barrier Reef (GBR) represents a challenging region for the wave model, in which wave heights are severely overestimated because most of the individual coral reefs and their strong dissipative effects could not be resolved by the local mesh. A two-step modeling strategy is proposed here to address this problem. First, individual coral reefs are regarded as unresolved obstacles and thus complete barriers to wave energy. Second, we adopt the unresolved obstacles source term proposed recently to parameterize the dissipative impact of these subgrid coral reefs. It is then demonstrated that this subgrid-scale reef parameterization enhances the model performance in the GBR dramatically, reducing the wave height bias from above 100 % to below 20 %. The source term balance and the sensitivity of model results to the grid resolution around the GBR are also discussed, illustrating the applicability of this two-step strategy to km-scale wave simulations.</p

Links between atmospheric aerosols and sea state in the Arctic Ocean

Sea spray emission is the largest mass flux of aerosols to the atmosphere with important impact on atmospheric radiative transfer. However, large uncertainties still exit in constraining this mass flux and its climate forcing, in particular in the Arctic, where sea ice and relatively low wind speed in summer constitute a significantly different regime compared to the global ocean. Sea state conditions and marine boundary layer stability are also critical variables, but their contribution is often overlooked. Here we present concurrent observations of sea state using a novel stereo camera system, sea spray through coarse mode aerosols, and meteorological variables to determine boundary layer stability in the Barents and Kara Seas during the 2021 Arctic Century Expedition. Our findings reveal that aerosol concentrations were highest over open waters, closely correlating with wave height, followed by wind speed, wave steepness, and wave age. Notably, these correlations were stronger under unstable marine boundary layer conditions, reflecting immediate sea spray generation. By analysing various combinations of sea and atmospheric variables, we identified the wave height Reynolds number as the most effective indicator of atmospheric sea spray concentration, explaining 57% of its variability in unstable conditions. Our study underscores the need to consider sea state, wind, and boundary layer conditions together to accurately estimate atmospheric sea spray concentrations in the Arctic

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