Eddy activities are particularly prominent in the Southern Ocean due to the instabilities of the Antarctic Circumpolar Current (ACC), which plays a critical role in energy transport of the global ocean. The Indian sector of the Southern Ocean is not only a typical eddy-rich region with strong Eddy Kinetic Energy (EKE) and associated energy conversions among different energy reservoirs (kinetic energy and potential energy of the eddy and mean flow), but also events of extreme EKE. In this study, a systematic energetics analysis framework is employed to examine the notable anomalies of an intensified EKE event observed in the southwest region of the Kerguelen Plateau in 2017 based on a reanalysis product. The EKE anomaly existing at all depths emerges in April, reaches its peak during the austral winter, and persists into the following summer. Energetics analysis indicates that the strong anomalous EKE is primarily determined by baroclinic instability, with distinct governing mechanisms at the surface and in the internal ocean. The anomalous intrusion of warm Circumpolar Deep Water intensifies the baroclinic energy conversion in the subsurface, which contributes to the observed EKE anomalies. Moreover, the anomalous strong wind-induced Ekman pumping serves to amplify the lifting of isopycnals, which enhances the baroclinic instability and subsequently intensifies the EKE anomalies. This study sheds new light on underlying mechanisms governing local polar dynamics and provides insights into the intricate interaction between ocean dynamics and energy distribution in the Antarctic.

Gayan Pathirana1,2, Kyung Min Noh1,3*, Dong-Geon Lee1, Huiji Lee1 and Jong-Seong Kug1*1Division of Environmental Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang, South Korea.2Department of Oceanography and Marine Geology, FMST, University of Ruhuna, Matara, Sri Lanka.3Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea.*Corresponding author. Email: [email protected], [email protected]: Indian Ocean Dipole, Biophysical Interaction, Phytoplankton

The comparison of a morphodynamic model results with observations is an essential part to establish its credibility. In the past multiple model were validated against observations for sand banks, coastlines or estuarine environments. Some modelling have studied the marine dunes migrations but are generally limited to a two-dimensional study. In the present study, a three-dimensional morphodynamic model were setup on an area where highly dynamic dunes are present. The modelling results were analysed and compared to in-situ observations either using a 2D and a 3D method. The vertical and horizontal differences with observations were then assessed using the known method and, based on these results, an updated validation method were proposed to overcome some issues that could interfere with the process.

Fungi in marine ecosystems play crucial roles as saprotrophs, parasites, and pathogens. The definition of marine fungi has evolved over the past century. Currently, “marine fungi” are defined as any fungi recovered repeatedly from marine habitats that are able to grow and/or sporulate in marine environments, form symbiotic relationships with other marine organisms, adapt and evolve at the genetic level, or are active metabolically in marine environments. While there are a number of recent reviews synthesizing our knowledge derived from over a century of research on marine fungi, this review article focuses on the state of knowledge on planktonic marine fungi from the coastal and open ocean, defined as fungi that are in suspension or attached to particles, substrates or in association with hosts in the pelagic zone of the ocean, and their roles in remineralization of organic matter and major biogeochemical cycles. This review differs from previous ones by focusing on biogeochemical impacts of planktonic marine fungi and methodological considerations for investigating their diversity and ecological functions. Importantly, we point out gaps in our knowledge and the potential methodological biases that might have contributed to these gaps. Finally, we highlight recommendations that will facilitate future studies of marine fungi. This article first provides a brief overview of the diversity of planktonic marine fungi, followed by a discussion of the biogeochemical impacts of planktonic marine fungi, and a wide range of methods that can be used to study marine fungi.

Pelagic tunicates (salps, pyrosomes) and fishes generate jelly-falls and/or fecal pellets that sink roughly 10 times faster than bulk oceanic detritus, but their impacts on biogeochemical cycles in the ocean interior are poorly understood. Using a coupled physical-biogeochemical model, we find that fast-sinking detritus decreased global net primary production and surface export, but increased deep sequestration and transfer efficiency in much of the extratropics and upwelling zones. Fast-sinking detritus generally decreased total suboxic and hypoxic volumes, reducing a “large oxygen minimum zone (OMZ)” bias common in global biogeochemical models. Newly aerobic regions at OMZ edges exhibited reduced transfer efficiencies in contrast with global tendencies. Reductions in water column denitrification resulting from improved OMZs improved simulated nitrate deficits relative to phosphate. The carbon flux to the benthos increased by 11% with fast-sinking detritus from fishes and pelagic tunicates, yet simulated benthic fluxes remained on the lower end of observation-based estimates.

Monthly global sea-air CO2 flux estimates from 1998-2020 are produced by extrapolation of surface water fugacity of CO2 (fCO2w) observations using an Extra-trees (ET) machine learning technique. This new product (AOML_ET) is one of the eleven observation-based submissions to the second REgional Carbon Cycle Assessment and Processes (RECCAP2) effort. The target variable fCO2w is derived using the predictor variables including date, location, sea surface temperature, mixed layer depth, and chlorophyll-a. A monthly resolved sea-air CO2 flux product on a 1˚ by 1˚ grid is created from this fCO2w product using a bulk flux formulation. Average global sea-air CO2 fluxes from 1998-2020 are -1.7 Pg C yr-1 with a trend of 0.9 Pg C decade-1. The sensitivity to omitting mixed layer depth or chlorophyll-a as predictors is small but changing the target variable from fCO2w to air-water fCO2 difference has a large effect, yielding an average flux of -3.6 Pg C yr-1 and a trend of 0.5 Pg C decade-1. Substituting a spatially resolved marine air CO2 mole fraction product for the commonly used zonally invariant marine boundary layer CO2 product yield greater influx and less outgassing in the Eastern coastal regions of North America and Northern Asia but with no effect on the global fluxes. A comparison of AOML_ET for 2010 with an updated climatology following the methods of Takahashi et al. (2009), that extrapolates the surface CO2 values without predictors, shows overall agreement in global patterns and magnitude.

A document by Nathan Lenssen. Click on the document to view its contents.

A document by Alex Omar Gonzalez. Click on the document to view its contents.

This study observed seasonal trends and inferred drivers of CO2 biogeochemistry at the air-water interface of Lake Superior. Underway carbon dioxide partial pressure pCO2 was measured in surface water during 69 transects spanning ice free seasons of 2019-2022. These data comprise the first multiannual pCO2 time series in the Laurentian Great Lakes. Surface water pCO2 was closely tied to increasing atmospheric pCO2 by a 100 day CO2 equilibration timescale, while seasonal variability was controlled equally by thermal and biophysical drivers during the ice-free season. Comparison to previous modeling efforts indicates that Lake Superior surface pCO2 increased at a similar rate as the atmosphere over the preceding two decades. Spatial heterogeneity in CO2 dynamics was highlighted by a salinity-based delineation of “riverine” and “pelagic” regimes, each of which displayed a net CO2 influx over Julian days 100-300 on the order of 30 Gmol C. These findings refine previous estimates of Lake Superior C fluxes, support predictions of anthropogenic CO2 invasion, point to new observation strategies for large lakes, and highlight an urgent need for studies of changes to lacustrine C cycling.

The El Niño-Southern Oscillation (ENSO) phenomenon – the dominant source of climate variability on seasonal to multi-year timescales – is predictable a few seasons in advance. Forecast skill at longer multi-year timescales has been found in a few models and forecast systems, but the robustness of this predictability across models has not been firmly established owing to the cost of running dynamical model predictions at longer lead times. In this study, we use a massive collection of multi-model hindcasts performed using model analogs to show that multi-year ENSO predictability is robust across models and arises predominantly due to skillful prediction of multi-year La Niña events following strong El Niño events.

Initialized climate model simulations have proven skillful for near-term predictability of the key physical climate variables. By comparison, predictions of biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate skillful predictions are possible for lead-times up to six years at global scale for some CMIP6 models. However, unlike core physical variables, biogeochemical variables are not directly initialized in existing decadal preciction systems, and extensive empirical parametrization of ocean-biogeochemistry in Earth System Models introduces a significant source of uncertainty. Here, we propose a new approach for improving the skill of decadal ocean carbon flux predictions using observationally-constrained statistical models, as alternatives to the ocean-biogeochemistry models. We use observations to train multi-linear and neural-network models to predict the ocean carbon flux. To account for observational uncertainties, we train using six different observational estimates of the flux. We then apply these trained statistical models using input predictors from the Canadian Earth System Model (CanESM5) decadal prediction system to produce new decadal predictions. Our hybrid GCM-statistical approach significantly improves prediction skill, relative to the raw CanESM5 hindcast predictions over 1990-2019. Our hybrid-model skill is also larger than that obtained by any available CMIP6 model. Using bias-corrected CanESM5 predictors, we make forecasts for ocean carbon flux over 2020-2029. Both statistical models predict increases in the ocean carbon flux larger than the changes predicted from CanESM5 forecasts. Our work highlights the ability to improve decadal ocean carbon flux predictions by using observationally-trained statistical models together with robust input predictors from GCM-based decadal predictions.

Seismic ocean thermometry uses sound waves generated by repeating earthquakes to measure temperature change in the deep ocean. In this study, waves generated by earthquakes along the Japan Trench and received at Wake Island are used to constrain temperature variations in the Kuroshio Extension region. This region is characterized by energetic mesoscale eddies and large decadal variability, posing a challenging sampling problem for conventional ocean observations. The seismic measurements are obtained from a hydrophone station off and a seismic station on Wake Island, with the seismic station's digital record reaching back to 1997. These measurements are combined in an inversion for the time and azimuth dependence of the range-averaged deep temperatures, revealing lateral and temporal variations due to Kuroshio Extension meanders, mesoscale eddies, and decadal water mass rearrangements. These results highlight the potential of seismic ocean thermometry for better constraining the variability and trends in deep-ocean temperatures. By overcoming the aliasing problem of point measurements, these measurements complement existing ship- and float-based hydrographic measurements.

Satellite microwave radiance observations are strongly sensitive to sea ice, but physical descriptions of the radiative transfer of sea ice and snow are incomplete. Further, the radiative transfer is controlled by poorly-known microstructural properties that vary strongly in time and space. A consequence is that surface-sensitive microwave observations are not assimilated over sea ice areas, and sea ice retrievals use heuristic rather than physical methods. An empirical model for sea ice radiative transfer would be helpful but it cannot be trained using standard machine learning techniques because the inputs are mostly unknown. The solution is to simultaneously train the empirical model and a set of empirical inputs: an “empirical state” method, which draws on both generative machine learning and physical data assimilation methodology. A hybrid physical-empirical network describes the known and unknown physics of sea ice and atmospheric radiative transfer. The network is then trained to fit a year of radiance observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), using the atmospheric profiles, skin temperature and ocean water emissivity taken from a weather forecasting system. This process estimates maps of the daily sea ice concentration while also learning an empirical model for the sea ice emissivity. The model learns to define its own empirical input space along with daily maps of these empirical inputs. These maps represent the otherwise unknown microstructural properties of the sea ice and snow that affect the radiative transfer. This “empirical state” approach could be used to solve many other problems of earth system data assimilation.

Mesoscale eddies modulate the stratification, mixing and dissipation pathways, and tracer transport of oceanic flows over a wide range of spatiotemporal scales. The parameterization of buoyancy and momentum fluxes associated with mesoscale eddies thus presents an evolving challenge for ocean modelers, particularly as modern climate models approach eddy-permitting resolutions. Here we present a parameterization targeting such resolutions through the use of a subgrid mesoscale eddy kinetic energy budget (MEKE) framework. Our study presents two novel insights: (1) both the potential and kinetic energy effects of eddies may be parameterized via a kinetic energy backscatter, with no Gent-McWilliams along-isopycnal transport; (2) a dominant factor in ensuring a physically-accurate backscatter is the vertical structure of the parameterized momentum fluxes. We present simulations of 1/2$^\circ$ and 1/4$^\circ$ resolution idealized models with backscatter applied to the equivalent barotropic mode. Remarkably, the global kinetic and potential energies, isopycnal structure, and vertical energy partitioning show significantly improved agreement with a 1/32$^\circ$ reference solution. Our work provides guidance on how to parameterize mesoscale eddy effects in the challenging eddy-permitting regime.

It is well known that the motion of flexible vegetation leads to drag reduction in comparison to rigid vegetation. In this study, we use a numerical model to investigate how the detailed motion of kelp fronds in response to forcing by surface gravity waves can impact the drag exerted by the kelp on waves. We find that this motion can be characterized in terms of three dimensionless numbers: (1) the ratio of hydrodynamic drag to buoyancy, (2) the ratio of blade length to wave excursion, and (3) the Keulegan-Carpenter number, which measures the ratio of drag to inertial forces. We quantify drag reduction, and find that inertial forces can significantly impact the amplitude of kelp motion and amount of kelp drag reduction. Under certain wave conditions, inertial forces can cause kelp fronds to accelerate more quickly relative to the wave, which can lead to increased drag reduction and reduced wave energy dissipation. In some conditions, frond motion leads to drag augmentation in comparison to rigid fronds. Additionally, we discuss other features of kelp motion, such as the degree of asymmetry, and their relationship with enhanced drag reduction.

In this paper we analyse the material coherence of oceanic eddies sampled by ships during 9 oceanographic campaigns, 8 of which were conducted in the Atlantic Ocean (EUREC4A-OA, M124, MSM60, MSM74, M160, HM2016611, KB2017606, KB2017618) and one in the Indian Ocean (Physindien 2011). After reviewing previous definitions of coherence, we perform a relative error analysis of our data. To identify the eddy cores and assess the material coherence of the well-sampled eddies (19 out of 28 eddies in total), we use criteria based on active tracers (potential vorticity, temperature, salinity). The maximum tracer anomaly is often below the pycnocline (below the frequency stratification maximum). Therefore, some eddies are not considered to be materially coherent using only surface data, whereas they are when we study their three-dimensional structure. Two methods are then presented to extrapolate eddy volumes from a single ship section. The horizontal and vertical resolutions of the data are critical for this determination. Our results show that the outermost closed contour of the Brunt-Vaisala frequency is a good approximation for the materially coherent eddy core to determine the eddy volume.

A document by Ben Cala. Click on the document to view its contents.

Recent field observations suggest that the air-sea momentum flux (or the drag coefficient) is significantly reduced when the dominant wind-forced surface waves are misaligned from local wind. Such conditions may occur under rapidly changing strong winds (such as under tropical cyclones) or in coastal shallow waters where waves are refracted by bottom topography. A recent Large Eddy Simulation (LES) study also shows that the drag coefficient is reduced by a misaligned strongly forced wave train (with a small wave age of 1.37). In order to investigate more realistic field conditions, this study employs LES to examine the effect of a misaligned (up to 90o) surface wave train over a wide range of wave age up to 10.95. For all wave ages examined, the drag coefficient is reduced compared to the flat surface condition when the misalignment angle exceeds around 22.5-45o. The drag reduction may occur even if the form drag of the wave train is positive.

NOAA’s Daily Optimum Interpolation Sea Surface Temperature (DOISST) indicates that globally averaged sea surface temperature (SST) broke record in March 2023 and set new record highs in April, July, and August 2023. This has raised intense media interest and public concern about causes and connections to climate change. Our analysis indicates that the record high SSTs qualified as marine heatwaves (MHWs) and even super-MHWs as defined in this study, and are attributed to three factors: (i) a linear trend, (ii) a shift to the warm phase of the multi-decadal Pacific-Atlantic-Arctic Oscillation (PAO) pattern which is identified in this study, and (iii) the transition from the triple-dip succession of La Niña events to the 2023 El Niño event. One-Sentence Summary The extreme warm SSTs in 2023 resulted from linear warming trends, a pattern of low-frequency oscillation, and the El Niño event.

A document by Shaokun Deng. Click on the document to view its contents.

The Southern Ocean’s eddy response to changing climate remains unclear. This study conducted a wind-forcing channel model, revealing that smaller mesoscale (under ~250 km) eddy kinetic energy (EKE), is suppressed, while larger-scale EKE increases with strengthened winds. A spectral EKE budget suggests that a shift in the scale of the conversion of eddy energy source and eddy-eddy interaction results in the non-monotonic multi-scale response of EKE to stronger winds. Mechanistically, this energetic response can be viewed as stronger zonal mean flow weakening smaller-scale mesoscale eddy and promoting larger-scale waves. This multi-scale EKE response also affects eddy transport and diffusivity. Smaller mesoscale eddy transport weakens in response to weakened smaller mesoscale EKE, while the larger scale transport is strengthened. These changes relate to scale-dependent diffusivity in response to EKE spectrum changes. This multi-scale eddy response to wind may have significant implications for understanding the Southern Ocean eddies under changing climate.

A document by Ramin Familkhalili. Click on the document to view its contents.

Convective rolls contribute largely to the exchange of momentum, sensible heat and moisture in the boundary layer. They have been shown to reinforce air-sea interaction under strong wind conditions. This raises the question of how surface turbulent fluxes can, in turn, affect the rolls. Representing the air-sea exchanges during extreme wind conditions is a major challenge in weather prediction and can lead to large uncertainties in surface wind speed. The sensitivity of rolls to different representations of surface fluxes is investigated using Large Eddy Simulations. The study focuses on the Mediterranean windstorm Adrian, where convective rolls resulting from thermal and dynamical instabilities are responsible for the transport of strong winds to the surface. Considering sea spray in the parameterization of surface fluxes significantly influences roll morphology. Sea spray increases heat fluxes and favors convection. With this more pronounced thermal instability, the rolls are 30\% narrower and extend over a greater height, and the downward transport of momentum is intensified by 40\%, resulting in higher wind speeds at the surface. Convective rolls vanish within a few minutes in the absence of momentum fluxes, which maintain the wind shear necessary for their organization. They also quickly weaken without sensible heat fluxes, which feed the thermal instability required for their development, while latent heat fluxes play minor role. These findings emphasize the necessity of precisely representing the processes occurring at the air-sea interface, as they not only affect the thermodynamic surface conditions but also the vertical transport of momentum within the windstorm.

Ocean ventilation translates atmospheric forcing into the ocean interior. The Southern Ocean is an important ventilation site for heat and carbon and is likely to influence the outcome of anthropogenic climate change. We conduct an extensive backwards-in-time trajectory experiment to identify spatial and temporal patterns of ventilation. Temporally, almost all ventilation occurs between August and November. Spatially, ‘hotspots’ of ventilation account for 60% of open-ocean ventilation on a 30 year timescale; the remaining 40% ventilates in a circumpolar pattern. The densest waters ventilate on the Antarctic shelf, primarily near the Antarctic Peninsula (40%) and the west Ross sea (20%); the remaining 40% is distributed across East Antarctica. Shelf-ventilated waters experience significant densification outside of the mixed layer.