The modelling of coastal Directional Wave Spectra (DWSs) often requires downscaling techniques integrating DWSs from open ocean boundaries. Dynamic downscaling methods reliant on numerical wave models are often computationally expensive. In coastal areas, wave dynamics are strongly influenced by the topography, implying that once the DWSs at the open ocean boundary are known, the DWSs at various locations along the coast are almost determined. This property can be utilized for statistical downscaling of coastal DWSs. This study presents a deep learning approach that can compute coastal DWSs from open ocean DWSs. The performance of the proposed downscaling model was evaluated using both numerical wave model data and buoy data in the Southern California Bight. The results show that the deep learning approach can effectively and efficiently downscale coastal DWSs without relying on any predefined spectral shapes, thereby holding promise for coastal wave climate studies.

Salt marshes are valuable ecosystems that provide numerous services and act as natural coastal defences by buffering storm waves and stabilising sediments. However, it is not clear whether they will be able to retain their resilience with accelerating rate in sea-level rise, possible increases in storm intensity and increasing land reclamation. The current paradigm is that a positive sediment budget supports the survival and accretion of salt marshes while a negative sediment budget causes marsh degradation. Here we present the results of a series of studies that used an integration of modelling and paleoenvironmental analysis and a sediment budget approach to investigate the resilience of estuaries and salt marshes to projected rise in sea-level, possible increases in storm activity and existing anthropogenic disturbance. The studies were conducted using the Ribble Estuary-NorthWest England-as a test case, the hydrodynamic model Delft3D to simulate the estuary morpho-dynamics under selected scenarios, and optically stimulated luminescence (OSL), geochemistry and particle size distribution analysis to reconstruct the past evolution and adaptation of the estuary morphology. Results showed that sea-level rise threatens estuary and marsh stability by promoting ebb dominance and triggering a net export of sediment. Conversely, storm surges aid the resilience of the system by promoting flood dominance and triggering a net import of sediment and have the potential to counteract the negative impact of sea-level rise by masking its effects on the sediment budget. The addition of embankments, on the other hand, can further promote ebb dominance in the system and intensify sediment export, further threatening marsh stability.References Leonardi, N., Ganju, N.K. and Fagherazzi, S. (2016). A linear relationship between wave power and erosion determines salt-marsh resilience to violent storms and hurricanes. Proceedings of the National Academy of  Sciences 113(1), 64-68. Ganju, N.K., Kirwan, M.L., Dickhudt, P.J., Guntenspergen, G.R., Cahoon, D.R. and Kroeger, K.D. (2015). Sediment transport-based metrics of wetland stability. Geophysical Research Letters, 42(19), 7992-8000.

This study uses large eddy simulations to investigate nutrient transport and uptake in suspended macroalgal farms. Various farm configurations and oceanic forcing conditions are examined, with the farm base located near the nutricline depth. We introduce the Damkohler number Da to quantify the balance between nutrient consumption by macroalgae uptake and supply by farm-enhanced nutrient transport. Most cases exhibit Da<1, indicating that farm-generated turbulence sufficiently contributes to upward nutrient fluxes, supporting macroalgae growth. High Da and starvation may occur in fully grown farm blocks, a configuration that generates weakest turbulence, particularly when combined with densely planted macroalgae or under weak flow conditions. Flow stagnation within the farm due to macroalgae drag may constrain the uptake efficiency and further increase the starvation risk. Mitigation strategies involve timely harvesting, avoiding dense macroalgae canopies, and selecting farm locations with robust ocean currents and waves. This study provides insights for sustainable macroalgal farm planning.

Volcanic meteo-tsunamis, though rare, can pose significant threats to people, as exemplified by the 2022 Hunga Tonga – Hunga Ha’apai (HT-HH) eruption in the SW Pacific. While various studies have delved into the complexities of such phenomena, none have explored analogous scenarios in regions with potential occurrence of large eruptions near or under the sea. We focus on coastal areas along the South China Sea (SCS), among the most densely populated on Earth and historically prone to volcanic activity, including the catastrophic 1883 Krakatau eruption. Here we strategically chose one intra-basin volcano, KW-23612 in the northern SCS, and three extra-basin volcanoes, Banua Wuhu in the Celebes Sea, and Kikai and Fukutoku-Oka-no-Ba in the northern Philippines Sea (southern Japan), from which we simulated volcanic meteo-tsunamis with scaled intensities of the HT-HH event, to assess which countries around the SCS could be more at risk from the occurrence of such phenomena. Our results show that the worst-case scenarios are produced by eruption/tsunamis from the northern SCS, producing offshore waves up to 10 cm offshore Macau and Hong Kong, and up to 20 cm offshore Manila. In contrast, countries bordering the shallow Sunda Shelf (Malaysia, Thailand, Cambodia, and southern Vietnam) seem less at risk from volcanic meteo-tsunamis, though we observed some amplification effects along the deeper Singapore Strait. This study is the first of its kind in the region and sets the basis to investigate amplification effects, and shallow coastal dynamics at key locations, after integrating higher resolution bathymetry data.

The Borderland Basins off Southern California are semi-isolated sea-floor depressions with connections to each other and to the open Pacific Ocean over narrow sills. A high-resolution, multi-year simulation is analyzed for its currents, stratification, and dissolved oxygen, with a focus on the mean conditions, intrinsic variability, and exchange rates with surrounding waters. The three shallowest, closest basins are given the most attention: Santa Barbara, Santa Monica, and San Pedro. From a combination of multiple means of estimation, the deep basin water mass renewal times are on the order of a year or more, and this time is somewhat shorter in the Santa Barbara Basin than the others.

A document by Shreyaa Sanjay. Click on the document to view its contents.

The Southern Ocean is central to the global overturning circulation. South of the Antarctic Polar Front, Antarctic Winter Water (WW) forms in the wintertime mixed layer below sea ice and becomes a subsurface layer following summertime restratification of the mixed layer, overlaying upwelled deep waters. Model simulations show that WW acts as a conduit to seasonally transform upwelled deep waters into intermediate waters. Yet, there remains little observational evidence of the distribution and seasonal characteristics of WW. Using 18 years of in situ observations, we show seasonal climatologies of WW thickness, depth, core temperature and salinity. This study reveals, for the first time, the distinct regionality and seasonality of WW. The seasonal cycle of WW characteristics is tied to the annual sea ice evolution, whilst the spatial distribution is impacted by the main topographic features in the Southern Ocean driving an equatorward flux of WW. Through the identification of these localized northward export regions of WW, this study provides further evidence suggesting an alternative view from the conventional ‘zonal mean’ perspective of the overturning circulation. We show that specific overturning pathways connecting the subpolar ocean to the global ocean can be explained by ocean-topography interactions.

Regional patterns of sea level rise are affected by a range of factors including glacial melting, which has occurred in recent decades and is projected to increase in the future, perhaps dramatically. Previous modeling studies have typically included fluxes from melting glacial ice only as a surface forcing of the ocean or as an offline addition to the sea surface height fields produced by climate models. However, observational estimates suggest that the majority of the meltwater from the Antarctic Ice Sheet actually enters the ocean at depth through ice shelf basal melt. Here we use simulations with an ocean general circulation model in an idealized configuration. The results show that the simulated global sea level rise pattern is sensitive to the depth at which Antarctic meltwater enters the ocean. Further analysis suggests that the response is dictated primarily by the steric response to the depth of the meltwater flux.

The gravitational settling of organic particles from the surface to the deep ocean is an important export pathway and one of the largest components of the marine biological carbon pump (BCP). The strength and efficiency of the gravitational pump is often measured using metrics reliant on reference depths and empirical formulations that parameterize the relationship between depth and flux or concentration. Here, BGC-Argo profiles were used to identify the isolume where POC concentration starts to decline, revealing attenuation trends below this isolume that are remarkably consistent across the global ocean. We developed a semi-mechanistic approach that uses observations from the first optical depth to predict POC concentration from the surface ocean to the base of the mesopelagic (1000 m), allowing assessments of spatial and temporal variability in BCP efficiencies. We find that rates of POC attenuation are high in areas of high biomass and low in areas of low biomass, supporting the view that bloom events sometimes result in a relatively weak deep biological pump characterized by low transfer efficiency to the base of the mesopelagic. Our isolume-based attenuation model was applied to satellite data to yield the first remote sensing-based estimate of integrated global POC stock of 3.02 Pg C for the upper 1000 m, with 1.27 Pg C of this global carbon stock located above the reference isolume where POC begins to attenuate.

This study characterized ocean biological carbon pump metrics in the second iteration of the REgional Carbon Cycle Assessment and Processes (RECCAP2) project, a coordinated, international effort to constrain contemporary ocean carbon air-sea fluxes and interior carbon storage trends using a combination of observation-based estimates, inverse models, and global ocean biogeochemical models. The analysis here focused on comparisons of global and biome-scale regional patterns in particulate organic carbon production and sinking flux from the RECCAP2 model ensemble against observational products derived from satellite remote sensing, sediment traps, and geochemical methods. There was generally encouraging model-data agreement in large-scale spatial patterns, though with substantial spread across the model ensemble and observational products. The global-integrated, model ensemble-mean export production, taken as the sinking particulate organic carbon flux at 100 m (6.41 ± 1.52 Pg C yr–1), and export ratio defined as sinking flux divided by net primary production (0.154 ± 0.026) both fell at the lower end of observational estimates. Comparison with observational constraints also suggested that the model ensemble may have underestimated regional biological CO2 drawdown and air-sea CO2 flux in high productivity regions. Reasonable model-data agreement was found for global-integrated, ensemble-mean sinking particulate organic carbon flux into the deep ocean at 1000 m (0.95 ± 0.64 Pg C yr–1) and the transfer efficiency defined as flux at 1000m divided by flux at 100m (0.121 ± 0.035), with both variables exhibiting considerable regional variability. Future modeling studies are needed to improve system-level simulation of interaction between model ocean physics and biogeochemical response.

A document by Pierre St-Laurent. Click on the document to view its contents.

In this paper we analyze the effect of material coherence on the transport properties of 9 eddies sampled during research cruises. We check the accuracy of our data and, after reviewing different definitions of coherence, we assess whether these eddies have retained a heterogeneous water mass in their cores. T, S anomalies on isopycnal surfaces are computed to highlight the different thermohaline properties between the eddy core and its surroundings. The maximum of the tracer anomaly is often located below the pycnocline. We find that while some of these eddies are not coherent according to surface data only, they are when their entire 3D structure is considered. We then present two methods for extrapolating eddy volumes from a single hydrographic section. The volume obtained from T,S anomalies on isopycnical surfaces is compared with that obtained by other criteria. Our results show that the outermost closed contour of the Brunt-Väisäla frequency is a good approximation for the eddy boundary when calculating its volume.

In this work, the impacts of spurious numerical salinity mixing ($\mathcal{M}_{num}$) on the larger-scale flow and tracer fields are characterized using idealized simulations. The idealized model is motivated by realistic simulations of the Texas-Louisiana shelf and features oscillatory near-inertial wind forcing. $\mathcal{M}_{num}$ can exceed the physical mixing from the turbulence closure ($\mathcal{M}_{phy}$) in frontal zones and within the mixed layer. This suggests simulated mixing processes in frontal zones may be driven largely by $\mathcal{M}_{num}$. Near-inertial alongshore wind stress amplitude is varied to identify a base case that maximizes the ratio of $\mathcal{M}_{num}$ to $\mathcal{M}_{phy}$. We then we test the sensitivity of the base case with three tracer advection schemes (MPDATA, U3HC4, and HSIMT) and conduct ensemble runs with perturbed bathymetry. Instability growth is evaluated with several analysis methods: volume-integrated eddy kinetic energy ($EKE$) and available potential energy ($APE$), surface and bottom isohaline variability, and alongshore-averaged salinity sections. While all schemes have similar total mixing, HSIMT simulations have over double the volume-integrated $\mathcal{M}_{num}$ and 20\% less $\mathcal{M}_{phy}$ relative to other schemes, which suppresses the release of $APE$ and reduces the $EKE$ by roughly 25\%. HSIMT instabilities are confined shoreward relative to the other schemes. This results in reduced isohaline variability and steeper isopycnals, evidence that enhanced numerical mixing suppresses instability growth.

Marine mesozooplankton play an important role for marine ecosystem functioning and global biogeochemical cycles. Their size structure, varying spatially and temporally, heavily impacts biogeochemical processes and ecosystem services. Mesozooplankton exhibit size changes throughout their life cycle, affecting metabolic rates and functional traits. Despite this variability, many models oversimplify mesozooplankton as a single, unchanging size class, potentially biasing carbon flux estimates. Here, we include mesozooplankton ontogenetic growth and reproduction into a 3-dimensional global ocean biogeochemical model, PISCES-MOG, and investigate the subsequent effects on simulated mesozooplankton phenology, plankton distribution, and organic carbon export. Utilizing an ensemble of statistical predictive models calibrated with a global set of observations, we generated monthly climatologies of mesozooplankton biomass to evaluate the simulations of PISCES-MOG. Our analyses reveal that the model and observation-based biomass distributions are comparable (r$_{pearson}$=0.40, total epipelagic biomass: 137TgC from observations vs. 232TgC in the model), with similar seasonality (r$_{pearson}$=0.25 for the months of maximal biomass). Including ontogenetic growth in the model induced cohort dynamics and variable seasonal dynamics across mesozooplankton size classes and altered the relative contribution of carbon cycling pathways. Younger and smaller mesozooplankton transitioned to microzooplankton in PISCES-MOG, resulting in a change in particle size distribution, characterized by a decrease in large particulate organic carbon (POC) and an increase in small POC generation. Consequently, carbon export from the surface was reduced by 10\%. This study underscores the importance of accounting for ontogenetic growth and reproduction in models, highlighting the interconnectedness between mesozooplankton size, phenology, and their effects on marine carbon cycling.

The CNRM-Cerfacs Climate Prediction System (C3PS) is a new research modeling tool for performing climate reanalyses and seasonal-to-multiannual predictions for a wide array of earth system variables. C3PS is based on the CNRM-ESM2-1 model including interactive aerosols and stratospheric chemistry schemes as well as terrestrial and marine biogeochemistry enabling a comprehensive representation of the global carbon cycle. C3PS operates through a seamless coupled initialization for the atmosphere, land, ocean, sea ice and biogeochemistry components that allows a continuum of predictions across seasonal to interannual time-scales. C3PS has also contributed to the Decadal Climate Prediction Project (DCPP-A) as part of the sixth Coupled Model Intercomparison Project (CMIP6). Here we describe the main characteristics of this novel earth system-based prediction platform, including the methodological steps for obtaining initial states to produce forecasts. We evaluate the entire C3PS initialisation procedure with the most up-to-date observations and reanalysis over 1960-2021, and we discuss the overall performance of the system in the light of the lessons learnt from previous and actual prediction platforms. Regarding the forecast skill, C3PS exhibits comparable seasonal predictive skill to other systems. At the decadal scale, C3PS shows significant predictive skill in surface temperature during the first two years after initialisation in several regions of the world. C3PS also exhibits potential predictive skill in net primary production and carbon fluxes several years in advance. This expands the possibility of applications of forecasting systems, such as the possibility of performing multi-annual predictions of marine ecosystems and carbon cycle.

This study introduces an ocean-based carbon dioxide removal (CDR) approach: Nearshore Macroalgae Aquaculture for Carbon Sequestration (N-MACS). By cultivating macroalgae in nearshore ocean surface areas, N-MACS aims to sequester CO2 with subsequent carbon storage. Utilizing an Earth System Model with intermediate complexity (EMIC), we explore the CDR potential of N-MACS alongside its impacts on the global carbon cycle, marine biogeochemistry and marine ecosystems. Our investigations unveil that coastal N-MACS could potentially sequester 0.7 to 1.1 GtC yr-1. However, it also significantly suppresses marine phytoplankton net primary productivity because of nutrient removal and canopy shading, counteracting approximately 30% of the N-MACS CDR capacity. This suppression of surface NPP, in turn, reduces carbon export out of the euphotic zone to the ocean interior, leading to elevated dissolved oxygen levels and diminished denitrification in present-day oxygen minimum zones. Effects due to harvesting-induced phosphorus removal continue for centuries even beyond the cessation of N-MACS.

Distributed Acoustic Sensing (DAS) is a photonics technology converting seafloor telecommunications and optical fiber cables into dense arrays of strain sensors, allowing to monitor various oceanic physical processes. Yet, several applications are hindered by the limited knowledge of the transfer function between geophysical variables and DAS measurements. This study investigates the quantitative relationship between surface gravity DAS-recorded wave-generated strain signals along the seafloor and the pressure at a colocated sensor. A remarkable linear correlation is found over various sea conditions allowing to reliably determine significant wave heights from DAS data. Utilizing linear wave potential theory, we derive an analytical transfer function linking cable deformation and wave kinematic parameters. This transfer function provides a first quantification of the effects related to waves and fiber responses. Our results validate DAS’s potential for real-time reconstruction of the surface gravity wave spectrum over extended coastal areas. It also enables the estimation of waves hydraulic parameters at depth without the need of offshore deployments.

Freshwater input from Greenland ice sheet melt has been increasing in the past decades from warming temperatures. To identify the impacts from enhanced meltwater input into the subpolar North Atlantic from 1997–2021, we use output from two nearly identical simulations in the eddy-rich model VIKING20X (1/20°) only differing in the freshwater input from Greenland: one with realistic interannually varying runoff increasing in the early 2000s and the other with climatologically (1961–2000) continued runoff. The majority of the additional freshwater remains within the boundary current enhancing the density gradient towards the warm and salty interior waters yielding increased current velocities. The accelerated boundary current shows a tendency towards eddy shedding into the Labrador Sea interior. Further, the experiments allow to attribute higher stratification and shallower mixed layers southwest of Greenland and deeper mixed layers in the Irminger Sea, particularly in 2015–2018, to the runoff increase in the early 2000s.

The Indian summer monsoon precipitation trend from 1979 to 2022 shows a substantial 40% increase over Northwest India, which is in agreement with the future projections of the Coupled Model Intercomparison Project 6 (CMIP6). The observationally constrained reanalysis dataset reveals that a prominent sea surface warming in the western equatorial Indian Ocean and the Arabian Sea might be responsible for the rainfall enhancement through strengthening the cross-equatorial monsoonal flow and associated evaporation. We show that the cross-equatorial monsoon winds over the Indian Ocean are strengthening due to the merging of Pacific Ocean trade winds and rapid Indian Ocean warming. These winds also enhance the latent heat flux (evaporation), and in combination, this results in increased moisture transport from the ocean toward the land.

We revisit the nature of the ocean bottom pressure (OBP) seasonal cycle by leveraging the mounting GRACE-based OBP record and its assimilation in the ocean state estimates produced by the project for Estimating the Circulation and Climate of the Ocean (ECCO). We focus on the mean seasonal cycle from both data and ECCO estimates, examining their similarities and differences and exploring the underlying causes. Despite substantial year-to-year variability, the 21-year period studied (2002–2022) provides a relatively robust estimate of the mean seasonal cycle. Results indicate that the OBP annual harmonic tends to dominate but the semi-annual harmonic can also be important (e.g., subpolar North Pacific, Bellingshausen Basin). Amplitudes and short-scale phase variability are enhanced near coasts and continental shelves, emphasizing the importance of bottom topography in shaping the seasonal cycle in OBP. Comparisons of GRACE and ECCO estimates indicate good qualitative agreement, but considerable quantitative differences remain in many areas. The GRACE amplitudes tend to be higher than those of ECCO typically by 10%–50%, and by more than 50% in extensive regions, particularly around continental boundaries. Phase differences of more than 1 (0.5) months for the annual (semiannual) harmonics are also apparent. Larger differences near coastal regions can be related to enhanced GRACE data uncertainties and also to the absence of gravitational attraction and loading effects in ECCO. Improvements in both data and model-based estimates are still needed to narrow present uncertainties in OBP estimates.

The High Seas, lying beyond the boundaries of nations’ Exclusive Economic Zones, cover the majority of the ocean surface and host roughly two thirds of marine primary production. Yet, only a small fraction of global wild fish catch comes from the High Seas, despite intensifying industrial fishing efforts. The surprisingly small fish catch could reflect economic features of the High Seas - such as the difficulty and cost of fishing in remote parts of the ocean surface - or ecological features resulting in a small biomass of fish relative to primary production. We use the coupled biological-economic model BOATS to estimate contributing factors, comparing observed catches with simulations where: (i) fishing cost depends on distance from shore and seafloor depth; (ii) catchability depends on seafloor depth or vertical habitat extent; (iii) regions with micronutrient limitation have reduced biomass production; (iv) the trophic transfer of energy from primary production to demersal food webs depends on depth; and (v) High Seas biomass migrates to coastal regions. Our results suggest that the most important features are ecological: demersal fish communities receive a large proportion of primary production in shallow waters, but very little in deep waters due to respiration by small organisms throughout the water column. Other factors play a secondary role, with migrations having a potentially large but uncertain role, and economic factors having the smallest effects. Our results stress the importance of properly representing the High Seas biomass in future fisheries projections, and clarify their limited role in global food provision.

As a marine Carbon Dioxide Removal (mCDR) approach, Ocean Alkalinity Enhancement (OAE) is emerging as a viable method for removing anthropogenic CO2 emissions from the atmosphere to mitigate climate change. To achieve substantial carbon reduction using this method, OAE would need to be widespread and scaled-up across the global ocean. However, the efficiency of OAE varies substantially across a range of space-time scales and as such field deployments must be carefully planned to maximize efficiency and minimize logistical costs and risks. Here we develop a mCDR efficiency framework based on the data-assimilative ECCO-Darwin ocean biogeochemistry model, which examines two key factors over seasonal to multi-decadal timescales: 1) mCDR potential, which quantifies the CO2 solubility of the upper ocean; and 2) dynamical mCDR efficiency, representing the full-depth impact of ocean advection, mixing, and air-sea CO2 exchange. To isolate and quantify the factors that determine dynamical efficiency, we develop a reduced complexity 1-D model, rapid-mCDR, as a computationally-efficient tool for evaluation of mCDR efficiency. Combining the rapid-mCDR model with ECCO-Darwin allows for rapid characterization of OAE efficiency at any location globally. This research contributes to our understanding and optimization of OAE deployments (i.e., deploying experiments in the real-world ocean) as an effective mCDR strategy and elucidates the regional differences and mechanistic processes that impact mCDR efficiency. The modeling tools developed in this study can be readily employed by research teams and industry to plan and complement future field deployments and provide essential Monitoring, Reporting, and Verification (MRV).

The balance between particulate inorganic carbon (PIC) and particulate organic carbon (POC) holds significant importance in carbon storage within the ocean. A recent investigation delved into the spatial distribution of phytoplankton and the physiological mechanisms governing their growth. Employing random forests, a machine learning technique, this study unveiled apparent relationships between POC and 10 environmental fields. In this work, we extend the use of random forests to compare how observed PIC and POC respond to environmental conditions. Our findings indicate that while both exhibit similar responses to certain environmental drivers, PIC is less sensitive to iron and more sensitive to light. Intriguingly, both PIC and POC display reduced sensitivity to CO2, contrary to previous studies, possibly due to the elevated pCO2 in our dataset. This research sheds light on the underlying processes influencing carbon sequestration and ocean productivity.

Autumn productivity is key to the large marine ecosystems of the Agulhas Bank, which support numerous economically important regional fisheries. Despite such importance, data is sparce on plankton composition in terms of primary or secondary producers, or on trophic transfer. While investigating autumn plankton composition we found that nanophytoplankton (2-20 µm) dominated carbon stocks, with lower contributions from picophytoplankton (<2 µm) and microphytoplankton (>20 µm). While picoplankton biomass exhibited a relationship with warm nutrient poor waters, nanoplankton showed no clear relationship to environmental parameters. The dominance of nanophytoplankton biomass on the Agulhas Bank highlights a critical role for micro-zooplankton grazing as a trophic transfer between these small plankton, meso-zooplankton and the higher trophic levels that make the bank so important for regional fisheries. Outside of localized coastal upwelling on the Agulhas Bank, this study highlights a significant role for nanoplankton and micro-zooplankton in supporting the bank’s large marine ecosystems.