Abstract Air‐sea gas exchange regulates the exchange of climatically important gases between the ocean and the atmosphere, shaping both climate and ocean biogeochemistry. Bubbles beneath the sea surface enhance this exchange by introducing an additional transfer pathway in parallel to the interfacial transfer route. Although the role of bubbles in gas flux has been debated since the 1980s, recent advances in laboratory experiments, field observations, and modeling have provided new insights. Bubble‐mediated gas transfer differs from interfacial transfer in three key ways: (a) it shows strong nonlinearity with wind speed due to its link with wave breaking; (b) it depends on gas solubility because of the finite volume and short lifetime of bubbles; and (c) it shifts the equilibrium toward slight oversaturation through the overpressure of submerged bubbles. These characteristics make bubble‐mediated gas transfer complicated to quantify, and existing observations and models indicate a wide range of bubble contributions to air‐sea carbon dioxide and oxygen exchange. Three critical knowledge gaps are identified: (a) limited understanding of near‐surface (0–1 m) bubble dynamics, including volume flux, size distribution, and evolution, which directly control the solubility and diffusivity dependence of bubble‐mediated gas exchange; (b) the absence of consistent field constraints spanning the full range of gas solubilities; and (c) the lack of knowledge to scale laboratory results to oceanic conditions. Addressing these gaps will require integrated efforts combining near‐surface bubble measurements and simulations, field observations of gas transfer across diverse solubilities using complementary techniques, and improved modeling frameworks.

The Surface Ocean CO2 Atlas (SOCAT) is a global scientific community effort to collate and provide additional quality control and standardisation for surface ocean carbon dioxide (CO2) data. Each year the international marine carbon community submit any new measurements collected on research vessels, ships of opportunity, moorings, uncrewed surface vehicles and sailing yachts for inclusion in the annual update of the SOCAT database. The data synthesis effort, which published its first data product in 2011, includes a variety of systems, sampling strategies, maintenance cycles and instrument calibrations. Each in-water CO2 gas measurement is paired, and linked, with a sea surface temperature (SST) measurement. However, the differences in measurement systems means that data pairs from different platforms are representative of differing depths in the ocean, whilst SST measurements can suffer from warming within the observation platform. These complexities can limit the accuracy and precision of any atmosphere-ocean CO2 assessments that use the SOCAT products. Here the SOCATv2025 database with an estimated uncertainty in the fugacity of CO2 in seawater (fCO2 (sw)) of less than 5 µatm is recalculated to a reference temperature at a consistent depth of 0.2 m using the European Space Agency (ESA) Climate Change Initiative (CCI) SST climate data record. This recalculation process of the fCO2 values does not assume isochemical conditions and so temperature driven carbonate speciation is captured. The data pairing is maintained so the resulting dataset is well suited for the analysis of atmosphere-ocean CO2 exchange. The synthesis cruise data and gridded data products, that include both the original and recalculated data, are provided and consistency with the original SOCAT data products and format is confirmed. The importance of robustly accounting for the observed warm bias is demonstrated as removing this signal by recalculation to a climate data record temperature shows a ~0.4 Pg C yr-1 (~12%) increase in the 2024 ocean CO2 sink (3.4 Pg C yr-1). These recalculated data products are needed for annual carbon assessments therefore these will be routinely provided each year following each annual SOCAT dataset release.

Sea-air carbon dioxide (CO2) flux is typically estimated from the product of the gas transfer velocity (K) and the CO2 fugacity difference between the ocean surface and atmosphere. Total gas exchange comprises interfacial transfer across the unbroken surface and bubble-mediated transfer from wave breaking. While interfacial transfer is symmetric for invasion and evasion, bubble-mediated transfer theoretically favours invasion due to hydrostatic pressure, though field evidence has been lacking. Here we provide direct field evidence of this asymmetry and develop an asymmetric flux equation. Applying the asymmetric equation reduces bias in K, and increases global oceanic CO2 uptake by 0.3-0.4 Pg C yr-1 (~15% on average from 1991 to 2020) relative to conventional estimates. Further evasion data are needed to better quantify the asymmetry factor. Our study suggests that the ocean may have absorbed more CO2 than previously thought, and the asymmetric equation should be used for future CO2 flux assessments.

North Sea human-made, offshore structures (e.g. oil/gas platforms, offshore wind farms) provide a hard substrate habitat for benthic marine species which can spread between sites during their larval stage. Here, we aim to address how the installation of additional human-made structures, like new wind farms, or decommissioning of existing ones, like oil and gas platforms at the end of service, contribute to changes in larval connectivity. We use particle tracking model simulations to assess the ecological connectivity of benthic species in the northern North Sea during two contrasting years to highlight seasonal to annual variability. The methodology of releasing an extensive set of particles over a wide area produces our Retrospective Particle Tracks dataset. The sets of simulations can be interrogated to understand if additional human-made structures placed in any locations in the northern North Sea could potentially affect the ecological connectivity. Network metrics were used to identify connectivity between sites. Clustering of existing structures identifies a region that acts as an interchange between other structures which may otherwise only be connected during intermittent periods. The addition of new human-made structures located in areas with stronger residual current flow would enhance the connectivity.

Full-scale tidal turbines deployed in tidal channels are subjected to complex flow due to the effects of local bathymetry and coastline shape which modify the flow directionality, shear, twist and speed of the underlying tidally forced flow. In response to these effects, the wake of an operational tidal turbine will vary spatially and temporally. In order to predict wake form, which is a key step for scaling up tidal energy as developments move from single devices to arrays, we have developed and demonstrated an open source turbine-embedded regional three-dimensional (3D) hydrodynamic model for power and wake prediction. Simulation outputs have been validated against in-situ measurements acquired via ADCPs positioned downstream of and adjacent to the rotor-plane of an operating tidal turbine. Model predictive performance is parameterised by the relative difference between modelled and measured power-weighted rotor averaged velocity using speed binning and temporal-averaging. In the absence of the turbine representation, the difference between model and measurement for ebb and flood was found to be 0.81% and 1.04% respectively at the flow speed of 2.5 m/s. With the turbine represented as an actuator disc in the model, the averaged error of the velocity profiles in the wake is 4.4% and 5.2% at ADCP locations that are 3.7D and 6.2D downstream of the rotor plane during ebb. The model has been designed for use on moderately-priced workstations and the promising results, in terms of capturing key 3D flow features and predictions of wake velocity deficits, is a starting point for further development and may provide baseline data for alternative (e.g., higher fidelity, slower performance, or lower fidelity including 2D models with much faster performance).

The ocean annually absorbs about a quarter of all anthropogenic carbon dioxide (CO2) emissions. Global estimates of air-sea CO2 fluxes are typically based on bulk measurements of CO2 in air and seawater and neglect the effects of vertical temperature gradients near the ocean surface. Theoretical and laboratory observations indicate that these gradients alter air-sea CO2 fluxes, because the air-sea CO2 concentration difference is highly temperature sensitive. However, in situ field evidence supporting their effect is so far lacking. Here we present independent direct air-sea CO2 fluxes alongside indirect bulk fluxes collected along repeat transects in the Atlantic Ocean (50° N to 50° S) in 2018 and 2019. We find that accounting for vertical temperature gradients reduces the difference between direct and indirect fluxes from 0.19 mmol m-2 d-1 to 0.08 mmol m-2 d-1 (N = 148). This implies an increase in the Atlantic CO2 sink of ~0.03 PgC yr-1 (~7% of the Atlantic Ocean sink). These field results validate theoretical, modelling and observational-based efforts, all of which predicted that accounting for near-surface temperature gradients would increase estimates of global ocean CO2 uptake. Accounting for this increased ocean uptake will probably require some revision to how global carbon budgets are quantified.

The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.

Climate change and plastic pollution are two of the most pressing environmental challenges caused by human activity, and they are directly and indirectly linked. We focus on the relationship between marine plastic litter and the air-sea flux of greenhouse gases (GHGs). Marine plastic litter has the potential to both enhance and reduce oceanic GHG fluxes, but this depends on many factors that are not well understood. Different kinds of plastic behave quite differently in the sea, affecting air-sea gas exchange in different, largely unknown, ways. The mechanisms of air-sea exchange of GHGs have been extensively studied and if air-sea gas transfer coefficients and concentrations of the gas in water and air are known, calculating the resulting GHG fluxes is reasonably straightforward. However, relatively little is known about the consequences of marine plastic litter for gas transfer coefficients, concentrations, and fluxes. Here we evaluate the most important aspects controlling the exchange of GHGs between the sea and the atmosphere and how marine plastic litter could change these. The aim is to move towards improving air-sea GHG flux calculations in the presence of plastic litter and we have largely limited ourselves to identifying processes, rather than estimating relative importance.

Several numerical methods such as CFD and BEMT have been used to study the influence of tidal turbines on the flow. The validity of the models, which are developed based on those methods, has been mostly assessed against lab-based experiments or smallscale deployments. This paper presents a novel numerical tool capable of simulating the effects of a full-scale turbine within TELEMAC-3D hydrodynamic models. It represents the turbine by modelling the thrust force exerted by the turbine on the flow as a stress distributed over the cross-sectional area of the turbine rotor. The performance of the developed tool has been assessed and validated against in-situ measurements downstream a full-scale turbine, which was deployed at the European Marine Energy Centre (EMEC) at the Fall of Warness in Orkney, as part of the Reliable Data Acquisition Platform for Tidal (ReDAPT) project. The validation results show that the tool succeeds in reproducing the turbine’s far-wake with less than 20% error margin, which can be utilised to provide valuable insight into the likely interaction between the individual turbines within an array of multiple devices. Additionally, the tool demonstrates the capability to accurately predict the turbine’s power output.

Islands energy systems are often separated from mainland energy markets. Islands routinely rely on a single imported source of energy, which exposes islands to economic risks, and an increased likelihood of system failure. Integrating renewable energy into island energy systems can provide diversity of energy supply and improved system efficiency, potentially yielding cheaper energy for island communities. However, this requires an appropriate energy extraction strategy in combination with sufficient storage to overcome the intermittent nature of the renewable energy resources. This paper investigates the most cost-effective method to integrate tidal energy into the Orkney energy system. It explores various approaches to achieving efficient energy extraction. Different energy generation patterns are examined to find the generation strategy that best fits the energy demand pattern of the isles, without conflicting with the existing supply. This study demonstrates the potential of integrating tidal energy into an island energy system without the need for expensive grid upgrades. It shows that limiting the capacity of the tidal device, and maximising the generation time at the most frequent flow velocities, increases the capacity factor of the installed system. This strategy improves the economic viability and commercial competitiveness of tidal energy.

We have recently shown the neglect of small temperature differences in the ocean mixed layer has led to substantial underestimates in the ocean sink for atmospheric CO2 as calculated from surface pCO2 observations, which we find should be increased by ~0.8 Pg Cyr-1 when globally integrated. Surface observations of ocean pCO2 such as those in the SOCAT (Surface Ocean CO2 Atlas, www.socat.info) are reported at a temperature typically measured at several metres depth, but co-location of satellite estimates of the subskin surface temperature (at a few centimetres depth) differ from this, and are on average lower. In addition the top millimetre or so of the ocean is cooler than the underlying subskin because the ocean is a source of radiative and latent heat to the atmosphere. These two temperature deviations have subtly different effects on the air-sea flux of CO2 as calculated by the gas exchange equation, but both result in an increase in the flux into the ocean and the combined effect is large. We are making available several datasets enabling calculation of these effects, including the regular provision of SOCAT data corrected to the subskin temperature, a climatology of the skin temperature deviation, and corrected ocean-atmosphere CO2 flux estimates for the period since 1985.

The ocean is a sink for ~25% of the atmospheric CO 2 emitted by human activities, an amount in excess of 2 petagrams of carbon per year (PgC yr −1 ). Time-resolved estimates of global ocean-atmosphere CO 2 flux provide an important constraint on the global carbon budget. However, previous estimates of this flux, derived from surface ocean CO 2 concentrations, have not corrected the data for temperature gradients between the surface and sampling at a few meters depth, or for the effect of the cool ocean surface skin. Here we calculate a time history of ocean-atmosphere CO 2 fluxes from 1992 to 2018, corrected for these effects. These increase the calculated net flux into the oceans by 0.8–0.9 PgC yr −1 , at times doubling uncorrected values. We estimate uncertainties using multiple interpolation methods, finding convergent results for fluxes globally after 2000, or over the Northern Hemisphere throughout the period. Our corrections reconcile surface uptake with independent estimates of the increase in ocean CO 2 inventory, and suggest most ocean models underestimate uptake.

The flow (flux) of climate-critical gases, such as carbon dioxide (CO2), between the ocean and the atmosphere is a fundamental component of our climate and an important driver of the biogeochemical systems within the oceans. Therefore, the accurate calculation of these air–sea gas fluxes is critical if we are to monitor the oceans and assess the impact that these gases are having on Earth's climate and ecosystems. FluxEngine is an open-source software toolbox that allows users to easily perform calculations of air–sea gas fluxes from model, in situ, and Earth observation data. The original development and verification of the toolbox was described in a previous publication. The toolbox has now been considerably updated to allow for its use as a Python library, to enable simplified installation, to ensure verification of its installation, to enable the handling of multiple sparingly soluble gases, and to enable the greatly expanded functionality for supporting in situ dataset analyses. This new functionality for supporting in situ analyses includes user-defined grids, time periods and projections, the ability to reanalyse in situ CO2 data to a common temperature dataset, and the ability to easily calculate gas fluxes using in situ data from drifting buoys, fixed moorings, and research cruises. Here we describe these new capabilities and demonstrate their application through illustrative case studies. The first case study demonstrates the workflow for accurately calculating CO2 fluxes using in situ data from four research cruises from the Surface Ocean CO2 ATlas (SOCAT) database. The second case study calculates air–sea CO2 fluxes using in situ data from a fixed monitoring station in the Baltic Sea. The third case study focuses on nitrous oxide (N2O) and, through a user-defined gas transfer parameterisation, identifies that biological surfactants in the North Atlantic could suppress individual N2O sea–air gas fluxes by up to 13 %. The fourth and final case study illustrates how a dissipation-based gas transfer parameterisation can be implemented and used. The updated version of the toolbox (version 3) and all documentation is now freely available.

The ability to routinely quantify global carbon dioxide (CO2) absorption by the oceans has become crucial: it provides a powerful constraint for establishing global and regional carbon (C) budgets, and enables identification of the ecological impacts and risks of this uptake on the marine environment. Advances in understanding, technology, and international coordination have made it possible to measure CO2 absorption by the oceans to a greater degree of accuracy than is possible in terrestrial landscapes. These advances, combined with new satellite‐based Earth observation capabilities, increasing public availability of data, and cloud computing, provide important opportunities for addressing critical knowledge gaps. Furthermore, Earth observation in synergy with in‐situ monitoring can provide the large‐scale ocean monitoring that is necessary to support policies to protect ocean ecosystems at risk, and motivate societal shifts toward meeting C emissions targets; however, sustained effort will be needed.

Various numerical methods such as CFD, BEM and RANS models have been used to study the interaction between tidal turbines and the tidal flow, and to investigate the performance of the tidal turbines. However, most of these studies consider idealised cases that cannot easily be translated to unsteady and non-uniform flow through a real channel [1]. Coastal tidal models provide an efficient and comprehensive approach to simulate tidal stream arrays in more realistic conditions. On the other hand, most of the studies which adopt this approach rely on 2D depth-averaged simulations to assess the performance of different tidal array layouts. 2D models ignore the effects of the turbine’s vertical position in the water column and the close proximity to the seabed or the surface on the overall performance. Contrary to 2D models, 3D models can better represent the various technologies and provide a more robust tool to assess tidal array performance. Tidal turbines are represented in the TELEMAC-2D as a drag force (similar to increasing the seabed friction) using DRAGFO subroutine. The drag force is applied as a friction stress spread out over an area representing the turbine. This area is defined as the sum of the area of the nodes inside the turbine envelope [2]. Building on this approached, we developed a code to capture the effects of the drag force, which is exerted by the turbines on the flow, and apply it as a head loss in TELEMAC-3D. This stress is treated as a source term in the shallow water equations. This paper describes the modelling approach of tidal turbines in TELEMAC-3D using SOURCE subroutine. Implementation of this approach will be assessed against a real measurements downstream Alstom DG4 tidal turbine, which was deployed in Fall of Warness, Orkney as part of ReDAPT project. Proposed session: Waves, tidal renewable and hydro power energy assessment

The contemporary air‐sea flux of CO2 is investigated by the use of an air‐sea flux equation, with particular attention to the uncertainties in global values and their origin with respect to that equation. In particular, uncertainties deriving from the transfer velocity and from sparse upper ocean sampling are investigated. Eight formulations of air‐sea gas transfer velocity are used to evaluate the combined standard uncertainty resulting from several sources of error. Depending on expert opinion, a standard uncertainty in transfer velocity of either ~5% or ~10% can be argued and that will contribute a proportional error in air‐sea flux. The limited sampling of upper ocean fCO2 is readily apparent in the Surface Ocean CO2 Atlas databases. The effect of sparse sampling on the calculated fluxes was investigated by a bootstrap method, that is, treating each ship cruise to an oceanic region as a random episode and creating 10 synthetic data sets by randomly selecting episodes with replacement. Convincing values of global net air‐sea flux can only be achieved using upper ocean data collected over several decades but referenced to a standard year. The global annual referenced values are robust to sparse sampling, but seasonal and regional values exhibit more sampling uncertainty. Additional uncertainties are related to thermal and haline effects and to aspects of air‐sea gas exchange not captured by standard models. An estimate of global net CO2 exchange referenced to 2010 of −3.0 ± 0.6 Pg C/year is proposed, where the uncertainty derives primarily from uncertainty in the transfer velocity.

High-resolution satellite images of ocean color and sea surface temperature reveal an abundance of ocean fronts, vortices and filaments at scales below 10 km but measurements of ocean surface dynamics at these scales are rare. There is increasing recognition of the role played by small scale ocean processes in ocean-atmosphere coupling, upper-ocean mixing and ocean vertical transports, with advanced numerical models and in situ observations highlighting fundamental changes in dynamics when scales reach 1 km. Numerous scientific publications highlight the global impact of small oceanic scales on marine ecosystems, operational forecasts and long-term climate projections through strong ageostrophic circulations, large vertical ocean velocities and mixed layer re-stratification. Small-scale processes particularly dominate in coastal, shelf and polar seas where they mediate important exchanges between land, ocean, atmosphere and the cryosphere, e.g., freshwater, pollutants. As numerical models continue to evolve toward finer spatial resolution and increasingly complex coupled atmosphere-wave-ice-ocean systems, modern observing capability lags behind, unable to deliver the high-resolution synoptic measurements of total currents, wind vectors and waves needed to advance understanding, develop better parameterizations and improve model validations, forecasts and projections. SEASTAR is a satellite mission concept that proposes to directly address this critical observational gap with synoptic two-dimensional imaging of total ocean surface current vectors and wind vectors at 1 km resolution and coincident directional wave spectra. Based on major recent advances in squinted along-track Synthetic Aperture Radar interferometry, SEASTAR is an innovative, mature concept with unique demonstrated capabilities, seeking to proceed toward spaceborne implementation within Europe and beyond.