Shallow nearshore coastal waters provide a wealth of societal, economic and ecosystem services, yet their topographic structure is poorly mapped due to a reliance upon expensive and time intensive methods. Space-borne bathymetric mapping has helped address these issues, but has remained dependent upon in situ measurements. Here we fuse ICESat-2 lidar data with Sentinel-2 optical imagery, within the Google Earth Engine geospatial cloud platform, to create wall-to-wall high-resolution bathymetric maps at regional-to-national scales in Florida, Crete and Bermuda. ICESat-2 bathymetric classified photons are used to train three Satellite Derived Bathymetry (SDB) methods, including Lyzenga, Stumpf and Support Vector Regression algorithms. For each study site the Lyzenga algorithm yielded the lowest RMSE (approx. 10-15%) when compared with in situ NOAA DEM data. We demonstrate a means of using ICESat-2 for both model calibration and validation, thus cementing a pathway for fully space-borne estimates of nearshore bathymetry in shallow, clear water environments.

Alkalinization of natural waters by the dissolution of natural or artificial minerals is a promising solution to sequester atmospheric CO$_2$ and counteract acidification. Here we address the alkalinization carbon capture efficiency (ACCE) by deriving an analytical factor that quantifies the increase in dissolved inorganic carbon in the water due to variations in alkalinity. We show that ACCE strongly depends on the water pH, with a sharp transition from minimum to maximum in a narrow interval of pH values. We also compare ACCE in surface freshwater and seawater and discuss potential bounds for ACCE in the soil water. Finally, we present two applications of ACCE. The first is a local application to 156 lakes in an acid-sensitive region, highlighting the great sensitivity of ACCE to the lake pH. The second is a global application to the surface ocean, revealing a latitudinal pattern of ACCE driven by differences in temperature and salinity.

The shape of ice-shelf cavities are a major source of uncertainty in understanding ice-ocean interactions. This limits assessments of the response of the Antarctic ice sheets to climate change. Here we use vibroseis seismic reflection surveys to map the bathymetry beneath the Ekström Ice Shelf, Dronning Maud Land. The new bathymetry reveals an inland-sloping trough, reaching depths of 1100 m below sea level, near the current grounding line, which we attribute to erosion by palaeo-ice streams. The trough does not cross-cut the outer parts of the continental shelf. Conductivity-temperature-depth profiles within the ice-shelf cavity reveal the presence of cold water at shallower depths and tidal mixing at the ice-shelf margins. It is unknown if warm water can access the trough. The new bathymetry is thought to be representative of many ice shelves in Dronning Maud Land, which together regulate the ice loss from a substantial area of East Antarctica.

A description and assessment of the first release of the Arctic Subpolar gyre sTate Estimate (ASTE_R1), a data-constrained ocean-sea ice model-data synthesis is presented. ASTE_R1 has a nominal resolution of 1/3o and spans the period 2002-2017. The fit of the model to an extensive (O(10^9)) set of satellite and in situ observations was achieved through adjoint-based nonlinear least-squares optimization. The improvement of the solution compared to an unconstrained simulation is reflected in misfit reductions of 77% for Argo, 50% for satellite sea surface height, 58% for the Fram Strait mooring, 65% for Ice Tethered Profilers, and 83% for sea ice extent. Exact dynamical and kinematic consistency is a key advantage of ASTE_R1, distinguishing the state estimate from existing ocean reanalyses. Through strict adherence to conservation laws, all sources and sinks within ASTE_R1 can be accounted for, permitting meaningful analysis of closed budgets at the grid-scale, such as contributions of horizontal and vertical convergence to the tendencies of heat and salt. ASTE_R1 thus serves as the biggest effort undertaken to date of producing a specialized Arctic ocean-ice estimate over the 21st century. Transports of volume, heat, and freshwater are consistent with published observation-based estimates across important Arctic Mediterranean gateways. Interannual variability and low frequency trends of freshwater and heat content are well represented in the Barents Sea, western Arctic halocline, and east subpolar North Atlantic. Systematic biases remain in ASTE_R1, including a warm bias in the Atlantic Water layer in the Arctic and deficient freshwater inputs from rivers and Greenland discharge.

Oceanography has entered an era of new observing platforms, such as biogeochemical Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centres will use multi-platform assimilation to integrate those valuable data into ecosystem reanalyses and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation and introduce multi-platform data assimilation in a (pre)operational model of the NWE Shelf-sea ecosystem. We test the impact of the different multi-platform system components (glider vs satellite, physical vs biogeochemical) on the simulated biogeochemical variables. To characterize the model performance we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical data assimilation, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.

A novel approach to improve seasonal to interannual sandy shoreline predictions is presented, whereby model free parameters can vary in time, adjusting to potential non-stationarity in the underlying model forcing. This is achieved by adopting a suitable data assimilation technique (Dual State-Parameter Ensemble Kalman Filter) within the established shoreline evolution model, ShoreFor. The method is first tested and evaluated using synthetic scenarios, specifically designed to emulate a broad range of natural sandy shoreline behavior. This approach is then applied to a real-world shoreline dataset, revealing that time-varying model free parameters are linked through physical processes to changing characteristics of the wave forcing. Greater accuracy of shoreline predictions is achieved, compared to existing stationary modelling approaches. It is anticipated that the wider application of this method can improve our understanding and prediction of future beach erosion patterns and trends in a changing wave climate.

Geologists have documented at least fourteen occurrences of “giant ooids”, a geologically rare type of carbonate allochem, in Neoproterozoic successions at low paleo-latitudes. Recent experiments and modeling demonstrated that ooid size reflects an equilibrium between precipitation and abrasion rates, such that ooid size could be used as a geological proxy for CaCO3 mineral saturation state (Ω). Here, the documented sizes of Neoproterozoic giant ooids were applied to estimate seawater , which provided a novel approach to constraining temperature, partial pressure of CO2, and alkalinity preceding Neoproterozoic glaciations. The results suggest that giant ooid formation was most plausible with seawater alkalinity elevated over its present value by at least a factor of two, and either much warmer (40C) or much colder (0C) climate than modern tropical carbonate platforms, which have important and divergent implications for climate states and ecosystem responses prior to the initiation of each Neoproterozoic glaciation.

In austral winter, biological productivity at the Angolan shelf reaches its maximum. The alongshore winds, however, reach their seasonal minimum suggesting that processes other than local wind-driven upwelling contribute to near-coastal cooling and upward nutrient supply, one possibility being mixing induced by internal tides (ITs). Here, we apply a three-dimensional ocean model to simulate the generation, propagation and dissipation of ITs at the Angolan continental slope and shelf. Model results are validated against moored acoustic Doppler current profiler and other observations. Simulated ITs are mainly generated in regions with a critical/supercritical slope typically between the 200- and 500-m isobaths. Mixing induced by ITs is found to be strongest close to the coast and gradually decreases offshore thereby contributing to the establishment of cross-shore temperature gradients. The available seasonal coverage of hydrographic data is used to design simulations to investigate the influence of seasonally varying stratification characterized by low stratification in austral winter and high stratification in austral summer. The results show that IT characteristics, such as their wavelengths, sea surface convergence patterns and baroclinic structure, have substantial seasonal variations and additionally strong spatial inhomogeneities. However, seasonal variations in the spatially-averaged generation, onshore flux and dissipation of IT energy are weak. By evaluating the change of potential energy, it is shown, nevertheless, that mixing due to ITs is more effective during austral winter. We argue this is because the weaker background stratification in austral winter than in austral summer acts as a preconditioning for IT mixing.

North African dust is known to be deposited in the Gulf of Mexico, but its deposition rate and associated supply of lithogenic dissolved metals, such as the abiotic metal thorium or the micronutrient metal iron, have not been well-quantified. 232Th is an isotope with similar sources as iron and its input can be quantified using radiogenic 230Th. By comparing dissolved 232Th fluxes at three sites in the northern Gulf of Mexico with upwind sites in the North Atlantic, we place an upper bound on North African dust contributions to 232Th and Fe in the Gulf of Mexico, which is about 30% of the total input. Precision on this bound is hindered by uncertainty in the relative rates of dust deposition in the North Atlantic and the northern Gulf of Mexico. Based on available radium data, shelf sources, including rivers, submarine groundwater discharge and benthic sedimentary releases are likely as important if not more important than dust in the budget of lithogenic metals in the Gulf of Mexico. In other words, it is likely there is no one dominant source of Th and Fe in the Gulf of Mexico. Finally, our estimated Fe input in the northern Gulf of Mexico implies an Fe residence time of less than 6 months, similar to that in the North Atlantic despite significantly higher supply rates in the Gulf of Mexico.

Previous studies have interpreted Last Interglacial (LIG; ~129-116 ka) sea-level estimates in multiple different ways to calibrate projections of future Antarctic ice-sheet (AIS) mass loss and associated sea-level rise. This study systematically explores the extent to which LIG constraints could inform future Antarctic contributions to sea-level rise. We develop a Gaussian process emulator of an ice-sheet model to produce continuous probabilistic projections of Antarctic sea-level contributions over the LIG and a future high-emissions scenario. We use a Bayesian approach conditioning emulator projections on a set of LIG constraints to find associated likelihoods of model parameterizations. LIG estimates inform both the probability of past and future ice-sheet instabilities and projections of future sea-level rise through 2150. Although best-available LIG estimates do not meaningfully constrain Antarctic mass loss projections or physical processes until 2060, they become increasingly informative over the next 130 years. Uncertainties of up to 50 cm remain in future projections even if LIG Antarctic mass loss is precisely known (+/-5 cm), indicating there is a limit to how informative the LIG could be for ice-sheet model future projections. The efficacy of LIG constraints on Antarctic mass loss also depends on assumptions about the Greenland ice sheet and LIG sea-level chronology. However, improved field measurements and understanding of LIG sea levels still have potential to improve future sea-level projections, highlighting the importance of continued observational efforts.

Turbulent mixing induced by breaking internal waves is key to the ocean circulation and global tracer budgets. While the classic marginal shear instability of Richardson number ∼ 1/4 has been considered as potentially relevant to turbulence wave breaking, its relevance to energetic zones where tides, winds, and buoyancy gradients excite non-linearly interacting processes has been suspect. We show that shear instability is indeed relevant in the ocean interior and propose an alternative generalized marginal stability criterion, based on the ratio of Ozmidov and Thorpe turbulence scales, which not only applies to the ocean interior, but remains relevant within turbulent boundary layers. This allows for accurate quantification of the transition from downwelling to upwelling zones in a recently emerged paradigm of ocean circulation. Our results help climate models more accurately calculate the mixing-driven deep ocean circulation and fluxes of tracers in the ocean interior.

The Lower St. Lawrence Seaway (LSLS), in eastern Canada, is an important habitat for several species of endangered baleen whale. As we seek to reduce the hazards that these endangered species face from human activity, there is increasing demand for detailed knowledge of their habitat use. Only a sparse network of hydrophones exists in the LSLS to remotely observe whales. However, there is also a network of onshore seismometers, designed to monitor earthquakes, that have sufficiently high sample rates to record fin and blue whale calls. We present a simple method for detecting band-limited, regularly repeating calls, such as the 20 Hz calls of fin and blue whales, and apply the method to build a catalog of fin and blue whale detections at 14 onshore seismometers across the LSLS, over approximately a four-year period. The resulting catalog contains >600000 fin whale calls and >60000 blue whale calls. Individual calls are rarely detected at more than one seismometer. Fin whale calls recorded onshore appear to travel mainly through solid earth, rather than only entering the earth at the shoreline, and they often have a complex ~2 s sequence of P-like and S-like phases. Onshore seismometers provide a valuable, previously unused source of data for monitoring baleen whales. However, in the LSLS, the current seismometer network cannot provide high-precision whale tracking alone, so a denser deployment of onshore and/or offshore seismometers is required.

Export of sinking particles from the surface ocean is critical for carbon sequestration and for providing energy to the deep-ocean biosphere. The magnitude and spatial patterns of this flux have been estimated in the past by in situ flux observations, satellite-based algorithms, and ocean biogeochemical models; however, these estimates remain uncertain. Here, we use a novel machine learning reconstruction of global in situ ocean particle size spectra from Underwater Vision Profiler 5 (UVP5) measurements, to determine particulate carbon fluxes. We combine global maps of particle size distribution parameters for large sinking particles with observationally-constrained empirical relationships to calculate the sinking carbon flux from the euphotic zone and the wintertime mixed layer depth. Our flux reconstructions are comparable to prior estimates, but suggest a less variable seasonal cycle in the tropical ocean, and a more persistent export in the Southern Ocean than previously thought. Because our estimates are not bounded by a specific depth horizon, we reconstruct export at multiple depths, and find that export from the wintertime mixed layer globally exceeds that from the euphotic zone. Our estimates provide a baseline for more accurate understanding of particle cycles in the ocean, and open the way to fully three-dimensional global reconstructions of particle size spectra and fluxes in the ocean, supported by the growing database of optical observations.

The Weddell Gyre’s variability on seasonal and interannual timescales is investigated using an ocean-sea ice model at three different horizontal resolutions. The model is evaluated against available observations to demonstrate that the highest resolution configuration (0.1$^{\circ}$ in the horizontal) best reproduces observed features of the region. The simulations suggest that the gyre is subject to large variability in its circulation that is not captured by summer-biased or short-term observations. The Weddell Gyre’s seasonal cycle consists of a summer minimum and a winter maximum and accounts for changes that are between one third and a half of its mean transport . On interannual time scales we find that the gyre’s strength is correlated with the local Antarctic easterlies and that extreme events of gyre circulation are associated with changes in sea ice concentration and the characteristics of warm inflow at the eastern boundary.

The Transition Zone Chlorophyll Front (TZCF) is a dynamic region of elevated chlorophyll concentrations in the Northeast Pacific that migrates from a southern winter (February) extent of approximately 30°N to a northern summer (August) extent of approximately 40°N. The transition zone has been highlighted as important habitat for marine animals and fisheries. We re-examine the physical and biological drivers of seasonal TZCF variability using a variety of remote sensing, reanalysis, and in-situ datasets. Satellite-based remote sensing estimates of chlorophyll and carbon concentrations show that seasonal TZCF migration primarily reflects a seasonal increase in the chlorophyll to carbon ratio, rather than changes in phytoplankton carbon. We use our data compilation to demonstrate how the seasonality of light and nutrient fluxes decouple chlorophyll and carbon seasonality at the transition zone latitudes. Seasonal mixed-layer-averaged light availability is positively correlated with carbon and negatively correlated with chlorophyll through the transition zone, while climatological nitrate profiles show that chlorophyll to carbon ratios are facilitated by wintertime nitrate entrainment. These empirical results are consistent with physiological data and models describing elevated chlorophyll to carbon ratios in low light, nutrient-replete environments, demonstrating the importance of latitudinal structure in interpreting seasonal chlorophyll dynamics at the basin scale.

Barrier island overwash occurs when the elevation of wave runup exceeds the dune crest and induces landward transport of sediment across a barrier island and deposition of a washover deposit. Washover deposition is generally attributed to major storms, is important for the maintenance of barrier island resilience to sea-level rise and is used to extend hurricane records beyond historical accounts by reconstructing the frequency and extent of washover deposits preserved in the sedimentary record. Here, we present a high-fidelity three-year record of washover evolution and overwash at a transgressive barrier island site. During the first year after establishment, washover volume and area increased 1,595% and 197%, respectively, from at least monthly overwash. Most of the washover accretion resulted from the site morphology having a low resistance to overwash, as opposed to being directly impacted by major storms. Washover deposits can accrete over multi-year time scales; therefore, paleowashover deposits are more complex than simply event beds.

Radiogenic lead (Pb) and neodymium (Nd) isotope compositions extracted from authigenic phases in marine sediments are sensitive tracers to reconstruct past ocean circulation and water mass mixing. Chemical reductive leaching of hydrogenetic ferromanganese oxyhydroxides from bulk sediments is the most practical way to recover past seawater Pb and Nd isotope signatures in the Southern Ocean, due to the scarcity of alternative archives. However, the leached signal could be compromised if substantial quantities of Pb and Nd were released from non-hydrogenetic sediment fractions during chemical extraction. Here we developed a very short 10-seconds leaching method to extract reliable seawater Pb and Nd isotope signals from sediments in the Atlantic sector of Southern Ocean. The effect of a previously recommended MgCl prewash, the role of chelate ligands in the leaching solution and length of leaching time were investigated. The results show that 10 seconds exposure time of sediments to reductive leaching extracted sufficient and more reliable hydrogenetic Pb and Nd compared with the commonly used 30-minute leaching approaches. The robustness of our improved leaching method was validated via direct comparison of Pb and Nd isotope signatures with actual seawater, porewater and corresponding sediment leachates from three stations in front of the Antarctic Filchner-Rønne Ice Shelf. Our findings suggest that in contrast previously studied sites on the West Antarctic continental shelf, the southern Weddell Sea shelf is not a location of pronounced benthic Nd fluxes to the water column.

We present a new brittle rheology and an accompanying numerical framework for large-scale sea-ice modelling. This rheology is based on a Bingham-Maxwell constitutive model and the Maxwell-Elasto-Brittle (MEB) rheology, the latter of which has previously been used to model sea ice. The key strength of the MEB rheology is its ability to represent the scaling properties of simulated sea-ice deformation in space and time. The new rheology we propose here, which we refer to as the brittle Bingham-Maxwell rheology (BBM), represents a further evolution of the MEB rheology. It is developed to address two main shortcomings of the MEB rheology and numerical implementation we were unable to address previously: excessive thickening of the ice in model runs longer than about one winter and a relatively high computational cost. In the BBM rheology and numerical framework these shortcomings are addressed by demanding that the ice deforms under convergence in a purely elastic manner when internal stresses lie below a given compressive threshold. Numerical performance is improved by introducing an explicit scheme to solve the ice momentum equation. In this paper we introduce the new rheology and numerical framework. Using an implementation of BBM in version two of the neXtSIM sea-ice model (neXtSIMv2), we show that it gives reasonable long term evolution of the Arctic sea-ice cover and very good deformation fields and statistics compared to satellite observations.

The reappearance of a northeast Pacific marine heatwave (MHW) sounded alarms in late summer 2019 for a warming event on par with the 2013–2016 MHW known as The Blob. Despite these two events having similar magnitudes in surface warming, differences in seasonality and salinity distinguish their evolutions. We compare and contrast the ocean’s role in the evolution and persistence of the 2013–2016 and 2019–2020 MHWs using mapped temperature and salinity data from Argo floats. An unusual near-surface freshwater anomaly in the Gulf of Alaska during 2019 increased the stability of the water column, preventing the MHW from penetrating as deeply as the 2013–2016 event. This freshwater anomaly likely contributed to the intensification of the MHW by increasing the near-surface buoyancy. The gradual buildup of subsurface heat content throughout 2020 in the region suggests the potential for persistent ecological impacts.

Predictable internal climate variability on decadal timescales (2-10 years) is associated with large-scale oceanic processes, however these predictable signals may be masked by the noisy climate system. One approach to overcoming this problem is investigating state-dependent predictability - how differences in prediction skill depend on the initial state of the system. We present a machine learning approach to identify state-dependent predictability on decadal timescales in the Community Earth System Model version 2 by incorporating uncertainty estimates into a regression neural network. We leverage the network’s prediction of uncertainty to examine state dependent predictability in sea surface temperatures by focusing on predictions with the lowest uncertainty outputs. In particular, we study two regions of the global ocean - the North Atlantic and North Pacific - and find that skillful initial states identified by the neural network correspond to particular phases of Atlantic multi-decadal variability and the interdecadal Pacific oscillation.

El Niño Southern Oscillation (ENSO) is the leading mode of interannual climate variability, with large socioeconomical and environmental impacts. The main conceptual model for ENSO, the Recharge Oscillator (RO), considers two independent modes: the fast zonal tilt mode in phase with central-eastern Pacific Temperature (Te), and the slow recharge mode in phase quadrature. However, usual indices (western or equatorial sea level/thermocline depth h) do not orthogonally isolate the slow recharge mode, leaving it correlated with Te. Furthermore the optimal index is currently debated. Here, by objectively optimizing the RO equations fit to observations, we develop an improved recharge index. (1) Te-variability is regressed out, building h_ind statistically-independent from Te. Capturing the pure recharge, h_ind reconciles usual indices. (2) The optimum is equatorial plus southwestern Pacific h_ind_eq+sw (because of ENSO Ekman pumping meridional asymmetry). Using h_ind_eq+sw, the RO becomes more consistent with observations. h_ind_eq+sw is more relevant for ENSO operational diagnostics.

To capture the effects of mesoscale turbulent eddies, coarse-resolution Eulerian ocean models resort to tracer diffusion parameterizations. Likewise, the effect of eddy dispersion needs to be parameterized when computing Lagrangian pathways using coarse flow fields. Dispersion in Lagrangian simulations is traditionally parameterized by random walks, equivalent to diffusion in Eulerian models. Beyond random walks, there is a hierarchy of stochastic parameterizations, where stochastic perturbations are added to Lagrangian particle velocities, accelerations, or hyper-accelerations. These parameterizations are referred to as the 1st, 2nd and 3rd order ‘Markov models’ (Markov-N), respectively. Most previous studies investigate these parameterizations in two-dimensional setups, often restricted to the ocean surface. On the other hand, the few studies that investigated Lagrangian dispersion parameterizations in three dimensions, where dispersion is largely restricted to neutrally buoyant surfaces, have focused only on random walk (Markov-0) dispersion. Here, we present a three-dimensional isoneutral formulation of the Markov-1 model. We also implement an anisotropic, shear-dependent formulation of random walk dispersion, originally formulated as a Eulerian diffusion parameterization. Random walk dispersion and Markov-1 are compared using an idealized setup as well as more realistic coarse and coarsened (50 km) ocean model output. While random walk dispersion and Markov-1 produce similar particle distributions over time when using our ocean model output, Markov-1 yields Lagrangian trajectories that better resemble trajectories from eddy-resolving simulations. Markov-1 also yields a smaller spurious dianeutral flux.

A large strike-slip earthquake occurred in the Caribbean Sea on 28 January 2020. We inverted teleseismic P-waveforms from the earthquake to construct a finite-fault model by a new method of inversion that simultaneously resolves the spatiotemporal evolution of fault geometry and slip. The model showed almost unilateral rupture propagation westward from the epicenter along a 300 km section of the Oriente transform fault with two episodes of rupture at speeds exceeding the local shear-wave velocity. Our modeling indicated that the 2020 Caribbean earthquake rupture encountered a bend in the fault system associated with a bathymetric feature near the source region. The geometric complexity of the fault system triggered multiple rupture episodes and a complex rupture evolution. Our analysis of the earthquake revealed complexity of rupture process and fault geometry previously unrecognized for an oceanic transform fault that was thought to be part of a simple linear transform fault system.

Western boundary currents (WBCs) have intensified and become more eddying in recent decades due to the spin-up of the ocean gyres, resulting in warmer open ocean temperatures. However, relatively little is known of how WBC intensification will affect temperatures in adjacent continental shelf waters where societal impact is greatest. We use the well-observed East Australian Current (EAC) to investigate WBC warming impacts on shelf waters and show that temperature increases are non-uniform in shelf waters along the latitudinal extent of the EAC. Shelf waters poleward of 32°S, are warming more than twice as fast as those equatorward of 32°S. We show that non-uniform shelf temperature trends are driven by an increase in lateral heat advection poleward of the WBC separation, along Australia’s most populous coastline. The large scale nature of the process indicates that this is applicable to WBCs broadly, with far-reaching biological implications.