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Abstract: Recent advances in explainable artificial intelligence (XAI) methods show promise for understanding predictions made by machine learning (ML) models. XAI explains how the input features are relevant or important for the model predictions. We train linear regression (LR) and convolutional neural network (CNN) models to make one-day predictions of sea-ice velocity in the Arctic from inputs of present-day wind velocity and previous-day ice velocity and concentration. We apply XAI methods to the CNN and compare explanations to variance explained by LR. We confirm the feasibility of using a novel XAI method (i.e. global layerwise relevance propagation (LRP)) to understand ML model predictions of sea-ice motion by comparing to established techniques. We investigate a suite of linear, perturbation-based, and propagation-based XAI methods in both local and global forms. Outputs from different explainability methods are generally consistent in showing that wind speed is the input feature with the highest contribution to ML predictions of ice motion, and we discuss inconsistencies in spatial variability of the explanations. Additionally, we show that CNN relies on both linear and non-linear relationships between the inputs and uses non-local information to make predictions. LRP shows that wind speed over land is highly relevant for predicting ice motion offshore. This provides a framework to show how knowledge of environmental variables (i.e. wind) on land could be useful for predicting other properties (i.e. sea-ice velocity) elsewhere.

The Southern Ocean modulates global biogeochemical (BGC) cycles substantially, affecting biological production and the global air-sea balance of carbon dioxide and interior dissolved oxygen content. Concurrently, the Southern Ocean is rich in highly dynamic mesoscale eddies. These eddies have the potential to alter local carbon, nutrient, and oxygen distributions through eddy pumping, stirring, and trapping. Additionally, the strong westerly winds could result in significant eddy-induced Ekman pumping counteracting the eddy pumping effects. However, the impact of mesoscale eddies on upper-ocean Southern Ocean biogeochemistry has not been quantified observationally at a regional scale.We now have nearly a decade of BGC observations from Argo floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM). In addition, the Mesoscale Eddy Trajectory Atlas, version 3.2, delayed time (Meta3.2DT) database provides us with a robust assessment of eddies as detected by satellite altimeter measurements. Together, the two datasets allow us to investigate the three-dimensional structure of the biogeochemistry in Southern Ocean eddies. Here, we co-locate Southern Ocean eddies with BGC Argo floats to characterize composite vertical and horizontal structures of dissolved inorganic carbon (DIC), oxygen, and nitrate inside anticyclonic and cyclonic eddies compared to the mean climatological fields. We conduct this analysis in several subregions with different dominant processes. We find positive DIC and nitrate anomalies in cyclonic eddies, which we attribute to upward eddy pumping. We also find positive oxygen anomalies near the surface, which we attribute to upwelled nutrients that enhance biological production, leading to enhanced photosynthesis. At depth, we find negative oxygen anomalies in cyclonic eddies, which may be driven both by enhanced respiration due to increased biological production as well as the heaving of isopycnals via eddy pumping. The opposite is true for anticyclonic eddies due to downward eddy pumping (negative DIC and nitrate anomalies; negative oxygen anomalies near the surface and positive oxygen anomalies at depth). The magnitudes of the eddy imprints on biogeochemistry vary by region, indicating that stratification and other background signals influence the magnitude of the effect of eddies in a region. Our findings can help us to interpret the influence of mesoscale eddies on the Southern Ocean carbon fluxes and biogeochemistry, including assessing the relative dominance of eddy pumping and eddy-induced Ekman pumping in different subregions of the Southern Ocean.

Abstract: The Surface Water Ocean Topography (SWOT) satellite mission provides high-resolution two-dimensional sea surface height (SSH) data with swath coverage. However, spatially correlated errors affect these SSH measurements, particularly in the cross-track direction. The scales of errors can be similar to the scales of ocean features. Conventionally, instrumental errors and ocean signals have been solved for independently in two stages. Here, we have developed a one-stage procedure that solves for the correlated error at the same time that data are assimilated into a dynamical ocean model. This uses the ocean dynamics to distinguish ocean signals from observation errors. We test its performance relative to the two-stage method using simplified dynamics and a data set consisting of westward propagating Rossby waves, along with correlated instrumental errors of varying magnitudes. In a series of tests, we found that the one-stage approach consistently outperforms the two-stage approach when estimating SSH signal and correlated errors. The one-stage approach can recover over 95% of the SSH signal, while skill for the two-stage approach drops significantly as error increases. Our findings suggest that solving for the correlated errors within the assimilation framework can provide an effective analysis approach, reducing the risks of confounding signal and instrument noise.

Abstract: The Southern Ocean is a region of intense air–sea exchange that plays a critical role for ocean circulation, global carbon cycling, and climate. Subsurface chlorophyll‐a maxima, annually recurrent features throughout the Southern Ocean, may increase the energy flux to higher trophic levels and facilitate downward carbon export. It is important that model parameterizations appropriately represent the chlorophyll vertical structure in the Southern Ocean. Using BGC‐Argo chlorophyll profiles and the Biogeochemical Southern Ocean State Estimate (B‐SOSE), we investigate the sensitivity of chlorophyll vertical structure to model parameters. Based on the sensitivity analysis results, we estimate optimized parameters, which efficiently improve the model consistency with observations. We characterize chlorophyll vertical structure in terms of Empirical Orthogonal Functions and define metrics to compare model results and observations in a series of parameter perturbation experiments. We show that chlorophyll magnitudes are likely to respond quasi‐symmetrically to perturbations in the analyzed parameters, while depth and thickness of the subsurface chlorophyll maximum show an asymmetric response. Perturbing the phytoplankton growth tends to generate more symmetric responses than perturbations in the grazing rate. We identify parameters that affect chlorophyll magnitude, subsurface chlorophyll or both and discuss insights into the processes that determine chlorophyll vertical structure in B‐SOSE. We highlight turbulence, differences in phytoplankton traits, and grazing parameterizations as key areas for improvement in models of the Southern Ocean.

The Southern Ocean is rich in highly dynamic mesoscale eddies and substantially modulates global biogeochemical cycles. However, the overall surface and subsurface effects of eddies on the Southern Ocean biogeochemistry have not been quantified observationally at a large scale. Here, we co-locate eddies, identified in the Meta3.2DT satellite altimeter-based product, with biogeochemical Argo floats to determine the effects of eddies on the dissolved inorganic carbon (DIC), nitrate, and dissolved oxygen concentrations in the upper 1,500 m of the ice-free Southern Ocean, as well as the eddy effects on the carbon fluxes in this region. DIC and nitrate concentrations are lower in anticyclonic eddies (AEs) and increased in cyclonic eddies (CEs), while dissolved oxygen anomalies switch signs above (CEs: positive, AEs: negative) and below the mixed layer (CEs: negative, AEs: positive). We attribute these anomalies primarily to eddy pumping (isopycnal heave), as well as eddy trapping for oxygen. Maximum anomalies in all tracers occur at greater depths in the subduction zone north of the Antarctic Circumpolar Current (ACC) compared to the upwelling region in the ACC, reflecting differences in background vertical structures. Eddy effects on air-sea CO2 exchange have significant seasonal variability, with additional outgassing in CEs in fall (physical process) and additional oceanic uptake in AEs and CEs in spring (biological and physical process). Integrated over the Southern Ocean, AEs contribute ∼0.03± 0.01 Pg C yr-1 (7 ±2% ) to the Southern Ocean carbon uptake, and CEs offset this by ∼0.01± 0.01 Pg C yr-1 (2 ±2% ). These findings underscore the importance of considering eddy impacts in observing networks and climate models.

Abstract: Over 9 years of hourly surface current data from high‐frequency radar (HFR) off the US West Coast are analyzed using a Bayesian least‐squares fit for tidal components. The spatial resolution and geographic extent of HFR data allow us to assess the spatial structure of the non‐phase‐locked component of the tide. In the frequency domain, the record length and sampling rate allow resolution of discrete tidal lines corresponding to well‐known constituents and the near‐tidal broadband elevated continuum resulting from amplitude and phase modulation of the tides, known as cusps. The FES2014 tide model is used to remove the barotropic component of tidal surface currents in order to evaluate its contribution to the phase‐locked variance and spatial structure. The mean time scale of modulation is 243 days for the M2 constituent and 181 days for S2, with overlap in their range of values. These constituents' modulated amplitudes are significantly correlated in several regions, suggesting shared forcing mechanisms. Within the frequency band M2 ± 5 cycles per year, an average of 48% of energy is not at the phase‐locked frequency. When we remove the barotropic model, this increases to 64%. In both cases there is substantial regional variability. This indicates that a large fraction of tidal energy is not easily predicted (e.g., for satellite altimeter applications). The spatial autocorrelation of the non‐phase‐locked variance fraction drops to zero over a distance of 150 km, a scale that is comparable to the swath width of the Surface Water and Ocean Topography altimeter.

Abstract: Meltwater from the Greenland Ice Sheet can alter the continental shelf/slope circulation and cross-shelf freshwater fluxes and limit deep convection in adjacent basins through surface freshening. We explore the impacts on the West Greenland Current and eastern Labrador Sea with different vertical distributions of the meltwater forcing. In this study, we present the results from global coupled ocean/sea ice simulations, forced with atmospheric reanalysis, that are mesoscale eddy-active (∼2–3-km horizontal spacing) and eddy-permitting (∼6–7-km horizontal spacing) in the study region. We compare the West Greenland Current in mesoscale eddy-active and eddy-permitting without meltwater to highlight the role of small-scale features. The mesoscale eddy-active configuration is then used to assess the change in the eastern Labrador Sea when meltwater is added to the surface or vertically distributed to account for mixing within fjords. In both simulations with meltwater, the West Greenland and West Greenland Coastal Currents are faster than in the simulation with no meltwater; their mean surface speeds are the highest in the vertical distribution case. In the latter case, there is enhanced baroclinic conversion at the shelf break compared to the simulation with no meltwater. When meltwater is vertically distributed, there is an increase in baroclinic conversion at the shelf break associated with increased eddy kinetic energy. In addition, in the eastern Labrador Sea, the salinity is lower and the meltwater volume is greater when meltwater is vertically distributed. Therefore, the West Greenland Current is sensitive to how meltwater is added to the ocean with implications for the freshening of the Labrador Sea. Significance Statement: Our goal is to understand how the flux of freshwater across the West Greenland continental slope into the Labrador Sea is modified by meltwater from the Greenland Ice Sheet. We compare the simulations of the ocean that capture key dynamics along the West Greenland continental slope that have no meltwater, meltwater added to the ocean surface, and meltwater distributed vertically to represent the mixing within fjords. When meltwater is added, the currents along the continental slope are faster, with the greatest increase when meltwater is vertically distributed. In that case, there is enhanced freshening of the Labrador Sea because modified density gradients generate more eddies. Proper representation of the vertical structure of meltwater is important for projecting the impact of freshwater on the subpolar North Atlantic.

Open-ocean polynyas formed over the Maud Rise, in the Weddell Sea, during the winters of 2016-2017. Such polynyas are rare events in the Southern Ocean and are associated with deep convection, affecting regional carbon and heat budgets. Using an ocean state estimate, we found that during 2017, early sea ice melting occurred in response to enhanced vertical mixing of heat, which was accompanied by mixing of salt. The melting sea ice compensated for the vertically mixed salt, resulting in a net buoyancy gain. An additional salt input was then necessary to destabilize the upper ocean. This came from a hitherto unexplored polynya-formation mechanism: an Ekman transport of salt across a jet girdling the northern flank of the Maud Rise. Such transport was driven by intensified eastward surface stresses during 2015-2018. Our results illustrate how highly localized interactions between wind, ocean flow and topography can trigger polynya formation in the open Southern Ocean.

Modelled water-mass changes in the North Pacific thermocline from CMIP6, both in the subsurface and at the surface, reveal the impact of the competition between anthropogenic aerosols and greenhouse gases (GHGs) over the past 6 decades. The aerosol effect overwhelms the GHG effect during 1950-1985 in driving salinity changes on density surfaces, while after 1985 the GHG effect dominates. These subsurface water-mass changes are traced back to changes at the surface, of which ~70% stems from the migration of density surface outcrops, equatorward due to regional cooling by anthropogenic aerosols and subsequent poleward due to warming by GHGs. Ocean subduction connects these surface outcrop changes to the main thermocline. Both observations and models reveal this transition in climate forcing around 1985 and highlight the important role of anthropogenic aerosol climate forcing on our oceans’ water masses.

Freshwater fishes are increasingly facing extinction. Some species will require conservation intervention such as habitat restoration and/or population supplementation through mass-release of hatchery fish. In California, USA, a number of conservation strategies are underway to increase abundance of the endangered Delta Smelt (Hypomesus transpacificus); however, it is unclear how different estuarine conditions influence hatchery fish. The goal of this study was to evaluate a year of Delta Smelt field deployments to inform species conservation strategies of suitable conditions for smelt physiology. Hatchery-reared Delta Smelt was deployed in experimental cages (seven deployments) throughout the Estuary in the winter, summer and fall of 2019. Effects of season and location of cage deployments on fish health (condition factor and histological condition of liver and gill), growth, thermal tolerance and survival were evaluated. The results indicate both seasonal and location differences, with high survival in the winter (100%) and fall (88-92%) compared to lower survival in summer (67%). In the summer, one of the study sites had no surviving fish following high temperature exposure, which peaked ~26°C. After 29 days in the cages, surviving Delta Smelt in summer and fall showed signs of nutritional stress that may be related to biofouling of the cages limiting passive food inputs, restriction of natural foraging behaviour by containment in the cages, and water temperatures that were too high given the chronically low pelagic productivity in the Estuary overall. Field measurements of upper thermal tolerance (CTmax) following caging exposures suggest that laboratory measures of CTmax may overestimate the realized tolerance in a more stochastic field environment. This study demonstrates the utility of using cages as an experimental tool to better understand aspects of Delta Smelt physiological responses to environmental changes across estuarine habitats in a more natural-field setting, while also highlighting potential limitations of using cages.

Abstract: Submesoscale currents and internal gravity waves achieve an intense turbulent cascade near the ocean surface (0 m – O(100) m depth), which is thought to give rise to significant energy sources and sinks for mesoscale eddies. Here, we characterise the contributions of Non-Wave Currents (NWCs; including eddies and fronts) and Internal Gravity Waves (IGWs; including near-inertial motions, lee waves and the internal wave continuum) to near-surface submesoscale turbulence in the Drake Passage. Using a numerical simulation, we combine Lagrangian filtering and a Helmholtz decomposition to identify NWCs and IGWs and to characterise their dynamics (rotational vs. divergent). We show that NWCs and IGWs contribute in different proportions to the inverse and forward turbulent kinetic energy cascades, based on their dynamics and spatiotemporal scales. Purely rotational NWCs cause most of the inverse cascade, while coupled rotational– divergent components of NWCs and coupled NWC–IGWs cause the forward cascade. The cascade changes direction at a spatial scale at which motions become increasingly divergent. However, the forward cascade is ultimately limited by the motions’ spatiotemporal scales. The bulk of the forward cascade (80 – 95%) is caused by NWCs and IGWs of small spatiotemporal scales (L

Modeled water-mass changes in the North Pacific thermocline, both in the subsurface and at the surface, reveal the impact of the competition between anthropogenic aerosols (AAs) and greenhouse gases (GHGs) over the past 6 decades. The AA effect overwhelms the GHG effect during 1950-1985 in driving salinity changes on density surfaces, while after 1985 the GHG effect dominates. These subsurface water-mass changes are traced back to changes at the surface, of which ~70% stems from the migration of density surface outcrops, equatorward due to regional cooling by AAs and subsequent poleward due to warming by GHGs. Ocean subduction connects these surface outcrop changes to the main thermocline. Both observations and models reveal this transition in climate forcing around 1985 and highlight the important role of AA climate forcing on our oceans' water masses.

Abstract: Physics-based simulations of Arctic sea ice are highly complex, involving transport between different phases, length scales, and time scales. Resultantly, numerical simulations of sea-ice dynamics have a high computational cost and model uncertainty. We employ data-driven machine learning (ML) to make predictions of sea-ice motion. The ML models are built to predict present-day sea-ice velocity given present-day wind velocity and previous-day sea-ice concentration and velocity. Models are trained using reanalysis winds and satellite-derived sea-ice properties. We compare the predictions of three different models: persistence (PS), linear regression (LR), and convolutional neural network (CNN). We quantify the spatio-temporal variability of the correlation between observations and the statistical model predictions. Additionally, we analyze model performance in comparison to variability in properties related to ice motion (wind velocity, ice velocity, ice concentration, distance from coast, bathymetric depth) to understand the processes related to decreases in model performance. Results indicate that a CNN makes skillful predictions of daily sea-ice velocity with a correlation up to 0.81 between predicted and observed sea-ice velocity, while the LR and PS implementations exhibit correlations of 0.78 and 0.69, respectively. The correlation varies spatially and seasonally; lower values occur in shallow coastal regions and during times of minimum sea-ice extent. LR parameter analysis indicates that wind velocity plays the largest role in predicting sea-ice velocity on one-day time scales, particularly in the central Arctic. Regions where wind velocity has the largest LR parameter are regions where the CNN has higher predictive skill than the LR.

Abstract: The core Argo array has operated with the design goal of uniform spatial distribution of 3° in latitude and longitude. Recent studies have acknowledged that spatial and temporal scales of variability in some parts of the ocean are not resolved by 3° sampling and have recommended increased core Argo density in the equatorial region, boundary currents, and marginal seas with an integrated vision of other Argo variants. Biogeochemical (BGC) Argo floats currently observe the ocean from a collection of pilot arrays, but recently funded proposals will transition these pilot arrays to a global array. The current BGC Argo implementation plan recommends uniform spatial distribution of BGC Argo floats. For the first time, we estimate the effectiveness of the existing BGC Argo array to resolve the anomaly from the mean using a subset of modeled, full-depth BGC fields. We also study the effectiveness of uniformly-distributed BGC Argo arrays with varying float densities at observing the ocean. Then, using previous Argo trajectories, we estimate the Argo array’s future distribution and quantify how well it observes the ocean. Finally, using a novel technique for sequentially identifying the best deployment locations, we suggest the optimal array distribution for BGC Argo floats to minimize objective mapping uncertainty in a subset of BGC fields and to best constrain BGC temporal variability.

Abstract: The Argo array provides nearly 4000 temperature and salinity profiles of the top 2000 meters of the ocean every 10 days. Still, Argo floats will never be able to measure the ocean at all times, everywhere. Optimized Argo float distributions should match the spatial and temporal variability of the many societally important ocean features that they observe. Determining these distributions is challenging because float advection is difficult to predict. Using no external models, transition matrices based on existing Argo trajectories provide statistical inferences about Argo float motion. We use the 24 years of Argo locations to construct an optimal transition matrix that minimizes estimation bias and uncertainty. The optimal array is determined to have a 2°×2° spatial resolution with a 90 day timestep. We then use the transition matrix to predict the probability of future float locations of the Core Argo array, the Global Biogeochemical Array, and the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) array. A comparison of transition matrices derived from floats using Argos System and Iridium communication methods shows the impact of surface displacements, which is most apparent near the equator. Additionally, we demonstrate the utility of transition matrices for validating models by comparing the matrix derived from Argo floats with that derived from a particle release experiment in the Southern Ocean State Estimate (SOSE).