Ocean bathymetry exerts a strong control on ice sheet-ocean interactions within Antarctic ice-shelf cavities, where it can limit the access of warm, dense water at depth to the underside of floating ice shelves. However, ocean bathymetry is challenging to measure within or close to ice-shelf cavities. It remains unclear how uncertainty in existing bathymetry datasets affect simulated sub-ice shelf melt rates. Here we infer linear sensitivities of ice shelf melt rates to bathymetric shape with grid-scale detail by means of the adjoint of an ocean general circulation model. Both idealised and realistic-geometry experiments of sub-ice shelf cavities in West Antarctica reveal that bathymetry has a strong impact on melt in localised regions such as topographic obstacles to flow. Moreover, response of melt to bathymetric perturbation is found to be non-monotonic, with deepening leading to either increased or decreased melt depending on location. Our computational approach provides a comprehensive way of identifying regions where refined knowledge of bathymetry is most impactful, and also where bathymetric errors have relatively little effect on modelled ice sheet-ocean interactions.

Diurnal tidal currents are the dominate contributors to diapycnal mixing in many regions along the pathways for warm Atlantic Water (AW) circulating within the Arctic Ocean along the continental slope. This mixing diffuses AW heat and salt into the cooler and fresher surroundings, including the upper ocean where ocean heat fluxes play a role in the stability of the ice pack. The strongest diurnal currents are associated with topographically-trapped vorticity waves, which are sensitive to stratification and mean flow. In models, these waves are also sensitive to choices for forcing and geometry. Sensitivity to background conditions implies that tidal currents and mixing will change as the Arctic evolves towards a new climate state. Here, as a first step towards understanding how diurnal tidal currents might change in a future Arctic Ocean, we describe results from a suite of high-resolution (dx=2 km) 2-D and 3-D models for Arctic diurnal tides, focusing on their currents at locations along the AW pathways. We first demonstrate that accurate representation of barotropic diurnal tides requires forcing with both open boundary conditions and the direct potential tide. Next, we use 3-D models with realistic, ocean background stratification and mean flow to describe the annual cycle of depth-averaged diurnal tidal currents. Finally, we investigate the baroclinic structure of diurnally forced waves including the generation of harmonics (semidiurnal and higher) that can contribute to mixing within the water column. Our results show that tides should be explicitly included in ocean and coupled predictive models for the Arctic to represent the feedbacks between tidal energetics and ocean mean state via mixing.

Harmful algal blooms (HABs) caused by the dinoflagellate Karenia brevis on the West Florida Shelf have become a nearly annual occurrence causing widespread ecological and economic harm. Effects range from minor respiratory irritation and localized fish kills to large-scale and long-term events causing massive mortalities to marine organisms. Reports of hypoxia on the shelf have been infrequent; however, there have been some indications that some HABs have been associated with localized hypoxia. We examined oceanographic data from 2004 to 2019 across the West Florida Shelf to determine the frequency of hypoxia and to assess its association with known HABs. Hypoxia was present in 5 of the 16 years examined and was always found shoreward of the 50-meter bathymetry line. There were 2 clusters of recurrent hypoxia: midshelf off the Big Bend coast and near the southwest Florida coast. We identified 3 hypoxic events that were characterized by multiple conductivity, temperature, and depth (CTD) casts and occurred concurrently with extreme HABs in 2005, 2014, and 2018. These HAB-hypoxia events occurred when K. brevis blooms initiated in early summer months and persisted into the fall likely driven by increased biological oxygen demand from decaying algal biomass and reduced water column ventilation due to stratification. There were also four years, 2011, 2013, 2015, and 2017, with low dissolved oxygen located near the shelf break that were likely associated with upwelling of deeper Gulf of Mexico water onto the shelf. We had difficulty in assessing the spatiotemporal extent of these events due to limited data availability and potentially unobserved hypoxia due to the inconsistent difference between the bottom of the CTD cast and the seafloor. While we cannot unequivocally explain the association between extreme HABs and hypoxia on the West Florida Shelf, there is sufficient evidence to suggest a causal linkage between them.

Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier-island evolution emphasize ocean-side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36-km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm-surge model results and observations of high-water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co-located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post-storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within two months. The partially filled features have created new ponds and lowland habitats that will likely persist for years. We conclude that this event represents a setback in the overwash/rollover behavior required for barrier transgression.

Understanding the droplet cloud and spray dynamics is important on the study of the ocean surface and marine boundary layer.The role that the wave energy and the type of wave breaking plays in the resulting distribution and dynamics of droplets is yet to be understood. The aim of this work was to generate violent plunging breakers in the laboratory and analyze the spray production by the crest of the wave when it impacts in the free surface. The droplet sizes and their dynamics were measured and the effect of different wind speeds on the droplet production was also considered. It was found that the mean radius increases with the wave energy and the presence of larger droplets (radius > 2 mm) in the vertical direction increases with the presence of wind. Furthermore, the normalized distribution of droplet sizes is consistent with the distribution of ligament-mediated spray formation. Also, indications of turbulence affecting the droplet dynamics at wind speeds of 5 m/s were found. The amount of large droplets (radius >1 mm) found in this work was larger than reported in the literature. An improved estimation of the initial distribution of large droplets can largely affect the evolution of the Sea Spray Generation Function, and therefore the estimation of energy and mass transport in the marine boundary layer.

In frontal zones, water masses that are tens of kilometers in extent with origins in the mixed layer can be identified in the pycnocline for days to months. Here, we explore the pathways and mechanisms of subduction, the process by which water from the surface mixed layer makes its way into the pycnocline, using a submesoscale-resolving numerical model of a mesoscale front. By identifying Lagrangian trajectories of water parcels that exit the mixed layer, we study the evolution of dynamical properties from a statistical standpoint. Velocity and buoyancy gradients increase as water parcels experience both mesoscale (geostrophic) and submesoscale (ageostrophic) frontogenesis and subduct beneath the mixed layer into the stratified pycnocline along isopycnals that outcrop in the mixed layer. Subduction is transient and occurs in coherent regions along the front, the spatial and temporal scales of which set the scales of the subducted water masses in the pycnocline. As a result, the tracer-derived vertical transport rate spectrum is flatter than the vertical velocity spectrum. An examination of specific subduction events reveals a range of submesoscale features that support subduction. Contrary to the forced submesoscale processes that sequester low potential vorticity (PV) anomalies in the interior, we find that PV can be elevated in subducting water masses. The rate of subduction is of similar magnitude to previous studies (~100 m/year), but the pathways that are unraveled in this study along with the Lagrangian evolution of properties on water parcels, emphasize the role of submesoscale dynamics coupled with mesoscale frontogenesis.

The Southern California Bight (SCB), an eastern boundary upwelling system, is impacted by global warming, acidification and deoxygetation, and receives anthropogenic nutrients from a coastal population of 20 million people. We describe the configuration, forcing, and validation of a realistic, submesoscale resolving ocean model as a tool to investigate coastal eutrophication. This modeling system represents an important achievement because it strikes a balance of capturing the forcing by U.S. Pacific Coast-wide phenomena, while representing the bathymetric features and submesoscale circulation that affect the vertical and horizontal transport of nutrients from natural and human sources. Moreover, the model allows to run simulations at timescales that approach the interannual frequencies of ocean variability, making the grand challenge of disentangling natural variability, climate change, and local anthropogenic forcing a tractable task in the near-term. The model simulation is evaluated against a broad suite of observational data throughout the SCB, showing realistic depiction of mean state and its variability with remote sensing and in situ physical-biogeochemical measurements of state variables and biogeochemical rates. The simulation reproduces the main structure of the seasonal upwelling front, the mean current patterns, the dispersion of plumes, as well as their seasonal variability. It reproduces the mean distributions of key biogeochemical and ecosystem properties. Biogeochemical rates reproduced by the model, such as primary productivity and nitrification, are also consistent with measured rates. Results of this validation exercise demonstrate the utility of fine-scale resolution modeling in support of management decisions on local anthropogenic nutrient discharges to coastal zones.

Organic matter (OM) sulfurization can enhance the preservation and sequestration of carbon in anoxic sediments, and it has been observed in sinking marine particles from marine O2-deficient zones. The magnitude of this effect on carbon burial remains unclear, however, because the transformations that occur when sinking particles encounter sulfidic conditions remain undescribed. Here, we briefly expose sinking marine particles from the eastern tropical North Pacific O2-deficient zone to environmentally relevant sulfidic conditions (20C, 0.5 mM [poly]sulfide, two days) and then characterize the resulting solid-phase organic and inorganic products in detail. During these experiments, the abundance of organic sulfur in both hydrolyzable and hydrolysis-resistant solids roughly triples, indicating extensive OM sulfurization. Lipids also sulfurize on this timescale, albeit less extensively. In all three pools, OM sulfurization produces organic monosulfides, thiols, and disulfides. Hydrolyzable sulfurization products appear within ≤ 200-m regions of relatively homogenous composition that are suggestive of sulfurized extracellular polymeric substances (EPS). Concurrently, reactions with particulate iron oxyhydroxides generate low and fairly uniform concentrations of iron sulfide (FeS) within these same EPS-like materials. Iron oxyhydroxides were not fully consumed during the experiment, which demonstrates that organic materials can be competitive with reactive iron for sulfide. These experiments support the hypothesis that sinking, OM- and EPS-rich particles in a sulfidic water mass can sulfurize within days, potentially contributing to enhanced sedimentary carbon sequestration. Additionally, sulfur-isotope and chemical records of organic S and iron sulfides in sediments have the potential to incorporate signals from water column processes.

Prediction of rapid intensification in tropical cyclones prior to landfall is a major societal issue. While air-sea interactions are clearly linked to storm intensity, the connections between the underlying thermal conditions over continental shelves and rapid intensification are limited. Here, an exceptional set of in-situ and satellite data are used to identify spatial heterogeneity in sea surface temperatures across the inner core of Hurricane Sally (2020), a storm that rapidly intensified over the shelf. A leftward shift in the region of maximum cooling was observed as the hurricane transited from the open gulf to the shelf. This shift was generated, in part, by the surface heat flux in conjunction the along and across-shelf transport of heat from storm-generated coastal circulation. The spatial differences in the sea surface temperatures were large enough to potentially influence rapid intensification processes suggesting that coastal thermal features need to be accounted for to improve storm forecasting as well as to better understand how climate change will modify interactions between tropical cyclones and the coastal ocean.

The ocean’s “biological pump” significantly modulates atmospheric carbon dioxide levels. However, the complexity and variability of processes involved introduces uncertainty in interpretation of transient observations and future climate projections. Much work has focused on “parametric uncertainty”, particularly determining the exponent(s) of a power-law relationship of sinking particle flux with depth. Varying this relationship’s functional form introduces additional “structural uncertainty”. We use an ocean biogeochemistry model substituting six alternative remineralization profiles fit to a reference power-law curve, to characterize structural uncertainty, which, in atmospheric pCO2 terms, is roughly 50% of the parametric uncertainty associated with varying the power-law exponent within its plausible global range, and similar to uncertainty associated with regional variation in power-law exponents. The substantial contribution of structural uncertainty to total uncertainty highlights the need to improve characterization of biological pump processes, and compare the performance of different profiles within Earth System Models to obtain better constrained climate projections.

Melt ponds play an important role in the seasonal evolution of Arctic sea ice. During the melt season, snow atop the sea ice begins to metamorphose and melt, forming ponds on the ice. These ponds reduce the albedo of the surface, allowing for increased solar energy absorption and thus further melting of snow and ice. Analyzing the spatial distribution and temporal evolution of melt ponds helps us understand the sea ice processes that occur during the summer melt season. It has been shown that the inclusion of melt pond parameters in sea ice models increases the skill of predicting the summer sea ice minimum extent. Previous studies have used remote sensing imagery to characterize surface features and calculate melt pond statistics. Here we use new observations of melt ponds obtained by the Digital Mapping System (DMS) flown onboard NASA Operation IceBridge (OIB) during two Arctic summer melt campaigns which surveyed thousands of kilometers of sea ice and resulted in more than 45,000 images. One campaign was conducted in the Beaufort Sea (July 2016), and one in the Lincoln Sea and the Arctic Ocean north of Greenland (July 2017). Using these data we expect to advance our understanding of the differences and similarities between melt pond features on young, thin sea ice seen in the Beaufort Sea versus those on multi-year ice. We have developed a pixel-based classification scheme by considering the different RGB spectral values associated with each surface type. We identify four sea ice surface types (level ice, rubbled ice, open water, and melt ponds). The classification scheme enables the calculation of parameters including melt pond fraction, ice concentration, melt pond area, and melt pond dimensions. We compare results with data from the Airborne Topographic Mapper (ATM), a laser altimeter also operated during these OIB missions. Given the extent over which the OIB data are available, regional information may be derived. Leveraging existing satellite data products, we examine whether the high-resolution airborne statistics are representative of the region and can be scaled up for comparison against satellite-derived parameters such as ice concentration and extent.

We decompose the monthly global Ocean Bottom Pressure (OBP) from GRACE(-FO) mass concentration solutions, with trends and seasonal harmonics removed from the signal, to extract 23 significant regional modes of variability. The 23 modes are analyzed and discussed considering Sea-Level Anomalies (SLA), Wind Stress Curl (WSC), and major climate indices. Two-thirds of the patterns correspond to extratropical regions and are substantially documented in other global or regional studies. Over the equatorial band, the identified modes are unprecedented, with an amplitude ranging between 0.5 and 1 centimeter. With smaller amplitude than extratropical patterns, they appear to be less correlated with the local SLA or WSC; yet, they present significantly coherent dynamics. The Pacific Ocean modes show significant correlations with the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO).

Plate motion is a remarkable Earth process and is widely ascribed to two primary driving forces: slab pull and ridge push. With the release of the first- and second-order stress fields since 1989, a few features of tectonic stresses provide strong constrain on these forces. The observed stresses are mainly distributed on the uppermost brittle part of the lithosphere. A modeling analysis, however, reveals that the stress produced by ridge push is dominantly distributed in the lower part of the lithosphere; Doglioni and Panza recently made an in-depth investigation on slab pull and found this force cannot be in accordance with observations. These findings of ridge push and slab pull suggest that there needs other force to be responsible for plate motion and tectonic stress. Here, we propose that the pressure of deep ocean water against the wall of continent yields enormous force (i.e., ocean-generated force) on the continent. The continent is fixed on the top of the lithosphere, this attachment allows ocean-generated force to be laterally transferred to the lithospheric plate. We show that this force may combine other forces to form force balances for the lithospheric plate, consequently, the African, Indian, South American, Australian, and Pacific plates obtain a movement of 4.52, 6.09, 2.11, 3.52, and 6.62 cm/yr, respectively. A torque balance modelling shows that the error between the movements calculated for 121 sample locations and the movements extracted from GSRM v.2.1 is less than 0.8 mm/yr in speed and 0.3o in azimuth.

Biogeochemical cycles in the Arctic Ocean are sensitive to the transport of materials from continental shelves into central basins by sea ice. However, it is difficult to assess the net effect of this supply mechanism due to the spatial heterogeneity of sea ice content. Manganese (Mn) is a micronutrient and tracer which integrates source fluctuations in space and time. The Arctic Ocean surface Mn maximum is attributed to freshwater, but studies struggle to distinguish sea ice and river contributions. Informed by observations from 2009 IPY and 2015 Canadian GEOTRACES cruises, we developed a three-dimensional dissolved Mn model within a 1/12 degree coupled ocean-ice model centered on the Canada Basin and the Canadian Arctic Archipelago (CAA). Simulations from 2002-2019 indicate that annually, 87-93% of Mn contributed to the Canada Basin upper ocean is released by sea ice, while rivers, although locally significant, contribute only 2.2-8.5%. Downstream, sea ice provides 34% of Mn transported from Parry Channel into Baffin Bay. While rivers are often considered the main source of Mn, our findings suggest that in the Canada Basin they are less important than sea ice. However, within the shelf-dominated CAA, both rivers and sediment resuspension are important. Climate induced disruption of the transpolar drift may reduce the Canada Basin Mn maximum and supply downstream. Other micronutrients found in sediments, such as Fe, may be similarly affected. These results highlight the vulnerability of the biogeochemical supply mechanisms in the Arctic Ocean and the subpolar seas to climatic changes.

Most marine plastic pollution originates on land. However, once plastic is at sea, it is difficult to determine its origin. Here we present a Bayesian inference framework to compute the probability that a piece of plastic found at sea came from a particular source. This framework combines information about plastic emitted by rivers with a Lagrangian simulation, and yields maps indicating the probability that a particle sampled somewhere in the ocean originates from a particular source. We applied the framework to the South Atlantic Ocean, focusing on floating river-sourced plastic. We computed the probability as a function of the particle age, at three locations, showing how probabilities vary according to the location and age. We computed the source probability of beached particles, showing that plastic found at a given latitude is most likely to come from the closest source. This framework lays the basis for source attribution of marine plastic.

The Alfred Wegener Institute Climate Model (AWI-CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice-ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max-Planck-Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI-CM performs better than the average of CMIP5 models. AWI-CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea ice extent in September over the past 30 years is 20-30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present-day climate under the strong emission scenario SSP585 are similar to the multi-model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2 to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical and Southern Ocean. Furthermore, in the northern mid-latitudes in boreal summer and autumn as well as in the southern mid-latitudes a more zonal atmospheric flow is projected throughout the year.

Reliable estimates of occurrence probabilities of sea level extremes are required in coastal planning (e.g. design floods) and to mitigate risks related to flooding. Probabilities of specific extreme events have been traditionally estimated from the observed extremes independently at each tide gauge location. However, this approach has shortcomings. Firstly, sea level observations often cover a relatively short historical time period and thus contain only a small number of extreme cases (e.g. annual maxima). This causes substantial uncertainties when estimating the distribution parameters. Secondly, exact information on sea level extremes between the tide gauge locations and incorporation of depen- dencies of adjacent stations is often lacking in the analysis. A partial remedy to these issues is to exploit spatial dependencies exhibited by the sea level extremes. These dependencies emerge from the fact that sea level variations are often driven by the same physical and dynamical factors at the neighboring stations. Bayesian hierarchical modeling offers a way to model these dependencies. The model structure allows to share information on sea level extremes between the neighboring stations and also provides a natural way to represent modeling uncertainties. In this study, we use Bayesian hierarchical modeling to estimate return levels of annual sea level maximum in the Finnish coastal region, located along the north-east part of the Baltic Sea. As annual maxima are studied, we use the generalized extreme value (GEV) distribution as the basis of our model. To tailor the model specifically for the target region, spatial dependencies are modeled using physical covariates which reflect the distinct geometry of the Baltic Sea. We illustrate the added value of the hierarchical model in comparison to the traditional one using the available long-term tide gauge time series in Finland. Careful analysis of the sources of uncertainties is necessary when extrapolating the return level estimates into the future. This work is a part of project PREDICT (Predicting extreme weather and sea level for nuclear power plant safety) that supports nuclear power plant safety in Finland.

Areas covered in compact sea ice are often assumed to prohibit upper ocean photosynthesis. Yet under-ice phytoplankton blooms (UIBs) have increasingly been observed in the Arctic, driven by anthropogenic changes to the optical properties of Arctic sea ice. Here we show the Southern Ocean can also support widespread UIBs. Using under ice-enabled BGC-Argo float data, we detail numerous high phytoplankton biomass events below compact sea ice preceding seasonal ice retreat, and classify 12 distinct UIB events. Using joint light, sea ice, and ocean conditions obtained from the ICESat-2 laser altimeter and 11 climate model contributions to CMIP6, we find that more than 4 million square kilometers of the compact-ice-covered Southern Ocean could support these events in late spring and early summer.

We highlight a mechanism for the co-production of research with local communities as a means of elevating the social relevance of the geosciences, increasing the potential for broader and more diverse participation. We outline the concept of an “equitable exchange” as an ethical framework guiding these interactions. This principled research model emphasizes that “currencies”- the rewards and value from participating in research - may differ between local communities and geoscientists. For those engaged in this work, an equitable exchange emboldens boundary spanning geoscientists to bring their whole selves to the work, providing a means for inclusive climates and rewarding cultural competency.

We investigate the Chukchi and the Beaufort seas, where salty and warm Pacific Water flows in from the Bering Strait and interacts with the sea ice, contributing to its summer melt. For the first time, thanks to in-situ measurements recorded by two saildrones deployed during summer 2019 and to refined sea ice filtering in satellite L-Band radiometric data, we demonstrate the ability of satellite Sea Surface Salinity (SSS) observed by SMOS and SMAP to capture SSS freshening induced by sea ice melt, referred to as meltwater lenses (MWL). The largest MWL observed by the saildrones during this period occupied a large part of the Chukchi shelf, with a SSS freshening reaching -5 pss. it persisted for up to one month, to this MWL, induced low SSS pattern which restricted the transfer of air-sea momentum to the upper, as illustrated by measured wind speed and vertical profiles of currents. Combined with satellite-based Sea Surface Temperature, satellite SSS provides a monitoring of the different water masses encountered in the region during summer 2019. Using sea ice concentration and estimated Ekman transport, we analyse the spatial variability of sea surface properties after the sea ice edge retreat over the Chukchi and the Beaufort seas. The two MWL captured by both, the saildrones and the satellite measurements, result from different dynamics. Over the Beaufort Sea, the MWL evolution follows the meridional sea ice retreat, whereas in the Chukchi Sea, a large persisting MWL is generated by advection of a sea ice filament.

This study isolates the influence of sea ice mean state on pre-industrial climate and transient 1850-2100 climate change within a fully coupled global model: The Community Earth System Model version 2 (CESM2). The CESM2 sea ice model physics is modified to increase surface albedo, reduce surface sea ice melt, and increase Arctic sea ice thickness and late summer cover. Importantly, increased Arctic sea ice in the modified model reduces a present-day late-summer ice cover bias. Of interest to coupled model development, this bias reduction is realized without degrading the global simulation including top-of-atmosphere energy imbalance, surface temperature, surface precipitation, and major modes of climate variability. The influence of these sea ice physics changes on transient 1850-2100 climate change is compared within a large initial condition ensemble framework. Despite similar global warming, the modified model with thicker Arctic sea ice than CESM2 has a delayed and more realistic transition to a seasonally ice free Arctic Ocean. Differences in transient climate change between the modified model and CESM2 are challenging to detect due to large internally generated climate variability. In particular, two common sea ice benchmarks - sea ice sensitivity and sea ice trends - are of limited value for comparing models with similar global warming. More broadly, these results show the importance of a reasonable Arctic sea ice mean state when simulating the transition to an ice-free Arctic Ocean in a warming world. Additionally, this work highlights the importance of large initial condition ensembles for credible model-to-model and observation-model comparisons.

The Indian Ocean is warming rapidly, with widespread effects on regional weather and global climate. Sea-surface temperature records indicate this warming trend extends back to the beginning of the 20th century, however the lack of a similarly long instrumental record of interior ocean temperatures leaves uncertainty around the subsurface trends. Here we utilize unique temperature observations from three historical German oceanographic expeditions of the late 19th and early 20th centuries: SMS Gazelle (1874–1876), Valdivia (1898–1899), and SMS Planet (1906–1907). These observations reveal a mean 20th century ocean warming that extends over the upper 750 m, and a spatial pattern of subsurface warming and cooling consistent with a 1°–2° southward shift of the southern subtropical gyre. These interior changes occurred largely over the last half of the 20th century, providing observational evidence for the acceleration of a multidecadal trend in subsurface Indian Ocean temperature.

Submesoscale currents, comprising fronts and mixed-layer eddies, exhibit a dual cascade of kinetic energy: a forward cascade to dissipation scales at fronts and an inverse cascade from mixed-layer eddies to mesoscale eddies. Within a coarse-graining framework using both spatial and temporal filters, we show that this dual cascade can be captured in simple mathematical form obtained by writing the cross-scale energy flux in the local principal strain coordinate system, wherein the flux reduces to the the sum of two terms, one proportional to the convergence and the other proportional to the strain. The strain term is found to cause the inverse energy flux to larger scales while an approximate equipartition of the convergent and strain terms capture the forward energy flux, demonstrated through model-based analysis and asymptotic theory. A consequence of this equipartition is that the frontal forward energy flux is simply proportional to the frontal convergence. In a recent study, it was shown that the Lagrangian rate of change of quantities like the divergence, vorticity and horizontal buoyancy gradient are proportional to convergence at fronts implying that horizontal convergence drives frontogenesis. We show that these two results imply that the primary mechanism for the forward energy flux at fronts is frontogenesis. We also analyze the energy flux through a Helmholtz decomposition and show that the rotational components are primarily responsible for the inverse cascade while a mix of the divergent and rotational components cause the forward cascade, consistent with our asymptotic analysis based on the principal strain framework.

Knowledge of the chemical speciation of particulate manganese (pMn) is important for understanding the biogeochemical cycling of Mn and other particle-reactive elements. Here, we present the synchrotron-based X-ray spectroscopy-derived average oxidation state (AOS) of pMn in the surface Arctic Ocean collected during the U.S. GEOTRACES Arctic cruise (GN01) in 2015. We show that the pMn AOS is less than 2.4 when sampled during the day and more than ~3.0 when sampled at night. We hypothesize that an active light-dependent redox cycle between dissolved Mn and particulate Mn(III/IV) exists during the day-night cycle in the surface Arctic Ocean, which occurs on the timescale of hours. The magnitude of observed pMn AOS is likely determined by the net effect of the length of the previous night and integrated light level before the end of pMn sampling.