Natural hazards such as floods, hurricanes, heatwaves, and wildfires cause significant economic losses (e.g., agricultural and property damage) as well as a high number of fatalities. Natural hazards are often driven by univariate or multivariate hydrometeorological drivers. Therefore, it is crucial to understand how and which hydrometeorological variables (i.e., drivers) combine to contribute to the impacts of these hazards. Additionally, when multiple drivers are associated with a hazard, traditional univariate risk assessment approaches are insufficient to cover the full spectrum of impact-relevant conditions originating from different combinations of multiple drivers. Based on historical socioeconomic loss data, we develop an impact-based approach to assess the influence of different hydrometeorological drivers on the impacts caused by different hazard event types. We use the Spatial Hazard Events and Losses Database for the United States (SHELDUS™) to identify the historical hazard events that caused socioeconomic impacts (property and crop damage, injuries, and fatalities) in our case study area, Miami-Dade County, in south Florida. For 9 different hazard types, we obtained data for 13 hydrometeorological drivers from historical in-situ observations and reanalysis products corresponding to the timing and locations of the hazard events found in the SHELDUS database. The relative importance of each hazard driver in generating impacts and the frequency of multiple drivers was then assessed. We found that many high-impact events were caused by multiple hydrometeorological drivers (i.e., compound events). For example, 61% of the recorded flooding events were compound events rather than univariate hazards and these contributed 99% of total property damage and 98.2% of total crop damage in Miami-Dade County. For several hazards, such as hurricanes/tropical storms and wildfires, all the events that caused damage are classified as compound events in our framework. Our findings emphasize the benefit of including socioeconomic impact information when analyzing hazard events, as well as the importance of analyzing all relevant hydrometeorological drivers to identify compound events.

The northern Antarctic Peninsula (NAP) is a key region of the Southern Ocean due to its complex ocean dynamics, distinct water mass sources, and the climate-driven changes taking place in the region. Despite the importance of macronutrients in fuelling primary production and driving the strong carbon uptake and storage, little is known about their spatiotemporal variability along the NAP. Hence, we explored a 24-year time series in this region, primarily sampled by the Brazilian High Latitude Group, to understand the processes involved in the spatial and interannual variability of macronutrients. We found high macronutrients concentrations, even in surface waters and under strong phytoplankton blooms. Minimum concentrations of dissolved inorganic nitrogen (16 μmol/ kg), phosphate (0.7 μmol/kg), and silicic acid (40 μmol/kg) along the NAP are higher than those recorded in surrounding regions. The main source of macronutrients is the intrusions of modified Circumpolar Deep Water (mCDW), and this is enhanced by local sources, such as organic matter remineralisation, water mass mixing, and mesoscale structures. However, we identified a depletion in silicic acid due to influence of Dense Shelf Water (DSW) from the Weddell Sea. Macronutrient concentrations shows substantial interannual variability driven by the balance between the intrusions of mCDW and advection of DSW, which is largely modulated by the Southern Annular Mode and to some extent by El Niño-Southern Oscillation. These findings are critical to improving our understanding of the natural variability of this Southern Ocean ecosystem and how it is responding to climate changes. Associate Editor

As the waters of marine primary production, the euphotic zone is the primary living environment for aquatic organisms. Eddies account for 90% of the ocean’s kinetic energy and affect marine organisms’ habitats by the excitation of vertical velocities and the horizontal advection of nutrients and ecosystems. Satellite observations indicate that anticyclones mainly deepen the euphotic zone depth, while cyclones do the opposite. Eddy-induced euphotic zone depth is inversely correlated with the eddy-induced chlorophyll concentration. The anomalies reach 5m on average in the region of high eddy amplitude and frequent eddy occurrence. In addition, we found that the anomalies have an extreme value in each of the 5°-23° and 23°-55° and reach a maximum at around 40 degrees with the increase of latitude. Secondly, the anomalies are characterized by large near-summer and small near-winter. In the eddy-center coordinate system, the minus gradient direction of the negative anomaly is consistent with the background flow field and the direction of eddy movement. Meanwhile, the anomaly increases along the radial direction to about 0.2r and then decreases. Finally, there is a significant linear correlation between the anomaly magnitude and eddy amplitude. The conclusion of this research and related mechanism explanation contributes to marine biology research and conservation, estimates of marine primary productivity, and understanding of the biogeochemical properties of eddy modulation in the upper water column.

Oceanographic structure is often represented as a collection of vertical profiles, i.e. temperature, salinity, and/or biogeochemical values at various depths. These profiles contain information about water mass structures and the boundaries between them, which are consequences of the integrated effects of water mass formation, advection, and destruction. In recent years, researchers have applied various unsupervised profile classification methods in an attempt to identify a set of “profile types” and the spatially coherent regimes associated with them. These efforts have identified a number of regimes that are consistent with existing oceanographic knowledge, and they have also identified previously under-appreciated structural differences. However, as this application area matures, questions remain about the strengths and limitations of these methods as applied to oceanography. A key question is “under what circumstances does unsupervised profile classification produce interpretable and scientifically useful knowledge?” Here, I explore the mechanisms and parameters of various unsupervised learning approaches, in particular Gaussian Mixture Modeling, in an attempt to clarify the conditions under which unsupervised learning produces robust, interpretable, and trustworthy understanding. As with pattern classification approaches in general, there is a tradeoff between interpretability and accuracy (the ability of the method to represent the full underlying structure of the system). As a case study, I explore an unsupervised profile classification application in the Weddell Gyre. I show that, using a combination of statistical guidance, expert judgment, and traditional oceanographic analysis, we can, in some cases, increase the interpretability of a profile classification model with acceptable losses in accuracy. The goal is to elucidate the conditions under which unsupervised learning can be fully integrated into the oceanographic knowledge generation process, both by confronting existing understanding and by highlighting new avenues for exploration.

Intense short-term wind events can flush multiple-inlet systems and even renew the water entirely. Nonetheless, little is known about the effect of wind variations at seasonal and interannual scales on the flushing of such systems. Here, we computed two Lagrangian transport time scales (LTTS), the residence and exposure times, for a multiple-inlet system (the Dutch Wadden Sea) over 36 years using a realistic numerical model simulation. Our results reveal pronounced seasonal and interannual variability in both system-wide LTTS. The seasonality of the LTTS is strongly anti-correlated to the wind energy from the prevailing directions, which are from the southwesterly quadrant and coincidentally aligned with the geographical orientation of the system. This wind energy, which is stronger in autumn-winter than in spring-summer, triggers strong flushing (and hence low values of the LTTS) during autumn-winter. The North Atlantic Oscillation (NAO) and the Scandinavia Pattern (SCAN) are shown to be the main drivers of interannual variability in the local wind and, ultimately, in both LTTS. However, this coupling is much more efficient during autumn-winter when these patterns show larger values and variations. During these seasons, a positive NAO and a negative SCAN induce stronger winds in the prevailing directions, enhancing the flushing efficiency of the system. The opposite happens during positive SCAN and negative NAO, when weaker flushing during autumn-winter is observed. Thus, large-scale atmospheric patterns strongly affect the interannual variability in flushing and are potential drivers of the long-term ecology and functioning of multiple-inlet systems.

Continental margins play an essential role in global ocean biogeochemistry and the carbon cycle; however, global assessments of this role remain highly uncertain. This uncertainty arises from large variability over a broad range of temporal and spatial scales of the processes that characterize these environments. High-resolution simulations with ocean biogeochemical models have emerged as essential tools to advance biogeochemical assessments at regional scales. Here, we examine the processes and balances for carbon, oxygen, and nitrogen cycles along the U.S. West Coast in an 11-year hindcast simulation with a submesoscale-permitting oceanic circulation-biogeochemical model. We highlight the importance of biogeochemical cycles on the continental shelf, and their connection to the broader regional context encompassing the California Current System. On the shelf, coastal and wind stress curl upwelling drive a vigorous overturning circulation that supports biogeochemical rates and fluxes that are approximately twice as large as offshore. Exchanges with the proximate sediments, submesoscale shelf currents, bottom boundary layer transport, and intensified cross-shelf export of shelf-produced materials impact coastal and open-ocean balances. While regional variability prevents extrapolation of our results to global margins, our approach provides a powerful tool to identify the dominant dynamics in different shelf setting and quantify their large-scale consequences.

During hurricane season, the U.S. Geological Survey (USGS) forecasts the probability of coastal change prior to named storm landfall. Forecasts both quantify potential storm effects on the sandy coastlines and test our understanding of the drivers of coastal change. The forecasts can also be used to aid emergency response and management decisions in real-time. This study analyzed the skill of three USGS forecasts of coastal change, defined as the probability of collision, overwash, and inundation (PCOI) along the approximately 250 km of Louisiana coast from Hurricanes Laura, Delta, and Zeta in 2020. To test forecast skill, forecasts were compared with coastal changes identified in post-storm emergency response aerial imagery. Forecasts accurately identified areas where overwash and inundation were likely (true positive forecast ratios >0.75). Forecasts also produced an overly conservative estimation of overwash and inundation (false positive forecast ratios 0.56). High false positive forecast ratios for overwash and inundation may be the result of an overestimate in forecast extreme water levels.

Two coupled climate models, differing primarily in horizontal resolution and treatment of mesoscale eddies, were used to assess the impact of perturbations in wind stress and Antarctic ice sheet (AIS) melting on the Southern Ocean meridional overturning circulation (SO MOC), which plays an important role in global climate regulation. The largest impact is found in the SO MOC lower limb, associated with the formation of Antarctic Bottom Water (AABW), which in both models is enhanced by wind and weakened by AIS meltwater perturbations. Even though both models under the AIS melting perturbation show similar AABW transport reductions of 4-5 Sv (50-60%), the volume deflation of AABW south of 30˚S is four times greater in the higher resolution simulation (-20 vs -5 Sv). Water mass transformation (WMT) analysis reveals that surface-forced dense water formation on the Antarctic shelf is absent in the higher resolution and reduced by half in the lower resolution model in response to the increased AIS melting. However, the decline of the AABW volume (and its inter-model difference) far exceeds the surface-forced WMT changes alone, which indicates that the divergent model responses arise from interactions between changes in surface forcing and interior mixing processes. This model divergence demonstrates an important source of uncertainty in climate modeling, and indicates that accurate shelf processes together with scenarios accounting for AIS melting are necessary for robust projections of the deep ocean’s response to anthropogenic forcing and role as the largest sink in Earth’s energy budget.

Persistent warming and water cycle change due to anthropogenic climate change modifies the temperature and salinity distribution of the ocean over time. This ‘forced’ signal of temperature and salinity change is often masked by the background internal variability of the climate system. Analysing temperature and salinity change in watermass-based coordinate systems has been proposed as an alternative to traditional Eulerian (e.g., fixed-depth, zonally-averaged) co-ordinate systems. The impact of internal variability is thought to be reduced in watermass co-ordinates, enabling a cleaner separation of the forced signal from background variability - or a higher ‘signal-to-noise’ ratio. Building on previous analyses comparing Eulerian and water-mass-based one-dimensional coordinates, here we recast two-dimensional co-ordinate systems - temperature-salinity (𝑇 − 𝑆), latitude-longitude and latitude-depth - onto a directly comparable equal-volume framework. We compare the internal variability, or ‘noise’ in temperature and salinity between these remapped two-dimensional co-ordinate systems in a 500 year pre-industrial control run from a CMIP6 climate model. We find that the median internal variability is lowest (and roughly equivalent) in 𝑇 − 𝑆 and latitude-depth space, compared with latitude-longitude co-ordinates. A large proportion of variability in 𝑇 − 𝑆 and latitude-depth space can be attributed to processes which operate over a timescale greater than 10 years. Overall, the signal-to-noise ratio in 𝑇 − 𝑆 co-ordinates is roughly comparable to latitude-depth co-ordinates, but is greater in regions of high historical temperature change. Conversely, latitude-depth co-ordinates have greater signal-to-noise ratio in regions of historical salinity change. Thus, we conclude that the climatic temperature change signal can be more robustly identified in watermass-co-ordinates.

Mesoscale eddies are abundant in the global oceans and known to affect marine biogeochemistry. Understanding their cumulative impact on the air-sea carbon dioxide (CO2) flux is likely important for quantifying the ocean carbon sink. Here, observations and Lagrangian tracking are used to estimate the air-sea CO2 flux of 67 long lived (i.e. > 1 year) mesoscale eddies in the South Atlantic Ocean over a 16 year period. We find that anticyclonic eddies originating from the Agulhas retroflection and cyclonic eddies originating from the Benguela upwelling act as net CO2 sinks over their lifetimes. In combination, the eddies significantly enhanced the CO2 sink into the South Atlantic Ocean by 0.08 ± 0.01%. Although this modification appears small, long lived eddies account for just ~0.4% of global ocean eddies and eddy activity is increasing; therefore, explicitly resolving eddy processes within all models used to assess the ocean carbon sink would appear critical.

Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Their seasonal development features fast and local changes in fractions of surface types demonstrating the necessity of improving melt pond fraction (MPF) products. We present a renewed method to extract MPF from Sentinel-2 satellite imagery, which is evaluated by MPF products from higher resolution satellite and helicopter-borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs amount to 17 % before and 23 % after the major drainage. Arctic-wide analysis of MPF for years 2017-2021 shows a consistent seasonal cycle in all regions and years.

Estimating the three geophysical variables significant wave height (SWH), sea surface height, and wind speed from satellite altimetry continues to be challenging in the coastal zone because the received radar echoes exhibit significant interference from strongly reflective targets such as mud banks, sheltered bays, ships etc. Fully focused SAR (FF-SAR) processing exhibits a theoretical along-track resolution of up to less than half a metre. This suggests that the application of FF-SAR altimetry might give potential gains over unfocused SAR (UF-SAR) altimetry to resolve and mitigate small-scale interferers in the along-track direction to improve the accuracy and precision of the geophysical estimates. The objective of this study is to assess the applicability of FF-SAR-processed Sentinel-6 Michael Freilich (S6-MF) coastal altimetry data to obtain SWH estimates as close as possible to the coast. We have developed a multi-mission FF-SAR processor and applied the coastal retracking algorithm CORALv2 to estimate SWH. We assess different FF-SAR and UF-SAR processing configurations, as well as the baseline Level-2 product from EUMETSAT, by comparison with the coastal, high-resolution SWAN-Kuststrook wave model from the Deltares RWsOS North Sea operational forecasting system. This includes the evaluation of the correlation, the median offset, and the percentage of cycles with high correlation as a function of distance to the nearest coastline. Moreover, we analyse the number of valid records and the L2 noise of the records. The case study comprises five coastal crossings of S6-MF that are located along the Dutch coast and the German coast along the East Frisian Islands in the North Sea. We find that the FF-SAR-processed dataset with a Level-1b posting rate of 140 Hz shows the greatest similarity with the wave model. We achieve a correlation of ~0.8 at 80% of valid records and a gain in precision of up to 29% of FF-SAR vs UF-SAR for 1-3 km from the coast. FF-SAR shows, for all cycles, a high correlation of greater than or equal to 0.8 for 1-3 km from the coast. We estimate the decay of SWH from offshore at 30 km to up to 1 km from the coast to amount to 26.4%+-3.1%.

For the first time in 2015, four dedicated hydrographic cruises – one in each season – took place around the Canary Islands to determinate the seasonality of the flows at the eastern boundary of the North Atlantic Subtropical Gyre. The Canary Current (CC) is the eastern boundary current of the North Atlantic Subtropical Gyre and links the Azores Current with the North Equatorial Current. The CC shows a seasonal behavior in its path and strength, flowing on its easternmost position in winter (3.4±0.3 Sv), through the Canary Islands in spring (2.1±0.7 Sv) and summer (2.0±0.6 Sv) and on its westernmost position in fall (3.2±0.4 Sv). At the Lanzarote Passage (LP), the dominant flow is southward except in fall, where a northward transport is observed at surface (1.1±0.3 Sv) and intermediate (1.3±0.2 Sv) layers. A historical composite observational seasonal cycle is built from all the available estimations on the area and fits the 2015 seasonal cycle. The LP seasonal cycle and seasonal amplitude match the seasonal cycle of the Atlantic Meridional Overturning Circulation (AMOC) measured by the RAPID-MOCHA data array.

The causes of the variations in CO2 of the past million years remain poorly understood. Imbalances between the input of elements from rock weathering and their removal from the atmosphere-ocean-biosphere system to the lithosphere likely contributed to reconstructed changes. We employ the Bern3D Earth system model of intermediate complexity to investigate carbon-climate responses to step-changes in the weathering input of phosphorus, alkalinity, carbon, and carbon isotope ratio (δ13C) in simulations extending up to 600,000 years. CO2 and climate approach a new equilibrium within a few ten thousand years, whereas the equilibration lasts several hundred thousand years for δ13C. These timescales represent a challenge for the initialization of sediment-enabled models and unintended drifts may be larger than forced signals in simulations of the last glacial-interglacial cycle. Changes in dissolved CO2 change isotopic fractionation during marine photosynthesis and δ13C of organic matter. This mechanism and changes in the organic matter export cause distinct spatio-temporal perturbations in δ13C of dissolved inorganic carbon. A cost-efficient emulator is built with the Bern3D responses and applied in contrasting literature-based weathering histories for the past 800,000 years. Differences between scenarios for carbonate rock weathering reach around a third of the glacial-interglacial CO2 amplitude, 0.05 ‰ for δ13C, and exceed reconstructed variations in marine carbonate ion. Plausible input from the decomposition of organic matter on shelves causes variations of up to 10 ppm in CO2 , 4 mmol m−3 in CO2−3, and 0.09‰ in δ13C. Our results demonstrate that weathering-burial imbalances are important for past climate variations.

Distributed Acoustic Sensing (DAS) enables data acquisition for underwater Earth Science with unprecedented spatial resolution. Submarine fibre optic cables traverse sea bottom features that can lead to suspended or decoupled cable portions, and are exposed to the ocean dynamics and to high rates of marine erosion or sediment deposition, which may induce temporal variations of the cable’s mechanical coupling to the ocean floor. Although these spatio-temporal fluctuations of the mechanical coupling affect the quality of the data recorded by DAS, and determine whether a cable section is useful or not for geophysical purposes, the detection of unsuitable cable portions has not been investigated in detail. Here, we report on DAS observations of two distinct vibration regimes of seafloor fibre optic cables: a high-frequency (> 2 Hz) regime we associate to cable segments pinned between seafloor features, and a low-frequency (< 1 Hz) regime we associate to suspended cable sections. While the low-frequency oscillations are driven by deep ocean currents, the high-frequency oscillations are triggered by the passage of earthquake seismic waves. Using Proper Orthogonal Decomposition, we demonstrate that high-frequency oscillations excite normal modes comparable to those of a finite 1D wave propagation structure. We further identify trapped waves propagating along cable portions featuring high-frequency oscillations. Their wave speed is consistent with that of longitudinal waves propagating across the steel armouring of the cable. The DAS data on cable sections featuring such cable waves are dominated by highly monochromatic noise. Our results suggest that the spatio-temporal evolution of the mechanical coupling between fibre optic cables exposed to the ocean dynamics and the seafloor can be monitored through the combined analysis of the two vibration regimes presented here, which provides a DAS-based method to identify underwater cable sections unsuitable for the analysis of seismic waves.

Significant multi-centennial climate variability with a clear peak at approximately 200 years is found in a pre-industrial control simulation conducted with the EC-Earth3 climate model. The oscillation mainly emerges from the North Atlantic and appears to be closely associated with the Atlantic Meridional Overturning Circulation (AMOC). By examining the salinity advection feedback, we find that the perturbation flow of mean subtropical-subpolar salinity gradients in the subpolar area governs as positive feedback to the AMOC anomaly. Meanwhile, the mean advection of salinity anomalies and the vertical mixing or convection acts as negative feedback to restrain the AMOC anomaly. In a warmer climate, although the AMOC becomes weaker, such low-frequency variability still exists, indicating the robustness of the salinity advection feedback mechanism.

Simple analytic models developed in this study are applied to long-term averages of reanalysis surface salinity data to quantify two fundamental properties of ocean currents. The first model is based on the new Freshening Length schema and its application to the Irminger Current yields a ratio of about 5 between the turbulent entrainment rates of surrounding fresher surface waters west and east of Greenland. The second model is based on the steady solution of the advection-diffusion equation subject to suitable boundary conditions. The application of this model to the spreading of fresh, snow-melt, water from the delta of the Po river in the northwest Adriatic Sea into the rest of the Sea yields a ratio of $8 \times 10^4$ m between the eddy exchange coefficient and the speed of advection in the Sea

Observations suggest that the tropical Pacific Ocean has lost oxygen since the 1960s leading to the expansion of its oxygen minimum zone (OMZ). Attribution to anthropogenic forcing is, however, difficult because of limited data availability and the large natural variability introduced by the Pacific Decadal Oscillation (PDO). Here, we evaluate the PDO influence on oxygen dynamics and OMZ extent using observations and hindcast simulations from two global ocean circulation models (NEMO-PISCES, MOM6-COBALT). In both models, the tropical Pacific oxygen content decreases by about 30 Tmol.decade$^{-1}$ and the OMZ volume expands by $1.3\times10^5$ km$^3$.decade$^{-1}$ during PDO positive phases, while variations of similar magnitude but opposite sign are simulated during negative phases. Changes in equatorial advective oxygen supply, partially offset by biological demand, control the oxygen response to PDO. Observations which cover 39\% of the tropical Pacific volume only partially capture spatio-temporal variability, hindering the separation of anthropogenic trend from natural variations.

Mesoscale eddies are unresolved in most of today’s global ocean models, and their effect on the large-scale ocean circulation needs to be parameterized. Greatbatch and Lamb (1990, GL90) suggested an eddy form stress parameterization that mixes geostrophic momentum in the vertical. The GL90 vertical viscosity scheme, which is equivalent to the Gent and McWilliams (1990, GM90) parameterization under the geostrophic assumption, has seen only very limited use, and exclusively in models that use z-coordinates and are of very coarse resolution. In this paper, we explore the GL90 parameterization in an idealized isopycnal coordinate model, both from a theoretical and practical perspective. We further compare the effects of the GM90 and GL90 parameterizations across a range of non-eddying to eddy-permitting resolutions. From a theoretical perspective, the GL90 parameterization is more attractive than the GM90 scheme for isopycnal coordinate models because GL90 provides an interpretation that is fully consistent with thickness-weighted isopycnal averaging, while GM90 cannot be entirely reconciled with any fully isopycnal averaging framework. From a practical perspective, the GL90 and GM90 parameterizations lead to extremely similar energy levels, flow and vertical structure, even though their energetic pathways are very different. The equivalence holds true from non-eddying through eddy-permitting resolution. We conclude that in isopycnal coordinate models, the GL90 parameterization provides a good–if not equivalent–alternative to the GM90 parameterization. The GL90 parameterization is more advantageous in terms of computational efficiency, ease of implementation, and numerical stability.

Temperature is central for ocean science but is still poorly sampled on the deep ocean. Here, we show that Distributed Acoustic Sensing (DAS) technology can convert several kilometer long seafloor fiber-optic (FO) telecommunication cables into dense arrays of temperature anomaly sensors with milikelvin (mK) sensitivity, allowing us to monitor oceanic processes such as internal waves and upwelling with unprecedented detail. We validate our observations with oceanographic in-situ sensors and an alternative FO technology. Practical solutions and recent advances are outlined to obtain continuous absolute temperatures with DAS at the seafloor. Our observations grant key advantages to DAS over established temperature sensors, showing its transformative potential for thermometry in ocean sciences and hydrography.

We examine the effects of the submesoscale in mediating the response to projected warming of phytoplankton new production and export using idealized biogeochemical tracers in a high-resolution regional model of the Porcupine Abyssal Plain region of the North Atlantic. We quantify submesoscale effects by comparing our control run to an integration in which submesoscale motions have been suppressed using increased viscosity. The warming climate over the 21st century reduces resolved submesoscale activity by a factor of 2-3. Annual new production is slightly reduced by submesoscale motions in a climate representative of the early 21st-century and slightly increased by submesoscale motions in a climate representative of the late 21st-century. Resolving the submesoscale, however, does not strongly impact the projected reduction in annual production under representative warming. Organic carbon export from the surface ocean includes both direct sinking of detritus (the biological gravitational pump) and advective transport mediated pathways; the sinking component is larger than advectively mediated transport by up to an order of magnitude across a wide range of imposed sinking rates. Submesoscales are responsible for most of the advective carbon export, however, which is thus largely reduced by a warming climate. In summary, our results demonstrate that resolving more of the submesoscale has a modest effect on present-day new production, a small effect on simulated reductions in new production under global warming, and a large effect on advectively-mediated export fluxes.

In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

While it has been recognized for some time that large-amplitude nonlinear internal waves (NLIW) can mobilise and transport sediment, quantitative observations of this process are rare. Rarer still are accompanying measurements or even estimates of suspended sediment mass concentration (SSC) during the passage of NLIW. Here we present high resolution observations of NLIW and the SSC response within the bottom boundary layer. The observations were made in 2017 in the Browse Basin on Australia’s Northwest Shelf in 250 m of water. We compare two direct calibration methods designed to overcome the inherent difficulty of directly observing SSC in deeper ocean environments, and employ Bayesian methods to estimate the uncertainty in SSC. Both calibration methods were used as bench-marking to infer SSC from a range of instrumentation deployed on a bottom-lander frame (acoustics, optical, and laser scattering). Estimates of near-bed SSC, with uncertainty, during NLIW passages are presented for each instrument. During a large NLIW event, the peak mean SSC estimate was 102 mg L$^{-1}$ with 95\% credible intervals of 93 and 112 mg L$^{-1}$, 0.87 m above the sea bed. We also examine the propagation of uncertainty to several derived quantities, such as SSC gradients. This work is the first step towards the quantitative analysis of sediment dynamics needed to develop parameterized models associated with the passage of NLIW.

We describe a framework for the simultaneous estimation of model parameters in a partial differential equation using sparse observations. Monte Carlo Markov Chain (MCMC) sampling is used in a Bayesian framework to estimate posterior probability distributions for each parameter. We describe the necessary components of this approach and its broad potential for application in models of unsteady processes. The framework is applied to three case studies, of increasing complexity, from the field of cohesive sediment transport. We demonstrate that the framework can be used to recover posterior distributions for all parameters of interest and the results agree well with independent estimates (where available). We also demonstrate how the framework can be used to compare different model parameterizations and provide information on the covariance between model parameters.