Attribution of the ocean acidification (OA) signal in estuarine carbonate system observations is necessary for quantifying the impacts of global anthropogenic emissions on water quality, and informing managers of the efficacy of potential mitigation options. We present an analysis of observational data to characterize dynamics and drivers of seasonal carbonate system variability in two seagrass habitats of Puget Sound, WA, USA, and estimate how carbon accumulations due to anthropogenic emissions interact with these drivers of carbonate chemistry to determine seasonally resolved rates of acidification in these habitats. Three independent simulations of accumulation from 1765 to 2100 were run using two previously published methods and one novel method for estimation. Our results revealed persistent seasonal differences in the magnitude of carbonate system responses to anthropogenic emissions caused by seasonal metabolic changes to the buffering capacity of estuarine waters. The seasonal variability of and is increased (while that of is decreased) and acidification rates are accelerated when compared with open-ocean estimates, highlighting how feedbacks between local metabolism and can control the susceptibility of estuarine habitats to OA impacts. The changes in seasonal variability can shorten the timeline to exceedance of established physiological thresholds for endemic organisms and existing Washington State water quality criteria for pH. We highlight how estimation uncertainties manifest in shallow coastal waters and limit our ability to predict impacts to coastal organisms and ecosystems from anthropogenic emissions.

A nonlinear frequency-domain model and a probabilistic wave breaking model have been employed together to simulate the propagation of nearshore wave breaking and to provide estimates of related statistical quantities such as skewness and asymmetry. This combination of models requires a pre-specification of the frequency dependence of dissipation. Prior work has suggested that a frequency-squared weighting for the dissipation term is most appropriate via physical arguments. However, the original frequency distribution function significantly underpredicts the higher-order moments, particularly the accuracy of asymmetry predictions is in need of further improvement. An intensity of frequency dependence for the breaking-induced damping coefficient is introduced here to further adjust the dissipation function in order to increase the accuracy of asymmetry predictions. By correcting the frequency dependence function with a new form of frequency dependence in the breaking coefficient, the model results are in better agreement with the measurements of the spectrum and higher-order statistics, as well as with the free surface elevation measurements. It is also seen from testing the model with three different cases that the more evident the influence of the breaking mechanism is on the wave transformation process, the more pronounced the contribution of this modification is.

The Bellingshausen Sea hosts heat transport onto the continental shelf, potentially enhancing ice shelf basal melt. Here, we use the GLORYS12V1 1993-2018 reanalysis to identify physical processes that set seasonal and interannual variability of water mass properties in the Eltanin and Latady Bays on the southern Bellingshausen Sea continental shelf. Annual means of potential temperature from 300 m to the seabed reveal interannual variability and allow separation into warm and cold regimes. The Amundsen Sea Low (ASL) is more intense and extends further east during the warm regime than the cold regime. In the warm regime, a wind-induced reduction of sea ice concentration near the coast increases surface heat loss, convection, and formation of cold dense water in winter, associated with a decrease in heat content of the southern Bellingshausen Sea over time and a net northward heat transport. In contrast, in the cold regime, increased sea ice concentration reduces surface heat loss and thus formation of cold, dense water. Combined with an increase in heat content over time and a net southward heat transport, this results in a warming of the southern Bellingshausen Sea. This suggests that variability in the deep water temperature in the southern Bellingshausen Sea is primarily due to local surface heat fluxes above the shelf. The variability of surface heat fluxes is related to the variability of the ASL and its influence on sea ice extent and local formation of cold, dense water in winter.

Despite their role in modulating the marine ecosystem, variability and drivers of low-oxygen events in the offshore northern Benguela Upwelling System (BenUS) have been rarely investigated due to the events' episodicity which is difficult to resolve using shipboard measurements. We address this issue using 4 months of high-resolution glider data collected between February and June 2018, 100 km offshore at 18°S. We find that oxygen (O) concentrations in the offshore northern Benguela are determined by the subsurface alternation of low-oxygen Angola-derived water and oxygenated water from the south at 100-500 m depth. We observe intermittent hypoxia (O < 60 μmol kg) which occurs on average for ∼30% of the 4 months deployment and is driven by the time-varying subsurface pulses of Angola-derived tropical water. Hypoxic events are rather persistent at depths of 300-450 m, while they are more sporadic and have weekly duration at shallower depths (100-300 m). We find extreme values of hypoxia, with O minima of 16 μmol kg, associated with an anticyclonic eddy spinning from the undercurrent flowing on the BenUS shelf and showing no surface signature. Fine-scale patchiness and water mass mixing are associated with cross-frontal stirring by a large anticyclone recirculating tropical water into the northern BenUS. The dominance of physical drivers and their high variability on short time scales reveal a dynamic coupling between Angola and Benguela, calling for long-term and high-resolution measurements and studies focusing on future changes of both tropical O minima and lateral fluxes in this region.

The exchange between estuaries and the coastal ocean is a key dynamical driver impacting nutrient and phytoplankton concentrations and regulating estuarine residence time, hypoxia, and acidification. Estuarine exchange flows can be particularly challenging to monitor because many systems have strong vertical and lateral velocity shear and sharp gradients in water properties that vary over space and time, requiring high-resolution measurements in order to accurately constrain the flux. The total exchange flow (TEF) method provides detailed information about the salinity structure of the exchange, but requires observations (or model resolution) that resolve the time and spatial co-variability of salinity and currents. The goal of this analysis is to provide recommendations for measuring TEF with the most efficient spatial sampling resolution. Results from three realistic hydrodynamic models were investigated. These model domains included three estuary types: a bay (San Diego Bay), a salt-wedge (Columbia River), and a fjord (Salish Sea). Model fields were sampled using three different mooring strategies, varying the number of mooring locations (lateral resolution) and sample depths (vertical resolution) with each method. The exchange volume transport was more sensitive than salinity to the sampling resolution. Most (>90%) of the exchange flow magnitude was captured by three to four moorings evenly distributed across the estuarine channel with a minimum threshold of 1-5 sample depths, which varied depending on the vertical stratification. These results can improve our ability to observe and monitor the exchange and transport of water masses efficiently with limited resources.

Along the west coasts of North, Central, and South America, sea surface temperature (SST) fronts are important for circulation dynamics and promoting biological activity. Prevailing equatorward winds during summer results in offshore Ekman transport and upwelling along the coast, where fronts often form between cold, upwelled water and warmer offshore waters. The interannual variability in winds, coastal upwelling, sea level anomalies, and SST in these regions have been linked to the El Niño-Southern Oscillation (ENSO), however SST fronts have received less attention. Here, we investigate the interannual variability of SST fronts off North, Central, and South America using satellite SST data spanning 1982-2018. Anomalies of fronts within 0-300 km offshore indicate interannual variability that coincides with ENSO events in most regions. Frontal activity generally decreases during El Niño events and increases during La Niña events. The decrease in fronts off Peru and Chile during El Niño coincides with the seasonal peak in frontal activity, while off the United States the decrease occurs when frontal activity is at a seasonal minimum. We also utilized satellite measurements of wind stress and sea level anomaly to investigate how ENSO oceanic and atmospheric forcing mechanisms affect frontal activity. Decreases in frontal activity during El Niño events are largely due to oceanic forcing (i.e., coastal Kelvin waves) off Central and South America and to both oceanic forcing and atmospheric teleconnections off the United States. This study furthers our understanding of the influence of ENSO on coastal upwelling regions in the eastern Pacific Ocean.

Over the Ross Sea shelf, annual primary production is limited by dissolved iron (DFe) supply. Here, a major source of DFe to surface waters is thought to be vertical resupply from the benthos, which is assumed most prevalent during winter months when katabatic winds drive sea ice formation and convective overturn in coastal polynyas, although the impact of these processes on water-column DFe distributions has not been previously documented. We collected hydrographic data and water-column samples for trace metals analysis in the Terra Nova Bay and Ross Ice Shelf polynyas during April-May 2017 (late austral fall). In the Terra Nova Bay polynya, we observed intense katabatic wind events, and surface mixed layer depths varied from ∼250 to ∼600 m over lateral distances <10 km; there vertical mixing was just starting to excavate the dense, iron-rich Shelf Waters, and there was also evidence of DFe inputs at shallower depths in the water column. In the Ross Ice Shelf polynya, wind speeds were lower, mixed layers were <300 m deep, and DFe distributions were similar to previous, late-summer observations, with concentrations elevated near the seafloor. Corresponding measurements of dissolved manganese and zinc, and particulate iron, manganese, and aluminum, suggest that deep DFe maxima and some mid-depth DFe maxima primarily reflect sedimentary inputs, rather than remineralization. Our data and model simulations imply that vertical resupply of DFe in the Ross Sea occurs mainly during mid-late winter, and may be particularly sensitive to changes in the timing and extent of sea ice production.

The Chukchi Sea is an increasing CO sink driven by rapid climate changes. Understanding the seasonal variation of air-sea CO exchange and the underlying mechanisms of biogeochemical dynamics is important for predicting impacts of climate change on and feedbacks by the ocean. Here, we present a unique data set of underway sea surface partial pressure of CO (CO) and discrete samples of biogeochemical properties collected in five consecutive cruises in 2014 and examine the seasonal variations in air-sea CO flux and net community production (NCP). We found that thermal and non-thermal effects have different impacts on sea surface CO and thus the air-sea CO flux in different water masses. The Bering summer water combined with meltwater has a significantly greater atmospheric CO uptake potential than that of the Alaskan Coastal Water in the southern Chukchi Sea in summer, due to stronger biological CO removal and a weaker thermal effect. By analyzing the seasonal drawdown of dissolved inorganic carbon (DIC) and nutrients, we found that DIC-based NCP was higher than nitrate-based NCP by 66%-84% and attributable to partially decoupled C and N uptake because of a variable phytoplankton stoichiometry. A box model with a non-Redfield C:N uptake ratio can adequately reproduce observed CO and DIC, which reveals that, during the intensive growing season (late spring to early summer), 30%-46% CO uptake in the Chukchi Sea was supported by a flexible stoichiometry of phytoplankton. These findings have important ramification for forecasting the responses of CO uptake of the Chukchi ecosystem to climate change.

We identified anomalously warm sea surface temperature (SST) events during 1980-2019 near the major upwelling center at Punta Lavapié in the central Chile-Peru Current System, using the European Centre for Medium-Range Weather Forecasts reanalysis and focusing on time scales of 10 days to 6 months. Extreme warm SST anomalies on these time scales mostly occurred in the austral summer, December through February, and had spatial scales of 1000s of km. By compositing over the 37 most extreme warm events, we estimated terms in a heat budget for the ocean surface mixed layer at the times of strongest warming preceding the events. The net surface heat flux anomaly is too small to explain the anomalous warming, even when allowing for uncertainty in mixed-layer depth. The composite mean anomaly of wind stress, from satellite ocean vector wind swath data, during the 37 anomalous warming periods has a spatial pattern similar to the resulting warm SST anomalies, analogous to previous studies in the California Current System. The weakened surface wind stress suggests reduced entrainment of cold water from below the mixed layer. Within 100-200 km of the coast, the typical upwelling-favorable wind stress curl decreases, suggesting reduced upwelling of cold water. In a 1000-km area of anomalous warming offshore, the typical downwelling-favorable wind stress curl also decreases, implying reduced downward Ekman pumping, which would allow mixed-layer shoaling and amplify the effect of the positive climatological summertime net surface heat flux.

The relative contributions of local and remote wind stress and air-sea buoyancy forcing to sea-level variations along the East Coast of the United States are not well quantified, hindering the understanding of sea-level predictability there. Here, we use an adjoint sensitivity analysis together with an Estimating the Circulation and Climate of the Ocean (ECCO) ocean state estimate to establish the causality of interannual variations in Nantucket dynamic sea level. Wind forcing explains 67% of the Nantucket interannual sea-level variance, while wind and buoyancy forcing together explain 97% of the variance. Wind stress contribution is near-local, primarily from the New England shelf northeast of Nantucket. We disprove a previous hypothesis about Labrador Sea wind stress being an important driver of Nantucket sea-level variations. Buoyancy forcing, as important as wind stress in some years, includes local contributions as well as remote contributions from the subpolar North Atlantic that influence Nantucket sea level a few years later. Our rigorous adjoint-based analysis corroborates previous correlation-based studies indicating that sea-level variations in the subpolar gyre and along the United States northeast coast can both be influenced by subpolar buoyancy forcing. Forward perturbation experiments further indicate remote buoyancy forcing affects Nantucket sea level mostly through slow advective processes, although coastally trapped waves can cause rapid Nantucket sea level response within a few weeks.

We describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.

Early studies revealed relationships between barium (Ba), particulate organic carbon and silicate, suggesting applications for Ba as a paleoproductivity tracer and as a tracer of modern ocean circulation. Here, we investigated the Arctic Ocean Ba cycle through a one-of-a-kind data set containing dissolved (dBa), particulate (pBa), and stable isotope Ba ratio (δBa) data from four Arctic GEOTRACES expeditions conducted in 2015. We hypothesized that margins would be a substantial source of Ba to the Arctic Ocean water column. The dBa, pBa, and δBa distributions all suggest significant modification of inflowing Pacific seawater over the shelves, and the dBa mass balance implies that ∼50% of the dBa inventory (upper 500 m of the Arctic water column) was supplied by nonconservative inputs. Calculated areal dBa fluxes are up to 10 μmol m day on the margin, which is comparable to fluxes described in other regions. Applying this approach to dBa data from the 1994 Arctic Ocean Survey yields similar results. The Canadian Arctic Archipelago did not appear to have a similar margin source; rather, the dBa distribution in this section is consistent with mixing of Arctic Ocean-derived waters and Baffin Bay-derived waters. Although we lack enough information to identify the specifics of the shelf sediment Ba source, we suspect that a sedimentary remineralization and terrigenous sources (e.g., submarine groundwater discharge or fluvial particles) are contributors.

As tides propagate inland, they become distorted by channel geometry and river discharge. Tidal dynamics in fluvial-marine transitions are commonly observed in high-energy tidal environments with relatively steady river conditions, leaving the effects of variable river discharge on tides and longitudinal changes poorly understood. To study the effects of variable river discharge on tide-river interactions, we studied a low-energy tidal environment where river discharge ranges several orders of magnitude, the diurnal microtidal Tombigbee River-Mobile Bay fluvial-marine transition, using water level and velocity observations from 21 stations. Results showed that diurnal tidal attenuation was reduced by the width convergence in seaward reaches and height convergence of the landward backwater reaches, with the channel convergence change location ∼40-50 km inland of the bayhead and seaward of the largest bifurcation. River events amplified tides in seaward regions and attenuated tides in landward regions. This created a region of river-induced peak amplitude seaward of the flood limit (i.e., bidirectional-unidirectional current transition), allowing more tidal energy to propagate inland. Tidal currents were attenuated and delayed more by river discharge than water levels, making the phase lag dynamic. The river impacts on the tides were delineated longitudinally and shifted seaward as river discharge increased, ranging up to ∼180 km. Results indicated the longitudinal shifts of river impacts on tides in alluvial systems can be estimated analytically using the ratio of river discharge to tidal discharge and the geometric convergence of the system. Our simple analytical theory provides a pathway for understanding the tide-river-geomorphic equilibrium along increasingly dynamic coasts.

Surface freshening through precipitation can act to stably stratify the upper ocean, forming a rain layer (RL). RLs inhibit subsurface vertical mixing, isolating deeper ocean layers from the atmosphere. This process has been studied using observations and idealized simulations. The present ocean modeling study builds upon this body of work by incorporating spatially resolved and realistic atmospheric forcing. Fine-scale observations of the upper ocean collected during the Dynamics of the Madden-Julian Oscillation field campaign are used to verify the General Ocean Turbulence Model (GOTM). Spatiotemporal characteristics of equatorial Indian Ocean RLs are then investigated by forcing a 2D array of GOTM columns with realistic and well-resolved output from an existing regional atmospheric simulation. RL influence on the ocean-atmosphere system is evaluated through analysis of RL-induced modification to surface fluxes and sea surface temperature (SST). This analysis demonstrates that RLs cool the ocean surface on time scales longer than the associated precipitation event. A second simulation with identical atmospheric forcing to that in the first, but with rainfall set to zero, is performed to investigate the role of rain temperature and salinity stratification in maintaining cold SST anomalies within RLs. Approximately one third, or 0.1°C, of the SST reduction within RLs can be attributed to rain effects, while the remainder is attributed to changes in atmospheric temperature and humidity. The prolonged RL-induced SST anomalies enhance SST gradients that have been shown to favor the initiation of atmospheric convection. These findings encourage continued research of RL feedbacks to the atmosphere.

A dataset of nearly 400 measurements of the particle size distribution (PSD) compiled from the Pacific, Atlantic, and Arctic Oceans is used to examine variability in the magnitude and shape of the PSD, and to characterize the partitioning of particle number, cross-sectional area, and volume concentration among defined size intervals. The results indicate that the relative contributions of three size classes based upon the pico-, nano-, and microplankton size range exhibit substantial changes among measures of particle size and between oceanic environments. The single-slope power law model commonly employed to characterize the PSD in aquatic studies is demonstrated to have significant limitations in capturing the complexity of PSD shapes observed for natural particle assemblages, and in consequence poorly predicts the relative contributions of these different size intervals. We show that specific percentile diameters derived from the cumulative distributions of particle size are strongly correlated with the contributions of these three size classes, and that these non-parametric descriptors of the cumulative distribution provide superior performance for estimating their contributions while requiring no assumption of underlying PSD shape. A comparison of these predictive relationships with independent field measurements suggests that this approach is generally robust for particle assemblages representing a wide diversity of marine environments.

The Kuroshio current separates from the Japanese coast to become the eastward flowing Kuroshio Extension (KE) characterized by a strong latitudinal density front, high levels of mesoscale (eddy) energy, and high chlorophyll (Chl). While satellite measurements of Chl show evidence of the impact of mesoscale eddies on the standing stock of phytoplankton, there have been very limited synoptic, spatially resolved in situ estimates of productivity in this region. Here, we present underway measurements of oxygen/argon supersaturation (ΔO/Ar), a tracer of net biological productivity, for the KE made in spring, summer, and early autumn. We find large seasonal differences in the relationships between ΔO/Ar, Chl, and sea level anomaly (SLA), a proxy for local thermocline depth deviations driven by mesoscale eddies derived from satellite observations. We show that the KE is a pronounced hotspot of high ΔO/Ar in spring, but corresponding surface Chl values are low and have no correlation with ΔO/Ar. In summer, there is a hotspot of productivity associated with the Oyashio front, where ΔO/Ar and Chl are strongly positively correlated. In autumn, ΔO/Ar and Chl are consistently low throughout the region and also positively correlated. By combining our analysis of the in situ ΔO/Ar data with complementary Argo, BGC-Argo, repeat hydrography, and SLA observations, we infer the combination of physical and biological controls that drive the observed distributions of ΔO/Ar and Chl. We find that the KE and Oyashio currents both act to supply nutrients laterally, fueling regions of high productivity in spring and summer, respectively.

A radiative transfer model was parameterized and validated using Biogeochemical Argo float data acquired between 2012 and 2017 across the Mediterranean Sea. Fluorescence-derived chlorophyll concentration, particulate optical backscattering at 700 nm, and fluorescence of chromophoric dissolved organic matter (CDOM) were used to parametrize the light absorption and scattering coefficients of the optically significant water constituents (such as pure water, non-algal particles, CDOM, and phytoplankton). The model was validated with in situ downwelling irradiance profiles and apparent optical properties derived both from irradiance profiles and satellite data, such as the diffuse attenuation coefficients and remote sensing reflectance. Results showed that by using regional parameterizations that are not only related to chlorophyll concentration and vertical distribution, the model was able to capture a more accurate spectral response in the examined wavelength range compared to chlorophyll-related (or Case 1) optical models. When using alternative models that incorporated also measurements of CDOM fluorescence or particulate optical backscattering, the model skill increased at all examined wavelengths. Finally, using a multi-spectral optical configuration also enabled the estimation of the relative contribution of separate water constituents in the examined spectral range. Simulations including non-algal particles and CDOM performed up to 61% and 79% better than when considering the optical properties of pure seawater alone. Moreover, a simulation including phytoplankton light absorption resulted in an error reduction of up to 42%, especially at 412 nm and with a more uniform response at the wavelengths considered.

The suspended particulate matter (SPM) concentration (unit: mg l) in surface waters is an essential measure of water quality and clarity. Satellite remote sensing provides a powerful tool to derive the SPM with synoptic and repeat coverage. In this study, we developed a new global SPM algorithm utilizing the remote sensing reflectance ( ()) at near-infrared (NIR), red, green, and blue bands (NIR-RGB) as input. The evaluations showed that the NIR-RGB algorithm could predict SPM with the median absolute percentage difference of ∼35%-39% over a wide range from ∼0.01 to >2,000 mg l. The uncertainty is smaller (29%-37%) for turbid waters where (671) ≥ 0.0012 sr and slightly higher (41%-44%) for clear waters where (671) < 0.0012 mg l. The algorithm was implemented with the global () data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. We provided a brief characterization of the spatial distribution and temporal trends of the SPM products in global waters based on the monthly SPM composites. Case studies of the SPM time series in coastal and inland waters suggest that the satellite SPM estimations registered spatial and seasonal variation and episodic events in regional scales as well. The VIIRS-generated global SPM maps provide a valuable addition to the existing ocean color products for environmental and climate applications.

We explored how algorithm (model) and measurement (observation) uncertainties can effectively be incorporated into empirical ocean color model development and assessment. In this study we focused on methods for deriving the particulate backscattering coefficient at 555 nm, (555) (m). We developed a simple empirical algorithm for deriving (555) as a function of a remote sensing reflectance line height (LH) metric. Model training was performed using a high-quality bio-optical dataset that contains coincident measurements of the spectral remote sensing reflectances, (λ) (sr), and the spectral particulate backscattering coefficients, (λ). The LH metric used is defined as the magnitude of (555) relative to a linear baseline drawn between (490) and (670). Using an independent validation dataset, we compared the skill of the LH-based model with two other models. We used contemporary validation metrics, including bias and mean absolute error (MAE), that were corrected for model and observation uncertainties. The results demonstrated that measurement uncertainties do indeed impact contemporary validation metrics such as mean bias and MAE. Zeta-scores and -tests for overlapping confidence intervals were also explored as potential methods for assessing model skill.

Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking. We combine NEMO-MEDUSA 2.0 output, that represents hydrodynamic and biological properties of seawater, with a particle-tracking framework. Different sizes and densities of particles (for different types of plastic) are simulated, showing that the global distribution of sinking timescales is largely size-dependent as opposed to density-dependent. The smallest particles we simulate (0.1 μm) start sinking almost immediately around the globe and their trajectories take the longest time to reach their first sinking depth (relative to larger particles). In oligotrophic subtropical gyres with low algal concentrations, particles between 1 and 0.01 mm do not sink within the simulation time of 90 days. This suggests that in addition to the comparatively well-known physical processes, biological processes might also contribute to the accumulation of floating plastic (of 1-0.01 mm) in subtropical gyres. Particles of 1 μm in the gyres start sinking largely due to vertical advection, whereas in the equatorial Pacific they are more dependent on biofouling. The qualitative impacts of seasonality on sinking timescales are small, however, localized sooner sinking due to spring algal blooms is seen. This study maps processes that affect the sinking of virtual microplastic globally, which could ultimately impact the ocean plastic budget.

We document an exceptional large-spatial scale case of changes in tidal range in the North Sea, featuring pronounced trends between -2.3 mm/yr at tide gauges in the United Kingdom and up to 7 mm/yr in the German Bight between 1958 and 2014. These changes are spatially heterogeneous and driven by a superposition of local and large-scale processes within the basin. We use principal component analysis to separate large-scale signals appearing coherently over multiple stations from rather localized changes. We identify two leading principal components (PCs) that explain about 69% of tidal range changes in the entire North Sea including the divergent trend pattern along United Kingdom and German coastlines that reflects movement of the region's semidiurnal amphidromic areas. By applying numerical and statistical analyses, we can assign a baroclinic (PC1) and a barotropic large-scale signal (PC2), explaining a large part of the overall variance. A comparison between PC2 and tide gauge records along the European Atlantic coast, Iceland, and Canada shows significant correlations on time scales of less than 2 years, which points to an external and basin-wide forcing mechanism. By contrast, PC1 dominates in the southern North Sea and originates, at least in part, from stratification changes in nearby shallow waters. In particular, from an analysis of observed density profiles, we suggest that an increased strength and duration of the summer pycnocline has stabilized the water column against turbulent dissipation and allowed for higher tidal elevations at the coast.