North Atlantic Subtropical Mode Water (NASTMW) serves as a major conduit for dissolved carbon to penetrate into the ocean interior by its wintertime outcropping events. Prior research on NASTMW has concentrated on its physical formation and destruction, as well as Lagrangian pathways and timescales of water into and out of NASTMW. In this study, we examine how dissolved inorganic carbon (DIC) concentrations are modified along Lagrangian pathways of NASTMW on subannual timescales. We introduce Lagrangian parcels into a physical-biogeochemical model and release these parcels annually over two decades. For different pathways into, out of, and within NASTMW, we calculate changes in DIC concentrations along the path (ΔDIC), distinguishing contributions from vertical mixing and biogeochemical processes. While the mean ΔD for parcels that persist within NASTMW in one year is relatively small at +6 µmol/L, this masks underlying dynamics: individual parcels undergo interspersed DIC depletion and enrichment, spanning several timescales and magnitudes. The strongest ΔDIC is during subduction of water parcels (+101 µmol/L  in one year), followed by transport out of NASTMW due to increases in density in water parcels (+10 µmol/L). Most DIC enrichment and depletion regimes span timescales of weeks, related to phytoplankton blooms. However, mixing and biogeochemical processes often oppose one another at short timescales, so the largest net DIC changes occur at timescales of more than 30 days. Our new Lagrangian approach complements bulk Eulerian approaches, which average out this underlying complexity, and is relevant to other biogeochemical studies, for example on marine carbon dioxide removal.

Understanding the pathways of floating material at the surface ocean is important to improve our knowledge on surface circulation and for its ecological and environmental impacts. Virtual particle simulations are a common method to simulate the dispersion of floating material. To advect the particles, ocean models’ velocities are usually used, but only recent ones include tidal forcing. Our research question is: What is the effect of tidal forcing on virtual particle dispersion and accumulation at the ocean surface? As inputs we use velocity outputs from eNATL60, a twin simulation with and without tidal forcing. We focus on the Açores Islands region and we find: 1) Surface particles have a larger displacement, but a lower distance travelled with than without tidal forcing 2) Surface accumulation seasonal differences depend on the spatial scale of the ocean structures 3) A greater variability in surface accumulation is present with tidal forcing.

Model simulations of past climates are increasingly found to compare well with proxy data at a global scale, but regional discrepancies remain. A persistent issue in modeling past greenhouse climates has been the temperature difference between equatorial and (sub-)polar regions, which is typically much larger in simulations than proxy data suggest. Particularly in the Eocene, multiple temperature proxies suggest extreme warmth in the southwest Pacific Ocean, where model simulations consistently suggest temperate conditions. Here we present new global ocean model simulations at 0.1° horizontal resolution for the middle-late Eocene. The eddies in the high-resolution model affect poleward heat transport and local time-mean flow in critical regions compared to the non-eddying flow in the standard low-resolution simulations. As a result, the high-resolution simulations produce higher surface temperatures near Antarctica and lower surface temperatures near the equator compared to the low-resolution simulations, leading to better correspondence with proxy reconstructions. Crucially, the high-resolution simulations are also much more consistent with biogeographic patterns in endemic-Antarctic and low-latitude-derived plankton, and thus resolve the long-standing discrepancy of warm subpolar ocean temperatures and isolating polar gyre circulation. The results imply that strongly eddying model simulations are required to reconcile discrepancies between regional proxy data and models, and demonstrate the importance of accurate regional paleobathymetry for proxy-model comparisons.

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

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.

Some lipid-biomarker-based sea surface temperature (SST) proxies applied in the modern Mediterranean Sea exhibit large offsets from expected values, generating uncertainties in climate reconstructions. Lateral transport of proxy carriers along ocean currents prior to burial can contribute to this offset between reconstructed and expected SSTs above the burial site and at the particle’s origin in the surface ocean. We perform virtual particle tracking experiments to simulate transport during sinking and derive a quantitative estimate of transport bias for alkenones and glycerol dibiphytanyl glycerol tetraethers (GDGTs), which form the basis of the UK’37 and TEX86 paleothermometers, respectively. We use sinking speeds appropriate for the export of various proxy carriers (6, 12, 25, 50, 100, 250, 500, and 1000 m d-1). For the assessed sinking speeds, lateral transport bias is generally small (always <0.75 °C) within the Mediterranean Sea and does not substantially contribute to the uncertainties in UK’37- or TEX86-based SSTs.

Beaches are thought to contain a large part of plastics entering the marine environment. Here, they can cause harm to biota, and can potentially break down into smaller fragments over time. To protect vulnerable beaches, it is advantageous to have information on the sources of this plastic. Here, we develop a universally applicable Bayesian framework to map sources for plastic arriving on a specific beach, applied to a beach in southwest the Netherlands. In this framework, we combine Lagrangian backtracking simulations of drifting particles with data of plastic input from coastlines, rivers and fishing activity. This facilitates spatiotemporal source attribution for plastic arriving at the specified beach. We show that the main sources are the east coast of the UK, the Dutch coast, the English channel (fisheries) and the Thames, Seine, Rhine and Trieux (rivers). We also show that particle age is a major uncertainty in source attribution using backtracking.