The transport of oil droplets following a surface oil spill was investigated using a uniform vertical eddy diffusivity model and the K‐profile parameterization model, which assumes a maximum K value at 1/3 depth of the mixed layer. The initial droplet size distribution was obtained based on the Delvigne and Sweeney (1988, https://doi.org/10.1007/s13131‐013‐0364‐7) model. Using a uniform eddy diffusivity K_ave, an exact analytical solution was used to produce the transient and steady state profile of the concentration of droplets of all sizes. It was found that the concentration at the surface is proportional to the droplet rise velocity and inversely proportional to K_ave. Thus, small droplets (smaller than 100 μm) do not persist at the water surface. It was found that K‐profile parameterization produces smaller concentrations at the water surface than the uniform K model. The impact of waves was introduced into the K‐profile parameterization model through a roughness height, z_o, that is comparable to the wave height. The investigation herein reveals that the Delvigne and Sweeney approach, commonly used in oil spill modeling, is not sufficient to predict the oil droplet size distribution, and that one needs to use a vertical eddy diffusivity to accurately predict the transport in the following hours and days. A new dimensionless formulation was provided to generalize the results, and showed that transport depends on three major parameters, the water friction speed, the mixed layer depth, and the droplet diameter.

High‐frequency measurements of waves, currents, and turbulence were made using the bottom‐mounted tripod equipped with the Nortek 6‐MHz acoustic Doppler velocimetry at eight mooring stations in the East China Shelf Seas. The observational data are analyzed to estimate the bottom drag coefficient and also the contributions from currents and waves. Variations of bottom drag coefficient caused by currents show no obvious relationship with water depth. Generally, the current‐induced drag coefficient decreases with the strengthening currents, and the wave‐induced drag coefficient increases with the enhancing waves. Synthesis analyses of the observational data reveal a scale relationship between the current‐induced drag coefficient and the turbulent Reynolds number and that between the wave‐induced drag coefficient and the bottom wave orbital velocity. The analyses show no significant impacts of waves on turbulent Reynolds stress, and the total bottom drag coefficient is the sum of that due to currents and waves. The empirical formula for bottom drag coefficient derived from this study may help to improve the simulation of tides, storm surges, and sediment transport in coastal seas.

This study reveals the seasonal variability of the lower and upper deep branches of the Pacific Meridional Overturning Circulation (L‐PMOC and U‐PMOC) in the Yap‐Mariana Junction (YMJ) channel, a major gateway for deep flow into the western Pacific. On the western side of the YMJ channel, mooring observations in 2017 and in 1997 show the seasonal phase of the L‐PMOC at depths of 3,800–4,400 m: strong northward flow with speed exceeding 20 cm s⁻¹ and lasting from December to next May and weak flow during the following 6 months. On the eastern side of the channel, mooring observations during 2014–2017 show two southward deep flows with broadly seasonal phases, one being the return flow of L‐PMOC below ~4,000 m and with the same phase of L‐PMOC but reduced magnitude. The second, shallower, southward deep flow corresponds to the U‐PMOC observed within 3,000–3,800 m and with opposite phase of L‐PMOC, that is, strong (weak) southward flow appearing during June–November (December–May). Seasonal variations of the L‐PMOC and U‐PMOC are accompanied by the seasonal intrusions of the Lower and Upper Circumpolar Waters (LCPW and UCPW) in lower and upper deep layers, which change the isopycnal structure and the deep currents in a way consistent with geostrophic balance.

In the context of Canada’s Ocean Protection Plan (OPP), improved coastal and near-shore modelling is needed to enhance marine safety and emergency response capacity in the aquatic environment. In this study, the Nucleus for European Modelling of the Ocean (NEMO) is adopted to develop an ocean forecasting system for Saint John harbour in the Bay of Fundy, on the east coast of Canada. The challenging regional oceanography is characterized by the presence of some of the world’s strongest tides, significant river runoff and complicated geometry. A three-level one-way nesting approach is used to downscale from a 1/12° North Atlantic-Arctic regional model to very-high-resolution port-scale around Saint John harbour. The three nested grids cover the outer shelf, the Bay of Fundy and finally the approach to the harbour with resolutions of 2.5 km, 500 m and 100 m respectively. Due to the lack of accurate runoff data at the Saint John River outlet, the model’s lateral open boundary condition is modified to introduce the river forcing with the observed time series of water level near the mouth of the river. Evaluation with observational data demonstrates the model’s accuracy for the simulation of tidal elevation and currents, non-tidal water level and currents, temperature and salinity. Comparison with the observed sea surface temperature demonstrates the improved model accuracy through increasing the horizontal resolution. Virtual Lagrangian trajectories computed using the modelled surface currents and including wind effects show good agreement with the observed trajectories of different types of surface drifters. This study demonstrates the capability of the NEMO modelling framework to provide very-high-resolution modelling at port-scale resolution for the Saint John harbour.

A high‐resolution baroclinic coastal ocean model is applied to study seasonal circulation and upwelling off South West Nova Scotia (SWNS) based on 1 year simulations for 2010. The model reasonably reproduces tidal currents, seasonal hydrography, and circulation from multiyear observations, in consistence with the observed strong seasonal variations of these properties in the study area. The main physical processes affecting circulation are analyzed using numerical experiments, with focus on the effect of tidal and density induced currents on topographic upwelling. It is confirmed that the shoreward near‐bottom currents and associated upwelling are tidally induced and persistent throughout the year. It is revealed that these currents have seasonal variability, with cross‐isobath component being strong in summer throughout a large area, but weaker and confined to deeper regions in winter. The seasonal variability of Scotian Current is the dominant forcing affecting the variability of onshore bottom currents. Lagrangian particle tracking identifies two major pathways of source waters arriving at the SWNS upwelling region. A large proportion of particles come from the east with the Scotian Current, mostly from the surface layer; and a small portion of water parcels come from a mean depth exceeding 100 m from the Gulf of Maine and Northeast Channel.

The Arctic Ocean is generally undersaturated in CO₂ and acts as a net sink of atmospheric CO₂. This oceanic uptake is strongly modulated by sea ice, which can prevent air–sea gas exchange and has major impacts on stratification and primary production. Moreover, carbon is stored in sea ice with a ratio of alkalinity to dissolved inorganic carbon that is larger than in seawater. It has been suggested that this storage amplifies the seasonal cycle of seawater pCO₂ and leads to an increase in oceanic carbon uptake in seasonally ice-covered regions compared to those that are ice-free. Given the rapidly changing ice scape in the Arctic Ocean, a better understanding of the link between the seasonal cycle of sea ice and oceanic uptake of CO₂ is needed. Here, we investigate how the storage of carbon in sea ice affects the air–sea CO₂ flux and quantify its dependence on the ratio of alkalinity to inorganic carbon in ice. To this end, we present two independent approaches: a theoretical framework that provides an analytical expression of the amplification of carbon uptake in seasonally ice-covered oceans and a simple parameterization of carbon storage in sea ice implemented in a 1D physical–biogeochemical ocean model. Sensitivity simulations show a linear relation between ice melt and the amplification of seasonal carbon uptake. A 30 % increase in carbon uptake in the Arctic Ocean is estimated compared to ice melt without amplification. Applying this relationship to different future scenarios from an earth system model that does not account for the effect of carbon storage in sea ice suggests that Arctic Ocean carbon uptake is underestimated by 5 % to 15 % in these simulations.