Measurements of turbulent fluctuations of horizontal and vertical components of velocity, salinity and suspended particulate matter are presented. Turbulent Prandtl numbers are found to increase with stratification and to become larger than 1. Consequently, the vertical turbulent mass transport is suppressed by buoyancy forces, before the turbulent kinetic energy (TKE) and vertical turbulent momentum exchange are inhibited. With increasing stratification, the buoyancy fluxes do not cease, instead they become countergradient. We find that buoyantly driven motions play an active role in the transfer of mass. This is in agreement with trends derived from Monin-Obukhov scaling. For positive Richardson flux numbers (Ri ), the log velocity profile in the near-bed layer requires correction with a drag reduction. For negative Ri , the log velocity profile should be corrected with a drag increase, with increasing |Ri |. This highlights the active role played by buoyancy in momentum transfer and the production of TKE. However, the data do not appear to entirely follow Monin-Obukhov scaling. This is consistent with the notion that the turbulence field is not in equilibrium. The large stratification results in the decay of turbulence and countergradient buoyancy fluxes act to restore equilibrium in the energy budget. This implies that there is a finite adjustment timescale of the turbulence field to changes in velocity shear and density stratification. The energy transfers associated with the source and sink function of the buoyancy flux can be modeled with the concept of total turbulent energy.

The Mediterranean Forecasting System (MFS) has been operational for a decade, and is continuously providing forecasts and analyses for the region. These forecasts comprise local- and basin-scale information of the environmental state of the sea and can be useful for tracking oil spills and supporting search-and-rescue missions. Data assimilation is a widely used method to improve the forecast skill of operational models and, in this study, the three-dimensional variational (OceanVar) scheme has been extended to include Argo float trajectories, with the objective of constraining and ameliorating the numerical output primarily in terms of the intermediate velocity fields at 350 m depth. When adding new datasets, it is furthermore crucial to ensure that the extended OceanVar scheme does not decrease the performance of the assimilation of other observations, e.g., sea-level anomalies, temperature, and salinity. Numerical experiments were undertaken for a 3-year period (2005-2007), and it was concluded that the Argo float trajectory assimilation improves the quality of the forecasted trajectories with ~15%, thus, increasing the realism of the model. Furthermore, the MFS proved to maintain the forecast quality of the sea-surface height and mass fields after the extended assimilation scheme had been introduced. A comparison between the modeled velocity fields and independent surface drifter observations suggested that assimilating trajectories at intermediate depth could yield improved forecasts of the upper ocean currents.

Energy transfer mechanisms between the atmosphere and the deep ocean have been studied for many years. Their importance to the ocean's energy balance and possible implications on mixing are widely accepted. The slab model by Pollard (Deep-Sea Res Oceanogr Abstr 17(4):795-812, 1970) is a well-established simulation of near-inertial motion and energy inferred through wind-ocean interaction. Such a model is set up with hourly wind forcing from the NCEP-CFSR reanalysis that allows computations up to high latitudes without loss of resonance. Augmenting the one-dimensional model with the horizontal divergence of the near-inertial current field leads to direct estimates of energy transfer spectra of internal wave radiation from the mixed layer base into the ocean interior. Calculations using this hybrid model are carried out for the North Atlantic during the years 1989 and 1996, which are associated with positive and negative North Atlantic Oscillation index, respectively. Results indicate a range of meridional regimes with distinct energy transfer ratios. These are interpreted in terms of the mixed layer depth, the buoyancy frequency at the mixed layer base, and the wind field structure. The average ratio of radiated energy fluxes from the mixed layer to near-inertial wind power for both years is approximately 12%. The dependence on the wind structure is supported by simulations of idealized wind stress fronts with variable width and translation speeds.

Tidal models that incorporate satellite altimeter data have historically shown discrepancies in accuracy between shallow and deep marine environments. A recent study suggests that these differences may partly stem from neglecting the nonlinear tide-surge interactions in tidal analyses. In this study, we introduce a novel method for estimating tidal constituents from satellite altimeter data in shallow waters, leveraging a 2D hydrodynamic model that accounts for these nonlinear interactions. This approach substantially reduces the variance of unaccounted water level variability, thereby benefiting the estimation. A distinctive feature of our method is the treatment of prior model tidal constituents as stochastic, which helps manage the low temporal resolution of altimeter data by ensuring that unresolved tidal constituents are not updated. We tested our method in the data-rich northwest European continental shelf region, using the high-resolution 2D Dutch Continental Shelf Model version 7 (DCSM). Results show a substantial reduction in the standard deviations of residual water level time series in the shallow waters around Great Britain and in the German Bight, from 11 cm to 5 cm. In deep waters (>200 m), the median standard deviation decreased from 6.8 cm to 6.2 cm. When compared to state-of-the-art ocean tide and surge corrections from publicly available models, our method outperformed them in shallow waters (median standard deviation of 6.0 cm versus 7.5 cm), though the alternative products performed better in deep waters (median standard deviation of 5.5 cm versus 6.2 cm). An estimate of the accuracy at satellite crossovers resulted in an estimated total tidal error of about 1.5 cm (RSS VD). We acknowledge that comparisons in shallow waters are complicated, as alternative products do not account for nonlinear tide-surge interactions. Overall, the demonstration along-track tidal product developed in this study shows potential for improving the tidal representation in the DCSM model. In data-poor regions, the number of tidal constituents that can be reliably estimated using the method may be limited, and alternative strategies might be needed to evaluate the model's uncertainty in representing tides.

Accurate storm surge modeling is essential for predicting coastal flooding and mitigating impacts on vulnerable regions. This study evaluates the influence of different sea surface drag parameterizations on surge predictions using the Global Tide and Surge Model (GTSM) over a 10-year period (2006-2015) and two storm events. Four model experiments were tested, ranging from a fully dynamic formulation, including variable air density, atmospheric stability, and sea-state-dependent drag, to a simplified constant-drag approach. Results show that advanced drag formulations reduced the underestimation of annual maximum surge values from 18% to 12% globally, with the variable Charnock parameter contributing the most. Conversely, using a constant Charnock value and thereby neglecting wave-dependent roughness increases prediction errors, especially in regions with highly variable sea states. Case studies of Storm Xaver (2013) and Hurricane Fiona (2022) show that advanced parameterizations better capture wind stress variations, reducing root mean square error from 0.21 m to 0.16 m for Xaver and improving surge predictions by up to 0.30 m for Fiona. Consistent with earlier studies, a persistent underestimation of extreme surge events remains across all experiments. While wave-dependent roughness improves performance, no single parameter fully explains this bias. However, wave-dependent roughness particularly enhances model performance in high-latitude and storm-prone areas, where sea state and atmospheric conditions vary widely. Our results show that variations in air density and atmospheric stability have minimal impact on surge height. As such, prioritizing the implementation of dynamic, sea-state-dependent drag formulations, particularly variable Charnock, is key to further improving the accuracy of storm surge forecasting systems and future projections.