Recently discovered, ocean submesoscales have attracted considerable attention due to their ability to change the upper ocean stratification, affect vertical transport, and induce a downscale cascade of energy toward dissipation. In this paper, we highlight the effect of submesoscale fronts and filaments on surface layer properties and dynamics during storm events, extending previous idealized simulations toward real‐ocean applications. Here, we use the Baltic Sea as a natural laboratory to study the rich submesoscale activity of this system with the help of realistic high‐resolution numerical simulations. These simulations reveal a wealth of cold submesoscale filaments with sharp lateral buoyancy gradients, strong surface convergence, and high vertical velocities. Highly heterogeneous Mixed Layer Depth (MLD) modulations are associated with these features, maintaining locally reduced MLDs even during storm events due to vigorous submesoscale restratification. The interaction of near‐surface turbulence and submesoscale restratification results in strong and highly efficient mixing inside the submesoscale fronts. Focusing on a typical filament, it is shown that frontogenesis is associated with the convergent cross‐front circulation arising from a turbulent thermal wind balance, consistent with previous studies. We show that the sharp fronts generated by this process may become symmetrically unstable, and show enhanced (modeled) energy dissipation rates that are in good quantitative agreement with existing theoretical estimates.

Microplastics (MPs) are omnipresent in the aquatic environment where they pose a risk to ecosystem health and functioning. However, little is known about the concentration and transport patterns of this particulate contaminant. Measurement campaigns remain expensive, and assessments of regional MP distributions need to rely on a limited number of samples. Thus, the prediction of potential MP sink regions in the sea would be beneficial for a better estimation of MP concentration levels and a better sampling design. Based on a sediment transport model, this study investigates the transport of different MP model particles, polyethylene-terephthalate (PET) and polyvinyl chloride (PVC) particles with simplified spherical sizes of 10 and 330 µm, under storm conditions. A storm event was chosen because extreme wave heights cause intense sediment erosion down to depths that are otherwise unaffected; therefore, these events are critical for determining accumulation regions. The calculation of metocean parameters for such extreme weather events is subject to uncertainties. These uncertainties originate from the imperfect knowledge of the initial conditions and lateral boundary conditions for regional models, which are necessary to be able to run a numerical model. Processes, which can be resolved by the model, are limited by the model's resolution. For the processes for which the model resolution is too coarse, parameterizations are used. This leads to additional uncertainty based on the model physics. This sensitivity study targets the propagation of uncertainty from the atmospheric conditions to MP erosion and deposition, on the basis of freely available models and data. We find that atmospheric conditions have a strong impact on the quantity of eroded and deposited material. Thus, even if the settling and resuspension properties of MP were known, a quantitative transport estimation by ocean models would still show considerable uncertainty due to the imperfect knowledge of atmospheric conditions. The uncertainty in the transport depends on the particle size and density, as transport of the larger and denser plastic particles only takes place under storm conditions. Less uncertainty exists in the location of erosional and depositional areas, which seems to be mainly influenced by the bathymetry. We conclude that while quantitative model predictions of sedimentary MP concentrations in marine sediments are hampered by the uncertainty in the wind fields during storms, models can be a valuable tool to select sampling locations for sedimentary MP concentrations to support their empirical quantification. The purpose of this study is to support the strategic planning of measurement campaigns, as the model predictions can be used to identify regions with larger net deposition after a specific storm event.

For more than a century, estuarine exchange flow has been quantified by means of the Knudsen relations which connect bulk quantities such as inflow and outflow volume fluxes and salinities. These relations are closely linked to estuarine mixing. The recently developed Total Exchange Flow (TEF) analysis framework, which uses salinity coordinates to calculate these bulk quantities, allows an exact formulation of the Knudsen relations in realistic cases. There are however numerical issues, since the original method does not converge to the TEF bulk values for an increasing number of salinity classes. In the present study, this problem is investigated and the method of dividing salinities, described by MacCready et al. (2018), is mathematically introduced. A challenging yet compact analytical scenario for a well-mixed estuarine exchange flow is investigated for both methods, showing the proper convergence of the dividing salinity method. Furthermore, the dividing salinity method is applied to model results of the Baltic Sea to demonstrate the analysis of realistic exchange flows and exchange flows with more than two layers.

The General Ocean Turbulence Model (GOTM) is a one-dimensional water column model, including a set of state-of-the-art turbulence closure models, and has widely been used in various applications in the ocean modeling community. Here, we extend GOTM to include a set of newly developed ocean surface vertical mixing parameterizations of Langmuir turbulence via coupling with the Community Vertical Mixing Project (CVMix). A Stokes drift module is also implemented in GOTM to provide the necessary ocean surface waves information to the Langmuir turbulence parameterizations, as well as to facilitate future development and evaluation of new Langmuir turbulence parameterizations. In addition, a streamlined workflow with Python and Jupyter notebooks is also described, enabled by the newly developed and more flexible configuration capability of GOTM. The newly implemented Langmuir turbulence parameterizations are evaluated against theoretical scalings and available observations in four test cases, including an idealized wind-driven entrainment case and three realistic cases at Ocean Station Papa, the northern North Sea, and the central Baltic Sea, and compared with the existing general length scale scheme in GOTM. The results are consistent with previous studies. This development extends the capability of GOTM towards including the effects of ocean surface waves and provides useful toolsets for the ocean modeling community to further study the effects of Langmuir turbulence in a broader scope.

In lakes and reservoirs, physical processes control temperature dynamics and stratification, which are important determinants of water quality. In large lakes, even extensive monitoring programs leave some of the patterns undiscovered and unresolved. Lake models can complement measurements in higher spatial and temporal resolution. These models require a set of driving data, particularly meteorological input data, which are compulsory to the models but at many locations not available at the desired scale or quality. It remains an open question whether these meteorological input data can be acquired in a sufficient quality by employing atmospheric models. In this study, we used the European Centre for Medium-Range Weather Forecasts’ (ECMWF) ERA-Interim atmospheric reanalysis data as meteorological forcing for the three-dimensional hydrodynamic General Estuarine Transport Model (GETM). With this combination, we modelled the spatio-temporal variation in water temperature in the large, shallow Lake Chaohu, China. The model succeeded in reproducing the seasonal patterns of cooling and warming. While the model did predict diurnal patterns, these patterns were not precise enough to correctly estimate the extent of short stratification events. Nevertheless, applying reanalysis data proved useful for simulating general patterns of stratification dynamics and seasonal thermodynamics in a large shallow lake over the year. Utilising reanalysis data together with hydrodynamic models can, therefore, inform about water temperature dynamics in the respective water bodies and, by that, complement local measurements.

The German Bight was exposed to record high riverine discharges in June 2013, as a result of flooding of the Elbe and Weser rivers. Several anomalous observations suggested that the hydrodynamical and biogeochemical states of the system were impacted by this event. In this study, we developed a biogeochemical model and coupled it with a previously introduced high-resolution hydrodynamical model of the southern North Sea in order to better characterize these impacts and gain insight into the underlying processes. Performance of the model was assessed using an extensive set of in situ measurements for the period 2011–2014. We first improved the realism of the hydrodynamic model with regard to the representation of cross-shore gradients, mainly through inclusion of flow-dependent horizontal mixing. Among other characteristic features of the system, the coupled model system can reproduce the low salinities, high nutrient concentrations and low oxygen concentrations in the bottom layers observed within the German Bight following the flood event. Through a scenario analysis, we examined the sensitivity of the patterns observed during July 2013 to the hydrological and meteorological forcing in isolation. Within the region of freshwater influence (ROFI) of the Elbe–Weser rivers, the flood event clearly dominated the changes in salinity and nutrient concentrations, as expected. However, our findings point to the relevance of the peculiarities in the meteorological conditions in 2013 as well: a combination of low wind speeds, warm air temperatures and cold bottom-water temperatures resulted in a strong thermal stratification in the outer regions and limited vertical nutrient transport to the surface layers. Within the central region, the thermal and haline dynamics interactively resulted in an intense density stratification. This intense stratification, in turn, led to enhanced primary production within the central region enriched by nutrients due to the flood but led to reduction within the nutrient-limited outer region, and it caused a widespread oxygen depletion in bottom waters. Our results further point to the enhancement of the current velocities at the surface as a result of haline stratification and to intensification of the thermohaline estuarine-like circulation in the Wadden Sea, both driven by the flood event.