T2: Ocean Surface Layer Energetics

Principal investigators: Dr. Nils Brüggemann (Max Planck Institute for Meterology), Dr. Jeff Carpenter (Helmholtz-Zentrum Hereon), Dr. Lars Czeschel (Universität Hamburg)

Sea surface temperature on 25 September 2007 from an eddy-resolving GETM simulation of the Baltic Sea (left), and AVHRR remote sensing data (right). Shown in the left panel is only the high-resolution area of the central Baltic Sea as described in Holtermann et al. (2014). Note that the colour shading is similar but not identical in these panels. The right panel is based on data from the German Federal Maritime and Hydrographic Agency (BSH); courtesy of H. Siegel (IOW).

The energy pathways of the submesoscales, which exist in the range between the mesoscale (on the order of 100 km) and the largest turbulent eddies (order of 1 m), will be quantified and parameterised so they can be incorporated into global climate models. This will be done using a numerical approach consisting of two different model studies specialised in both turbulent flows and regional ocean processes, as well as a dedicated field program using the Baltic Sea as a "natural laboratory" for the measurement of submesoscale energy pathways.

The surface mixing layer (SML) is the ocean side of the air-sea interface through which the fluxes of energy, momentum and tracers have to pass in a coupled atmosphere-ocean system. Pathways and transformations of energy, momentum and tracers in the SML are complex, highly variable, and not sufficiently understood. Even in high-resolution ocean models, energy and momentum budgets are energetically inconsistent because the additional energy reservoirs and transformation processes due to unresolved processes (e.g.,mesoscale/submesoscale motions, surface waves) are either ignored or not correctly taken into account. In coarse-resolution climate models, the situation is even worse. The goal of this subproject is therefore to investigate energy transport and transformation processes in the SML that are relevant for the ocean-atmosphere coupling in climate models.

Our major efforts to understand the energy budget of the SML will be conducted through the use of idealised Large Eddy Simulations (LES), high-resolution ocean modelling, and coordinated field surveys including high-resolution turbulence observations. The results from the LES and field work will be used in a realistic model to understand the energy pathways associated with submesoscale motions in the SML, and to test the developed parameterisations.

Main findings of phase 1

In WP2, we analyzed a realistic high-resolution numerical simulation focusing on the central basin of the Baltic Sea, an area where available observations from a field campaign confirm that features persistent lateral density gradients and rich submesoscale activity, hence forming an ideal natural laboratory for this study. The simulation revealed a strong thermal frontal structure that persists during autumn and had not been reported previously. Cold submesoscale filaments with sharp lateral buoyancy gradients, strong surface convergence and high vertical velocities arise from this front. Highly heterogeneous Mixed Layer Depth (MLD) patterns appear, with the shallowest MLDs found in the vicinity of submesoscale features. As it turned out, submesoscales are able to maintain shallow MLDs during storms and induce vigorous and rapid restratification when the wind subsides, creating significant temporal MLD variability. The interaction of strong near-surface turbulence and submesoscale restratification results in highly efficient mixing inside submesoscale fronts.

Sketch of the submesoscale frontal structure and frontal instabilities at the edge of a dense upwelling filament. Figure taken from the T2 PhD thesis of Peng (2020).

In WP3, we investigated submesoscale frontal dynamics, instabilities, and mixing processes inside dense upwelling filaments, based on data from the central CRC cruise M132 with R/V Meteor in the south-east Atlantic Ocean (Benguela upwelling system). With the help of specialized intrumentation, including a towed research catamaran and high-resolution turbulence microstructure measurements, we were able to obtained a detailed view of the structure of all dynamically relevant parameters (e.g., vertical shear and vorticity, vertical and cross-front stratification, energy dissipation) inside narrow submesoscale fronts and filaments at unprecedented resolution.  This data set allowed us to test the real-ocean relevance of recent theoertical and numerical ideas regarding the submesoscale dynamics of surface-layer fronts.

As summarized in the figure, our analysis showed that the effect of the front is reflected in a gradual transition from purely wind-driven turbulence towards mixing energized by forced symmetric instability (FSI). Our microstructure data were in excellent agreement with previous numerical studies, suggesting that the energy dissipation due to FSI scales with the Ekman buoyancy flux, i.e. with the rate at which the cross-front Ekman transport moves dense water on top of light water. Our high-resolution catamaran-based velocity measurements also allowed us, for the first time, to demonstrate that the vorticity in the cyclonic flank of the frontal jet may be strong enough to fully suppress FSI. In this case, turbulence is fueled by marginal shear instability. Our data therefore provide the first direct and conclusive evidence for the combined relevance of FSI, inertial instability, and marginal shear instability for overall kinetic energy dissipation in real-ocean submesoscale fronts and filaments (see Peng et al., 2020). 

LES Simulations of Energy Fluxes in the Surface

“However at Submesoscales, a lack of observations means that it is not yet clear which process dominate in energy dissipation.

Josh Pein, PhD T2

I am a physical oceanographer working as a PhD at the University of Hamburg under the supervision of Dr. Nils Brüggemann (Universität Hamburg), Dr. Jeff Carpenter (Helmholtz Zentrum Geesthacht), Dr. Lars Czeschel (Universität Hamburg).

I am investigating the energetics in the oceanic surface mixed layer.

I studied a dual major in `Environmental Sciences` as well as `Atmospheric and Ocean Sciences a the University of Cape Town, a true amalgamation of the earth sciences. Following a successful research cruise in the Southern Ocean in 2015, I moved my studies to the IfM in Hamburg.

I am a member of the TRR subproject T2 “Ocean Surface Layer Energetics”. The importance of the upper-ocean Surface Mixed Layer (SML), an interface between the ocean and Atmosphere goes without saying. It is responsible for communicating atmospheric fluxes into the ocean interior, and is the most energetic part of the ocean! Processes in the SML interact to produce a variety of energy transfers. However at Submesoscales, a lack of observations means that it is not yet clear which process dominate in energy dissipation. Consequently, climate models often artificially create or dissipate energy. T2 seeks to rectify this! Using a combination of observations and large eddy simulations, the main aim of our subproject is to identify, quantify and parameterize these dominant processes. Ultimately, this will expand our understanding of the conceptual energy cycle of the ocean, providing more energetically consistent surface mixed layer parameterisations for climate models.

I am responsible for running, and the analysis of the LES. One set up of interest, and common place in the upper ocean, are oceanic fronts. Often close to thermal wind balance, not quite in equilibrium, they are unstable to a “family” of possible submesoscale instabilities.

The figure below, produced from one of our runs, is an example of such a set up. It shows the evolution of a baroclinic front in the mixed layer. The colour scale gives the buoyancy and the white contours indicate the associated eastward jet.

After 6 hours symmetric instability develops at the southern flank of the jet, as the relative vorticity of the background flow reduces the potential vorticity below zero (a necessary condition for symmetric instability). After 24h we can see the development of baroclinic instability on a much larger scale. The development is not symmetric around the background jet as the symmetric instability has already re-stratified large parts of the southern flank. We are especially interested in the impact of the so called ‘secondary instabilities’, such as Kelvin-Helmholtz instability, which accompany symmetric and baroclinic instabilities. In order to explore the role of the ‘secondary instabilities’ for the mixing and energy dissipation in the mixed layer, our LES simulations demand grid resolutions of (O)1m.

High-resolution data for a better understanding of energy budgets

I am driven by the translation of large amounts of data into palpable results that improve the understanding of a system while also allowing the identification of further knowledge gaps.

Larissa Schultze, Postdoc T2

My name is Larissa Schultze and I am a Postdoc at the Helmholtz-Zentrum Geesthacht. I am passionate about data and I am eager learn about and implement methods that support the analysis of collected measurements and of simulation results. I am driven by the translation of large amounts of data into palpable results that improve the understanding of a system while also allowing the identification of further knowledge gaps.

Within the TRR 181, I work with principal investigator Jeff Carpenter in the subproject T2, in which we tackle the energy transfers of the surface mixed layer. I make use of observational methods and numerical modelling to study stratification, turbulence and mixing in shallow seas. The observational approach focuses on the processing and analysis of high-resolution data collected by autonomous underwater gliders equipped with an instrument package for small-scale turbulence measurements. Generally, the gliders are controlled via satellite and are able to uninterruptedly collect data for several weeks even under adverse weather conditions. The gliders are able to measure physical properties ranging from the surface of the water column until approximately a thousand meters depth. This, for example, advances knowledge of turbulence levels, mixing rates and heat transfers across the water column during storms. As for the numerical modelling, I conduct Large Eddy Simulations using PALM (Parallelized Large Eddy Simulation Model for atmospheric and oceanic flows) to improve the understanding of wind-wave dynamics.