Reports
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.
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.
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.
Hunting fronts
SML fronts also host various frontal instabilities which are considered as routes to mixing and energy dissipation in the energy cascade.
Hi, my name is Jen-Ping Peng. I am a PhD student of the subproject T2: “Energy budget of the ocean surface mixed layer” under supervision of Dr. Lars Umlauf at the Leibniz Institute for Baltic Sea Research (IOW) in Warnemünde. I investigate the oceanic surface mixed layer (SML), typically known to have substantial turbulent mixing driven by vertical surface forcing such as wind stress and surface buoyancy fluxes. However, the processes inside the SML are considerably complicated by strong horizontal density gradients (e.g., fronts, filaments), which may induce restratification that competes with mixing. SML fronts also host various frontal instabilities which are considered as routes to mixing and energy dissipation in the energy cascade. We address surface-layers fronts and their associated restratification and mixing processes based on the data collected from several cruises in different areas of the ocean.
The analysis of data from research cruises is one of the main tasks of my PhD. The TRR181 cruises took place in the Benguela upwelling system (South-East Atlantic Ocean) in 2016, closely coordinated with subproject L3 using drifters, and in the Central Baltic Sea in 2017 and 2018. These two study areas are characterized by the rich presence of fronts and filaments, ideally suited for the investigation of the processes studied in this subproject. I participated in two research campaigns in the central Baltic Sea. Together with our T2 colleagues from HZG, we were hunting fronts with specialized instrumentations, including turbulence microstructure profilers, a Scanfish, a research catamaran, and ocean gliders.
I am currently analyzing data obtained from the Benguela upwelling system toward a better understanding of the formation and decay of an upwelling filament, and related instabilities and mixing. I am also involved in the analysis of a related data set that we collected in a frontal region in the central Baltic Sea.
Focussing on the ocean surface mixed layer
Our scope is to investigate the sub-mesoscale structures and the surface mixed layer instabilities in order to develop new parameterisations of energy consistent pathways.
My name is Evridiki and I’m PhD candidate working with Prof. Dr. Hans Burchard, in subproject T2. Our research will be focused mainly on the ocean surface mixed layer which is a highly complex and energetic region. The upper ocean is characterized by a relative shallow mixing layer with weak stratification due to turbulent mixing. Our scope is to investigate the sub-mesoscale structures and the surface mixed layer instabilities in order to develop new parameterisations of energy consistent pathways, associated with these motions. For that we will use the General Estuarine Transport Model (GETM) which includes turbulence closure models provided by GOTM, diagnostic tools for the numerical mixing and dissipation but also adaptive vertical coordinates that can resolve the sub-mesoscale features. The configurations will include idealized high resolution simulations as well as hindcast simulations of the Central Baltic Sea. In order to validate the model, the results will be combined with field observations.
