Estimating scale dependent energy fluxes in the meso-to submesoscale-regime in the North Atlantic Ocean using spectral and structure function methods

The energy cycle in ocean models is still biased due to the large uncertainty regarding how processes in the mesoscale and submesoscale regimes are represented. Since mesoscale turbulence is largely geostrophic, it features an energy transfer towards larger scales. In contrast, submesoscale turbulen...

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Bibliographic Details
Main Authors: Leimann, I., Grisel, A., Walter, M., Dräger-Dietel, J., Epke, M.
Format: Conference Object
Language:English
Published: 2023
Subjects:
Online Access:https://gfzpublic.gfz-potsdam.de/pubman/item/item_5019237
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Summary:The energy cycle in ocean models is still biased due to the large uncertainty regarding how processes in the mesoscale and submesoscale regimes are represented. Since mesoscale turbulence is largely geostrophic, it features an energy transfer towards larger scales. In contrast, submesoscale turbulence can contain both geostrophic and ageostrophic dynamics which makes the direction of the energy flux less clear. Determining the kinetic energy spectrum of meso- to submesoscale turbulence in the ocean is challenging, since it depends on the horizontal resolution of data sets. Gridded satellite data give a good global overview, but are currently barely Rossby radius resolving. We here estimate the kinetic energy spectral fluxes from SSH data which give the geostrophic part, and compare them to spectral fluxes from a submesoscale permitting ocean model with a high-resolution (500m) focus region in the North Atlantic. The kinetic energy spectral fluxes are found to exhibit both inverse and forward cascades, with a stronger inverse cascade in turbulent areas and maximum inverse wavenumber increasing with latitude. In the model, the amplitude of the inverse cascade is up to five times higher than in the gridded satellite data. In addition to the spectral analysis we use structure functions which are the moments of velocity increments between two points and provide information about the properties of turbulent dynamics at different scales. This diagnostic is more readily obtained from observations, such as surface drifter data, which are globally available and can connect a range of scales from 10m to 1000km.