Collaborative Research: A global census of submesoscale energetics using in-situ drifter observations and a high resolution ocean model

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Oceanic motions are turbulent over a wide range of scales, but observationally this turbulence has primarily been investigated at the smallest ( 1km) and at the largest ( 100km) scales. Many of the properties of the oceanic flow field at intermediate scales, referred to as the submesoscales, have remained relatively elusive because of observational limitations: most high-resolution in-situ observational measurements have limited spatial range while satellite-based velocity estimates have limited spatial resolution. In addition, satellite-based surface velocities are estimated using the simplified physics assumptions (geostrophy), which breaks down at the submesoscales. Overall, a global view of kinetic energy as a function of length scale in the submesoscale range is not currently available. The primary goals of this project are i) to estimate kinetic energy distribution and transfers at submesoscales, ii) to understand the role of balanced and wave-like flow components in setting these submesoscale energetics, and iii) to quantify how and assess why these submesoscale flow properties vary globally. This research will quantify global submesoscale kinetic energy content, its dynamical characteristics, and transfers as a function of spatial-scale, using existing surface drifter observations from NOAA. Global observations of kinetic energy at these scales have never been examined before: this work is a unique opportunity to characterize the spatial patterns and seasonal variability of ocean submesoscale flows, and to assess the effects of mixed layer depth and surface forcing on energy content at these scales. These estimates will provide the first global observational baseline to compare against future observations and high-resolution simulations, and one such comparison will be performed in this work. In addition, these observations will elucidate the energy budget of the global ocean by quantifying energy transfers across scales. In coarse resolution climate models, subgrid-scale parameterizations represent the effects of submesoscale motions: the baseline provided by this work will help improve these parameterizations in the future. The analysis will provide a useful ground truth to validate and calibrate future satellite observations, and to quantify biases in high resolution ocean models. Improved understanding of ocean energetics also has direct relevance for the development of better subgrid scale parameterizations for ocean and climate models. Additionally, this project will generate documented and open-source Python code for processing observational and synthetic Lagrangian data for future studies of ocean energetics. In terms of workforce training, this project will support one graduate student, who will learn how to analyze high-resolution model data using parallel processing tools in Python. Two undergraduate students will conduct suitable research projects and will be mentored through the Research Experiences for Undergraduates program at two different institutions. Two early-career scientists will be supported by this project.To achieve its goals, this study will analyze the position and velocity data from the drifting surface buoys of the Global Drifter Program, with the help of two-point spatial statistics. Specifically, it will use the second order structure function to quantify how kinetic energy is distributed as a function of scale, and the third order structure function to quantify how kinetic energy is transferred across scales. Additionally, it will make use of Lagrangian filtering to quantify the statistical properties of and interactions between balanced and wave-like motions. These observational data analyses will be supported by the analysis of a high-resolution global ocean simulation, which will allow for the quantification of the biases caused by Lagrangian sampling.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.