Observing, Modeling, and Parametrizing Oceanic Mixed Layer Transport Processes

Introduction

Although crucial in determining the oceanic distribution of heat, biological nutrients, carbon, and pollutants, the circulation dynamics that govern oceanic vertical transport processes of physical and biogeochemical properties through the near surface layer (i.e., mixed-layer; ML) are yet to be comprehensively quantified. Recently, we and others have demonstrated that submesoscale currents (SMCs) -- newly discovered flow structures consisting of fronts, filaments, and eddies -- have a strong influence on these exchange processes, which need to be fully explored and characterized.

Challenges in Measurement

The high spatiotemporal variability of SMCs and the complex physics that determine their interactions with other ML phenomena, like surface gravity waves and near-inertial waves, render in situ measurements of these processes extremely difficult to obtain.

Furthermore, current climate models lack the grid resolution and variable forcing components required to adequately represent ML physics, making it one of the greatest uncertainties in climate projections.

Research Objectives

The proposed research will address this critical gap through three objectives:

1. Develop the numerical capability to simulate ML physics in a realistic inhomogeneous environment while resolving boundary layer turbulence and wave dynamics.
2. Develop a theoretical framework for a physics-based parametrization of ML vertical exchange rates.
3. Directly measure turbulent mixing, tracer distribution, and transport rates near SMCs in situ, providing the crucial observational support necessary to guide and fine-tune the parameterizations.

Methodology

To achieve this goal, we will:

• Extend our frontogenesis theory.
• Analyze particle and tracer concentrations in carefully designed realistic and nested large-eddy simulations.
• Examine drifter trajectories and passive tracer spreading in multi-asset field campaigns.

Expected Impact

This synergistic approach will substantially impact oceanic biogeochemical modeling, pollutant transport mitigation, and climate projections.