Physically-Based Ocean Transport

Introduction

The ocean absorbs 90% of the heat associated with global warming and 30% of anthropogenic CO2. How such tracers are accumulated and redistributed within the turbulent ocean is a central issue of long-term climate prediction. The challenge stems from the existence of ocean mesoscale eddies: turbulent vortices tens of kilometers wide that are not resolved by climate models despite being key contributors to ocean transport.

Current Challenges

In the absence of a better theory, the associated transport is parameterized in global models using ad hoc coefficients with arbitrary depth dependence. The present project will improve upon this unsatisfactory state of the art.

Project Overview

Based on a multi-method approach combining theory, laboratory experiments, numerical simulations, and satellite data analysis, I will derive a physically-based parameterization for turbulent transport in the 3D ocean. The derivation hinges on my recent quantitative theoretical advances for the magnitude and 3D structure of turbulent transport in the canonical models of oceans and atmospheres (the Charney, Eady, and Phillips models):

1. I will augment these theories by including the additional physical ingredients of the real ocean: bottom slope, arbitrary large-scale flow, and density stratification, etc.
2. I will determine the frictional dissipation on the ocean floor by combining rotating-platform laboratory experiments with 3D-printed realistic ocean-floor topography.
3. I will infer transport and bottom friction independently through the combination of satellite and profiler data.
4. I will derive the resulting parameterization using multiple-scale expansion before implementing it in a state-of-the-art climate model.

Future Implications

As opposed to the current practice of adjusting transport coefficients to the current state of the ocean, the physically-based parameterization will remain valid in a warming climate. This is a necessary condition both for paleoclimate studies and for reliable climate forecasts over the coming centuries to millennia.