Ocean circulation control of heat and carbon uptake

Extra supervisors: Dr Phil Goodwin (Southampton), Dr Alessandro Tagliabue (University of Liverpool)

Introduction:

This studentship examines a fundamental question of how the ocean uptake of heat and carbon from the atmosphere are related to each other. There is a general expectation that the ocean uptake of heat and carbon will increase and follow each other given the rise in atmospheric CO2 and the background warming of the climate system. We wish to assess how the ocean uptake of heat and carbon varies, and how they are related to each other, for different ongoing changes in ocean circulation, including changes in the meridional overturning in the North Atlantic and Southern Ocean.

This project is motivated by the question of why global warming is nearly linearly proportional to carbon emissions, a central outcome of the IPCC [2013] report [Stocker, 2013]. We have explained this response by assuming that the global ocean uptake of heat and CO2 due to climate change is similar to each other [Goodwin, Williams & Ridgwell, 2015, Nature Geoscience]. However, what is unknown is how similar the ocean uptake of heat and carbon is for changes in ocean circulation, such as changes in meridional overturning in the North Atlantic and Southern Ocean, or El Nino/La Nina cycles.

Project Summary:

This project aims to investigate how the ocean uptake of heat and CO2 varies for changes in ocean circulation, including regional changes in ocean overturning and El Nino/La Nina states.

The plan of work for the student involves analysing the thermal and carbon responses of the ocean and climate system using a hierarchy of models, perturbed by changes in physical forcing.

Our research questions are:

• ocean heat and CO2 uptake are likely to be similar for the upper ocean involving gyre circulation;

• ocean heat and CO2 uptake are likely to differ for the deep ocean involving the overturning circulation, where there is an asymmetrical response in the Atlantic and Pacific.

The student will investigate the ocean heat and CO2 uptake for a range of physical perturbations, including changes in North Atlantic and Southern Ocean overturning, and in El Nino/La Nina cycles.

These physical perturbations will be applied to a range of simple to more complex models including:

• 2 layer model of the ocean [Gnandesikan, 1999], where changes in upper ocean heat content will be assessed, and including a slab atmosphere to provide the radiative forcing;

• an efficient multi-layer ocean box model for an idealised global domain [Goodwin, 2012];

• a state of the art MIT ocean general circulation model, which we have used to explore how ocean overturning affects atmospheric CO2 on millennial timescales [Lauderdale et al.,2013];

• the Fast Ocean Atmosphere Model (FOAM), NCAR Community Earth System Model to explore ocean overturning and heat uptake in a coupled atmosphere and ocean model.

The outcomes of the work are relevant to a central question of the last IPCC report [Stocker, 2013], which is why surface warming is linearly dependent on carbon emissions. In our view, this response is a consequence of the how the ocean takes up heat and carbon [Goodwin et al., 2014] and long-term dependencies of the climate system [Williams et al., 2012]. This project will test that assertion.

This work plan can be revised and modified according to the input and aptitude of the student.

The student will have the opportunity for an extended visit to project partners, Jon Lauderdale and Mick Follows at MIT, to gain skills in integrating the MIT GCM. Training in the idealised atmospheric-ocean coupled model is provided by David Schultz at Manchester.

Applicants should have a strong academic track record with a science degree, such as including Ocean Sciences, Meteorology, Mathematics, Physics or Engineering. The project involves analysing data and integrating ocean models, so that the student needs to have an aptitude for quantitative work. Prior experience in computational and numerical work is though not required, as training in developing simple models and analysing data is provided in the first year of the PhD.