Quantifying the role of AMOC decline in climate change impacts

Project Details

Project Description

Projections of regional climate change are of vital importance for societies planning adaptation and mitigation strategies, yet these projections are still plagued by large uncertainties. This project will focus on one particular source of uncertainty, namely the Atlantic Meridional Overturning Circulation (AMOC) which transports heat northwards in the Atlantic Ocean and thereby has an important influence on the climate of the adjacent continents. 

Climate models consistently predict a weakening of the AMOC in response to greenhouse gas forcing, but with a large uncertainty in the strength of this decline. This uncertainty in ocean circulation is expected to lead to uncertainty in impacts as diverse as Northern Hemisphere temperatures, African rainfall patterns, tropical cyclones and European rainfall and storms. However, due to the coupled nature of the climate system, it has not yet been possible to definitively attribute uncertainty in these impacts to uncertainty in the AMOC. Other features of the climate system, such as overall climate sensitivity, are also simulated differently across the range of models, and may contribute to the uncertainty in these regional climate change impacts. Identifying the contributions to uncertainty from different components of the climate system, such as the AMOC, is therefore vital to targeting model development where it is most likely to improve confidence in climate change projections. 

This project will attempt to address the question of the AMOC’s impact on projections of regional climate. In the first component, the student will analyse simulations from the new CMIP6 database of models, which will feed into the next report of the Intergovernmental Panel on Climate Change. The aim will be to examine how different projections of key regional climate change indices are related to the projected change in the AMOC and other key global climate indicators. This will give an initial estimate of the relative sensitivity of regional climate to AMOC uncertainty. A key aspect will be to determine to what extent the differences in the AMOC projections are independent of other uncertainties, such as the strength of the overall climate change response in the model (climate sensitivity). 
The next stage of work will involve performing novel experiments with the Met Office’s state-of-the-art coupled atmosphere-ocean climate model and a detailed analysis of the results. A set of simulations of the 21st century will be performed which will all share the same predicted greenhouse gas forcing but will be engineered to give a range of possible rates of AMOC decline. This will be achieved by adding salinity perturbations to the model in the high-latitude North Atlantic to specifically influence the AMOC. Analysis of this set of experiments will provide a further estimate of the sensitivity of a range of climate impacts to the strength of the AMOC response over the coming century. This approach has the benefit of the AMOC not being itself dependent on other facets of the climate change response (since it is essentially imposed). The student will relate the findings of this novel modelling to the results from the analysis of the CMIP6 projections.
By the end of the project, the student will have derived two new estimates of the importance of AMOC uncertainty on regional climate change. This will allow recommendations to be made which will provide the climate research community with information on how important it is to focus on improving modelling AMOC for better regional prediction (alongside other reasons to be interested in AMOC, such as for decadal predictions).      

The work will involve analysis of existing climate model data using a programming language such as Python. The student will also perform the new climate model experiments on a joint supercomputing facility with support from supervisors and others. 

Please contact Tim Woollings on tim.woollings@physics.ox.ac.uk if you are interested in this project