Abrupt changes in the climate system could have potentially devastating socio-economic impacts. Simulating them in future climate scenarios is therefore of great importance. Future climate change scenarios are often based on the average or mean of climate model projections where abrupt changes and tipping points can appear in one or a few realizations of a subset of the models (Drijfhout et al. 2015). Additionally, climate models are often tuned to simulate a stable version of the present-day climate and remain untested in abrupt climate shift scenarios.
We propose to extend the findings of Drijfhout et al. (2015) with the newest generation of climate model simulations, generating a catalog of abrupt changes, along with analysis of the relevant feedbacks that may lead to abrupt change. For instance, changes in ocean heat and freshwater transports have a large impact on the Atlantic Meridional Overturning Circulation (AMOC), which is the main mode of ocean circulation in the Atlantic and impacts European climate. The initial focus will be on AMOC tipping points, with an additional focus on other tipping points that can be chosen from the catalogue of abrupt changes (i.e. abrupt sea ice loss, vegetation changes, etc.).
In Drijfhout et al. (2015) search, selection and classification criteria were developed allowing identification of abrupt climate changes in model simulations. New scripts and tools will become available in the Tipping Point analysis led by Profs Drijfhout and Lenton of the EU-funded program OptimESM. In a first phase, the student will apply available scripts to the newest set of climate model projections (CMIP6).
In a second phase, the student will focus on the AMOC, and the role of model bias, resolution and model physics on the likelihood and predictability of AMOC tipping and occurrence of Early Warning Signals, using the methodology of Mecking et al. (2017) and existing (new) observations from the subpolar North Atlantic to assess how close this system is to a freshwater-related tipping point.
In a third phase, the student will focus on one or more tipping element(s) of their own choice, perform a relevant feedback analysis, and subsequently investigate how the biased climate states simulated in the coupled climate models affect these feedbacks, amplifying or hampering nonlinear growth and abrupt climate change.
The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted at the National Oceanography Centre, Southampton, UK. Specific training will
- Learning to use a range of tools from simple numerical and mathematical models to advanced climate models. The candidate will be encouraged to attend summer schools on topics relevant to the project (i.e. ocean/climate dynamics, climate statistics, big-data, etc.).
- Receive training in the use of coding languages such as Python, MATLAB, Ferret and/or Fortran.
- Optional training in ocean observation techniques, which will include the opportunity to take part in a research expedition. More information on past and upcoming research expeditions led by the NOC listed here: https://noc.ac.uk/science/research-expeditions
The student will join the multi-disciplinary modelling team at UoS/NOC and receive training in analysis of large model/observational datasets. They will acquire a solid background in ocean circulation and climate change theories and theories on tipping points in a changing climate. They will join an active team of postdoctoral researchers and postgraduate students focusing on the role of the ocean in climate and connect to the tipping-point-analysis team in OptimESM. They will be encouraged to present results at national and international conferences.
Please see https://inspire-dtp.ac.uk/how-apply for details.
Drijfhout et al. 2015: Catalogue of abrupt shifts in Intergovernmental Panel on Climate Change climate models. Proceedings of the National Academy of Sciences of the United States of America, 112, E5777-E5786, doi:10.1073/pnas.1511451112.
Mecking et al. 2017: The effect of model bias on Atlantic freshwater transport and implications for AMOC bi-stability. Tellus A: Dynamic Meteorology and Oceanography, 69(1), p.1299910.
Boers, N. 2021 Observation-based early-warning signals for a collapse of the Atlantic Meridional Overturning Circulation. Nat. Clim. Change 11, 680–688.