Loading…
Loading grant details…
| Funder | Engineering and Physical Sciences Research Council |
|---|---|
| Recipient Organization | Imperial College London |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Sep 29, 2028 |
| Duration | 1,460 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2926199 |
A shutdown of the Atlantic overturning circulation, triggered by increased surface freshening, is considered as a potential transition into a fundamentally different climate regime. However, the actual risks of crossing this tipping point, the underlying dynamics, and the climate impacts remain elusive.
Thus, this project will test the hypothesis that increased freshwater discharges from Greenland and the Arctic will fundamentally change the North Atlantic Ocean circulation, triggering a transition into a different climate state.
Starting from the two-box model developed by Kuhlbrodt et al. (2001), which consists of a seasonal mixed layer, a deep layer, and a stochastic noise term, the model will be extended to include: the observed trend in surface freshening; observed increases in the seasonal freshwater cycle; improved estimates of lateral eddy fluxes and mixing; negative feedbacks in the atmospheric forcing; as well as newly developed volume estimates of a potential Arctic freshwater release. These new elements are derived from a substantially grown repertoire of observations, new methods to infer the variability of freshwater, and new insights into the ocean-atmosphere feedback to freshwater.
Thus, in contrast to more complex models, the idealised models developed in this project will build on realistic parameter ranges and are designed to capture critical feedback mechanisms.
After formulating the model, a dynamical systems approach will be applied on it to test for the existence of critical freshwater thresholds and determine the physical underpinnings. Large-scale climate impacts will be assessed by estimating ocean responses and atmospheric feedbacks using conceptual, reduced-order models.
Imperial College London
Complete our application form to express your interest and we'll guide you through the process.
Apply for This Grant