Published Research

My scientific projects use models to explain and synthesize climate data, estimate model parameters, assess uncertainties, and deepen our understanding of Earth’s climate. Specifically, I am interested in investigating complex relationships between global and local phenomena.

Improving estimates of heat and material transports within the Earth system, which are not directly observable and remain a critical source of uncertainty in climate science, is one of my long term goals. I have made significant contributions to our understanding of the observed Earth energy budget and water cycle.

My published research has ...

  • demonstrated that data collected by an array of ocean robots like Argo allow us to infer basin scale transports via data assimilation (Forget, 2005, Forget et al., 2008a, Forget et al., 2008b, Forget, 2010. This gave us improved estimates of the meridional ocean circulation for example.

  • mapped out ocean temperature, salinity, and sea level variance from sparse data, and attributed it to processes and scales (Forget and Wunsch, 2007; Forget and Ponte, 2015). We can now better distinguish large-scale climate responses from meso-scale signals in the ocean.

  • derived water mass transformation estimates that bring into agreement ocean observations and atmospheric reanalyses (Forget, 2010, Forget et al., 2011, Speer and Forget, 2013). A robust view of seasonal heating and cooling at mid-latitude was thus obtained.

  • established that turbulent transport rate parameters can be inferred from observation of the large scale ocean state through inverse modeling (Forget et al., 2015a, Forget et al., 2015b). We showed that optimized parameters reduce spurious model drifts up to multi-centennial time scales.

  • provided a synthetic view of regional sea level variability over the satellite record and estimated the contribution of different physical processes (Forget and Ponte, 2015). We showed how wind stress at the basin scale dominates inter-annual sea level variability.

  • found that structural uncertainty in models (e.g., changing advection schemes) is a significant issue for decadal ocean state estimation, even though parametric uncertainty (e.g., diffusion and advection rates) tends to be a bigger problem (Forget et al., 2015a).

  • revealed that global ocean heat transport is dominated by the tropical Pacific when considered from the perspective of Earth’s Energy budget (Forget and Ferreira, 2019).

  • characterized the global overturning circulation by tracking virtual particles over thousands of years in a data constrained model. This allowed us to evaluate three main pathways for the global ocean conveyor belt (Rousselet et al., 2020, Rousselet et al., 2021).

  • assimilated data in a particle tracking model to constrain the convergence of plastic garbage in the surface ocean layer of oceanic gyres (Peytavin et al., 2021).