Abstract:
The North Atlantic Ocean circulation is the result of a range of physical processes, from large-scale gyre circulation (subtropical and subpolar), associated Ekman transports, inter-gyre boundary exchanges, westward intensification, watermass transformation at high latitudes along continental boundaries and in the interior, complex ("return") flows at depth, Arctic sub-Arctic exchanges, efficient communication between the tropics and mid-to-high latitude through wave propagation along boundaries, Rossby wave propagation, geostrophic eddies, and submesoscale processes, to name but a few. Interactions with the atmosphere and topography set crucial boundary conditions on the flow. Much of that circulation has been subsumed under the Atlantic Meridional Overturning Circulation (AMOC), a metric that provides a heavily space (and time)-integrated depiction of the circulation.
Understanding the role that the different elements, which make up the circulation, play, has involved a diverse and heterogeneous stream of observations (satellite and in-situ), which, taken together, constitute a sparse, eclectic observing system. Arguably, a rigorous way to combine the knowledge reservoir offered by the available, yet incomplete observations with the knowledge reservoir that is encapsulated in the governing equations of motion, rendered in the form of numerical models, is through formal ocean state and parameter estimation. The adjoint-based effort pursued by the Estimating the Circulation and Climate of the Ocean (ECCO) consortium has produced state estimates that have provided valuable insights into the AMOC in a number of studies. Beyond the use of the adjoint for state estimation, the tool has proven powerful in causal, dynamical attribution studies of subtropical and subpolar North (and South) Atlantic MOC. Furthermore, use of sensitivity (derivative) information are enabling rigorous studies of quantitative observing system design within the framework of Hessian-based uncertainty quantification.
I provide an overview of how the adjoint-based modeling framework supports studies of AMOC variability and observing system design. Time permitting, I will provide a brief outlook on an effort to seamlessly integrate inverse methods and scientific machine learning using the concept of differentiable programming for Earth system models in the programming language Julia (DJ4Earth).
What is the Joint Oslo Seminar (JOS):
- Atmospheric and climate sciences have a stronghold in Oslo among the four institutions University of Oslo, the Meteorological Institute, CICERO and NILU.
- This joint seminar invites renowned international experts to contribute to an informal series of lectures, meant to create interaction with the Oslo atmospheric and climate science community on recent highlights and analysis in the field.
- All seminars will be held on Thursdays (12:15 pm -1pm).