Stochastic Transport in Upper Ocean Dynamics II

lt;b>Bertrand Chapron is a Director of Research at Ifremer - French Research Institute for Exploitation of the Sea, France. His research activities lie in applied mathematics, physical oceanography, electromagnetic wave theory and its applications to ocean remote sensing, and data processing.
Dan Crisan is a Professor at the Department of Mathematics of Imperial College London, UK, and Director of the EPSRC Centre for Doctoral Training in the Mathematics of Planet Earth. His current research interests lie in stochastic analysis, fluid dynamics, nonlinear filtering and probabilistic numerical methods.
Darryl Holm is a Professor of Mathematics at Imperial College London, UK, and a Fellow of Los Alamos National Laboratory, USA. His works have applied geometric mechanics in many topics, including geophysical fluid dynamics (GFD) for ocean circulation, stochastic fluid dynamics, turbulence, nonlinear waves, and stochastic optimal control for shape analysis.

Étienne Mémin is a Director of Research at Inria - National Institute for Research in Digital Science and Technology, France. His research focuses on stochastic modeling of fluid flows and data assimilation, an activity that crosses disciplines such as geophysics, fluid mechanics,  and applied mathematics.
Anna Radomska is a Programme Project Manager at Imperial College London, UK.

Internal tides energy transfers and interactions with the mesoscale circulation in two contrasted areas of the North Atlantic.- Sparse-stochastic model reduction for 2D Euler equations.- Effect of Transport Noise on Kelvin-Helmholtz instability.- On the 3D Navier-Stokes Equations with Stochastic Lie Transport.- On the interactions between mean flows and inertial gravity waves in the WKB approximation.- Toward a stochastic parameterization for oceanic deep convection.- Comparison of Stochastic Parametrization Schemes using Data Assimilation on Triad Models.- An explicit method to determine Casimirs in 2D geophysical flows.- Correlated structures in a balanced motion interacting with an internal wave.- Linear wave solutions of a stochastic shallow water model.- Analysis of Sea Surface Temperature variability using machine learning.- Data assimilation: A dynamic homotopy-based coupling approach.- Constrained random diffeomorphisms for data assimilation.- Stochastic compressible Navier-Stokes equations under location uncertainty.- Data driven stochastic primitive equations with dynamic modes decomposition.