146 citations · 430 across the 9 of their papers we have counts for
9 papers
Ensemble forecasts in reproducing kernel Hilbert space family
Benjamin Dufée, Bérenger Hug, Etienne Mémin +1
A methodological framework for ensemble-based estimation and simulation of high dimensional dynamical systems such as the oceanic or atmospheric flows is proposed. To that end, the…
A consistent stochastic large-scale representation of the Navier-Stokes equations
Arnaud Debussche, Berenger Hug, Etienne Memin
In this paper we analyze the theoretical properties of a stochastic representation of the incompressible Navier-Stokes equations defined in the framework of the modeling under loca…
Hamiltonian formulation of the stochastic surface wave problem
Evgueni Dinvay, Etienne Memin
We devise a stochastic Hamiltonian formulation of the water wave problem. This stochastic representation is built within the framework of the modelling under location uncertainty.…
Eigenvalues of Autocovariance Matrix: A Practical Method to Identify the Koopman Eigenfrequencies
Yicun Zhen, Bertrand Chapron, Etienne Memin +1
To infer eigenvalues of the infinite-dimensional Koopman operator, we study the leading eigenvalues of the autocovariance matrix associated with a given observable of a dynamical s…
Learning Variational Data Assimilation Models and Solvers
Ronan Fablet, Bertrand Chapron, Lucas. Drumetz +3
This paper addresses variational data assimilation from a learning point of view. Data assimilation aims to reconstruct the time evolution of some state given a series of observati…
Geophysical flows under location uncertainty, Part III: SQG and frontal dynamics under strong turbulence conditions
Valentin Resseguier, Etienne Memin, Bertrand Chapron
Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly modified to include an advec…
Geophysical flows under location uncertainty, Part II: Quasi-geostrophy and efficient ensemble spreading
Valentin Resseguier, Etienne Memin, Bertrand Chapron
Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly modified to include an advec…
Stochastic modelling and diffusion modes for proper orthogonal decomposition models and small-scale flow analysis
Valentin Resseguier, Etienne Mémin, Dominique Heitz +1
We present here a new stochastic modelling in the constitution of fluid flow reduced-order models. This framework introduces a spatially inhomogeneous random field to represent the…
Fluid flow dynamics under location uncertainty
Etienne Mémin
We present a derivation of a stochastic model of Navier Stokes equations that relies on a decomposition of the velocity fields into a differentiable drift component and a time unco…