504 citations · 1.2k across the 18 of their papers we have counts for
18 papers
Optimal Parameterizing Manifolds for Anticipating Tipping Points and Higher-order Critical Transitions
Mickaël D. Chekroun, Honghu Liu, James C. McWilliams
A general, variational approach to derive low-order reduced systems is presented. The approach is based on the concept of optimal parameterizing manifold (OPM) that substitutes the…
The High-Frequency and Rare Events Barriers to Neural Closures of Atmospheric Dynamics
Mickaël D. Chekroun, Honghu Liu, Kaushik Srinivasan +1
Recent years have seen a surge in interest for leveraging neural networks to parameterize small-scale or fast processes in climate and turbulence models. In this short paper, we po…
Turbulence closure with small, local neural networks: Forced two-dimensional and -plane flows
Kaushik Srinivasan, Mickael D. Chekroun, James C. McWilliams
We parameterize sub-grid scale (SGS) fluxes in sinusoidally forced two-dimensional turbulence on the -plane at high Reynolds numbers (Re25000) using simple 2-layer Convolu…
Transitions in Stochastic Non-equilibrium Systems: Efficient Reduction and Analysis
Mickaël D. Chekroun, Honghu Liu, James C. McWilliams +1
A central challenge in physics is to describe non-equilibrium systems driven by randomness, such as a randomly growing interface, or fluids subject to random fluctuations that acco…
Overlapping boundary layers in coastal oceans
Chao Yan, James C. McWilliams, Marcelo Chamecki
Boundary layer turbulence in coastal regions differs from that in deep ocean because of bottom interactions. In this paper, we focus on the merging of surface and bottom boundary l…
Generation of attached Langmuir circulations by a suspended macroalgal farm
Chao Yan, James C. McWilliams, Marcelo Chamecki
In this study, we focus on Langmuir turbulence in the deep ocean with the presence of a large macroalgal farm using a Large Eddy Simulation method. The wave-current interactions ar…