Journal ArticleDOI
Stochastic 2D primitive equations: Central limit theorem and moderate deviation principle
TLDR
This is the first result about the limit theorem and the moderate deviations for stochastic primitive equations driven by multiplicative noise and the weak convergence method is established.Abstract:
In this paper, we establish a central limit theorem and a moderate deviation for two-dimensional stochastic primitive equations driven by multiplicative noise. This is the first result about the limit theorem and the moderate deviations for stochastic primitive equations. The proof of the results relies on the weak convergence method and some delicate and careful a p r i o r i estimates.read more
Citations
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Conservative stochastic PDE and fluctuations of the symmetric simple exclusion process
TL;DR: In this article, the authors provided a model for the fluctuations of the symmetric simple exclusion process about its hydrodynamic limit based on an approximating sequence of stochastic PDEs with nonlinear, conservative noise.
Journal ArticleDOI
Moderate deviation principle for the 2D stochastic convective Brinkman–Forchheimer equations
TL;DR: In this article, the authors studied the asymptotic behavior of the two-dimensional stochastic convective Brinkman-Forchheimer (SCBF) equations for the motion of incompressible viscous fluid.
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Semilinear stochastic partial differential equations: central limit theorem and moderate deviations
Rangrang Zhang,Jie Xiong +1 more
TL;DR: In this paper, the authors established a central limit theorem and moderate deviation principle for a class of semilinear stochastic partial differential equations driven by multiplicative noise on a bounded domain.
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Global well-posedness of stochastic 2D primitive equations with random initial conditions
Guoli Zhou,Boling Guo +1 more
TL;DR: In this article, the authors considered 2D stochastic primitive equations (PEs) driven by affine-linear multiplicative white noise and with random initial conditions and obtained the global well-posedness of the PEs when the random initial condition satisfies sufficient Malliavin regularity.
Journal ArticleDOI
LDP and CLT for SPDEs with transport noise
Lucio Galeati,Dejun Luo +1 more
TL;DR: In this paper , the authors consider solutions to stochastic partial differential equations with transport noise, which are known to converge, in a suitable scaling limit, to solution of the corresponding deterministic PDE with an additional viscosity term.
References
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Book
Large Deviations Techniques and Applications
Amir Dembo,Ofer Zeitouni +1 more
TL;DR: The LDP for Abstract Empirical Measures and applications-The Finite Dimensional Case and Applications of Empirically Measures LDP are presented.
Book
Geophysical Fluid Dynamics
TL;DR: In this article, the authors propose a quasigeostrophic motion of a Stratified Fluid on a Sphere (SFL) on a sphere, which is based on an Inviscid Shallow-Water Theory.
Book
A weak convergence approach to the theory of large deviations
TL;DR: The Laplace Principle for the Random Walk Model with Discontinuous Statistics as mentioned in this paper has been extended to the continuous-time Markov Processes with continuous statistics, and the Laplace principle has been used for the continuous time Markov Chain model as well.
Journal ArticleDOI
Stochastic climate models, part II. Application to sea-surface temperature anomalies and thermocline variability
TL;DR: In this paper, it is shown that large-scale, long-time sea surface temperature (SST) anomalies may be explained naturally as the response of the oceanic surface layers to short-time-scale atmospheric forcing.
Journal ArticleDOI
On the generation of waves by turbulent wind
TL;DR: In this article, it was shown that the most prominent waves are ripples of wavelength λcr = 1·7 cm, corresponding to the minimum phase velocity c = (4gT/ρ)1/4 and moving in directions cos-1(c/Uc) to that of the mean wind, where Uc is the "convection velocity" of the surface pressure fluctuations of length scale λ cr or approximately the average wind speed at a height λCr above the surface.