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Related papers: Estimating eddy diffusivities from noisy Lagrangia…

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A Bayesian approach is developed for the inference of an eddy-diffusivity field from Lagrangian trajectory data. The motion of Lagrangian particles is modelled by a stochastic differential equation associated with the advection-diffusion…

Atmospheric and Oceanic Physics · Physics 2019-09-04 Y. K. Ying , J. R. Maddison , J. Vanneste

Standard and anomalous transport in incompressible flow is investigated using multiscale techniques. Eddy-diffusivities emerge from the multiscale analysis through the solution of an auxiliary equation. From the latter it is derived an…

Condensed Matter · Physics 2009-10-22 L. Biferale , A. Crisanti , M. Vergassola , A. Vulpiani

We introduce a 3D multiscale kinematic velocity field as a model to simulate Lagrangian turbulent dispersion. The incompressible velocity field is a nonlinear deterministic function, periodic in space and time, that generates chaotic mixing…

Chaotic Dynamics · Physics 2009-11-13 Guglielmo Lacorata , Andrea Mazzino , Umberto Rizza

Low Stokes number particles at dilute concentrations in turbulent flows can reasonably be approximated as passive scalars. The added presence of a drift velocity due to buoyancy or gravity when considering the transport of such passive…

Fluid Dynamics · Physics 2024-11-20 Omkar B. Shende , Liam Storan , Ali Mani

The diffusive properties in velocity fields whose small scales are parameterized by non $\delta$-correlated noise is investigated using multiscale technique. The analytical expression of the eddy diffusivity tensor is found for a 2D steady…

Condensed Matter · Physics 2009-10-31 P. Castiglione , A. Crisanti

We research adaptive maximum likelihood-type estimation for an ergodic diffusion process where the observation is contaminated by noise. This methodology leads to the asymptotic independence of the estimators for the variance of observation…

Statistics Theory · Mathematics 2017-12-05 Shogo H. Nakakita , Masayuki Uchida

We research adaptive maximum likelihood-type estimation for an ergodic diffusion process where the observation is contaminated by noise. This methodology leads to the asymptotic independence of the estimators for the variance of observation…

Statistics Theory · Mathematics 2018-05-30 Shogo H. Nakakita , Masayuki Uchida

One issue associated with the use of Large-Eddy Simulation (LES) to investigate the dispersion of small inertial particles in turbulent flows is the accuracy with which particle statistics and concentration can be reproduced. The motion of…

Mesoscale eddies are critical in ocean circulation and the global climate system. Standard eddy identification methods are usually based on deterministic optimal point estimates of the ocean flow field. However, uncertainty exists in…

Dynamical Systems · Mathematics 2024-09-24 Jeffrey Covington , Nan Chen , Stephen Wiggins , Evelyn Lunasin

Methodologies to improve disdrometer processing, loosely based on mathematical techniques common to the field of particle flow and fluid mechanics, are examined and tested. The inclusion of advection and vertical wind field estimates…

Atmospheric and Oceanic Physics · Physics 2015-05-13 John E. Lane , Takis Kasparis , Philip T. Metzger , W. Linwood Jones

The large-scale/long-time transport of inertial particles of arbitrary mass density under gravity is investigated by means of a formal multiple-scale perturbative expansion in the scale-separation parametre between the carrier flow and the…

Fluid Dynamics · Physics 2019-02-13 Marco Martins Afonso , Andrea Mazzino , Paolo Muratore-Ginanneschi

In this work, a stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the large-scale oceanic circulation. This stochastic framework arises from a decomposition of the…

Geophysics · Physics 2022-07-26 Long Li , Bruno Deremble , Noé Lahaye , Etienne Mémin

This paper addresses the estimation of uncertain distributed diffusion coefficients in elliptic systems based on noisy measurements of the model output. We formulate the parameter identification problem as an infinite dimensional…

Optimization and Control · Mathematics 2015-06-11 Jeff Borggaard , Hans-Werner van Wyk

We use the recently developed Macroscopic Forcing Method [Mani and Park, Physical Review Fluids, 6:054607, 2021] to compute the scale-dependent eddy diffusivity characterizing ensemble-averaged scalar and momentum transport in…

Fluid Dynamics · Physics 2022-01-19 Yasaman Shirian , Ali Mani

In this paper, we consider the adaptive Eulerian--Lagrangian method (ELM) for linear convection-diffusion problems. Unlike the classical a posteriori error estimations, we estimate the temporal error along the characteristics and derive a…

Numerical Analysis · Mathematics 2012-09-07 Xiaozhe Hu , Young-Ju Lee , Jinchao Xu , Chensong Zhang

We present a novel methodology based on filtered data and moving averages for estimating effective dynamics from observations of multiscale systems. We show in a semi-parametric framework of the Langevin type that our approach is…

Numerical Analysis · Mathematics 2022-01-25 Giacomo Garegnani , Andrea Zanoni

Measurements of atmosphere-surface exchange are largely limited by the availability of fast-response gas analyzers; this limitation hampers our understanding of the role of terrestrial ecosystems in atmospheric chemistry and global change.…

Atmospheric and Oceanic Physics · Physics 2024-09-04 Anas Emad

Lagrangian descriptors provide a global dynamical picture of the geometric structures for arbitrarily time-dependent flows with broad applications. This paper develops a mathematical framework for computing Lagrangian descriptors when…

Fluid Dynamics · Physics 2023-07-11 Nan Chen , Evelyn Lunasin , Stephen Wiggins

In this work, eddy diffusivity is derived from the energy spectra for the stable and convective regimes in the planetary boundary layer. The energy spectra are obtained from a spectral model for the inertial subrange that considers the…

Atmospheric and Oceanic Physics · Physics 2024-08-20 A. Goulart , J. M. S. Suarez , M. J. Lazo , J. C. Marques

Statistical inference for stochastic processes has advanced significantly due to applications in diverse fields, but challenges remain in high-dimensional settings where parameters are allowed to grow with the sample size. This paper…

Statistics Theory · Mathematics 2025-01-29 Dmytro Marushkevych , Francisco Pina , Mark Podolskij
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