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We consider a recently introduced continuous data assimilation (CDA) approach for downscaling a coarse resolution configuration of the 2D Benard convection equations into a finer grid. In this CDA, a nudging term, estimated as the misfit…

Optimization and Control · Mathematics 2015-12-22 M. U. Altaf , E. S. Titi , O. M. Knio , L. Zhao , M. F. McCabe , I. Hoteit

Inclined turbulent thermal convection by large Rayleigh numbers in extremely small-Prandtl-number fluids is studied based on results of both, measurements and high-resolution numerical simulations. The Prandtl number $Pr\approx0.0093$…

Data assimilation plays a crucial role in modern weather prediction, providing a systematic way to incorporate observational data into complex dynamical models. The paper addresses continuous data assimilation for a model arising as a…

Analysis of PDEs · Mathematics 2026-02-03 Eduard Feireisl , Piotr Gwiazda , Agnieszka Świerczewska-Gwiazda

We are concerned with infinite Prandtl number Rayleigh--B\'enard convection with Navier-slip boundary conditions. The goal of this work is to estimate the average upward heat flux measured by the nondimensional Nusselt number $Nu$ in terms…

Analysis of PDEs · Mathematics 2026-03-24 Christian Seis

Numerical simulations of turbulent Rayleigh-B\'enard convection in an ideal gas, using either the anelastic approximation or the fully compressible equations, are compared. Theoretically, the anelastic approximation is expected to hold in…

Solar and Stellar Astrophysics · Physics 2015-05-27 Jan Verhoeven , Thomas Wiesehöfer , Stephan Stellmach

Rayleigh-B\'enard convection (RBC) is a fundamental problem of fluid dynamics, with many applications to geophysical, astrophysical, and industrial flows. Understanding RBC at parameter regimes of interest requires complex physical or…

Computational Physics · Physics 2021-01-29 Andrew Clarke , Chris Davies , Daniel Ruprecht , Steven Tobias , Jeffrey S. Oishi

Variational data assimilation optimizes for an initial state of a dynamical system such that its evolution fits observational data. The physical model can subsequently be evolved into the future to make predictions. This principle is a…

Machine Learning · Computer Science 2021-05-21 Thomas Frerix , Dmitrii Kochkov , Jamie A. Smith , Daniel Cremers , Michael P. Brenner , Stephan Hoyer

With the increasing penetration of high-frequency sensors across a number of biological and physical systems, the abundance of the resulting observations offers opportunities for higher statistical accuracy of down-stream estimates, but…

Optimization and Control · Mathematics 2020-11-06 Shushu Zhang , Vivak Patel

We prove stochastic stability of the three-dimensional Rayleigh-B\'enard convection in the infinite Prandtl number regime for any pair of temperatures maintained on the top and the bottom. Assuming that the non-degenerate random…

Analysis of PDEs · Mathematics 2023-09-15 Juraj Földes , Armen Shirikyan

Rayleigh-B\'enard convection is numerically simulated in two- and three-dimensions using a recently developed two-component lattice Boltzmann equation (LBE) method. The density field of the second component, which evolves according to the…

comp-gas · Physics 2016-08-31 Xiaowen Shan

Rayleigh-Benard convection in a cylindrical container can take on many different spatial forms. Motivated by the results of Hof, Lucas and Mullin [Phys. Fluids 11, 2815 (1999)], who observed coexistence of several stable states at a single…

Fluid Dynamics · Physics 2010-04-02 Katarayna Borońska , Laurette S. Tuckerman

An intrinsic property of almost any physical measuring device is that it makes observations which are slightly blurred in time. We consider a nudging-based approach for data assimilation that constructs an approximate solution based on a…

Analysis of PDEs · Mathematics 2018-09-05 Michael S. Jolly , Vincent R. Martinez , Eric J. Olson , Edriss S. Titi

Data assimilation (DA) integrates observations with model forecasts to produce optimized atmospheric states, whose physical consistency is critical for stable weather forecasting and reliable climate research. Traditional Bayesian DA…

Atmospheric and Oceanic Physics · Physics 2026-03-05 Hang Fan , Lei Bai , Ben Fei , Yi Xiao , Kun Chen , Yubao Liu , Yongquan Qu , Fenghua Ling , Pierre Gentine

Two-dimensional direct numerical simulations are conducted for convection sustained by uniform internal heating in a horizontal fluid layer. Top and bottom boundary temperatures are fixed and equal. Prandtl numbers range from 0.01 to 100,…

Fluid Dynamics · Physics 2015-03-13 David Goluskin , Edward A. Spiegel

Data assimilation of observational data into full atmospheric states is essential for weather forecast model initialization. Recently, methods for deep generative data assimilation have been proposed which allow for using new input data…

4D-variational data assimilation is applied to the Lorenz '63 model to introduce a new method for parameter estimation in chaotic climate models. The approach aims to optimise an Earth system model (ESM), for which no adjoint exists, by…

Atmospheric and Oceanic Physics · Physics 2025-04-18 Philip David Kennedy , Abhirup Banerjee , Armin Köhl , Detlef Stammer

Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and…

Computational Engineering, Finance, and Science · Computer Science 2017-05-09 Timo Heister , Juliane Dannberg , Rene Gassmöller , Wolfgang Bangerth

Rayleigh-B\'enard convection, i.e. the flow of a fluid between two parallel plates that is driven by a temperature gradient, is an idealised setup to study thermal convection. Of special interest are the statistics of the turbulent…

Rayleigh-B\'enard convection in the turbulent regime is studied using statistical methods. Exact evolution equations for the probability density function of temperature and velocity are derived from first principles within the framework of…

Fluid Dynamics · Physics 2011-03-04 J. Lülff , M. Wilczek , R. Friedrich

Many dynamical systems are difficult or impossible to model using high fidelity physics based models. Consequently, researchers are relying more on data driven models to make predictions and forecasts. Based on limited training data,…

Chaotic Dynamics · Physics 2025-04-09 Max M. Chumley , Firas A. Khasawneh