PARTICLE FILTERS IN A MULTISCALE ENVIRONMENT: WITH APPLICATION TO THE LORENZ-96 ATMOSPHERIC MODEL

DOI10.1142/S0219493711003450zbMath1261.60042MaRDI QIDQ3174009

N. Sri Namachchivaya, Jun Hyun Park, Hoong Chieh Yeong

Publication date: 11 October 2011

Published in: Stochastics and Dynamics (Search for Journal in Brave)

zbMATH Keywords

nonlinear filteringapplicationLorenz-96 modelstochastic dimensional reduction

Mathematics Subject Classification ID

Dynamical systems in fluid mechanics, oceanography and meteorology (37N10) Signal detection and filtering (aspects of stochastic processes) (60G35) Averaging method for ordinary differential equations (34C29) Stochastic partial differential equations (aspects of stochastic analysis) (60H15)

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Uses Software

• EnKF

Cites Work

• Particle approximations for a class of stochastic partial differential equations
• Nonlinear filtering and measure-valued processes
• A computational strategy for multiscale systems with applications to Lorenz 96 model
• A survey of numerical methods for nonlinear filtering problems
• Stochastic processes and filtering theory
• Numerical techniques for multi-scale dynamical systems with stochastic effects
• Application of Girsanov theorem to particle filtering of discretely observed continuous-time non-linear systems
• Sequential Monte Carlo Methods in Practice
• Time-discretization of the zakai equation for diffusion processes observed in correlated noise
• Dimensional reduction in nonlinear filtering
• A PROBLEM IN STOCHASTIC AVERAGING OF NONLINEAR FILTERS
• Particle Filters for Partially Observed Diffusions
• Convergence of a Branching Particle Method to the Solution of the Zakai Equation
• Random perturbations of Hamiltonian systems
• Reduction of deterministic coupled atmosphere–ocean models to stochastic ocean models: a numerical case study of the Lorenz–Maas system
• Stochastic differential equations. An introduction with applications.