Data assimilation: theory and practice
APA
(2025). Data assimilation: theory and practice. SciVideos. https://youtube.com/live/UV1XaMiigkU
MLA
Data assimilation: theory and practice. SciVideos, Aug. 07, 2025, https://youtube.com/live/UV1XaMiigkU
BibTex
@misc{ scivideos_ICTS:32479,
doi = {},
url = {https://youtube.com/live/UV1XaMiigkU},
author = {},
keywords = {},
language = {en},
title = {Data assimilation: theory and practice},
publisher = {},
year = {2025},
month = {aug},
note = {ICTS:32479 see, \url{https://scivideos.org/index.php/icts-tifr/32479}}
}
Abstract
Data assimilation is a set of methods for incorporating sparse observations of a complex dynamical system, either deterministic or stochastic, into incomplete models of these systems. Mathematically this is the problem of nonlinear filtering and computationally, they are based on a variety of techniques including Markov chain Monte Carlo, optimization, importance sampling. This tutorial will begin with a quick introduction to the Bayesian underpinnings of data assimilation followed by applications to chaotic dynamical systems.