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Advanced Data Assimilation for GeosciencesLecture Notes of the Les Houches School of Physics: Special Issue, June 2012$
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Éric Blayo, Marc Bocquet, Emmanuel Cosme, and Leticia F. Cugliandolo

Print publication date: 2014

Print ISBN-13: 9780198723844

Published to Oxford Scholarship Online: March 2015

DOI: 10.1093/acprof:oso/9780198723844.001.0001

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An introduction to inverse modelling and parameter estimation for atmosphere and ocean sciences

An introduction to inverse modelling and parameter estimation for atmosphere and ocean sciences

Chapter:
(p.461) 20 An introduction to inverse modelling and parameter estimation for atmosphere and ocean sciences
Source:
Advanced Data Assimilation for Geosciences
Author(s):

M. Bocquet

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198723844.003.0020

This chapter is a short survey of the inverse modelling and parameter estimation methods currently used in the atmosphere and ocean sciences. The focus is on the estimation of model parameters. This can go as far as large parameter fields such as forcing fields that may drive or constrain a model. Future efficient data assimilation systems will probably incorporate these fields as part of control space. This overview of inverse modelling techniques describes regularization, information processing, Bayesian, and maximum entropy on the mean approaches, and estimation of the regularization parameters. Each concept introduced in this overview is illustrated using the concrete example of the inversion of the Chernobyl radionuclides source term with the help of a three-dimensional dispersion model.

Keywords:   inverse modelling, parameter estimation, Bayesian, regularization, maximum entropy on the mean, Chernobyl

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