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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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Selected topics in multiscale data assimilation

Selected topics in multiscale data assimilation

Chapter:
(p.413) 18 Selected topics in multiscale data assimilation
Source:
Advanced Data Assimilation for Geosciences
Author(s):

M. Bocquet

L. Wu

F. Chevallier

M. R. Kookhan

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198723844.003.0018

This chapter discusses several approaches to developing original theoretical approaches to assimilate information at a given scale and consistently propagate it to other scales. This is motivated by the fact that models and observations both provide information at various spatial and temporal scales, but their respective scales do not necessarily match. This chapter discusses several approaches to this problem, such as the construction of a multiscale best linear unbiased estimator (BLUE). This approach is applied to the design of efficient adaptive grids in control space with minimal aggregation errors. Examples are chosen in the field of atmospheric constituents such as the inverse modelling of mesoscale CO2 fluxes and the observability of a nuclear test from the United Nations International Monitoring System.

Keywords:   multiscale, best linear unbiased estimator, BLUE, adaptive grid, control space, aggregation error

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