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Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations

Dual numbers allow for automatic, exact evaluation of the numerical derivative of high-dimensional functions at an arbitrary point with minimal coding effort. We use dual numbers to construct tangent linear and adjoint model code for a biogeochemical ocean model and apply it to a variational (4D-Var...

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Detalles Bibliográficos
Autores principales: Mattern, Jann Paul, Edwards, Christopher A., Hill, Christopher N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795413/
https://www.ncbi.nlm.nih.gov/pubmed/31618274
http://dx.doi.org/10.1371/journal.pone.0223131
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author Mattern, Jann Paul
Edwards, Christopher A.
Hill, Christopher N.
author_facet Mattern, Jann Paul
Edwards, Christopher A.
Hill, Christopher N.
author_sort Mattern, Jann Paul
collection PubMed
description Dual numbers allow for automatic, exact evaluation of the numerical derivative of high-dimensional functions at an arbitrary point with minimal coding effort. We use dual numbers to construct tangent linear and adjoint model code for a biogeochemical ocean model and apply it to a variational (4D-Var) data assimilation system when coupled to a realistic physical ocean circulation model with existing data assimilation capabilities. The resulting data assimilation system takes modestly longer to run than its hand-coded equivalent but is considerably easier to implement and updates automatically when modifications are made to the biogeochemical model, thus making its maintenance with code changes trivial.
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spelling pubmed-67954132019-10-20 Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations Mattern, Jann Paul Edwards, Christopher A. Hill, Christopher N. PLoS One Research Article Dual numbers allow for automatic, exact evaluation of the numerical derivative of high-dimensional functions at an arbitrary point with minimal coding effort. We use dual numbers to construct tangent linear and adjoint model code for a biogeochemical ocean model and apply it to a variational (4D-Var) data assimilation system when coupled to a realistic physical ocean circulation model with existing data assimilation capabilities. The resulting data assimilation system takes modestly longer to run than its hand-coded equivalent but is considerably easier to implement and updates automatically when modifications are made to the biogeochemical model, thus making its maintenance with code changes trivial. Public Library of Science 2019-10-16 /pmc/articles/PMC6795413/ /pubmed/31618274 http://dx.doi.org/10.1371/journal.pone.0223131 Text en © 2019 Mattern et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mattern, Jann Paul
Edwards, Christopher A.
Hill, Christopher N.
Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title_full Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title_fullStr Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title_full_unstemmed Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title_short Dual number-based variational data assimilation: Constructing exact tangent linear and adjoint code from nonlinear model evaluations
title_sort dual number-based variational data assimilation: constructing exact tangent linear and adjoint code from nonlinear model evaluations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6795413/
https://www.ncbi.nlm.nih.gov/pubmed/31618274
http://dx.doi.org/10.1371/journal.pone.0223131
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