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Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model

In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical p...

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Detalles Bibliográficos
Autores principales: Jansson, Fredrik, Edeling, Wouter, Attema, Jisk, Crommelin, Daan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059568/
https://www.ncbi.nlm.nih.gov/pubmed/33775144
http://dx.doi.org/10.1098/rsta.2020.0073
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author Jansson, Fredrik
Edeling, Wouter
Attema, Jisk
Crommelin, Daan
author_facet Jansson, Fredrik
Edeling, Wouter
Attema, Jisk
Crommelin, Daan
author_sort Jansson, Fredrik
collection PubMed
description In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical parameters whose values are not exactly known, and uncertainty related to modelling choices such as the selection of numerical discretization methods, of the spatial domain size and resolution, and the use of different model formulations. While the former kind is commonly studied e.g. with forward uncertainty propagation, we explore the use of such techniques to also assess the latter kind. From a climate modelling perspective, uncertainties in the convective response and cloud formation are of particular interest, since these affect the cloud-climate feedback, one of the dominant sources of uncertainty in current climate models. Therefore we analyse the DALES model in the RICO case, a well-studied convection benchmark. We use the VECMA toolkit for uncertainty propagation, assessing uncertainties stemming from physical parameters as well as from modelling choices. We find substantial uncertainties due to small random initial state perturbations, and that the choice of advection scheme is the most influential of the modelling choices we assessed. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’.
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spelling pubmed-80595682022-02-02 Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model Jansson, Fredrik Edeling, Wouter Attema, Jisk Crommelin, Daan Philos Trans A Math Phys Eng Sci Articles In this study, we investigate uncertainties in a large eddy simulation of the atmosphere, employing modern uncertainty quantification methods that have hardly been used yet in this context. When analysing the uncertainty of model results, one can distinguish between uncertainty related to physical parameters whose values are not exactly known, and uncertainty related to modelling choices such as the selection of numerical discretization methods, of the spatial domain size and resolution, and the use of different model formulations. While the former kind is commonly studied e.g. with forward uncertainty propagation, we explore the use of such techniques to also assess the latter kind. From a climate modelling perspective, uncertainties in the convective response and cloud formation are of particular interest, since these affect the cloud-climate feedback, one of the dominant sources of uncertainty in current climate models. Therefore we analyse the DALES model in the RICO case, a well-studied convection benchmark. We use the VECMA toolkit for uncertainty propagation, assessing uncertainties stemming from physical parameters as well as from modelling choices. We find substantial uncertainties due to small random initial state perturbations, and that the choice of advection scheme is the most influential of the modelling choices we assessed. This article is part of the theme issue ‘Reliability and reproducibility in computational science: implementing verification, validation and uncertainty quantification in silico’. The Royal Society Publishing 2021-05-17 2021-03-29 /pmc/articles/PMC8059568/ /pubmed/33775144 http://dx.doi.org/10.1098/rsta.2020.0073 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Jansson, Fredrik
Edeling, Wouter
Attema, Jisk
Crommelin, Daan
Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title_full Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title_fullStr Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title_full_unstemmed Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title_short Assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
title_sort assessing uncertainties from physical parameters and modelling choices in an atmospheric large eddy simulation model
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059568/
https://www.ncbi.nlm.nih.gov/pubmed/33775144
http://dx.doi.org/10.1098/rsta.2020.0073
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