artículo de publicación periódica.page.titleprefix
Model selection: using information measures from ordinal symbolic analysis to select model subgrid-scale parameterizations

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dc.contributor.authorPulido, Manuel
dc.contributor.authorRosso, Osvaldo A.
dc.date.accessioned2019-08-14T19:20:45Z
dc.date.available2019-08-14T19:20:45Z
dc.date.issued2017
dc.description.abstract"The use of information measures for model selection in geophysical models with subgrid parameterizations is examined. Although the resolved dynamical equations of atmospheric or oceanic global numerical models are well established, the development and evaluation of parameterizations that represent subgrid-scale effects pose a big challenge. For climate studies, the parameters or parameterizations are usually selected according to a root-mean-square error criterion that measures the differences between the model-state evolution and observations along the trajectory. However, inaccurate initial conditions and systematic model errors contaminate root-mean-square error measures. In this work, information theory quantifiers, in particular Shannon entropy, statistical complexity, and Jensen–Shannon divergence, are evaluated as measures of the model dynamics. An ordinal analysis is conducted using the Bandt–Pompe symbolic data reduction in the signals. The proposed ordinal information measures are examined in the two-scale Lorenz-96 system. By comparing the two-scale Lorenz-96 system signals with a one-scale Lorenz-96 system with deterministic and stochastic parameterizations, the study shows that information measures are able to select the correct model and to distinguish the parameterizations, including the degree of stochasticity that results in the closest model dynamics to the two-scale Lorenz-96 system."en
dc.identifier.issn0022-4928
dc.identifier.urihttp://ri.itba.edu.ar/handle/123456789/1710
dc.language.isoenen
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/10.1175/JAS-D-16-0340.1
dc.relationinfo:eu-repo/grantAgreement/ANPCyT/PICT/2015-2368/AR. Ciudad Autónoma de Buenos Aires
dc.relationinfo:eu-repo/grantAgreement/CONICET/PIP/11220120100414CO/AR. Ciudad Autónoma de Buenos Aires
dc.subjectPARAMETRIZACIONes
dc.subjectTEORIA DE LA INFORMACIONes
dc.subjectMODELOS MATEMATICOSes
dc.subjectMODELOS CLIMATICOSes
dc.titleModel selection: using information measures from ordinal symbolic analysis to select model subgrid-scale parameterizationsen
dc.typeArtículos de Publicaciones Periódicases
dc.typeinfo:eu-repo/semantics/acceptedVersion
dspace.entity.typeArtículo de Publicación Periódica
itba.description.filiationFil: Pulido, Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Pulido, Manuel. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura; Argentina.
itba.description.filiationFil: Rosso, Osvaldo A. Instituto Tecnológico de Buenos Aires; Argentina.
itba.description.filiationFil: Rosso, Osvaldo A. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Rosso, Osvaldo A. Universidad de los Andes; Chile.
itba.description.filiationFil: Rosso, Osvaldo A. Universidade Federal de Alagoas; Brasil.

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