Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis
Main Author: | |
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Publication Date: | 2016 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Revista Ciência e Natura (Online) |
Download full: | https://periodicos.ufsm.br/cienciaenatura/article/view/20095 |
Summary: | Atmospheric circulation models combine different modules for a good description of the atmospheric dynamics. One of these modules is the representation of surface coverage, since the dynamics depends on the interaction between the atmosphere and the surface of the planet. However, these modules depend on a number of parameters that need to be adjusted. The parameter adjustment process is called model calibration. In this study, the IBIS (Integrated Biosphere Simulator) model is calibrated following a multi-objective strategy. The Pareto set, which embraces the non-dominated solutions in the search space of objective functions, is determined by a version of multi-objective genetic algorithm (NSGA-II). The model sensitivity to the parameters is evaluated by the Morris’ method. Synthetic data for calibration were obtained from the Tapajós National Forest (FloNa Tapajós), located near to the 67 km from Santarém-Cuiabá highway (2,51S, 54,58W). |
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Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity AnalysisMULTI-OBJECTIVE CALIBRATION OF IBIS MODEL BY GENETIC ALGORITHM WITH PARAMETRIC SENSITIVITY ANALYSISMulti-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós.Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós.Atmospheric circulation models combine different modules for a good description of the atmospheric dynamics. One of these modules is the representation of surface coverage, since the dynamics depends on the interaction between the atmosphere and the surface of the planet. However, these modules depend on a number of parameters that need to be adjusted. The parameter adjustment process is called model calibration. In this study, the IBIS (Integrated Biosphere Simulator) model is calibrated following a multi-objective strategy. The Pareto set, which embraces the non-dominated solutions in the search space of objective functions, is determined by a version of multi-objective genetic algorithm (NSGA-II). The model sensitivity to the parameters is evaluated by the Morris’ method. Synthetic data for calibration were obtained from the Tapajós National Forest (FloNa Tapajós), located near to the 67 km from Santarém-Cuiabá highway (2,51S, 54,58W).Atmospheric circulation models combine different modules for a good description of the atmospheric dynamics. One of these modules is therepresentation of surface coverage, since the dynamics depends on the interaction between the atmosphere and the surface of the planet.However, these modules depend on a number of parameters that need to be adjusted. The parameter adjustment process is called modelcalibration. In this study, the IBIS (Integrated Biosphere Simulator) model is calibrated following a multi-objective strategy. The Pareto set,which embraces the non-dominated solutions in the search space of objective functions, is determined by a version of multi-objective geneticalgorithm (NSGA-II). The model sensitivity to the parameters is evaluated by the Morris’ method. Synthetic data for calibration wereobtained from the Tapajós National Forest (FloNa Tapajós), located near to the 67 km from Santarém-Cuiabá highway (2,51S, 54,58W).Universidade Federal de Santa Maria2016-07-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaenatura/article/view/2009510.5902/2179460X20095Ciência e Natura; Vol. 38 (2016): SPECIAL EDITION: IX WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA; 90-97Ciência e Natura; v. 38 (2016): EDIÇÃO ESPECIAL: IX WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA; 90-972179-460X0100-8307reponame:Revista Ciência e Natura (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMenghttps://periodicos.ufsm.br/cienciaenatura/article/view/20095/pdfAraújo, Amarísio da SilvaVelho, Haroldo de CamposMinjiao, Luinfo:eu-repo/semantics/openAccess2022-10-14T13:33:33Zoai:ojs.pkp.sfu.ca:article/20095Revistahttps://periodicos.ufsm.br/cienciaenatura/indexPUBhttps://periodicos.ufsm.br/cienciaenatura/oaicienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br2179-460X0100-8307opendoar:2022-10-14T13:33:33Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis MULTI-OBJECTIVE CALIBRATION OF IBIS MODEL BY GENETIC ALGORITHM WITH PARAMETRIC SENSITIVITY ANALYSIS |
title |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
spellingShingle |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis Araújo, Amarísio da Silva Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. |
title_short |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
title_full |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
title_fullStr |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
title_full_unstemmed |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
title_sort |
Multi-Objective Calibration of ibis Model by Genetic Algorithm with Parametric Sensitivity Analysis |
author |
Araújo, Amarísio da Silva |
author_facet |
Araújo, Amarísio da Silva Velho, Haroldo de Campos Minjiao, Lu |
author_role |
author |
author2 |
Velho, Haroldo de Campos Minjiao, Lu |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Araújo, Amarísio da Silva Velho, Haroldo de Campos Minjiao, Lu |
dc.subject.por.fl_str_mv |
Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. |
topic |
Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. Multi-objective calibration. IBIS model. Morris’ method. NSGA-II. FloNa Tapajós. |
description |
Atmospheric circulation models combine different modules for a good description of the atmospheric dynamics. One of these modules is the representation of surface coverage, since the dynamics depends on the interaction between the atmosphere and the surface of the planet. However, these modules depend on a number of parameters that need to be adjusted. The parameter adjustment process is called model calibration. In this study, the IBIS (Integrated Biosphere Simulator) model is calibrated following a multi-objective strategy. The Pareto set, which embraces the non-dominated solutions in the search space of objective functions, is determined by a version of multi-objective genetic algorithm (NSGA-II). The model sensitivity to the parameters is evaluated by the Morris’ method. Synthetic data for calibration were obtained from the Tapajós National Forest (FloNa Tapajós), located near to the 67 km from Santarém-Cuiabá highway (2,51S, 54,58W). |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-07-20 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/cienciaenatura/article/view/20095 10.5902/2179460X20095 |
url |
https://periodicos.ufsm.br/cienciaenatura/article/view/20095 |
identifier_str_mv |
10.5902/2179460X20095 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaenatura/article/view/20095/pdf |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Ciência e Natura; Vol. 38 (2016): SPECIAL EDITION: IX WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA; 90-97 Ciência e Natura; v. 38 (2016): EDIÇÃO ESPECIAL: IX WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA; 90-97 2179-460X 0100-8307 reponame:Revista Ciência e Natura (Online) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Revista Ciência e Natura (Online) |
collection |
Revista Ciência e Natura (Online) |
repository.name.fl_str_mv |
Revista Ciência e Natura (Online) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
cienciaenatura@ufsm.br || centraldeperiodicos@ufsm.br |
_version_ |
1839277880286117888 |