Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon

The West African monsoon (WAM) is a complex climatic system with major impacts. This study uses a surrogate-based framework to quantify uncertainties in model parameterizations and to improve simulations with the ICON model. By applying Gaussian process and principal component regression, the approa...

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Autor principal: Fischer, Matthias
Formato: Online
Idioma:inglês
Publicado em: KIT Scientific Publishing 2025
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Acesso em linha:ONIX_20251202T160246_9783731514428_7
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author Fischer, Matthias
author_browse Fischer, Matthias
author_facet Fischer, Matthias
author_sort Fischer, Matthias
collection Directory of Open Access Books
description The West African monsoon (WAM) is a complex climatic system with major impacts. This study uses a surrogate-based framework to quantify uncertainties in model parameterizations and to improve simulations with the ICON model. By applying Gaussian process and principal component regression, the approach enables efficient sensitivity analysis and optimization. Results highlight key parameter influences on the WAM and demonstrate the framework’s effectiveness.
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institution Directory of Open Access Books
language eng
publishDate 2025
publishDateRange 2025
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publisherStr KIT Scientific Publishing
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spelling doab-20.500.12854ir-1698122025-12-03T05:10:34Z Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon Fischer, Matthias Westafrikanischer Monsun Surrogatmodelle Gaußprozessregression Unsicherheitsquantifizierung Parameteroptimierung West African monsoon surrogate models Gaussian process regression uncertainty quantification parameter optimization thema EDItEUR::P Mathematics and Science::PD Science: general issues The West African monsoon (WAM) is a complex climatic system with major impacts. This study uses a surrogate-based framework to quantify uncertainties in model parameterizations and to improve simulations with the ICON model. By applying Gaussian process and principal component regression, the approach enables efficient sensitivity analysis and optimization. Results highlight key parameter influences on the WAM and demonstrate the framework’s effectiveness. 2025-12-03T05:10:33Z 2025-12-03T05:10:33Z 2025-12-02T15:12:34Z 2025 book ONIX_20251202T160246_9783731514428_7 1614-3914 (Online) https://library.oapen.org/handle/20.500.12657/108899 9783731514428 https://directory.doabooks.org/handle/20.500.12854/169812 eng Schriftenreihe des Instituts für Technische Mechanik, Karlsruher Institut für Technologie open access image/jpeg Attribution-ShareAlike 4.0 International https://library.oapen.org/bitstream/20.500.12657/108899/1/9783731514428.pdf KIT Scientific Publishing KIT Scientific Publishing 10.5445/KSP/1000182604 10.5445/KSP/1000182604 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731514428 KIT Scientific Publishing 164 Karlsruhe, Germany open access
spellingShingle Westafrikanischer Monsun
Surrogatmodelle
Gaußprozessregression
Unsicherheitsquantifizierung
Parameteroptimierung
West African monsoon
surrogate models
Gaussian process regression
uncertainty quantification
parameter optimization
thema EDItEUR::P Mathematics and Science::PD Science: general issues
Fischer, Matthias
Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title_full Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title_fullStr Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title_full_unstemmed Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title_short Surrogate-based uncertainty quantification and parameter optimization in simulations of the West African monsoon
title_sort surrogate based uncertainty quantification and parameter optimization in simulations of the west african monsoon
topic Westafrikanischer Monsun
Surrogatmodelle
Gaußprozessregression
Unsicherheitsquantifizierung
Parameteroptimierung
West African monsoon
surrogate models
Gaussian process regression
uncertainty quantification
parameter optimization
thema EDItEUR::P Mathematics and Science::PD Science: general issues
topic_facet Westafrikanischer Monsun
Surrogatmodelle
Gaußprozessregression
Unsicherheitsquantifizierung
Parameteroptimierung
West African monsoon
surrogate models
Gaussian process regression
uncertainty quantification
parameter optimization
thema EDItEUR::P Mathematics and Science::PD Science: general issues
url ONIX_20251202T160246_9783731514428_7
work_keys_str_mv AT fischermatthias surrogatebaseduncertaintyquantificationandparameteroptimizationinsimulationsofthewestafricanmonsoon