Kapak Resmi

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...

Ful tanımlama

Kaydedildi:
Yazar: Fischer, Matthias
Materyal Türü: Online
Dil:İngilizce
Baskı/Yayın Bilgisi: KIT Scientific Publishing 2025
Konular:
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
Online Erişim:ONIX_20251202T160246_9783731514428_7
Etiketler: Etiketle
Etiket eklenmemiş, İlk siz ekleyin!
Özet: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.

Benzer Materyaller