Establishment and Evaluation of an Ensemble Bias Correction Framework for the Short-Term Numerical Forecasting on Lower Atmospheric Ducts

Based on the COAWST (Coupled Ocean–Atmosphere–Wave–Sediment Transport) model, this study developed an atmospheric refractivity forecasting model incorporating ensemble bias correction by combining five bias correction algorithms with the Bayesian Model Averaging (BMA) method. Hindcast tests conducte...

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Detaylı Bibliyografya
Asıl Yazarlar:	Huan Guo, Bo Wang, Jing Zou, Xiaofeng Zhao, Bin Wang, Zhijin Qiu, Hang Wang, Lu Liu, Xiaolei Liu, Hanyue Wang
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	MDPI AG 2025-12-01
Seri Bilgileri:	Journal of Marine Science and Engineering
Konular:	atmospheric duct Bayesian model averaging deep learning ensemble forecasting model bias correction model evaluation
Online Erişim:	https://www.mdpi.com/2077-1312/13/12/2397
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Establishment and Evaluation of an Ensemble Bias Correction Framework for the Short-Term Numerical Forecasting on Lower Atmospheric Ducts

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