A deep learning approach for spatial error correction of numerical seasonal weather prediction simulation data

ABSTRACTNumerical Weather Prediction (NWP) simulations produce meteorological data in various spatial and temporal scales, depending on the application requirements. In the current study, a deep learning approach, based on convolutional autoencoders, is explored to effectively correct the error of t...

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Detalles Bibliográficos

Principais autores:	Stelios Karozis, Iraklis A. Klampanos, Athanasios Sfetsos, Diamando Vlachogiannis
Formato:	Artigo
Idioma:	Inglês
Publicado:	Taylor & Francis Group 2023-04-01
Series:	Big Earth Data
Assuntos:	Seasonal weather prediction neural networks convolutional autoencoder evidence transfer
Acceso en liña:	https://www.tandfonline.com/doi/10.1080/20964471.2023.2172820
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