Hindcasting with cluster-based analogues

Balsa, Carlos; Rodrigues, Carlos Veiga; Araújo, Leonardo Oliveira; Rufino, José

http://hdl.handle.net/10198/24630

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Autores

Balsa, Carlos

Rodrigues, Carlos Veiga

Araújo, Leonardo Oliveira

Rufino, José

Resumo(s)

The reconstruction of meteorological observations or deterministic predictions for a certain variable and station may be performed with data from other variables at that station, or from other nearby stations. This is a hindcasting problem, known from some time to be solvable using the Analogues Ensemble (AnEn) method. However, depending on the dimension and granularity of the datasets used for the reconstruction, this method may be computationally very demanding, even if parallelization is used. In this paper, the AnEn method is combined with K-means clustering, allowing for a considerable acceleration of the reconstruction task, while keeping the accuracy of the results.

Palavras-chave

Hindcasting Analogues ensemble K-means Time series

URI

http://hdl.handle.net/10198/24630

Citação

Balsa, Carlos; Rodrigues, C. Veiga; Araújo, Leonardo; Rufino, José (2021). Hindcasting with cluster-based analogues. In First International Conference, ARTIIS 2021. p. 346-360. ISBN 978-3-030-90240-7

DOI

10.1007/978-3-030-90241-4_27

Coleções

ESTiG - Publicações em Proceedings Indexadas à WoS/Scopus

Licença CC

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