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| Titel |
S4CAST v2.0: sea surface temperature based statistical seasonal forecast model |
| VerfasserIn |
R. Suárez-Moreno, B. Rodriguez-Fonseca |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 11 ; Nr. 8, no. 11 (2015-11-06), S.3639-3658 |
| Datensatznummer |
250116662
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| Publikation (Nr.) |
 copernicus.org/gmd-8-3639-2015.pdf |
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| Zusammenfassung |
| Sea surface temperature is the key variable when tackling seasonal to decadal
climate forecasts. Dynamical models are unable to properly reproduce tropical
climate variability, introducing biases that prevent a skillful
predictability. Statistical methodologies emerge as an alternative to improve
the predictability and reduce these biases. In addition, recent studies have
put forward the non-stationary behavior of the teleconnections between
tropical oceans, showing how the same tropical mode has different impacts
depending on the considered sequence of decades. To improve the
predictability and investigate possible teleconnections, the sea surface temperature based statistical seasonal foreCAST model (S4CAST)
introduces the novelty of considering the non-stationary links between the
predictor and predictand fields. This paper describes the development of
the S4CAST model whose operation is focused on studying the impacts of sea
surface temperature on any climate-related variable. Two applications focused
on analyzing the predictability of different climatic events have been
implemented as benchmark examples. |
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