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ZENODO
Software . 2015
Data sources: Datacite
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ZENODO
Software . 2015
Data sources: ZENODO
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S4CAST_v2.0

Authors: Suárez-Moreno, Roberto; Rodríguez-Fonseca, Belén;
Abstract

Sea Surface Temperature based Statistical Seasonal foreCAST model (S4CAST) has been developed as a MATLAB® toolbox to study the predictability of climate-related variables that keep a link with sea surface temperature due to its potential as a source of seasonal predictability. The model analyzes changes in relationships between the predictor and predictand fields throughout the study period to improve forecasts.

Related Organizations
Keywords

sea surface temperature, seasonal predictability, statistical forecast modeling, stationarity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1