Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 8, 3639-3658, 2015
https://doi.org/10.5194/gmd-8-3639-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
06 Nov 2015
S4CAST v2.0: sea surface temperature based statistical seasonal forecast model
R. Suárez-Moreno1,2 and B. Rodríguez-Fonseca1,2 1Departamento de Geofísica y Meteorología, Facultad de Físicas, Universidad Complutense de Madrid, Plaza de las Ciencias 1, 28040 Madrid, Spain
2Instituto de Geociencias (IGEO), Facultad de Ciencias Geológicas, Universidad Complutense de Madrid – CSIC, C/José Antonio Novais 12, 28040 Madrid, Spain
Abstract. 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.

Citation: Suárez-Moreno, R. and Rodríguez-Fonseca, B.: S4CAST v2.0: sea surface temperature based statistical seasonal forecast model, Geosci. Model Dev., 8, 3639-3658, https://doi.org/10.5194/gmd-8-3639-2015, 2015.
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Short summary
The non-stationary links between sea surface temperature and global atmospheric circulation have served to create the S⁴CAST model. Here we describe the model, based on a statistical tool to be focused on the study of teleconnections and predictability of any climate-related variable that keeps a link with sea surface temperature. Due to its intuitive operation and free availability of the code, the model can be used both to supplement general circulation models and in a purely academic context.
The non-stationary links between sea surface temperature and global atmospheric circulation have...
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