Stochastic modeling of climatic variability in dendrochronology

[1] Climatic variability can be characterized by invariant quantities arising from the analysis of scaling properties of paleoclimatic records. In this paper we discuss a stochastic model that reproduces the variability and the long-range correlation observed in dendrochronological time series. We have found that non-Gaussian distributions are better suited to describe the climatic variability embedded in these data. Our results indicate that Gaussian distribution fails to capture the large fluctuation —extreme events— that characterized climatic variability in these time series. This might have applications on the study of extreme weather events on future climate scenarios.

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