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Rainfall Time Series Exploration via Non Parametric Approach

Ibrahim Lawal Kane, Fadhilah Yusof

Abstract


In evaluating the long-term variations in meteorological and hydrological records, the idea of ?regime shifts? or change point is becoming very popular in recent years. This concept received a formidable motivation after a step-like change in the global climate system during the late 1970?s although a realization of the significance of that event came more gradually. In this study, the Singular Spectrum Analysis (SSA), a powerful non-parametric technique in time series analysis, has been applied to rainfall data sets of some locations in peninsular Malaysia. The method follows a sequential application to reconstruct the time series by embedding to produce a trajectory matrix which later decomposed using singular value decomposition (SVD). The approach is able to detect and extract patterns such as trends, oscillations or noise from the observed rainfall data sets. This result may give more precise insight into the climate period background of peninsular Malaysia.

Keywords


Time Series Reconstruction; Embedding; Singular Value Decomposition; Trend; Singular Spectrum Analysis;

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