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An Extended Singular Spectrum Transformation (Sst) for the Investigation of Kenyan Precipitation Data : Volume 20, Issue 4 (12/07/2013)

By Itoh, N.

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Book Id: WPLBN0003989624
Format Type: PDF Article :
File Size: Pages 15
Reproduction Date: 2015

Title: An Extended Singular Spectrum Transformation (Sst) for the Investigation of Kenyan Precipitation Data : Volume 20, Issue 4 (12/07/2013)  
Author: Itoh, N.
Volume: Vol. 20, Issue 4
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Itoh, N., & Marwan, N. (2013). An Extended Singular Spectrum Transformation (Sst) for the Investigation of Kenyan Precipitation Data : Volume 20, Issue 4 (12/07/2013). Retrieved from

Description: University of Potsdam Interdisciplinary Center for Dynamics of Complex Systems (DYCOS), Campus Golm, Building 14 Karl-Liebknecht-Str. 24, 14476, Potsdam, Germany. In this paper a change-point detection method is proposed by extending the singular spectrum transformation (SST) developed as one of the capabilities of singular spectrum analysis (SSA). The method uncovers change points related with trends and periodicities. The potential of the proposed method is demonstrated by analysing simple model time series including linear functions and sine functions as well as real world data (precipitation data in Kenya). A statistical test of the results is proposed based on a Monte Carlo simulation with surrogate methods. As a result, the successful estimation of change points as inherent properties in the representative time series of both trend and harmonics is shown. With regards to the application, we find change points in the precipitation data of Kenyan towns (Nakuru, Naivasha, Narok, and Kisumu) which coincide with the variability of the Indian Ocean Dipole (IOD) suggesting its impact of extreme climate in East Africa.

An extended singular spectrum transformation (SST) for the investigation of Kenyan precipitation data

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