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Long-term daily rainfall pattern recognition: application of principal component analysis


Othman, Melawani and Ash’aari, Zulfa Hanan and Mohamad, Nur Diyana (2015) Long-term daily rainfall pattern recognition: application of principal component analysis. Procedia Environmental Sciences, 30. pp. 127-132. ISSN 1878-0296


This study aims to identify the daily rainfall pattern over a 20 year period (1994–2013) using data from 89 stations positioned throughout Malaysia by applying Principal Component Analysis (PCA). Six components were retained using PCA with total variance of 53.43%. The first and the second component encompassed regions that show characteristics of Northeast and Southwest monsoons respectively. The fourth component, which covers the northern regions of peninsular Malaysia, shows two peaks in rainfall amount received per year. The third, fifth and sixth components show distinction between regions that mostly cover Sabah and Sarawak

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Additional Metadata

Item Type: Article
Divisions: Faculty of Environmental Studies
DOI Number: https://doi.org/10.1016/j.proenv.2015.10.022
Publisher: Elsevier
Keywords: Rainfall; Pattern; Variation; PCA; Kriging; Interpolation
Depositing User: Mas Norain Hashim
Date Deposited: 03 May 2016 03:02
Last Modified: 03 May 2016 06:39
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.proenv.2015.10.022
URI: http://psasir.upm.edu.my/id/eprint/42989
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