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

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...

Full description

Bibliographic Details
Main Authors: Othman, Melawani, Ash’aari, Zulfa Hanan, Mohamad, Nur Diyana
Format: Article
Language:English
Published: Elsevier 2015
Online Access:http://psasir.upm.edu.my/id/eprint/42989/1/1-s2.0-S1878029615006167-main.pdf
Description
Summary: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