Citation
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
Abstract
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
Download File
Official URL or Download Paper: http://www.sciencedirect.com/science/article/pii/S...
|
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 |
Statistic Details: | View Download Statistic |
Actions (login required)
View Item |