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

机译:长期每日降雨模式识别:主成分分析的应用

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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.
机译:本研究旨在通过应用主成分分析(PCA),在20年期间(1994-2013)(1994-2013)(1994-2013)识别每日降雨模式(1994-2013)通过应用主成分分析(PCA)。 使用PCA保留六种组分,总方差为53.43%。 第一个和第二个组件包括分别显示东北和西南季风特征的地区。 涵盖半岛马来西亚北部地区的第四个组成部分显示每年收到的降雨量的两个峰。 第三个,第五和第六组分显示了大多数覆盖沙巴和沙捞越的地区之间的区别。

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