Functional Data Analysis Technique on Daily Rainfall Data: A Case Study at North Regionof Peninsular Malaysia

The study of rainfall features and patterns are very useful for water managementsystems, water resources engineering and also in agricultural planning. It can be beneficial inorder to reduce the risks and losses. Functional data analysis technique is one of the methodcan be used to explore and display the pattern and variation of the rainfall data. Thistechnique displays the pattern in the form of curves. The first and second derivatives of thecurves represent the rate of change and the acceleration of the curves. The objective of thestudy is to model two rainfall features; rainfall amount and rainfall occurrence by usingfunctional data analysis technique at eight rainfall stations from the north part of PeninsularMalaysia. Markov chain model has been used to model the rainfall occurrence and Fourierbasis to smoothing the data. The results show that both of the rainfall features have similarbimodal pattern. Although the mean curves are slightly similar, the first peak of variancecurve for rainfall occurrence is higher than the second peak which is difference with variancecurve for rainfall amount. The relationship between rainfall amount and rainfall occurrencefor both observed and estimated curve is also discussed.