Journal of Mathematics and Statistics

Bayesian Changepoint Analysis of the Extreme Rainfall Events

Wan Zawiah Wan Zin, Abdul Aziz Jemain and Kamarulzaman Ibrahim

DOI : 10.3844/jmssp.2012.85.91

Journal of Mathematics and Statistics

Volume 8, Issue 1

Pages 85-91

Abstract

Problem statement: This study assesses recent changes in extremes of annual rainfall in Peninsular Malaysia based on daily rainfall data for 50 rain-gauged stations over the period 1975-2004. Approach: Eight indices that represent the extreme events are defined and analyzed, which are extreme Dry Spell (XDS), extreme Rain-Sum (XRS), extreme wet-day intensities at 95% and 99% percentiles (I95 and I99), proportion of extreme rainfall amount to the total rainfall amount (R95& R99) and frequency of extreme wet-day at 95 and 99% percentiles (N95 and N99). Bayesian approach based on a single shifting model is used to investigate the change in the mean level of these extreme rainfall indices. The detection on whether the change has occurred or not is analyzed followed by the estimation of the location of change point. Results: The results of the analysis showed that half of the stations considered displayed significant changes. The analysis also found that in general, the changes occurred in the early 90s. More than 75% of the stations which recorded significant changes are situated on the west coast of the peninsula. Conclusion/Recommendations: The west coast of Peninsular Malaysia displays more significant changes in trend especially at stations located in urban areas compared to the east coast of the peninsula. In terms of the Bayesian methods used, the existence of any outlier in the data series may influence the result since the analysis is based on mean value which is very sensitive to any outlier.

Copyright

© 2012 Wan Zawiah Wan Zin, Abdul Aziz Jemain and Kamarulzaman Ibrahim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.