Rainfall analysis in the Northern Region of Peninsular Malaysia

Modeling of rainfall is important for assessing the possible impacts of climate change. To achieve accurate projections of rainfall events, availability of sufficient hydrological station data is critical. Precipitation is one of the most important meteorological variables for hydrological modeling....

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Main Authors: Abdul Halim, Syafrina, Abas, Norzaida, Osman, Noor Shazwani
Format: Article
Published: Institute of Advanced Science Extension (IASE) 2017
Online Access:http://psasir.upm.edu.my/id/eprint/62904/
http://www.science-gate.com/IJAAS/V4I11/Syafrina.html
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spelling my.upm.eprints.629042022-11-25T00:35:05Z http://psasir.upm.edu.my/id/eprint/62904/ Rainfall analysis in the Northern Region of Peninsular Malaysia Abdul Halim, Syafrina Abas, Norzaida Osman, Noor Shazwani Modeling of rainfall is important for assessing the possible impacts of climate change. To achieve accurate projections of rainfall events, availability of sufficient hydrological station data is critical. Precipitation is one of the most important meteorological variables for hydrological modeling. In cases where long series of observed precipitation are not available, they can be stochastically generated by weather generators. Advanced Weather Generator (AWE-GEN) has been proven to generate precipitation data at the temperate climate regions with Gamma distribution being incorporated in the model to represent rainfall intensity. However, in a tropical climate such as Malaysia, some studies disputed the incorporation of Gamma distribution. As such, in this study, Weibull a heavy tail distribution is proposed to be used. The AWE-GEN has well performed in the wetter region such as the eastern of the peninsular. However, rainfall distribution within Peninsular Malaysia is highly variable temporally and spatially. The northern region is drier especially during the southwest monsoon season. This region receives minimal rain during the northeast monsoon due to the presence of the Titiwangsa Range which obstructs the region from getting rain by the north easterly winds. Therefore, the objectives of the study are two-fold. First, this study compares the performance of Gamma and Weibull that are incorporated in the AWE-GEN in simulating rainfall series for the northern region of the peninsular. Second, the monthly rainfall and the extreme rainfall series are simulated using the better distribution. The performances of Gamma and Weibull distributions are compared using the goodness of fit test, Root Mean Square Error (RMSE). Results showed that Gamma is the better distribution in simulating rainfall at rainfall stations located at the outer parts of the northern coast whereas Weibull is the better distribution for stations located in the interior parts of the northern coast. Hourly and daily extreme rainfalls seem to be well captured at all stations. Similarly, wet spell length is well simulated while in contrast, dry spell length is slightly underestimated at all stations. Overall, Gamma and Weibull produce commendable results in simulating extreme rainfall as well as wet spell length throughout the northern region of the peninsular. Institute of Advanced Science Extension (IASE) 2017-11 Article PeerReviewed Abdul Halim, Syafrina and Abas, Norzaida and Osman, Noor Shazwani (2017) Rainfall analysis in the Northern Region of Peninsular Malaysia. International Journal of Advanced and Applied Sciences, 4 (11). pp. 11-16. ISSN 2313-626X; ESSN: 2313-3724 http://www.science-gate.com/IJAAS/V4I11/Syafrina.html 10.21833/ijaas.2017.011.002
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Modeling of rainfall is important for assessing the possible impacts of climate change. To achieve accurate projections of rainfall events, availability of sufficient hydrological station data is critical. Precipitation is one of the most important meteorological variables for hydrological modeling. In cases where long series of observed precipitation are not available, they can be stochastically generated by weather generators. Advanced Weather Generator (AWE-GEN) has been proven to generate precipitation data at the temperate climate regions with Gamma distribution being incorporated in the model to represent rainfall intensity. However, in a tropical climate such as Malaysia, some studies disputed the incorporation of Gamma distribution. As such, in this study, Weibull a heavy tail distribution is proposed to be used. The AWE-GEN has well performed in the wetter region such as the eastern of the peninsular. However, rainfall distribution within Peninsular Malaysia is highly variable temporally and spatially. The northern region is drier especially during the southwest monsoon season. This region receives minimal rain during the northeast monsoon due to the presence of the Titiwangsa Range which obstructs the region from getting rain by the north easterly winds. Therefore, the objectives of the study are two-fold. First, this study compares the performance of Gamma and Weibull that are incorporated in the AWE-GEN in simulating rainfall series for the northern region of the peninsular. Second, the monthly rainfall and the extreme rainfall series are simulated using the better distribution. The performances of Gamma and Weibull distributions are compared using the goodness of fit test, Root Mean Square Error (RMSE). Results showed that Gamma is the better distribution in simulating rainfall at rainfall stations located at the outer parts of the northern coast whereas Weibull is the better distribution for stations located in the interior parts of the northern coast. Hourly and daily extreme rainfalls seem to be well captured at all stations. Similarly, wet spell length is well simulated while in contrast, dry spell length is slightly underestimated at all stations. Overall, Gamma and Weibull produce commendable results in simulating extreme rainfall as well as wet spell length throughout the northern region of the peninsular.
format Article
author Abdul Halim, Syafrina
Abas, Norzaida
Osman, Noor Shazwani
spellingShingle Abdul Halim, Syafrina
Abas, Norzaida
Osman, Noor Shazwani
Rainfall analysis in the Northern Region of Peninsular Malaysia
author_facet Abdul Halim, Syafrina
Abas, Norzaida
Osman, Noor Shazwani
author_sort Abdul Halim, Syafrina
title Rainfall analysis in the Northern Region of Peninsular Malaysia
title_short Rainfall analysis in the Northern Region of Peninsular Malaysia
title_full Rainfall analysis in the Northern Region of Peninsular Malaysia
title_fullStr Rainfall analysis in the Northern Region of Peninsular Malaysia
title_full_unstemmed Rainfall analysis in the Northern Region of Peninsular Malaysia
title_sort rainfall analysis in the northern region of peninsular malaysia
publisher Institute of Advanced Science Extension (IASE)
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/62904/
http://www.science-gate.com/IJAAS/V4I11/Syafrina.html
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score 13.188404