Projections of future extreme rainfall events using statistical downscaling in Malaysia

Climate change is one of the greatest challenges for water resources management. Intensity and frequency of extreme rainfalls are increasing due to enhanced greenhouse gas effect caused by climate change. A lot of research has been done in developing innovative methods for assessing the impacts of c...

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Main Author:	Abdul Halim, Syafrina
Format:	Thesis
Language:	English
Published:	2016
Subjects:	T Technology (General)
Online Access:	http://eprints.utm.my/id/eprint/78608/1/SyafrinaAbdulHalimPRAZAK2016.pdf
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id	my-utm-ep.78608
record_format	uketd_dc
spelling	my-utm-ep.786082018-08-29T07:53:01Z Projections of future extreme rainfall events using statistical downscaling in Malaysia 2016-02 Abdul Halim, Syafrina T Technology (General) Climate change is one of the greatest challenges for water resources management. Intensity and frequency of extreme rainfalls are increasing due to enhanced greenhouse gas effect caused by climate change. A lot of research has been done in developing innovative methods for assessing the impacts of climate change on rainfall extremes. Climate change strongly depends on General Circulation Model (GCM) outputs since they play a pivotal role in the understanding of climate change. However due to their coarse resolution, statistical downscaling is widely applied to match the scale between the GCM and the station scale. This research proposed to establish statistical downscaling model that was able to generate hourly rainfall data for future projection of hourly extreme rainfall in Peninsular Malaysia. An Advanced Weather Generator (AWE-GEN) built on stochastic downscaling principles was applied for simulating hourly rainfall data. The model construction involved 40 stations over Peninsular Malaysia with observations from 1975 to 2005. To account for uncertainties, an ensemble of multi-model namely GFDL-CM3, IS-CM5A-LR, MIROC5, MRI-CGCM3 and NorESM1-M were obtained from the dataset compiled in the WCRP’s, CMIP5. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). To address the problem of unavailability of rainfall data at remote areas over Peninsular Malaysia, this research also examined the spatial variability of rainfall and temperature parameters using Locally Weighted Regression. Results of the AWE-GEN showed its capability to simulate rainfall for Peninsular Malaysia. Both hourly and 24 hour extreme rainfall showed an increase for future. Extremes of dry spell was projected to decrease in future whereas extremes of wet spell was expected to remain unchanged. Simulations of present climate using interpolated parameters showed promising results for the studied regions. 2016-02 Thesis http://eprints.utm.my/id/eprint/78608/ http://eprints.utm.my/id/eprint/78608/1/SyafrinaAbdulHalimPRAZAK2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:97140 phd doctoral Universiti Teknologi Malaysia, UTM Razak School in Engineering and Advanced Technology UTM Razak School in Engineering and Advanced Technology
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Abdul Halim, Syafrina Projections of future extreme rainfall events using statistical downscaling in Malaysia
description	Climate change is one of the greatest challenges for water resources management. Intensity and frequency of extreme rainfalls are increasing due to enhanced greenhouse gas effect caused by climate change. A lot of research has been done in developing innovative methods for assessing the impacts of climate change on rainfall extremes. Climate change strongly depends on General Circulation Model (GCM) outputs since they play a pivotal role in the understanding of climate change. However due to their coarse resolution, statistical downscaling is widely applied to match the scale between the GCM and the station scale. This research proposed to establish statistical downscaling model that was able to generate hourly rainfall data for future projection of hourly extreme rainfall in Peninsular Malaysia. An Advanced Weather Generator (AWE-GEN) built on stochastic downscaling principles was applied for simulating hourly rainfall data. The model construction involved 40 stations over Peninsular Malaysia with observations from 1975 to 2005. To account for uncertainties, an ensemble of multi-model namely GFDL-CM3, IS-CM5A-LR, MIROC5, MRI-CGCM3 and NorESM1-M were obtained from the dataset compiled in the WCRP’s, CMIP5. The projections of extreme precipitation were based on the RCP 6.0 scenario (2081-2100). To address the problem of unavailability of rainfall data at remote areas over Peninsular Malaysia, this research also examined the spatial variability of rainfall and temperature parameters using Locally Weighted Regression. Results of the AWE-GEN showed its capability to simulate rainfall for Peninsular Malaysia. Both hourly and 24 hour extreme rainfall showed an increase for future. Extremes of dry spell was projected to decrease in future whereas extremes of wet spell was expected to remain unchanged. Simulations of present climate using interpolated parameters showed promising results for the studied regions.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdul Halim, Syafrina
author_facet	Abdul Halim, Syafrina
author_sort	Abdul Halim, Syafrina
title	Projections of future extreme rainfall events using statistical downscaling in Malaysia
title_short	Projections of future extreme rainfall events using statistical downscaling in Malaysia
title_full	Projections of future extreme rainfall events using statistical downscaling in Malaysia
title_fullStr	Projections of future extreme rainfall events using statistical downscaling in Malaysia
title_full_unstemmed	Projections of future extreme rainfall events using statistical downscaling in Malaysia
title_sort	projections of future extreme rainfall events using statistical downscaling in malaysia
granting_institution	Universiti Teknologi Malaysia, UTM Razak School in Engineering and Advanced Technology
granting_department	UTM Razak School in Engineering and Advanced Technology
publishDate	2016
url	http://eprints.utm.my/id/eprint/78608/1/SyafrinaAbdulHalimPRAZAK2016.pdf
_version_	1747818027277090816

Projections of future extreme rainfall events using statistical downscaling in Malaysia

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