An evaluation of statistical model for downscaling precipitation

Climate change affects water availability and the conditions will be worsened with increasing water demands. The relative performance of GCMs depends on the size of the region, location, and on the variables being analyzed. For this study the model output of HadCM3 GCM was employed for the A2 (Mediu...

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Main Author:	Gholizadeh, Shahaboddin Hossein
Format:	Thesis
Published:	2010
Subjects:	TA Engineering (General) Civil engineering (General)
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spelling	my-utm-ep.191562020-02-09T03:22:19Z An evaluation of statistical model for downscaling precipitation 2010 Gholizadeh, Shahaboddin Hossein TA Engineering (General). Civil engineering (General) Climate change affects water availability and the conditions will be worsened with increasing water demands. The relative performance of GCMs depends on the size of the region, location, and on the variables being analyzed. For this study the model output of HadCM3 GCM was employed for the A2 (Medium- High Emissions) and B2 (Medium-Low Emission) Scenarios. HadCM3 is a coupled atmospheric-ocean GCM developed at Hadley Centre for Climate Prediction and Research, UK. The atmospheric part of HadCM3 has a horizontal resolution of 2.5° latitude x 3.75° longitude, and has 19 vertical levels. HadCM3 is applied in this study because the model is widely applied in climate change impact studies and the model provides daily predictor variables with coverage all over the world includes Malaysia that can be used for the Statistical Downscaling Model (SDSM). In this study, Statistical Downscaling Model (SDSM) was applied using two stations in Kerian, Perak consisted to Kolam Air Bukit Merah and Ladang Sungai Kerian. These stations would be used to evaluate mean daily precipitations, wet days, wet spell length and dry spell length which are related with current situations 1961-1990 and the future projections 2010-2039, 2040-2069 and 2070-2099.The availability of the data for observed situation were serves by National Centre of Environmental Prediction (NCEP) which are provides in 40 years starting from 1961. By providing this evaluation, the results showed the fluctuations every 30 years. Within this projection, it shows the decrement of wet days and wet spell length due to increment of future climate change. Frequency analysis techniques were carried out using two model distribution which are Gumbel and Generalised Extreme Value (GEV). This distribution showed the return periods due to flood monitoring based on 50 and 100 years. With this consideration, SDSM is measured as the workbench to interpret implication of climate change caused by carbon dioxide concentrations in the present and future development. 2010 Thesis http://eprints.utm.my/id/eprint/19156/ http://libraryopac.utm.my/client/en_AU/main/search/results?qu=An+evaluation+of+statistical+model+for+downscaling+precipitation&te= masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Gholizadeh, Shahaboddin Hossein An evaluation of statistical model for downscaling precipitation
description	Climate change affects water availability and the conditions will be worsened with increasing water demands. The relative performance of GCMs depends on the size of the region, location, and on the variables being analyzed. For this study the model output of HadCM3 GCM was employed for the A2 (Medium- High Emissions) and B2 (Medium-Low Emission) Scenarios. HadCM3 is a coupled atmospheric-ocean GCM developed at Hadley Centre for Climate Prediction and Research, UK. The atmospheric part of HadCM3 has a horizontal resolution of 2.5° latitude x 3.75° longitude, and has 19 vertical levels. HadCM3 is applied in this study because the model is widely applied in climate change impact studies and the model provides daily predictor variables with coverage all over the world includes Malaysia that can be used for the Statistical Downscaling Model (SDSM). In this study, Statistical Downscaling Model (SDSM) was applied using two stations in Kerian, Perak consisted to Kolam Air Bukit Merah and Ladang Sungai Kerian. These stations would be used to evaluate mean daily precipitations, wet days, wet spell length and dry spell length which are related with current situations 1961-1990 and the future projections 2010-2039, 2040-2069 and 2070-2099.The availability of the data for observed situation were serves by National Centre of Environmental Prediction (NCEP) which are provides in 40 years starting from 1961. By providing this evaluation, the results showed the fluctuations every 30 years. Within this projection, it shows the decrement of wet days and wet spell length due to increment of future climate change. Frequency analysis techniques were carried out using two model distribution which are Gumbel and Generalised Extreme Value (GEV). This distribution showed the return periods due to flood monitoring based on 50 and 100 years. With this consideration, SDSM is measured as the workbench to interpret implication of climate change caused by carbon dioxide concentrations in the present and future development.
format	Thesis
qualification_level	Master's degree
author	Gholizadeh, Shahaboddin Hossein
author_facet	Gholizadeh, Shahaboddin Hossein
author_sort	Gholizadeh, Shahaboddin Hossein
title	An evaluation of statistical model for downscaling precipitation
title_short	An evaluation of statistical model for downscaling precipitation
title_full	An evaluation of statistical model for downscaling precipitation
title_fullStr	An evaluation of statistical model for downscaling precipitation
title_full_unstemmed	An evaluation of statistical model for downscaling precipitation
title_sort	evaluation of statistical model for downscaling precipitation
granting_institution	Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department	Faculty of Civil Engineering
publishDate	2010
_version_	1747815395060875264

An evaluation of statistical model for downscaling precipitation

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