An automated ststistical downscaling approach for hydrological based climate change in humid tropical area

Many Climate Models have been developed to assist scientist to forecast climate changes. The Automated Statistical Downscaling (ASD) model is considered a new recent model to perform this task. The aim of this study is to explore the applications of ASD model in the projection of the future climate...

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Main Author: Talib, Saif Ali
Format: Thesis
Language:English
Published: 2014
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Online Access:http://eprints.utm.my/id/eprint/41586/1/SaifAliTalibMFKA2014.pdf
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spelling my-utm-ep.415862017-09-11T06:41:00Z An automated ststistical downscaling approach for hydrological based climate change in humid tropical area 2014-01 Talib, Saif Ali GB Physical geography Many Climate Models have been developed to assist scientist to forecast climate changes. The Automated Statistical Downscaling (ASD) model is considered a new recent model to perform this task. The aim of this study is to explore the applications of ASD model in the projection of the future climate changes in humid tropical region. Global Climate Models (GCMs) provides climate impacts information from higher resolution, but there are many impacts require climate information of a smaller resolution. Downscaling is a method to link global scaling prediction to regional prediction. NCEP and CGCM3.1 predictors are used to link these two scales. Multi Linear Regression approach in the ASD model is applied to calibrate NCEP predictors with rainfall data for the period 1961 to 1975 and the results shows that the three stations were calibrated with low RMSE values. The results are validated by using CGCM3.1 and NCEP data for the period 1976 to 1990. The geographic location of the predictors has an influence on the number of predictors available, since the selected station is located within a grid box near the equator making it affected by coriolis effect, limited set of predictors are available. A2 and A1B SRES emission scenarios are used for future projection scenarios for the periods 2011-2040, 2041-2070, and 2071-2100. Five statistical indices that are used namely: mean rainfall, Standard Deviation, 90th percentile, wet days and Consecutive Dry days has been evaluated. A2 and A1B scenarios results shows that certain months will experience an increase in rainfall in terms of intensity and frequency while other months will experience a significant decline. 2014-01 Thesis http://eprints.utm.my/id/eprint/41586/ http://eprints.utm.my/id/eprint/41586/1/SaifAliTalibMFKA2014.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Civil Engineering Faculty of Civil Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic GB Physical geography
spellingShingle GB Physical geography
Talib, Saif Ali
An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
description Many Climate Models have been developed to assist scientist to forecast climate changes. The Automated Statistical Downscaling (ASD) model is considered a new recent model to perform this task. The aim of this study is to explore the applications of ASD model in the projection of the future climate changes in humid tropical region. Global Climate Models (GCMs) provides climate impacts information from higher resolution, but there are many impacts require climate information of a smaller resolution. Downscaling is a method to link global scaling prediction to regional prediction. NCEP and CGCM3.1 predictors are used to link these two scales. Multi Linear Regression approach in the ASD model is applied to calibrate NCEP predictors with rainfall data for the period 1961 to 1975 and the results shows that the three stations were calibrated with low RMSE values. The results are validated by using CGCM3.1 and NCEP data for the period 1976 to 1990. The geographic location of the predictors has an influence on the number of predictors available, since the selected station is located within a grid box near the equator making it affected by coriolis effect, limited set of predictors are available. A2 and A1B SRES emission scenarios are used for future projection scenarios for the periods 2011-2040, 2041-2070, and 2071-2100. Five statistical indices that are used namely: mean rainfall, Standard Deviation, 90th percentile, wet days and Consecutive Dry days has been evaluated. A2 and A1B scenarios results shows that certain months will experience an increase in rainfall in terms of intensity and frequency while other months will experience a significant decline.
format Thesis
qualification_level Master's degree
author Talib, Saif Ali
author_facet Talib, Saif Ali
author_sort Talib, Saif Ali
title An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
title_short An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
title_full An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
title_fullStr An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
title_full_unstemmed An automated ststistical downscaling approach for hydrological based climate change in humid tropical area
title_sort automated ststistical downscaling approach for hydrological based climate change in humid tropical area
granting_institution Universiti Teknologi Malaysia, Faculty of Civil Engineering
granting_department Faculty of Civil Engineering
publishDate 2014
url http://eprints.utm.my/id/eprint/41586/1/SaifAliTalibMFKA2014.pdf
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