E3S Web Conf.
Volume 65, 2018International Conference on Civil and Environmental Engineering (ICCEE 2018)
|Number of page(s)||11|
|Published online||26 November 2018|
Evaluation of SRE Scenarios for Penang, Selangor and Johor in Peninsular Malaysia using PRECIS Regional Climate Model (RCM)
Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Jalan Universiti, Bandar Barat, 31900 Kampar, Perak, Malaysia
* Corresponding author: firstname.lastname@example.org
Climate change is unambiguous as there is much evidence from around the world showing that changes have already occurred. This phenomenon is in response to an array of human activities, notably the release of greenhouse gases; an understanding of the rate, mode and scale of this change is now of literally vital importance to society. Researchers utilize climate models to study the dynamics of our changing climate and also to make future projections. Climate models are basic representation of many interactions within the Earth’s climate which includes the atmosphere, land surface, oceans and ice. These models are typically quantitative in nature and range from simple depictions of the climate to very complex ones. In this present study, downscaled PRECIS regional climate models (RCMs) were used to project the average minimum and average maximum temperatures and average precipitation for Penang, Selangor and Johor in Peninsular Malaysia. The RCM projections for these three states were developed based on ECHAM4 A2 and ECHAM5 A1B scenarios for the years 1980 to 2069 and ECHAM4 B2 scenario for the years 2010 to 2069. Bias correction will be applied to the simulated historical data to remove common systematic model errors. Historical observation data of monthly average minimum and maximum temperatures and monthly average rainfall from the Malaysian Meteorological Department (MMD) will be used in the bias correction. Finally, a RCM scenario which matches with the historical observation data of the three states for future projections will be recommended.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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