Statistical Downscaling of Regional Climate Model: A Case Study in Penang Island, Malaysia

Abstract

<p>Flooding events are the most devastating natural disasters that Malaysia had experienced these recent years. It has become a challenge for the government and society to mitigate the flood events that occurs naturally, especially when climate change had worsened the situation. This study focuses on changes of rainfall, maximum and minimum temperature in Penang. With the fast growth rate of resident population and its economic status, obtaining the suitable and viable future climate scenario is crucial and significant to enhancing the flood forecasting capabilities in the Penang Island. The dataset obtained from CanESM2 GCM was used to generate the regionalized rainfall and temperature data based on Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment report (AR5) Representative Concentration Pathways (RCPs) of 4.5 and 8.5 W/m2 emission scenario. The downscaling period (2005–2100) for maximum temperature (Tmax) and minimum temperature (Tmin) and rainfall time were developed using the statistical downscaling technique. For reliability analysis, the model outputs were analysed with Probability Density Function (PDF), Linear Regression and Pearson Correction Test. Based on the reliability analysis outcomes, the possible causes for acknowledging that the Penang Island could follow the high emission scenario RCP 8.5. This indicates that the average monthly rainfall and temperature of Penang Island may increase consequential of the regional climate change, resulting from an increasing population, the industrial development and ever-escalating transportation needs.</p>