Assessment of future rainfall patterns in Cameron Highlands using the statistically downscaled local climate model

• Main Author: Liu, Ni Qiao
• Format: Final Year Project / Dissertation / Thesis
• Published: 2023
• Subjects: GA Mathematical geography. Cartography; TD Environmental technology. Sanitary engineering
• Online Access: http://eprints.utar.edu.my/6216/1/23AGM00482_Liu_Niqiao.pdf; http://eprints.utar.edu.my/6216/
• Institution: Universiti Tunku Abdul Rahman

Due to the disasters, such as heavy rainfall and landslides, that have occurred in Cameron Highlands in recent years, significant damage has been inflicted on public property safety and the health of the people. This study seeks to explore future precipitation changes in different scenarios and spatiotemporal contexts. The aim is to provide insights that government agencies can consider when formulating guiding principles or land-use plans. It is important to note that the scenarios presented by the local precipitation model generated in this study are merely possibilities and not definite outcomes. Research aims: 1) To develop the local climate model using the statistical downscaling approach. 2)To assess the performance of the statistically downscaled local climate model based on SSP2- 4.5 and SSP5-8.5. 3). To analyse the changes in rainfall patterns (2015–2100) using spatial analysis. The study compared historical observed and simulated data, finding the model effectively represented Tmax, Tmin, and Relative Humidity from 1983 to 2014, but had limitations in reproducing historical precipitation. Bias correction using the Delta Method was applied to address underestimation. Statistical methods confirmed the reliability of the generated historical models. For the Local Climate Model (2015-2100), Station 1 and 2 showed similar precipitation changes under SSP2-4.5 and SSP5-8.5 until 2063, after which they diverged. Station 3 experienced significantly higher precipitation changes. Anomalous precipitation under SSP5-8.5 transitioned from negative to positive anomalies around 2049. The impact of SSP5-8.5 on precipitation seemed greater than SSP2-4.5, less influenced by terrain. Spatial analysis showed elevation differences and a correlation between altitude and precipitation, with higher altitudes experiencing increased precipitation.