Climate change impact under CanESM2 on future rainfall in the state of Kelantan using Artificial Neural Network

Abstract

Abstract Kelantan is a state in Peninsular Malaysia that is highly vulnerable to extreme events such as drought and floods which are becoming worse because of climate change due to global warming that is caused by human activities. This study aims to evaluate the potential impacts of climate change on the future of rainfall in Kelantan using Artificial Neural Network. CanESM2 under three Representative Concentration Pathways (RCPs), namely RCPs 2.6, 4.5, and 8.5 for 2011-2100 are incorporated with the ANN model and are used to compare the baseline period (1972 to 2018). In general, the simulated rainfall that downscaled by using the ANN model approximates the observed rainfall (during the calibration and validation periods) reasonably well. The study also shows that the ANN model anticipates a major increase in annual rainfall in the 2080s for the RCP 8.5 scenario.