Genetic Programming for Downscaling Extreme Rainfall Events

Abstract

Downscaling extreme rainfall events is a major challenge in climate change study. A Genetic Programming (GP) based method is used in this article for the downscaling of extreme rainfall events in the East coast of peninsular Malaysia during northeast monsoon season. The principal components of Global Circulation Model (GCM) parameters at four points surrounding the study area are used as predictors. Four GP models are developed for the prediction of rainy days and extreme rainfall events such as rainfall more than 99 percentile, rainfall more than 95 percentile and rainfall more than 90 percentile in a year. All possible numerical, logical and trigonometric operators are used to find multi-level GP models for the downscaling. Daily rainfall data during monsoon season for the time periods 1961-1990 and 1991-2000 are used for model calibration and validation, respectively. The results show that the models can predict extreme rainfall events in the East coast of Malaysia with reasonable accuracy.