Physical- emipirical models for prediction of seasonal rainfall extremes of Peninsular Malaysia
Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Reliable prediction of rainfall extremes is vital for disaster management, particularly in the context of increasing rainfall extremes due to global climate change. Physical-empirical models have been developed in this study using three widely used Machine Learning (ML) methods namely, Support Vector Machines (SVM), Random Forests (RF), Bayesian Artificial Neural Networks (BANN) for the prediction of rainfall and rainfall related extremes during Northeast Monsoon (NEM) in Peninsular Malaysia from synoptic predictors.
Description
Keywords
Extreme rainfall, Climate forecasting, Physical-empirical model, Machine learning algorithm, Recursive feature elimination
Citation
Pour, S. H., Abd Wahab, A. K., & Shahid, S. (2020). Physical-empirical models for prediction of seasonal rainfall extremes of Peninsular Malaysia. Atmospheric Research, 233, 104720.