Identifying rainfall patterns using Fourier series: A case of daily rainfall data in Sarawak, Malaysia

Abstract

Abstract The a im for this paper is to fit Fourier series on the daily rainfall data to describe the rainfall patterns and to identify the time frame of the wettest and the driest period for the studied stations. The estimated parameter of the Fourier series in modelling the mean daily rainfall amount received were obtained using the method of Generalized Linear Model and the performance was evaluated using the analysis of deviance. Following the objective, the daily rainfall data ranges from 41 to 58 years over four stations in Sarawak namely Kuching, Miri, Bintulu a nd Sibu are studied. Results showed three harmonics is appropriate in modelling the mean daily rainfall received for Kuching, Sibu and Miri stations. However, only two harmonics was found to be fitted the mean daily rainfall amount received significantly for Bintulu station. The wettest month of the studied stations wa s estimated to occur in late December to early January, whereas the driest month is in March for Miri station, April for Bintulu, July for Kuching a nd June for Sibu station. The information gained from this study can be used to monitor the occurrence of flood and drought events in the area so that future action can be taken to reduce the impacts.