Modeling Seasonality of Rainfall by Nonlinear curve Fitting to Monthly Rainfall Time Series of Jorhat
Author(s) -
Gouri Goutam,
Sudeepta Pran
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016911440
Subject(s) - series (stratigraphy) , seasonality , computer science , nonlinear system , time series , climatology , hydrology (agriculture) , environmental science , meteorology , geology , machine learning , geotechnical engineering , geography , paleontology , physics , quantum mechanics
In this paper, an attempt to model the temporal variability of rainfall is made by performing a time series analysis on the monthly rainfall data of Jorhat from 1994 to 2013 (excluding 2003). The monthly rainfall time series showed seasonality with a prominent frequency of 0.083 cycles per year. A curve fitting technique by nonlinear regression on the original rainfall time series and on the resulting regular residuals of the subsequent fits is performed to model the seasonality of the rainfall. The selected model is capable of showing the same seasonality and frequency of rainfall variability as that of the original rainfall time series. The selected model has the potentiality to be replicated to model rainfall in places showing similar seasonality as that of the present case.
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