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Volume 91 (2024)

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Advances and Applications in Statistics

and the fitted model for the number of rainy days is the

with no constant included in the models. The results from the periodogram analysis showed that the rainfall and the number of rainy day series contained significant periodic component of 12 months which are the same results of the seasonal phenomena of ARIMA Box and Jenkins models. The ARIMA with seasonal model possibly predicts the monthly rainfall and the number of rainy days one year ahead with acceptable accuracy.

Advances and Applications in Statistics
Volume 15, Issue 1, Pages 27 - 48 (March 2010)

APPLICATIONS OF BOX-JENKINS MODELS TO RAINFALL DATA OF CHIANG MAI PROVINCE IN THAILAND
Montip Tiensuwan and Sukuman Sarikavanich

Abstract:
In this paper, a time series analysis is adopted as a technique for forecasting of monthly rainfall and number of rainy days. The data sets are recorded by the meteorological department of Chiang Mai from January 1982 to August 2006. The Box-Jenkins technique is used for identifying the parameters of an Autoregressive Integrated Moving Average (ARIMA) model. The Akaike information criterion, the Schwarz’s Bayesian criterion and the mean square error are used throughout to test for simplification of any particular model. The periodogram analysis is used to confirm the existence of a seasonal period in the ARIMA model. The results from time series analysis showed that the fitted model for the rainfall is the

and the fitted model for the number of rainy days is the

Keywords and phrases: autocorrelation, Box-Jenkins model, partial autocorrelation, periodogram analysis, rainfall, time series analysis.

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