Forecasting monthly rainfall and temperature patterns in Van Province, Türkiye, using ARIMA and SARIMA models: a long-term climate analysis
Veysel Süleyman Yavuz
Abstract
ABSTRACT This study investigates monthly rainfall and temperature trends in Van Province, Türkiye, using ARIMA and SARIMA models, with a dataset spanning from 1955 to 2023. The ARIMA(3,1,0) model for rainfall and ARIMA(0,1,1) model for temperature were selected based on Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values, achieving AIC scores of 788.224 and 172.077, respectively. To address seasonality, SARIMA models were also applied, with SARIMA(3,1,0)(2,1,0)[12] for rainfall and SARIMA(0,1,1)(2,1,0)[12] for temperature, yielding AIC scores of 672.061 and 163.669. Diagnostic tests, including the Ljung–Box and Jarque–Bera tests, confirmed model adequacy by indicating minimal autocorrelation and normal residual distributions. These models successfully captured seasonal and long-term patterns, offering valuable insights for regional planning in water resource management and agriculture. The study underscores the potential of ARIMA and SARIMA models for climate forecasting, with suggestions for future enhancements using hybrid approaches to improve predictions under non-linear conditions.