Abstract
Weather forecasting is an important issue in meteorology and scientific research.In this research, the Seasonal Auto Regressive.Integrated Moving Average.(ARIMA) model which is based on Box-Jenkins method was adopted to build the forecasting model. The max. Monthly temperature data for Kerbala city for the period (Jan.1980 to Dec.2016) was employed. The autocorrelation and partial autocorrelation functions for time series data from years 1980 to 2015 were used to identify the most appropriate orders of the ARIMA models. The validation test of these models were performed using the monthly max. Temperature of the year 2016. To calculate the model's accuracy and compare among them, statistical criteria such as MAE, RMSE, MAPE, and R2 were used. The model (2, 1, 2) × (1, 1, 1)12 gave the most accurate results and used to forecast the monthly max. Temperature for the period (2017 to 2021) for study region.
Highlights
Time series forecasting is considered a major tool in meteorology and environmental applications such as humidity, rainfall, temperature, stream flow, etc
The present paper aims to develop a time series seasonal ARIMA model using the max
At first the data was checked, and it seems some missing data for some months in the year 2003, these missing data filled by the average max. monthly temperature for each month to make the time series is continuous and sufficient for analysis
Summary
Time series forecasting is considered a major tool in meteorology and environmental applications such as humidity, rainfall, temperature, stream flow, etc. In this technique, the past data must be adopted to develop the best model for forecasting future values, i.e. it is a process for calculating future values through understanding the past [1]. Sarraf et al used 20year -old data of the average monthly temperature and Relative humidity of Ahvaz station, Iran. They applied the ARIMA model using time series analysis program (ITSM) [7]. The data from 1951 to 2014 was used as training, while that through 2015–2017 considered as the testing set [8]
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