• Gorikapudi Manidheer Babu
• Tammisetty Venkata Padma
• Bondili Jahnavi
• Peravali Bhavitha
• Pullagura Anuradha

In meteorology and scientific research, weather forecasting is a crucial topic. For this study, the forecasting model was constructed using the Box-Jenkins method-based Seasonal Auto Regressive Integrated Moving Average (ARIMA) model. The period from January 1968 to December 2018's monthly rainfall data for Balodabazar, Bemetara, Raipur city was used. The best ARIMA model orders were determined using the autocorrelation and partial autocorrelation functions for time series data spanning the years 1968 to 2018. Statistical measures like RMSE and R2 were used to compute the accuracy of each model and compare them. The models used to forecast the monthly rainfall for the Balodabazar (1,0,1) (1,1,1), Bemetara (0,0,2) (0,1,1), and Raipur (1,0,1) (0,1,1) yielded the most accurate results.

forecasting, ARIMA model, box-jenkins method, rainfall, RMSE and R2

"Weather Prediction Using Time Series Analysis (Arima Model) ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.465-472, November-2024, Available :http://www.jetir.org/papers/JETIRGO06049.pdf

"Weather Prediction Using Time Series Analysis (Arima Model) ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. pp465-472, November-2024, Available at : http://www.jetir.org/papers/JETIRGO06049.pdf