Modeling and forecasting meteorological factors using BATS and TBATS models for the Keonjhar district of Orissa

Weather factors such as temperature and humidity are indispensable for good agriculture.The best-suitable products can be selected according to the optimal of these weather factors. In this study, data on maximum temperature, minimum temperature, morning relative humidity and evening relative humidity was analyzed from 31st January, 1921 to 31st December, 2020 in India. The BATS (Exponential Smoothing Method + Box-Cox Transformation + ARMA model for residuals) and TBAT (BATS + Trigonometric Seasonal) models are conducted for forecasting procedures. According to some selection criteria, the best models are specified for all weather factors. Extensive tables and graphics are presented in the study. The data series was divided into train set and test set. The result obtained from train set based on goodness of fit, BATS model performed as a best model. For error estimation using testing data set, BATS model performed well for maximum temperature, morning and evening relative humidity. Both models were performed significantly atpar in minimum temperature data series. Using the results and forecasts obtained in this study, the researcher or scientist should be focused on the weather condition which is more concerned parameter for agriculture.