Machine Learning based rainfall forecasting in different season in Bangladesh

The main purpose of this study was to assess recent changes in rainfall intensity and seasonal rainfall variability in Bangladesh. By exploring the data collaboratively, daily rainfall records from 34 meteorological stations spread throughout 7 areas of Bangladesh between 1989 and 2018 were used to analyze changes in rain intensity and seasonal rainfall variability. The variability of spring and summer rainfall increased during the last 30 years, but winter fall showed less variability in seasonal totals in the last 30 years[12]. During the last 30 years (1989–2018), the accuracy of rainfall estimation has been above 65%. The changing pattern of the climate means neither scarcity nor heavy rainfall affects rural or urban life to a great extent. The classification analysis models have been developed for the rainfall prediction of 34 metrological stations in Bangladesh. Rainfall data analysis revealed an escalating tendency throughout the monsoon and post-monsoon seasons, while the winter season revealed a descending trend and the pre-monsoon season showed no discernible change. In the same time frame, it was discovered that the annual average rainfall trend was declining at a rate of 0.023 mm per year. The effects of rainfall patterns on agriculture are significant in Bangladesh.