Modeling Precipitation Patterns with Time Series Autoregression Techniques

India's reliance on the monsoon for critical rainfall is threatened by a concerning trend: the Indian Meteorological Department (IMD) reports a 10 % decrease in average monsoon rainfall since the 1950s, with a projected further decline of 15–20 % by the end of the 21st century. This decline has dire implications for agriculture, water resources, and the economy, leading to more frequent droughts, substantial crop losses, and water shortages. Contributing factors include climate change, land use changes, and aerosol pollution. In response, the Indian government has implemented measures like drought management plans, improved water conservation, climate-smart agriculture promotion, and efforts to combat air pollution. Our research harnesses advanced AutoRegression techniques, highlighting the remarkable 0.8563 R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> score and RMSE as low as 39.06.