Modeling Precipitation Patterns in Alappuzha -Kerala: An Analysis of Regression and Time Series Approaches

In this work, the relationship between precipitation and meteorological parameters in the Alappuzha district in the Kerala region, India, has been analyzed using real-time data obtained from NASA's POWER project. The experiment considers T2M, RH2M, WS2M, and PETCORR parameter values and employs statistical analysis techniques, including correlation, regression, and time series modeling, to examine the relationships between these variables and to forecast future precipitation levels. The findings report that the meteorological variables analyzed in this experiment have a significant impact on precipitation. The parameters such as temperature, relative humidity, and wind speed are identified as key factors that influence precipitation in the region. The regression and time series models developed in this work provide high accuracy in predicting precipitation levels with the time series model that outperforms the regression model. The machine learning-based visualizations provide insights into the trends and occurrences in the data. The performance comparison of the regression and time series models based on R2 score and other testing metrics helps to evaluate their suitability for practical applications. The experimental findings have significant implications for policymakers and stakeholders in Alappuzha and other flood-prone regions, highlighting the importance of monitoring and forecasting meteorological variables to mitigate the impacts of floods caused by extreme precipitation events.