Rainfall Dataset of India

The India Weather Forecast built a state-level standard rainfall forecast system using a multi-model ensemble approach with model outputs from five prominent worldwide NWP centers. Pre-assigned grid point weights based on anomalous correlations (CC) between values observed and predicted are established for each element model using two seasonal datasets, and multi provision of appropriate predictions are created in real-time similar resolution. Then, forecasts are created for each state node lying within a given district by averaging the ensemble prediction fields' values. We utilize a dataset including monthly rainfall data from 1901 to 2015 that has been preprocessed to remove missing values and perform feature engineering. To forecast rainfall, we use machine learning methods such as Random Forest, Lasso, and Ridge Regression models. To examine the accuracy of rainfall predictions, the models are trained and tested for year-month and state-by-state analyses.