A Survey of Rainfall Prediction Using Deep Learning

Abstract

Prediction of rainfall is a difficult task because of the high volatility and complicated nature of the atmospheric data. Recently, various deep learning methods were successfully applied to forecast rainfall. We survey papers that employ deep learning techniques to predict rainfall using meteorological data. The papers are examined in terms of the deep learning methods applied, location of the study area, types of metrics and software used for implementing the model and, year-wise publication of the papers. From the surveyed papers, we found that deep learning methods can be applied successfully for rainfall prediction and they are found to be superior than the traditional machine learning methods and shallow neural network models. We also provide future directions for research in the area of rainfall prediction.