This work focuses on applying machine learning in both forecasting of the weather and in climate modeling. This paper reviews literature on the current trends with reference to the efficiency of machine learning to enhance the performance and future prediction of computational methods. The assessment of a number of machine learning methods for finding short and long term predictions is attempted in the study using ensemble methods and neural networks. The implementation and deployment concerns are included with the approaches to data collecting, processing, and model making. The conclusions imply that, from time to time, machine learning models outperform conventional physics-based models and seem to have a special advantage in predicting short-term conditions. The climatic forecasts for long-term and the events of extreme weather still present challenges, nevertheless.

This work focuses on applying machine learning in both forecasting of the weather and in climate modeling.