International Journal of Advanced Engineering and Technology

Authors
Amnah Saeed Sulaiman Aldhanhani, Muhammed Sirajul Huda Kalathingal, Shaher Bano Mirza, Fouad Lamghari Ridouane

Abstract
Among the major challenge that climatic department encounters are to predict the weather properly. These forecasts are significant because they impact daily living as well as the economics of a county or even a region. Weather forecasting is especially vital since it is the first line of defense against natural catastrophes. They also aid in reducing deprivation and limiting the mitigation procedures that must be implemented following a natural disaster. Many academics recently suggested that machine learning algorithms may make reasonable weather forecasts despite having no deep understanding of climate science. Relatively high scientific methods and practices, such as machine learning algorithm implementations, are required for an efficient comprehension of weather patterns. In this work, we employed the random forest machine learning classifier to characterize the meteorological sets of data with approx. 80% accuracy.