Machine learning is a new tool that is being used more and more everyday across different disciplines. Professor of Atmospheric and Oceanic Sciences Jacob Bortnik illustrates the diverse ways to apply machine learning to Earth and space sciences in his Eos publication. Machine learning uses large and complex data steps to reveal unanticipated patterns and relationships. By revealing these patterns, scientists can learn what parameters affect the output most and work to change this.
Because machine learning is fairly new, young scientists may not know how to apply it to their discipline. Professor Bortnik explains the applications of machine learning in Earth and space science data and how it can catalyze new and creative uses. Hopefully this inspires scientists to use machine learning, whether it be to create global climate models or to predict the evolution of hurricanes.
Ten Ways to Apply Machine Learning in Earth and Space Sciences