Artificial Intelligence in the Marine and Atmospheric Sciences: A Review of Applications and Challenges

AI has great potential for oceanography and atmospheric sciences, but it also has some limitations and challenges. In this manuscript, we review the current and future AI applications in these fields, such as monitoring marine biodiversity, modeling deep-sea resources, predicting ocean parameters, and studying marine pollution. We offer a comprehensive guide for researchers, practitioners, educators, and students who are interested in or working on AI-related problems in oceanography and atmospheric sciences. We describe how to apply AI in research in research, such as defining the research question and objective, collecting and preprocessing the data, selecting and implementing the AI algorithm, training and testing the AI model, evaluating and validating the performance and uncertainty of the AI model, and interpreting and explaining the results and findings of the AI model. We also introduce some popular software packages for machine learning and deep learning, such as scikit-learn, TensorFlow, and PyTorch. These packages can provide tools for data preprocessing, model training, evaluation, and visualization. This manuscript aims to provide a comprehensive overview and reference for AI applications in oceanography and atmospheric sciences.

Keywords:

Artificial Intelligence , Oceanography , Atmospheric Science