Applying Machine Learning in the Environmental Sciences
Dr. Sue Ellen Haupt
National Center for Atmospheric Research
Tuesday, October 10, 2023, 2 PM ET
Artificial intelligence (AI) and machine learning (ML) have become important tools for the environmental scientist, both in research and in application. These methods have become quite popular in recent years, but they are not new. Early applications in the 1980’s featured more heuristic expert systems approaches, but by the 1990’s supervised learning methods were beginning to predominate. Many researchers began finding innovative uses for ML in the 1990s. Uses continued to progress to the point where these tools have become nearly as standard as statistical analyses.
The environmental sciences possess a host of interesting problems amenable to advancement by intelligent techniques. We will review the evolution from the early applications and how they have impacted these sciences. We will discuss the types of applications that have been most prevalent. The talk will touch on topics in weather forecasting, probabilistic prediction, climate applications, optimization problems, downscaling model runs, and emulating processes in models. We will finish with a look at where AI is being applied to environmental science, appears to be going in the future, and some thoughts on how these methods might be best blended with the physical / dynamical modeling approaches to further advance our science.
Dr. Haupt is an NCAR Senior Scientist in the Research Applications Laboratory (RAL) of NCAR. She leads projects in renewable energy prediction, coupling mesoscale models to microscale models, and in applying artificial intelligence. She is a Fellow of the American Meteorological Society (AMS); Commissioner of the AMS Commission on the Weather, Water, and Climate Enterprise of AMS; and Contributing and Founding Director of the World Energy and Meteorology Council. Dr. Haupt is an expert in applications of artificial intelligence in the environmental sciences, boundary layer meteorology, large scale atmospheric dynamics, renewable energy, dynamical systems, numerical methods, and computational fluid dynamics.
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