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A machine learning model created at CSU has improved forecasters confidence in storm predictions and is now used daily by the National Weather Services Storm Prediction Center and Weather Prediction Center.

The model, developed in the Department of Atmospheric Science by a team led by Schumacher, is capable of accurately predicting excessive rainfall, hail and tornadoes four to eight days in advance. The model is called CSU-MLP for Colorado State University-Machine Learning Probabilities.

Schumachers team worked with NWS forecasters over six years to test and refine the model for their purposes. The CSU code is now running on the Storm Prediction Centers and Weather Prediction Centers operational computer systems, helping forecasters predict hazardous weather, so people in harms way have enough lead time to prepare.

The atmospheric scientists trained the model on historical records of severe weather and NOAA reforecasts, retrospective forecasts run with todays improved numerical models.

Team member Allie Mazurek, a Ph.D. student, is working on explainable AI for the CSU-MLP forecasts. Shes trying to figure out which atmospheric data inputs are most important to the models predictions, so the model will be more transparent for forecasters.

These new tools that use AI for weather prediction are developing quickly and showing some really promising and exciting results, Schumacher said. But they also have limitations, just like traditional weather prediction models and human forecasters have strengths and limitations. The best way to advance the field and improve forecasts will be to take advantage of each of their strengths: the AI for what its good at, which is identifying patterns in massive datasets; numerical weather prediction models for being grounded in the physics; and humans for synthesizing, understanding and communicating.

Schumacher discusses the promise and limitations of AI for weather prediction in more detail in this piece in The Conversation, co-authored by Aaron Hill, a former CSU research scientist who is now a faculty member at the University of Oklahoma.

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