Precise forecasting of occurrences such as tornadoes and hail up four to eight days in advance. As severe weather approaches with potential life-threatening hazards such as heavy rain, hail, or tornadoes, early warnings, and precise predictions are crucial. Weather researchers at Colorado State Uni
Researchers have developed a machine learning model, the CSU-MLP, capable of accurately predicting hazardous weather events such as tornadoes and hail four to eight days in advance. The team has collaborated with the national Storm Prediction Center to test and refine the model, enhancing forecasters’ confidence in their predictions and potentially saving lives.
“Our statistical models can benefit operational forecasters as a guidance product, not as a replacement,” Hill said. CSU Ph.D. student Allie Mazurek discusses the CSU-MLP with forecaster Andrew Moore. Credit: Provided/Allie MazurekThe model is trained on a very large dataset containing about nine years of detailed historical weather observations over the continental U.S. These data are combined with meteorological retrospective forecasts, which are model “re-forecasts” created from outcomes of past weather events.
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