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Machine learning model helps forecasters improve confidence in storm prediction: Accurate predictions of events like tornadoes and hail four to eight days in advance

Machine learning model helps forecasters improve confidence in storm prediction: Accurate predictions of events like tornadoes and hail four to eight days in advance
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United States , Colorado State University , Allie Mazurek , Aaron Hill , Russ Schumacher , American Meteorological Society , Storm Prediction Center , Department Of Atmospheric Science , Atmospheric Science , Colorado State Climatologist , Colorado State University Machine Learning ,

Machine learning model helps forecasters improve confidence in storm prediction

Machine learning model helps forecasters improve confidence in storm prediction
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United States , Colorado State University , Aaronj Hill , Andrew Moore , Russ Schumacher , Aaron Hill , Allie Mazurek , American Meteorological Society , Department Of Atmospheric Science , Storm Prediction Center , Storm Prediction , State University , Atmospheric Science , Colorado State Climatologist , Colorado State University Machine Learning , New Paradigm , Medium Range Severe Weather Forecasts , Probabilistic Random Forest , Based Predictions ,

CSU machine learning model helps forecasters

When severe weather is brewing and life-threatening hazards like heavy rain, hail or tornadoes are possible, advance warning and accurate predictions are of utmost importance. Colorado State University weather researchers have given storm forecasters a powerful new tool to improve confidence in their forecasts and potentially save lives.

Over the last several years, Russ Schumacher, professor in the Department of Atmospheric Science and Colorado State Climatologist, has led a team developing a sophisticated machine learning model for advancing skillful prediction of hazardous weather across the continental United States. First trained on historical records of excessive rainfall, the model is now smart enough to make accurate predictions of events like tornadoes and hail four to eight days in advance – the crucial sweet spot for forecasters to get information out to the public so they can prepare. The model is called CSU-MLP, or Colorado State University-Machine Learning Prob ....

United States , Colorado State University , Allie Mazurek , Aaron Hill , Russ Schumacher , American Meteorological Society , Storm Prediction Center , Department Of Atmospheric Science , Method Of Research , State University , Atmospheric Science , Colorado State Climatologist , Colorado State University Machine Learning , New Paradigm , Medium Range Severe Weather Forecasts , Probabilistic Random Forest ,