A Comparison of Neural-Network and Surrogate-Severe Probabilistic Convective Hazard Guidance Derived from a Convection-Allowing Model
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DOI: 10.1175/waf-d-20-0036.1
Abstract: A feed-forward neural network (NN) was trained to produce gridded probabilistic convective hazard predictions over the contiguous United States. Input fields to the NN included 174 predictors, derived from 38 variables output by 497 convection-allowing… read more here.
Keywords: probabilistic convective; convection allowing; surrogate; model ... See more keywords
Evaluating machine learning-based probabilistic convective hazard forecasts using the HRRR: Quantifying hazard predictability and sensitivity to training choices
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DOI: 10.1175/waf-d-23-0221.1
Abstract: The High Resolution Rapid Refresh (HRRR) model provides hourly-updating forecasts of convective-scale phenomena, which can be used to infer the potential for convective hazards (e.g., tornadoes, hail, and wind gusts), across the United States. We… read more here.
Keywords: skill; hrrrv4; hrrr; convective hazard ... See more keywords