Machine Learning

Severe weather forecasts from artificial intelligence weather prediction models
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Extended range machine-learning severe weather guidance based on the operational GEFS
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Can Ingredients-Based Forecasting be Learned? Disentangling a Random Forest's Severe Weather Predictions
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Observation Definitions and their Implications in Machine Learning-based Predictions of Excessive Rainfall
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Machine Learning for Forecasting
Machine learning tools are being used to generate valuable products that aid operational forecasting
Last updated on Aug 7, 2025
Machine Learning for Forecasting
A New Paradigm for Medium-Range Severe Weather Forecasts: Probabilistic Random Forest–Based Predictions
Abstract Historical observations of severe weather and simulated severe weather environments (i.e., features) from the Global Ensemble Forecast System v12 (GEFSv12) Reforecast Dataset (GEFS/R) are used in conjunction to train and test random forest (RF) machine learning (ML) models to probabilistically forecast severe weather out to days 4–8.
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A New Paradigm for Medium-Range Severe Weather Forecasts: Probabilistic Random Forest–Based Predictions
Forecasting excessive rainfall with random forests and a deterministic convection-allowing model
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From random forests to flood forecasts: A research to operations success story
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Forecasting severe weather with random forests
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