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Artificial Intelligence Weather Prediction Model Performance for Hurricane Helene (2024)
Extended range machine-learning severe weather guidance based on the operational GEFS
DOI
Severe weather forecasts from artificial intelligence weather prediction models
Can Ingredients-Based Forecasting be Learned? Disentangling a Random Forest's Severe Weather Predictions
DOI
Observation Definitions and their Implications in Machine Learning-based Predictions of Excessive Rainfall
DOI
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.
DOI
A New Paradigm for Medium-Range Severe Weather Forecasts: Probabilistic Random Forest–Based Predictions
Influence of a portable near-surface observing network on experimental ensemble forecasts of deep convection hazards during VORTEX-SE
DOI
Forecasting excessive rainfall with random forests and a deterministic convection-allowing model
DOI
From random forests to flood forecasts: A research to operations success story
DOI
Factors influencing ensemble sensitivity-based targeted observing prediction at convection-allowing resolutions
DOI