Machine Learning

A Diffusion-Based Framework for High-Resolution Precipitation Forecasting over CONUS
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
A Novel Approach Heat Risk Analysis Using ML and URMA, Nocturnal Trends in Houston TX during the 2022 TRACER
BoltCast, Medium-range Lightning Prediction with Neural and Long-Short Term Memory Networks
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
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.
DOI
A New Paradigm for Medium-Range Severe Weather Forecasts: Probabilistic Random Forest–Based Predictions