Evaluation, Tuning, and Interpretation of Neural Networks for Working with Images in
Meteorological Applications in: Bulletin of the American Meteorological Society Volume 101 Issue …

Extracting valuable information from large sets of diverse meteorological data is a time-
intensive process. Machine-learning methods can help to improve both speed and accuracy …

Intense thunderstorms threaten life and property, impact aviation, and are a challenging
forecast problem, particularly without precipitation-sensing radar data. Trained forecasters …

In recent years, artificial intelligence and specifically artificial neural networks (NNs) have
shown great success in solving complex, nonlinear problems in earth sciences. Despite their …

Distinguishing Characteristics of Tornadic and Nontornadic Supercell Storms from Composite
Mean Analyses of Radar Observations in: Monthly Weather Review Volume 148 Issue 12 …

Previous studies have shown that increases in flash rates detected in ground-based
lightning data can be a precursor to severe weather hazards. Lightning data from the …

Increases in flash rates detected in ground-based lightning data can be a precursor to
severe weather hazards [12, 6, 9]. Lightning data from the Geostationary Lightning Mapper …

The method of neural networks (aka deep learning) has opened up many new opportunities
to utilize remotely sensed images in meteorology. Common applications include image …