We present an overview of recent work on using artificial intelligence (AI)/machine learning
(ML) techniques for forecasting convective weather and its associated hazards, including …

Abadi, M., and Coauthors, 2016: Tensorflow: A system for large-scale machine learning.
Proc. 12th USENIX Symp. on Operating Systems Design and Implementation (OSDI'16) …

Recently, the use of machine learning in meteorology has increased greatly. While many
machine learning methods are not new, university classes on machine learning are largely …

Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal
vorticity (ω h) by the updraft. This rotation induces dynamic lifting that can stretch near …

Using Near-Ground Storm Relative Helicity in Supercell Tornado Forecasting in: Weather and
Forecasting Volume 34 Issue 5 (2019) Jump to Content Jump to Main Navigation Logo Logo …

Over the past decade the use of machine learning in meteorology has grown rapidly.
Specifically neural networks and deep learning have been used at an unprecedented rate …

Previous studies have identified environmental characteristics that skillfully discriminate
between severe and significant-severe weather events, but they have largely been limited …

The Influences of Effective Inflow Layer Streamwise Vorticity and Storm-Relative Flow on
Supercell Updraft Properties in: Journal of the Atmospheric Sciences Volume 77 Issue 9 (2020) …

Sufficient low-level storm-relative flow is a necessary ingredient for sustained supercell
thunderstorms and is connected to supercell updraft width. Assuming a supercell exists, the …

Adlerman, EJ, and KK Droegemeier, 2002: The sensitivity of numerically simulated cyclic
mesocyclogenesis to variations in model physical and computational parameters. Mon …