[HTML][HTML] Using artificial intelligence to improve real-time decision-making for high-impact weather

A McGovern, KL Elmore, DJ Gagne… - Bulletin of the …, 2017 - journals.ametsoc.org
Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

A review of machine learning for convective weather

A McGovern, RJ Chase, M Flora… - … Intelligence for the …, 2023 - journals.ametsoc.org
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 …

[HTML][HTML] Storm-based probabilistic hail forecasting with machine learning applied to convection-allowing ensembles

DJ Gagne, A McGovern, SE Haupt… - Weather and …, 2017 - journals.ametsoc.org
Forecasting severe hail accurately requires predicting how well atmospheric conditions
support the development of thunderstorms, the growth of large hail, and the minimal loss of …

Forecasting different types of convective weather: A deep learning approach

K Zhou, Y Zheng, B Li, W Dong, X Zhang - Journal of Meteorological …, 2019 - Springer
A deep learning objective forecasting solution for severe convective weather (SCW)
including short-duration heavy rain (HR), hail, convective gusts (CG), and thunderstorms …

Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques

A Mostajabi, DL Finney, M Rubinstein… - Npj Climate and …, 2019 - nature.com
Lightning discharges in the atmosphere owe their existence to the combination of complex
dynamic and microphysical processes. Knowledge discovery and data mining methods can …

Influences of CAPE on hail production in simulated supercell storms

Y Lin, MR Kumjian - Journal of the Atmospheric Sciences, 2022 - journals.ametsoc.org
Lasting updrafts are necessary to produce severe hail; conventional wisdom suggests that
extremely large hailstones require updrafts of commensurate strength. Because updraft …

An empirical model relating US monthly hail occurrence to large‐scale meteorological environment

JT Allen, MK Tippett, AH Sobel - Journal of Advances in …, 2015 - Wiley Online Library
An empirical model relating monthly hail occurrence to the large‐scale environment has
been developed and tested for the United States (US). Monthly hail occurrence for each grid …

How many types of severe hailstorm environments are there globally?

Z Zhou, Q Zhang, JT Allen, X Ni… - Geophysical Research …, 2021 - Wiley Online Library
Understanding how severe hailstorms will respond to climate change remains challenging
partially due to an incomplete understanding of how different environments produce hail …

Application of machine learning to large hail prediction-The importance of radar reflectivity, lightning occurrence and convective parameters derived from ERA5

B Czernecki, M Taszarek, M Marosz, M Półrolniczak… - Atmospheric …, 2019 - Elsevier
This study presents a concept for coupling remote sensing data and environmental variables
with machine learning techniques for the prediction of large hail events. In particular, we …

Application of random forest algorithm in hail forecasting over Shandong Peninsula

H Yao, X Li, H Pang, L Sheng, W Wang - Atmospheric research, 2020 - Elsevier
To improve the accuracy of hail forecasting, this study applies the random forest (RF)
algorithm in hail identification and prediction in Shandong Peninsula. Hail observation data …