Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

Advanced machine learning models have recently achieved high predictive accuracy for
weather and climate prediction. However, these complex models often lack inherent …

Given the growing use of Artificial intelligence (AI) and machine learning (ML) methods
across all aspects of environmental sciences, it is imperative that we initiate a discussion …

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 …

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 …

We have developed additive logistic models for the occurrence of lightning, large hail (≥ 2
cm), and very large hail (≥ 5 cm) to investigate the evolution of these hazards in the past, in …

Supercell storms are commonly responsible for severe hail, which is the costliest severe
storm hazard in the United States and elsewhere. Radar observations of such storms are …

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 …

Hail is one of the costliest natural hazards in Switzerland and causes extensive damage to
agriculture, cars, and infrastructure each year. In a warming climate, hail frequency and its …

Severe convective storms, in particular supercells, are occasionally responsible for a large
number of property losses and damage in Spain. This paper aims to study the synoptic …