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

Climate variability and weather phenomena can cause extremes and pose significant risk to
society and ecosystems, making continued advances in our physical understanding of such …

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 …

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 …

Excessive rainfall is difficult to forecast, and there is a need for tools to aid Weather
Prediction Center (WPC) forecasters when generating Excessive Rainfall Outlooks (EROs) …

Weather forecasting has always been challenging due to the atmosphere's complex and
dynamic nature. Weather conditions such as rain, clouds, clear skies, and sunniness are …

In recent years, the use of deep learning methods has rapidly increased in many research
fields. Similarly, they have become a powerful tool within the climate scientific community …

Thunderstorms are recognized as one of the most disastrous weather threats in Canada
because of their power to cause substantial damage to human-made structures and even …

Historical observations of severe weather and simulated severe weather environments (ie,
features) from the Global Ensemble Forecast System v12 (GEFSv12) Reforecast Dataset …

The mountainous areas are vulnerable to climate change and may have many socio-
economic and environmental implications. The changing pattern of meteorological variables …