The importance of severe weather events is underscored by the severe effects in human lives, infrastructure and the environment. Severe storms cause disruption in services nation-wide provided by the Coast Guard, Port and transportation authorities, and electric power utilities, among others; for example, weather-induced blackouts of electricity distribution grids have caused over $1.5 trillion of damage in the US since the 1980s according to the 2018 report “Billion-Dollar Weather/Climate Disasters” by the U.S. Department of Commerce NOAA/NCDC. Skillful prediction of such extreme events through numerical weather prediction, statistical techniques or their combination in hybrid dynamical-statistical methods is crucial for managing preparedness, emergency response, and mitigation of impacts. Forecast uncertainty estimation and communication of severe weather predictions remain a challenge and often overshadow the successes and improvements in weather forecasting over the last decade. There is a need to connect state-of-the-science severe weather forecast methods with communication of the forecast and its uncertainties to inform, educate and protect the public as well as critical infrastructure. This session is dedicated to the prediction of severe weather and solicits abstracts from a broad range of research focused on: forecasting extreme weather events; understanding sources of forecast uncertainty and methods for improvement; and addressing the communication of the forecast between scientists, stakeholders and the general public by defining the best use of forecast information.