Severe weather in the form of winter storms, tornadoes, hurricanes and heat waves is a cause of major disruptions in human lives, critical infrastructure and the environment. 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. Understanding forecast uncertainty (due to e.g. initial conditions and model error, or unresolved physical processes) improves situational awareness and influences confidence in impact modeling. This session is dedicated to the assessment of extreme weather prediction and associated impacts and solicits abstracts from a broad range of research focused on:

• Forecasting of extreme weather across various temporal and spatial scales.
• Understanding sources of forecast uncertainty.
• Influence of weather forecast uncertainty on preparing for and managing impacts of severe weather (e.g. floods, power outages).
• Social vulnerability to extreme weather, particularly for sensitive populations and minorities.