Atmospheric hazards, for example heavy precipitation or damaging wind gusts, can lead to major material and human losses. Accurately forecasting the meteorological process responsible for the hazard, and the hazard itself, is necessary to protect lives and property. In-depth understanding of these hazards and severe weather phenomena is necessary to accurately represent the relevant processes in models and to forecast them.

With increasing computer power, operational forecast systems have begun to resolve convective scales, yet many hazards are still sub-grid scale phenomena relying on crude parameterizations. However, the promising horizon uncovered by Artificial Intelligence (AI) techniques suggests fruitful synergies between classical computational models and AI to improve severe weather phenomena forecasts.

Furthermore, as our climate changes, certain hazards are likely to become more common and as such an in-depth understanding of how climate change impacts atmospheric hazards is needed.

This session welcomes contributions which increase our understanding of mesoscale and microscale atmospheric processes that might represent a hazard for people, property and the environment. Studies devoted to enhancing our physical and dynamical understanding of severe weather phenomena and their hazards are of particular interest as are contributions incorporating conceptual, observational and modelling research.

Topics of interest include but are not limited to:
1. Deep convection and related hazards: hail, lightning, tornadoes, waterspouts, derechos and downbursts.
2. Mesoscale cyclones (polar lows, medicanes, tropical-like cyclones, mediterranean cyclones) and related hazards: Flash-floods and heavy rain events, strong winds, floods etc.
3. Orographic flows and related hazards: severe gap, barrier, katabatic and foehn winds
4. Cold season hazards: Freezing rain, icing, intense snow falls, cold extremes, fog
5. Warm season hazards: severe droughts, heatwaves