Abstracts are solicited regarding the predictability and attribution of weather/ climate extremes and their impacts.
Weather and climate extremes often have large impacts, so it is critical that we better understand these events, improve their prediction, and gain knowledge of how and why they are changing as the planet warms. This session aims to bring together physics-based and data-driven approaches to the study of extremes and their impacts. Studies focusing on either hazards associated with extremes or directly on societal impacts (including health, insurance, energy, and other sectors) are welcome. A particular goal of this session is to explore novel approaches to the predictability of extremes, and facilitate a deeper understanding of their impacts in our changing climate. We particularly encourage submissions from early career scientists and underrepresented groups.
Topics of interest include but are not limited to:
Predictability of extremes, especially from forecasting and applied viewpoints.
Attribution of extreme events
Data-driven and AI approaches to forecasting extremes and impacts
Predictability and forecasting of the impacts of extreme events, particularly in the context of informing early warning systems
Attribution of extreme event impacts, losses etc.
Applications of attribution techniques e.g. climate litigation
Weather and climate extremes often have large impacts, so it is critical that we better understand these events, improve their prediction, and gain knowledge of how and why they are changing as the planet warms. This session aims to bring together physics-based and data-driven approaches to the study of extremes and their impacts. Studies focusing on either hazards associated with extremes or directly on societal impacts (including health, insurance, energy, and other sectors) are welcome. A particular goal of this session is to explore novel approaches to the predictability of extremes, and facilitate a deeper understanding of their impacts in our changing climate. We particularly encourage submissions from early career scientists and underrepresented groups.
Topics of interest include but are not limited to:
Predictability of extremes, especially from forecasting and applied viewpoints.
Attribution of extreme events
Data-driven and AI approaches to forecasting extremes and impacts
Predictability and forecasting of the impacts of extreme events, particularly in the context of informing early warning systems
Attribution of extreme event impacts, losses etc.
Applications of attribution techniques e.g. climate litigation