Extreme weather and climate events such as heat waves, floods, tornadoes, hurricanes, droughts, and wildfires can have disastrous impacts on society. Changing climate, population, and development patterns may enhance the risks these extreme events pose to society in many regions globally. A non-analog future may make it increasingly difficult to use historical observations and conventional statistical approaches to assess the future probability of extreme events and their associated risks to society. More complete risk assessment frameworks are required. This session focuses on research that addresses the challenges of climate-informed risk assessment. We invite work that uses a novel assessment framework including, but not limited to, uses of state-of-the-art climate models, machine learning, and new data, for understanding and assessing changes in the extreme event characteristics and their effects on physical risks and impacts across social and economic components of society.

Chia-Ying Lee is the primary convener of NH44B: Climate-Informed Risk Assessment for Extreme Events.