The principal manner in which global climate change likely affects societies around the world is through changes in high-impact weather, such as weather extremes and changes in local climate.
This vulnerability of society calls for a realistic local representation of specific synoptic (extreme) weather events under projected future climate conditions to provide relevant information for policy- and decision makers.
This project explores and implements an approach which uses a new data assimilation technique to investigate the impact of climate warming on the manifestation of specific synoptic weather patterns. As such, specific observed weather events may be transposed into a future warmer climate in a dynamically consistent manner leaving the synoptic scale variability free to adapt over time to the large-scale circulation.
This allows us to answer the question “How exactly do observed present-day weather extremes manifest themselves under global climate change?”
This method provides an efficient means to aid policy- and decision makers both in mitigation and in adaptation strategies and to communicate the impact of climate warming to the popular audience.