Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
CL2.6 | Attributing observed changes and events in natural, managed, and human systems to climate change
Attributing observed changes and events in natural, managed, and human systems to climate change
Convener: Sabine Undorf | Co-conveners: Veronika Huber, Matthias Mengel, Lukas Gudmundsson, Sihan LiECSECS
Impact attribution aims to identify and quantify climate change as a driver of observed changes in natural, managed, or human systems. As an emerging field of science, attribution of climate change impacts extends and transfers the concept of attribution from evaluating links between observed changes in weather/climate and anthropogenic climate forcing factors (such as increasing greenhouse gas concentrations), to ensuing changes in natural, managed, and human systems. Given the importance of non-climatic human influences on many of these systems, novel approaches are required to single out the imprint of (anthropogenic) climate change. This session addresses progress in the attribution of observed changes or events in systems affected by climate and weather. Such systems include but are by no means limited to ecosystems, water, agriculture, health, or economics. This hence goes beyond the attribution of purely physical phenomena. The session aims to explore the diversity of methods employed across disciplines and schools of thought.

We welcome studies that address questions such as “(How much) has climate change contributed to changes in crop yields over time?" or "(How much) has climate change influenced the magnitude or frequency of flooding or landslide events?”. Contributions that evaluate all steps of the climate-impact chain are considered relevant. An example would be the attribution of an observed socio-economic impact (e.g., food price) via changes in the biophysical system (e.g., agricultural drought) to greenhouse gas-forcing of the climate system, using counterfactual model data such as from CMIP, SMILEs, or weather@home. Equally relevant are studies that focus on significant steps along the climate-impact chain, such as attributing an observed biophysical impact (e.g., species migration) to observed climate change, using counterfactual climate data derived from the observational record like in ISIMIP3a.