Predicting and Fingerprinting Climate Change using Linear Response Theory

Response theory (RT) for nonequilibrium systems provides powerful tools for understanding the link between climate variability and climate change, for performing climate change projections and for understanding the fundamental properties of tipping points. We will recapitulate the theoretical basis of the theory as well as some case studies in climate models of different level of complexity. We will also show how RT provides a useful angle for better framing some key fundamental issues associated with geoengineering strategies. Finally, we will present recent results suggesting that RT provides the physical and mathematical foundations behind optimal fingerprinting methods for climate change detection and attribution (D&A). D&A studies have played a major role in shaping contemporary climate science and have provided key motivations supporting global climate policy negotiations. Such studies have shown how to associate observed climatic patterns of climate change with acting forcings - both anthropogenic and natural ones - with the goal of making statements on the acting drivers of climate change. D&A techniques are based on the concept of Pearl causality: one investigates the changes in a system following the adoption of alternative courses of action. Our angle allows one to clearly frame assumptions, strengths and potential pitfalls of optimal fingerprinting methods. The take-home message is that, by and large, detection and attribution is based upon a solid framework but one should re-examine classical notions of natural variability by considering the concept of snapshot/pullback attractor.&nbsp
The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)