• 14:30 - Valerio Lucarini (University of Leicester)

  Titolo: Detecting and Attributing Change in Climate and Complex Systems: Foundations, Green's Functions, and Nonlinear Fingerprints

  Abstract: Detection and attribution (D&A) studies are cornerstones of climate science, providing crucial evidence for policy decisions. Their goal is to link observed climate change patterns to anthropogenic and natural drivers via the optimal fingerprinting method (OFM). We show that response theory for nonequilibrium systems offers the physical and dynamical basis for OFM, including the concept of causality used for attribution. Our framework clarifies the method's assumptions, advantages, and potential weaknesses. We use our theory to perform D&A for prototypical climate change experiments performed on an energy balance model and on a low-resolution coupled climate model. We also explain the underpinnings of degenerate fingerprinting, which offers early warning indicators for tipping points. Finally, we extend the OFM to the nonlinear response regime. Our analysis shows that OFM has broad applicability across diverse stochastic systems influenced by time-dependent forcings, with potential relevance to ecosystems, quantitative social sciences, and finance, among others.

• 15:20 - Discussione

• 15:30 - Gianmarco Del Sarto (Technische Universität Darmstadt)

  
  Titolo: Some Perspective on Climate Change through Energy Balance Models

  
  Abstract:  In this seminar, I will present how Energy Balance Models (EBMs) can be used to explore climate change dynamics. The first part focuses on ongoing research that investigates a fast-slow system where solar radiation acts as the fast component, while a zero-dimensional EBM describes the slow component. This model exhibits mathematical parallels with the seminal stochastic EBM inspired by Hasselmann's proposal, and we explore these similarities in terms of deterministic limits, fluctuations, and large deviations. In the second part, if time allows, I will discuss a completed research project that extends the analysis of 1D EBMs by introducing local instability effects and additive white noise. The model captures the super-greenhouse effect, a tropical feedback mechanism, and incorporates fast weather fluctuations as white noise. By studying the long-term behaviour of the model's invariant measure, we investigate the link between increased greenhouse gas concentrations and extreme weather events.

• 16:20 - Discussione

• 16:3 - Tavola Rotonda moderata da Piermarco Cannarsa 

  
  

Speriamo di vedervi numerosi, sia in presenza che online!

Saluti,

Marta Leocata (a nome del gruppo Climath)