Interdisciplinary Approaches in the Study of Climate Extremes

Climate extremes, including heatwaves, extreme precipitation, tropical cyclones, and related hazards, pose significant risks to society and ecosystems.
Recent advancements in observational techniques, numerical modeling, theoretical frameworks, and AI methods have greatly improved our understanding and prediction of these extremes. However, despite significant progress, key challenges remain unresolved, particularly in achieving a thorough understanding of the physical drivers of extreme events, improving the transparency of AI-based prediction methods, and evaluating the vulnerability and resilience of cities to their impacts. To address these challenges, we present various approaches drawn from different fields, including dynamical systems theory, explainable AI, and NLP-based methods. Given the flexible and generalizable nature of these methods, we believe they may pave the way toward more robust solutions for addressing the challenges posed by climate extremes.