Stochastic Methods and Complexity Science in Climate Research and Modeling

Abstract

The 2021 Nobel prize for physics was awarded to two climate scientists, Syukuro Manabe and Klaus Hasselmann, and the physicist Giorgio Parisi. While at first sight the work of Parisi seems not to be related to climate science, this is not the case. Giorgio Parisi developed and contributed to many complexity science methods which are nowadays widely used in climate science. Giorgi Parisi also was involved in the development of the “stochastic resonance” idea to explain paleoclimate variability, while Klaus Hasselmann developed stochastic climate models. Here we review and discuss their work from a complex and stochastic systems perspective in order to highlight those aspects of their work. For instance, fractal and multi-fractal analysis of climate data is now widely used and many weather prediction and climate models contain stochastic parameterizations, topics Parisi and Hasselmann have pioneered. Furthermore, Manabe’s work was key to understanding the effects of anthropogenic climate change by the development of key advances in the parameterization of convection and radiative forcing in climate models. We discuss also how their inventive research has shaped current climate research and is still influencing climate modeling and future research directions.