In the analysis of dynamical systems, the correlation dimension is a useful indicator describing the fractal structure of invariant sets. Other measures, such as the Lyapunov exponents and the entropy, provide complementary information on the time scale of predictability of the system.
Computational models employed for simulations of weather and climate have limited spatial resolution, currently around 2 km for regional weather models and 100 km for global climate models.
Davide was given the award for “his exceptional contributions to developing the theory of extreme values for dynamical systems and its use for analysing the underlying properties of the dynamics of the atmosphere and the climate system.”
Solar radiation and the earth’s rotation are the primary drivers of large-scale atmospheric motions, while turbulence adds a layer of complexity at small scales. This picture is further complicated by ocean–land interactions, vegetation, anthropocentric forcing, and the hydrological cycle.
Extreme, high-impact weather events have serious social and economic consequences, and have garnered widespread scientific and media attention. Understanding their drivers and improving their prediction is therefore a topic of crucial societal and economic value, where the interests of academia, policy makers and private stakeholders converge.
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