The project concerns the study of the climate system starting with applying recently developed innovative perspectives
for nonlinear dynamical analysis of geophysical data.
The goal is to apply and interpret topological data analysis and complementary nonlinear techniques to understand and model
the fundamental processes at play in direct or indirect observations and on a large span of time scales.
In particular lessons learned from the study of the dynamics of the atmospheric flow at intra-seasonal and seasonal time-scales
will be applied to better understand current limitations in the predictability of variables related to
renewable energy production and to the development of proper strategies to quantify and reduce forecast uncertainty.
Implementing and applying novel nonlinear data analysis methods to the study of climate dynamics and variability in South America and the South Atlantic, with a particular focus on seasonal climate variability, Lagrangian transport and renewable energy production.