The climate system is a dissipative, nonlinear, complex and heterogeneous system that exhibits natural variability on many scales of motion, in time as well as space, and that is subject to both natural and anthropogenic external forcings. The theory of nonlinear dynamical systems provides a powerful way of considering nonlinear systems of equations that govern geophysical and other flows and phenomena, from biology to society. Low-order models in climate dynamics are highly desirable, since they can provide insight about dynamic interactions between different components of the climate system at a much lower computational cost than those required from high-resolution numerical simulations. These simple models can be used to understand the development of large scale anomalies in atmospheric circulation in the Southern hemisphere and also contribute to understanding their predictability at seasonal scales for concrete applications such as renewable energy productions. The possibility of improving our current understanding of noise-driven systems with the new tools will also be considered.