Abstract
The dynamical properties of time‐ and space‐averaged observables of a simplified one‐dimensional thermal convection model are explored and compared to those of the fine scale variables. It is found that averaging reduces the domain of variability of the system, favors persistence of correlations in time and space, and reduces the “effective” dimensionality of the underlying attractor. Furthermore, space and time averages display enhanced predictability, characterized by an error growth rate smaller than the one of the fine scale variables.
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