Characterizing memory in atmospheric time series

Atmospheric dynamics originates persistent and/or intermittent structures spanning over several spatial and temporal scales. The dynamical instabilities trigger abrupt transitions between these meteorological structures. An approach based on the theory of renewal processes is proposed to describe these critical transition events. An alternative statistical analysis to qualitatively estimate the memory content of atmospheric time series is reviewed and an application to turbulence data in the Atmospheric Boundary Layer is illustrated. The connection between the proposed analysis and the assumption of a local flux-gradient relationship is also discussed.

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