Macroscopic characterization of data sets by using the average absolute deviation

This paper describes a method for getting a synthesis of the knowledge about a given system, assuming that a data set x of measurements of a variable Ξ is known: i.e., separate data are combined in order to form a coherent whole, à la thermodynamics. For getting the macroscopic characterization of time series data, one takes advantage of the average absolute deviation concept together with an already known thermodynamic-like approach. thod is applied to the macroscopic characterization of existing time series for the Vostok Antarctica ice cores (deuterium content of the ice and temperature variation) for a depth range between 0 and 3,310 meters, and the age of the ice between 0 and 422,766 years before the present.