Stochastic field theory for the ionospheric fluctuations in Equatorial Spread F. (April 2019)

• Record Type: Journal Article
• Authors: Materassi, Massimo
• Is Part Of: Chaos, solitons and fractals. Volume 121(2019)
• Page Start: 186
• Page End: 210
• Publication Date: 2019-04
• Subjects: Non-equilibrium processes in physics -- Chemistry and geophysics (20.22, 20.03, 20.16) -- Fluctuations and random processes (70.1); Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2019.01.027
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: Definition of intrinsic "irregularity seeding" components in the equation of motion of the ionospheric fluctuations n : use of the local time derivative of electric charge density ξ = ∂ t ρ c and of the recombination rate R as noise fields. Stochastic partial derivative equation for the ionospheric flucutations, with ξ and R as noise terms. Construction of a functional formalism for the stochastic PDE for n . Calculation of the realization probability density functional for Gaussian noises ( ξ, R ) and for Gaussian ξ and exponentially distributed R . Abstract: In order to construct an analytical model of evolution for the plasma structures in the ionospheric Equatorial Spread F, an attempt is presented to include the plasma perturbations "seeding" the instabilities that cause the Equatorial Spread F in a theoretically consistent way. This is done assuming that the local discrepancies from quasi neutrality and from zero ionization-loss-and-production to be noise terms in the ionospheric density balance equation: doing so, the balance equation becomes a stochastic equation. The program is then to obain the probability that a certain evolution of the ionospheric density takes place from the interplay between plasma dynamics and noise statistics, i.e. to produce a stochastic field theory for the ionospheric density. The expression of this realization probability is obtained in the mathematically tractable cases of noises with Gaussian or exponential distribution. Then, practical limits and possible developments of these achievements are discussed.