Correlation based modeling of the ionospheric magnetic field

TL;DR

This paper develops a correlation-based statistical model of the ionospheric magnetic field using satellite data, representing the fields in solar coordinates, and demonstrates its ability to reconstruct surface observations with high accuracy.

Contribution

It introduces a novel correlation-based modeling approach for ionospheric magnetic fields that incorporates solar coordinate representation and covariance analysis.

Findings

Accurately reconstructs ionospheric field patterns from synthetic data.

Demonstrates successful application to real observatory data.

Provides a new statistical framework for ionospheric magnetic field modeling.

Abstract

Patterns of the magnetic signature of ionospheric currents, generated from an empirical model based on satellite observations, are used to build a statistical correlation based model for ionospheric fields. In order to stabilize the dynamics and to take into account the dominant role of the sun, the fields are represented in solar magnetic coordinates. The covariance structure is analyzed and a second order process that approximates the full dynamics is generated. We show that for synthetic data observations located at the Earth observatories, the full ionospheric field pattern as observed on the earth surface can be reconstructed with good precision. As a proof of principle we provide a first application to the inversion based on real observatory data.