Entropic and Informational Interpretation of SuperDARN Ionospheric Data within the ZIP Framework

This work presents an application of the ZIP Framework to publicly available SuperDARN ionospheric radar data. The ZIP Framework introduces an entropic and informational perspective on physical fields, treating entropy as a measurable structural property rather than as mere statistical disorder. In this contribution, standard radar-derived plasma velocity data are analyzed using information-theoretic diagnostics, including entropy evolution, entropic flow, and a structural index. The purpose of this work is not to revise or challenge the original physical interpretation of the SuperDARN dataset, nor to replace established magnetohydrodynamic (MHD) descriptions. Instead, it demonstrates that the same observational data carry an additional, complementary layer of informational structure that can be quantified independently of energy-based variables. All data used in this analysis are publicly available, and the methodology is fully reproducible. This work is intended as a companion application illustrating how the ZIP Framework may serve as an auxiliary diagnostic tool for complex physical systems characterized by turbulence and multiscale dynamics.