Empirical probability model of the cold plasma environment in Jovian inner magnetosphere

TL;DR

This paper presents an empirical probabilistic model of cold plasma in Jupiter's inner magnetosphere, predicting plasma parameters at specified percentiles to aid mission analysis.

Contribution

It introduces a novel probabilistic model that predicts plasma parameters based on spacecraft location and desired percentile, improving upon mean state models.

Findings

Model accurately predicts plasma parameters at different percentiles.

Model incorporates variability in plasma environment.

Designed for JUICE mission analysis.

Abstract

A new empirical, analytical model of cold plasma (< 10 keV) in the Jovian inner magnetosphere is constructed. Plasmas in this energy range impact surface charging. A new feature of this model is predicting each plasma parameter for a specified probability (percentile). The new model was produced as follows. We start from a reference model for each plasma parameter, which was scaled to fit the data of Galileo plasma spectrometer. The scaled model was then represented as a function of radial distance, magnetic local time, and magnetic latitude, presumably describing the mean states. Then, the deviation of the observed values from the model were attribute to the variability in the environment, which was accounted for by the percentile at a given location.The input parameters for this model are the spacecraft position and the percentile. The model is inteded to be used for the JUICE mission analysis.