Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations

Thompson, Rhys L., Morley, Steven K., Watt, Clare, Bentley, Sarah and Williams, Paul D. (2021) Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations. Space Weather, 19 (2). e2020SW002602. ISSN 1542-7390

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Official URL: https://doi.org/10.1029/2020SW002602

Abstract

Both ground and space observations are used extensively in the modeling of space weather processes within the Earth’s magnetosphere. In radiation belt physics modeling, one of the key phase‐space coordinates is L*, which indicates the location of the drift paths of energetic electrons. Global magnetic field models allow a subset of locations on the ground (mainly subauroral) to be mapped along field lines to a location in space and transformed into L*, provided that the initial ground location maps to a closed drift path. This allows observations from ground, or low‐altitude space‐based platforms to be mapped into space in order to inform radiation belt modeling. Many data‐based magnetic field models exist; however, these models can significantly disagree on mapped L* values for a single point on the ground, during both quiet times and storms. We present a state of the art probabilistic L* mapping tool, Pro‐L*, which produces probability distributions for L* corresponding to a given ground location. Pro‐L* has been calculated for a high resolution magnetic latitude by magnetic local time grid in the Earth’s Northern Hemisphere. We have developed the probabilistic model using 11 years of L* calculations for seven widely used magnetic field models. Usage of the tool is highlighted for both event studies and statistical models, and we demonstrate a number of potential applications.

Item Type: Article
Uncontrolled Keywords: adiabatic invariants, CARISMA, ground magnetometers, IMAGE, stochastic modeling, SuperMAG
Subjects: F500 Astronomy
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 07 May 2021 14:22
Last Modified: 31 May 2021 14:38
URI: http://nrl.northumbria.ac.uk/id/eprint/46117

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