In radiation belt physics radial distance is often thought of by L*, which approximates the distance from the Earth’s centre to an equatorial point (if we were to assume a dipole magnetic field). Global magnetic field models allow a subset of locations on the ground to be mapped along field lines to a location in space and transformed into L*, provided that 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 modelling. In current modelling efforts a decision must therefore be made for the global magnetic field model to implement. 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* is an extensive dataset comprising 11 years worth of hourly L* values for 7 global magnetic field models, spanning a high resolution grid in the Northern Hemisphere where ground instruments for radiation belt studies are mostly located. Accompanying each L* approximation, the McIlwain L, magnetic field amplitude and Cartesian location are also stored. Data was generated using the International Radiation Belt Environment Modelling
library (IRBEM-Lib), a collection of FORTRAN 77 processes for radiation belt modelling which compute magnetic coordinates and drift shells using various external magnetic field models, hosted in the Python package Spacepy. The data is formatted in yearly compressed csv files, with each row a particular hour containing all of the mentioned variables for each magnetic field model, the corresponding grid points’ magnetic latitude, magnetic longitude, and magnetic local time (MLT). Therefore, each hour index appears for each grid point.