This dataset is the MLT-averaged plasmapause position calculated for the NSF GEM Challenge Events. We use the recently developed Plasma density in the Inner magnetosphere Neural network-based Empirical (PINE) model [Zhelavskaya et al., 2017]. The PINE density model was developed using neural networks and was trained on the electron density data set from the Van Allen Probes Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) [Kletzing et al., 2013].

The model reconstructs the plasmasphere dynamics well (with a cross-correlation of ~0.95 on the test set), and its global reconstructions of plasma density are in good agreement with the IMAGE EUV images of the global distribution of He+. We compare the electron number density value given by the PINE model with the density threshold separating plasmaspheric-like and trough-like density given by [Sheeley et al., 2001] and get the plasmapause position in each MLT. Then, we calculate the MLT-averaged plasmapause position. The. time resolution is 1 hour.

These data files presenting the Magnetic Local Time (MLT)-averaged plasmapause position used in the simulations in Wang et al [2020]. The data are presented as the following three tabular ASCII files (.dat) :

Lpp_PINE_Sheely_Mean_Mar15_Mar20.dat: content, column1 time [day], column 2 L [Re (Earth Radii)]
Lpp_PINE_Sheely_Mean_May30_Jun02.dat: content, column1 time [day], column 2 L [Re (Earth Radii)]
Lpp_PINE_Sheely_Mean_Sep17_Sep26.dat: content, column1 time [day], column 2 L [Re (Earth Radii)]