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2014 
We expanded our previous work on L* neural networks that used empirical magnetic field models as the underlying models by applying and extending our technique to drift shells calculated from a physicsbased magnetic field model. While empirical magnetic field models represent an average, statistical magnetospheric state, the RAMSCB model, a firstprinciples magnetically selfconsistent code, computes magnetic fields based on fundamental equations of plasma physics. Unlike the previous L* neural networks that include McIlwain L and mirror point magnetic field as part of the inputs, the new L* neural network only requires solar wind conditions and the Dst index, allowing for an easier preparation of input parameters. This new neural network is compared against those previously trained networks and validated by the tracing method in the International Radiation Belt Environment Modeling (IRBEM) library. The accuracy of all L* neural networks with different underlying magnetic field models is evaluated by applying the electron phase space density (PSD)matching technique derived from the Liouville\textquoterights theorem to the Van Allen Probes observations. Results indicate that the uncertainty in the predicted L* is statistically (75\%) below 0.7 with a median value mostly below 0.2 and the median absolute deviation around 0.15, regardless of the underlying magnetic field model. We found that such an uncertainty in the calculated L* value can shift the peak location of electron phase space density (PSD) profile by 0.2 RE radially but with its shape nearly preserved. Yu, Yiqun; Koller, Josef; Jordanova, Vania; Zaharia, Sorin; Friedel, Reinhard; Morley, Steven; Chen, Yue; Baker, Daniel; Reeves, Geoffrey; Spence, Harlan; Published by: Journal of Geophysical Research: Space Physics Published on: 03/2014 YEAR: 2014 DOI: 10.1002/jgra.v119.310.1002/2013JA019350 
2012 
1] The temporal and spatial development of the ring current is evaluated during the 23\textendash26 October 2002 highspeed stream (HSS) storm, using a kinetic ring currentatmosphere interactions model with selfconsistent magnetic field (RAMSCB). The effects of nondipolar magnetic field configuration are investigated on both ring current ion and electron dynamics. As the selfconsistent magnetic field is depressed at large (>4RE) radial distances on the nightside during the storm main phase, the particles\textquoteright drift velocities increase, the ion and electron fluxes are reduced and the ring current is confined closer to Earth. In contrast to ions, the electron fluxes increase closer to Earth and the fractional electron energy reaches \~20\% near storm peak due to better electron trapping in a nondipolar magnetic field. The ring current contribution to Dst calculated using BiotSavart integration differs little from the DPS relation except during quiet time. RAMSCB simulations underestimate SYMH minimum by \~25\% but reproduce very well the storm recovery phase. Increased anisotropies develop in the ion and electron velocity distributions in a selfconsistent magnetic field due to energy dependent drifts, losses, and dispersed injections. There is sufficient free energy to excite whistler mode chorus, electromagnetic ion cyclotron (EMIC), and magnetosonic waves in the equatorial magnetosphere. The linear growth rate of whistler mode chorus intensifies in the postmidnight to noon sector, EMIC waves are predominantly excited in the afternoon to midnight sector, and magnetosonic waves are excited over a broad MLT range both inside and outside the plasmasphere. The wave growth rates in a dipolar magnetic field have significantly smaller magnitude and spatial extent. Jordanova, V.; Welling, D.; Zaharia, S.; Chen, L.; Thorne, R.; Published by: Journal of Geophysical Research Published on: 09/2012 YEAR: 2012 DOI: 10.1029/2011JA017433 
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