Empirical model of the near-geosynchronous magnetic field
About this model
Empirical modeling of the quiet and storm-time geosynchronous magnetic field by V. A. Andreeva and N. A. Tsyganenko
A dynamical empirical model of the near-geosynchronous magnetic field has been constructed, based on a recently developed RBF approach and a multi-year set of spacecraft data taken by THEMIS, Polar, Cluster, and Van Allen Probes missions including 133 geomagnetic storms in the time interval between 1996 and 2016. The model describes the field as a function of Cartesian solar-magnetic coordinates, dipole tilt angle, solar wind ram pressure, and of a set of dynamic variables representing the response of the magnetosphere to the external driving/loading during the active phase of a space weather event, followed by the internal relaxation/dissipation during the storm recovery. In terms of the disturbance level, the model's validity range extends to intense storms with peak Sym-H values down to -150 nT. The spatial validity domain is a toroidal volume bounded by the inner (L ~ 4) and outer (L ~ 9) dipolar L-shells, which allows the model to be used for tracing field lines to magnetically map geosynchronous spacecraft locations down to low altitudes. The model has been validated on independent out-of-sample magnetic field data and compared with an earlier empirical model and GOES-15 data taken in 2012 and 2015.
One can find detailed information about the model in this paper.
To use this model, one should also download the model parameter file and (optional) solar wind input parameter file.
Yearly input parameter files
Yearly files (1995-2016) below contain complete sets of input parameters for the near-geosynchronous RBF magnetic field model. Each file has the name 'YEAR_OMNI_5m_with_GEO_RBF_TA17_drivers.dat' and it is about 14MB. Data format is explained in this file.
Download input parameters format
How to cite
Andreeva, V. A., & Tsyganenko, N. A. (2018). Empirical modeling of the quiet and storm time geosynchronous magnetic field. Space Weather, 16, 16- 36. https://doi.org/10.1002/2017SW001684.