posted on 2019-06-14, 12:38authored byS. J. Wharton, D. M. Wright, T. K. Yeoman, A. S. Reimer
The eigenfrequencies of standing Alfvén waves on closed magnetospheric field lines can be estimated using the cross-phase technique. These eigenfrequencies can be used to monitor the plasma mass density distribution along the field line. So far, this has only been applied to ground-based magnetometer data. The Super Dual Auroral Radar Network (SuperDARN) radars offer some benefits over magnetometers. They provide greater spatial resolution and coverage, as well as direct sensing above the E region ionosphere, which screens ultralow frequency (ULF) waves from the ground. However, there are significant data quality issues. These include the uncertain origin of radar backscatter, uneven sampling of data due to data gaps, and inaccurate fitting to the autocorrelation functions. Artificial backscatter from an ionospheric heater has been used to remove the uncertainty in backscatter location. We have developed a Lomb-Scargle cross-phase analysis for application to discontinuous radar data. The First Principles Fitting Methodology has been used to improve the fitted data products derived from the autocorrelation functions. Using these techniques, we have shown that it is possible to measure eigenfrequencies with SuperDARN data, and we have verified an example using ground-based magnetometer data. Finally, we have demonstrated that the eigenfrequency signature in this example was caused by a broadband source of energy.
Funding
S. J. W. was supported by NERC Studentship NE/L002493/1. T. K. Y. was supported by STFC Grant ST/H002480/1 and NERC Grant NE/K011766/1. The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by the national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, the United Kingdom, and the United States. The authors would also like to thank the IMAGE magnetometer team for providing the data. This research used the SPECTRE High Performance Computing Facility at the University of Leicester.
History
Citation
Journal of Geophysical Research: Space Physics, 2019, 124(2) pp. 996-1012
Author affiliation
/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Physics and Astronomy
The rawacf data files can be found at http://vt.superdarn.org/. The data are available at http://space.fmi.fi/image/beta/. The OMNI solar wind data are publicly available from the NASA Space Physics Data Facility, Goddard Space Flight Center (http://omniweb.gsfc.nasa.gov/ow.html). The LMFIT2 software can be found at https://github.com/asreimer/lmfit2.