Voyager 2 solar plasma and magnetic field spectral analysis for intermediate data sparsity. Issue 5 (31st May 2016)

• Record Type: Journal Article
• Authors: Gallana, Luca; Fraternale, Federico; Iovieno, Michele; Fosson, Sophie M.; Magli, Enrico; Opher, Merav; Richardson, John D.; Tordella, Daniela
• Is Part Of: Journal of geophysical research. Volume 121:Issue 5(2016:May)
• Page Start: 3905
• Page End: 3919
• Publication Date: 2016-05-31
• Subjects: solar wind -- data sparsity -- missing data spectral recovery -- spectral analysis; Magnetospheric physics -- Periodicals; Space environment -- Periodicals; Cosmic physics -- Periodicals; Planets -- Atmospheres -- Periodicals; Heliosphere (Astrophysics) -- Periodicals; Geophysics -- Periodicals; 523.01
• DOI: 10.1002/2015JA021830
• Languages: English
• ISSNs: 2169-9380

Abstract

Abstract: The Voyager probes are the furthest, still active, spacecraft ever launched from Earth. During their 38 year trip, they have collected data regarding solar wind properties (such as the plasma velocity and magnetic field intensity). Unfortunately, a complete time evolution of the measured physical quantities is not available. The time series contains many gaps which increase in frequency and duration at larger distances. The aim of this work is to perform a spectral and statistical analysis of the solar wind plasma velocity and magnetic field using Voyager 2 data measured in 1979, when the gap density is between the 30% and 50%. For these gap densities, we show the spectra of gapped signals inherit the characteristics of the data gaps. In particular, the algebraic decay of the intermediate frequency range is underestimated and discrete peaks result not from the underlaying data but from the gap sequence. This analysis is achieved using five different data treatment techniques coming from the multidisciplinary context: averages on linearly interpolated subsets, correlation without data interpolation, correlation of linearly interpolated data, maximum likelihood data reconstruction, and compressed sensing spectral estimation. With five frequency decades, the spectra we obtained have the largest frequency range ever computed at five astronomical units from the Sun; spectral exponents have been determined for all the components of the velocity and magnetic field fluctuations. Void analysis is also useful in recovering other spectral properties such as micro and integral scales. Key Points: Solar wind data voids treatment Enhanced fluctuation power spectral analysis Over five decades of frequency recovery spectral range