Relative contribution of the magnetic field barrier and solar wind speed in ICME-associated Forbush decreases
arXiv:1605.09537 · doi:10.3847/0004-637X/828/2/104
Abstract
We study 50 cosmic ray Forbush decreases (FDs) from the Oulu neutron monitor data during 1997-2005 that were associated with Earth-directed interplanetary coronal mass ejections (ICMEs). Such events are generally thought to arise due to the shielding of cosmic rays by a propagating diffusive barrier. The main processes at work are the diffusion of cosmic rays across the large-scale magnetic fields carried by the ICME and their advection by the solar wind. In an attempt to better understand the relative importance of these effects, we analyse the relationship between the FD profiles and those of the interplanetary magnetic field (B) and the solar wind speed (Vsw). Over the entire duration of a given FD, we find that the FD profile is generally well (anti)correlated with the B and Vsw profiles. This trend holds separately for the FD main and recovery phases too. For the recovery phases, however, the FD profile is highly anti-correlated with the Vsw profile, but not with the B profile. While the total duration of the FD profile is similar to that of the Vsw profile, it is significantly longer than that of the B profile.
19 pages, 5 figures, 2 tables, Accepted for publication in ApJ
References in corpus (4)
- Forbush decreases and turbulence levels at CME fronts
- Self-similar expansion of solar coronal mass ejections: implications for Lorentz self-force driving
- Solar Modulation of Cosmic Rays during the Declining and Minimum Phases of Solar Cycle 23: Comparison with Past Three Solar Cycles
- Understanding Forbush decrease drivers based on shock-only and CME-only models using global signature of February 14, 1978 event
Cited by in corpus (3)
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