Physics – Plasma Physics
Scientific paper
May 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006agusmsh51a..04p&link_type=abstract
American Geophysical Union, Fall Meeting 2007, abstract #SH51A-04
Physics
Plasma Physics
4475 Scaling: Spatial And Temporal (1872, 3270, 4277), 7800 Space Plasma Physics, 7839 Nonlinear Phenomena (4400, 6944), 7857 Stochastic Phenomena (3235, 3265, 4475), 7863 Turbulence (4490)
Scientific paper
In solar wind turbulence, the probability distribution functions (PDFs) of time delayed velocity differences δ vj(τ)= vj(t+τ)-vj(t) and magnetic field differences δ Bj(τ)= Bj(t+τ)-Bj(t) are not self-similar, even when the time scale τ is restricted to the inertial range of the turbulence (approximately the range extending from 10 s to 104 s). An interesting study of solar wind data by Hnat, Chapman, and Rowlands [2003] suggests that even though the PDFs for the individual vector components are not self similar, the PDFs for the mass density ρ, kinetic energy density ρ v2=ρ v· v, and magnetic energy density B2=B· B, are all self-similar in the inertial range. In an attempt to confirm this claim, a similar analysis is performed using all available data from the Wind and ACE spacecraft---data acquired in the ecliptic plane near 1 AU. The analysis utilizes the largest data sets available in order to adequately resolve the tails of the probability distributions. The results of this study indicate that: (1) The first order PDF of Δ B2(τ)= B2(t+τ)-B2(t) appears to exhibit self-similar behavior in the inertial range. (2) The first order PDFs of proton density npand kinetic energy density npv2 do not exhibit self-similar behavior in the inertial range. (3) The first order PDF of kinetic energy density measured relative to the mean flow np(v-v¯)2 appears to be self-similar in the inertial range, that is, it is self-similar to within the error bars of the measurement. Larger data sets and more precise measurements are required to further validate these results although, at the moment, Wind and ACE are the largest and highest quality solar wind data sets available. Theoretical implications of these results for solar wind modeling are also discussed.
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