By Alina Bendt (CFSA, University of Warwick)
The in-situ measurements of the solar wind by Solar Orbiter provide the opportunity to study turbulence at very high Reynolds numbers in a nearly collissionless plasma. Turbulence is a potential contributor to the heating, structure, and dynamics of the solar wind. With Solar Orbiter it is now possible to study the evolution of solar wind turbulence. We use Solar Orbiter observations of nine extended intervals of homogeneous turbulence to determine under what conditions turbulent magnetic field fluctuations may be characterized as: (i) wave-packets and (ii) coherent structures. We perform the first systematic scale-by-scale decomposition of the magnetic field using two wavelets known to resolve wave-packets and discontinuities, the Daubechies 10 and Haar respectively. We compare the functional forms of the fluctuation probability distributions obtained from these wavelet decompositions via quantile-quantile plots. The comparison of the fluctuation pdfs between the two wavelets reveals three distinct regimes of behaviour and establishes a crossover range between wave-packet and coherent structure phenomenology in the inertial and kinetic ranges. The crossover range is seen to exhibit a distinct 2-component functional form. And the behaviour of the crossover range depends on the heliocentric distance and field alignment angle. As coherent structures and wave-wave interactions are both candidates to mediate the turbulent cascade, these results offer new insights into the distinct physics of the inertial and kinetic ranges.
Probability distribution functions (pdfs) comparison between Haar and Db10 wavelet
decompositions of the magnetic field. Pdfs are shown for Bperp(Vsw ⋅ B)} for four
example intervals (rows). The chosen intervals (top down) are at 0.989 au with β=0.95
and θ=18.07°, at 0.934 au with β=2.08 and θ=160.93°, at 0.597 au with β=2.48 and θ=68.63°,
and at 0.37 au with β=0.76 and θ=16.82°. The scales shown are increasing from left to right
at 0.25, 0.5, 2 and 8 s. Empty purple circles are obtained from the Db10 wavelet decomposition,
while green circles are from the Db10 wavelet decomposition. The pdfs are normalised by bin
width and overall number of samples of magnetic field data. The number of bins is scaled by
the standard deviation σ at the corresponding scale and bins with less than 10 counts are
discarded. The error is estimated as √n, where ν is the bin count, error bars are too small to
be resolved visually.
See publication for further information:
Bendt, A., Chapman, S. C., Dudok de Wit, T. (2024). The relative prevalence of wave packets and coherent structures in the inertial and kinetic ranges of turbulence as seen by Solar Orbiter. The Astrophysical Journal, 971:179.
https://iopscience.iop.org/article/10.3847/1538-4357/ad54bc
By Sarah Glauert (British Antartic Survey)
Pitch angle distributions (PADs) are widely used in radiation belt modelling, for example, to create boundary conditions, to map observations from low to high equatorial pitch angles and to calculate phase-space density from observations. In the SWIMMR Sat-Risk project we needed them to map observations made at higher latitudes to the equator. As we couldn’t find a comprehensive enough model in the literature, we developed our own. The technique we used to derive the PADs also provides a loss timescale (used in radial diffusion models), so we also obtained a model for loss timescales. The new models are calculated from drift-averaged diffusion coefficients that represent all the VLF waves that typically interact with radiation belt electrons and cover 2 ≤L*≤7, 100 keV ≤ E ≤ 5 MeV and all levels of geomagnetic activity defined by the Kp index. They show good agreement with observations and the contribution of individual waves is demonstrated: magnetosonic waves have little effect on loss timescales when lightning-generated whistlers are present and chorus waves contribute to loss even in low levels of geomagnetic activity. The shape of the PADs depends on the dominant waves. When chorus is dominant the PADs have little activity dependence, unlike the corresponding loss timescales. Distributions peaked near 90o are formed by plasmaspheric hiss for L*≤3 and E < 1 MeV, and by EMIC waves for L*> 3 and E >1 MeV. When hiss dominates, increasing activity broadens the distribution but when EMIC waves dominate increasing activity narrows the distribution.
Normalised, drift-averaged pitch angle distributions for the given L* and energies.
Purple lines show PADs for 1 ≤Kp< 2, cyan for 3 ≤Kp< 4 and yellow for 5 ≤Kp< 6. The dotted lines
are distributions derived from observations in Allison et al. (2018) for 0 ≤ Kp < 2 (purple),
2 ≤ Kp ≤ 4 (cyan) and Kp> 4 (yellow).
See publication for further information:
Glauert, S. A., Atkinson, J. W., Ross, J. P., & Horne, R. B. (2024). A new model of electron pitch angle distributions and loss timescales in the Earth's radiation belts. Journal of Geophysical Research: Space Physics, 129, e2023JA032249.
https://doi.org/10.1029/2023JA032249