Dynamical critical scaling of electric field fluctuations in the greater cusp and magnetotail implied by HF radar observations of F-region Doppler velocity

Abstract

Abstract. Akasofu's solar wind ε parameter describes the coupling of solar wind energy to the magnetosphere and ionosphere. Analysis of fluctuations in ε using model independent scaling techniques including the peaks of probability density functions (PDFs) and generalised structure function (GSF) analysis show the fluctuations were self-affine (mono-fractal, single exponent scaling) over 9 octaves of time scale from ∼46 s to ∼9.1 h. However, the peak scaling exponent α 0 was a function of the fluctuation bin size, so caution is required when comparing the exponents for different data sets sampled in different ways. The same generic scaling techniques revealed the organisation and functional form of concurrent fluctuations in azimuthal magnetospheric electric fields implied by SuperDARN HF radar measurements of line-of-sight Doppler velocity, v LOS , made in the high-latitude austral ionosphere. The PDFs of v LOS fluctuation were calculated for time scales between 1 min and 256 min, and were sorted into noon sector results obtained with the Halley radar, and midnight sector results obtained with the TIGER radar. The PDFs were further sorted according to the orientation of the interplanetary magnetic field, as well as ionospheric regions of high and low Doppler spectral width. High spectral widths tend to occur at higher latitude, mostly on open field lines but also on closed field lines just equatorward of the open-closed boundary, whereas low spectral widths are concentrated on closed field lines deeper inside the magnetosphere. The v LOS fluctuations were most self-affine (i.e. like the solar wind ε parameter) on the high spectral width field lines in the noon sector ionosphere (i.e. the greater cusp), but suggested multi-fractal behaviour on closed field lines in the midnight sector (i.e. the central plasma sheet). Long tails in the PDFs imply that "microbursts" in ionospheric convection occur far more frequently, especially on open field lines, than can be captured

A decade of the Super Dual Auroral Radar Network (SuperDARN): scientific achievements, new techniques and future directions

“…One area where large-scale statistical analysis may have a large impact in the future is in the emerging area of complexity science. Indeed, initial studies have already been made, studying the temporal (Parkinson 2006) and spatial (Abel et al 2006) scaling of ionospheric convection velocities measured by SuperDARN, and finding evidence for scale-free structure of velocity fluctuations. Future studies of this type will address the complex structure of SuperDARN data products such as convection vorticity and reconnection rate measurements.…”

Investigating turbulent structure of ionospheric plasma velocity using the Halley SuperDARN radar

“…a measure of fluctuations with no characteristic scales (power law), over a wide range of scales. Examples include (a) power spectra of ground magnetic fields (Cambell, 1976;Francia et al, 1995;Consolini et al, 1998;Weatherwax et al, 2000;Abel and Freeman, 2002), and ionospheric electric fields (Kintner, 1976;Weimer et al, 1985;Bering et al, 1995;Buchert et al, 1999;Abel and Freeman, 2002;Golovchanskaya et al, 2006), (b) probability density functions (PDFs) of durations between threshold crossings of the auroral electrojet indices AU and AL (Freeman et al, 2000), (c) PDFs of durations, areas, and other quantities of auroral bright patches (Lui et al, 2000;Uritsky et al, 2002;Kozelov et al, 2004) and (d) structure functions of the auroral electrojet indices AU, AL and AE, the polar cap index PC (Takalo et al, 1993;Takalo and Timonen, 1998;Hnat et al, 2002), ground magnetic fields (Pulkkinen et al, 2006) and ionospheric convection (Parkinson, 2006;Abel et al, 2006).…”

Complexity in the high latitude HF radar spectral width boundary region

“…The idea was to establish a data base of relatively continuous 1-s resolution data to help define the fractal qualities of the velocity fluctuations observed above and below the SWB. Here fluctuation in the location of the SWB itself are analysed using peak scaling and generalised structure function (GSF) analysis, as described by Hnat et al (2002aHnat et al ( , b, 2003Hnat et al ( , 2005, , and Parkinson (2006a). These analyses provide a comprehensive decomposition of the statistical characteristics of fluctuating data.…”

“…Golovchanskaya (2007) postulated the source regions of turbulence are not necessarily magnetically conjugate in the magnetotail. Parkinson (2006a) and Able et al (2006) performed generalised structure analysis (GSF) of HF radar velocity fluctuations and identified approximately scale-free regimes, often taken as evidence for a turbulent cascade.…”