Complexity in the scaling of velocity fluctuations in the high-latitude F-region ionosphere

Abstract

Abstract. The temporal scaling properties of F-region velocity fluctuations, δv los , were characterised over 17 octaves of temporal scale from τ =1 s to <1 day using a new data base of 1-s time resolution SuperDARN radar measurements. After quality control, 2.9 (1.9) million fluctuations were recorded during 31.5 (40.4) days of discretionary mode soundings using the Tasmanian (New Zealand) radars. If the fluctuations were statistically self-similar, the probability density functions (PDFs) of δv los would collapse onto the same PDF using the scaling P s (δv s , τ )=τ α P (δv los , τ ) and δv s =δv los τ −α where α is the scaling exponent. The variations in scaling exponents α and multi-fractal behaviour were estimated using peak scaling and generalised structure function (GSF) analyses, and a new method based upon minimising the differences between re-scaled probability density functions (PDFs). The efficiency of this method enabled calculation of "α spectra", the temporal spectra of scaling exponents from τ =1 s to ∼2048 s. The large number of samples enabled calculation of α spectra for data separated into 2-h bins of MLT as well as two main physical regimes: Population A echoes with Doppler spectral width <75 m s −1 concentrated on closed field lines, and Population B echoes with spectral width >150 m s −1 concentrated on open field lines. For all data there was a scaling break at τ ∼10 s and the similarity of the fluctuations beneath this scale may be related to the large spatial averaging (∼100 km×45 km) employed by SuperDARN radars. For Tasmania Population B, the velocity fluctuations exhibited approximately mono fractal power law scaling between τ ∼8 s and 2048 s (34 min), and probably up to several hours. The scaling exponents were generally less than that expected for basic MHD turbulence (α=0.25), except close to magnetic dusk where they peaked towards the basic MHD value. For Population A, the scaling exponents were larger than for Population B, having values generally Correspondence to: M. L. Parkinson (m.parkinson@latrobe.edu.au) in the range expected for basic MHD and Kolmogorov turbulence (α=0.25-0.33). The α spectra exhibited complicated variations with MLT and τ which must be related to different physical processes exerting more or less influence.

Collective dynamics of bursty particle precipitation initiating in the inner and outer plasma sheet

“…Several recent publications focused on the electric field fluctuations in the same region (Abel et al, 2006(Abel et al, , 2007Parkinson, 2006Parkinson, , 2008. Although the scaling exponents reported in these papers describe a different aspect of auroral complexity, they can be reconciled with our analysis assuming that the electric field and the emission intensity fluctuations are generated by the same physical phenomenon.…”

“…The spatial and temporal electric field scaling exponents reported by Abel et al (2006) and Parkinson (2006) for the auroral region equatorward of the open-closed boundary relate to each other as 0.39/0.21≈1.86. In the monofractal approximation (Parkinson, 2008), this ratio should be equal to z, and the scaling relation given above should hold. Using the estimates of z given above, one can conjecture that the correlation structure of the auroral electric field fluctuations is largely controlled by the A 2 mode of bursty CPS dynamics, which is consistent with the dominating energy contribution of this mode.…”

Spatial distribution of average vorticity in the high‐latitude ionosphere and its variation with interplanetary magnetic field direction and season

“…To investigate to what extent the average values of vorticity that are presented in maps of FAC and vorticity are actually a good representation of the “typical” values in these regions. Previous large statistical studies of ionospheric velocity fluctuations [ Abel et al , 2007; Parkinson , 2008] have shown that the distribution of velocity fluctuations (in both time and space) is distinctly non‐Gaussian, with heavy tails.…”

Statistical maps of small‐scale electric field variability in the high‐latitude ionosphere

“…The statistical properties of small‐scale electric field or velocity variability have been investigated using data from the Dynamics Explorer (DE) 2 low‐altitude satellite [ Heppner et al , 1993; Golovchanskaya et al , 2002; Johnson and Heelis , 2005; Golovchanskaya et al , 2006; Golovchanskaya , 2007; Matsuo and Richmond , 2008] and from ground‐based coherent backscatter radars [ Abel et al , 2007, 2009; Parkinson , 2008; Cousins and Shepherd , 2012]. In these studies, the observed variability is found to depend on scale size, on season or dipole tilt angle, on gradients or shears in the background plasma drift and on location in geomagnetic coordinates.…”