Signatures of the ionospheric cusp in digital ionosonde measurements of plasma drift above Casey, Antarctica

Parkinson, M. L.; Breed, A. M.; Dyson, P. L.; Morris, R. J.

doi:10.1029/1999ja900178

Cited by 11 publications

(3 citation statements)

References 31 publications

(23 reference statements)

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“…However, measurements made on much shorter timescales suggest that there is more going on than just low‐frequency variations associated with large‐scale reorganization of the throat. Heppner et al [1993], and Matsuo et al [2003] (also see Parkinson et al [1999]), find the variability maximum in the same MLAT and MLT range that we do (between 0500 MLT and 1300 MLT, in the upper part of our observed MLAT range). These measurements involve much faster timescales than ours.…”

Section: Discussionsupporting

confidence: 83%

Parametric dependence of electric field variability in the Sondrestrom database: A linear relation with Kp

Cosgrove

Thayer

2006

J. Geophys. Res.

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[1] Motivated by the question of the auroral region contribution to thermospheric heating, the database from the Sondrestrom incoherent scatter radar is used to study the variability of the high-latitude vector electric field. The ability of various geophysical parameters to describe the variability is evaluated, using a minimum variance criterion, and it is found that the standard deviation ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffihjẼ À hẼij 2 i q scales linearly with Kp. It is also found that magnetic latitude and magnetic local time are important descriptors and that the specific dependance largely agrees with variability measurements made by the DE 2 satellite, even though the latter measurements probe a much higher frequency range. A number of other parameters are found to be less important as descriptors, including the IMF clock angle and the season. Thermospheric global circulation models currently incorporate an auroral zone heat source in the form of Joule heating associated with the mean electric field hẼi, where the mean is taken over temporal and spatial scales below the models resolution. However, comparison of the modeling outputs with MSIS suggests that the auroral zone heat source is underestimated. Because it is the mean of the squared electric field that determines Joule heating and not the square of the mean, the electric field variability ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffihjẼ À hẼij 2 i q has been put forward as the missing source. Our results indicate that this heat source may be parameterized by Kp, which carries the further implication that the variability is associated with a global-scale phenomenon.

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Section: Discussionsupporting

confidence: 83%

Parametric dependence of electric field variability in the Sondrestrom database: A linear relation with Kp

Cosgrove

Thayer

2006

J. Geophys. Res.

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“…Time series of LOS Doppler velocity, v los , measured by high-latitude SuperDARN radars are often exceptionally bursty. Digital ionosonde measurements of polar cap drift share a similar quality, especially when measurements are made in proximity to the ionospheric cusp (Parkinson et al, 1999). The presence of barely resolved flow bursts can make the time series seem amorphous.…”

Section: High-latitude Velocity Fluctuationsmentioning

confidence: 84%

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

Parkinson

2008

Ann. Geophys.

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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.

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“…Non-uniform convection flows from small (∼1 km) to large scales (∼1000 km) (Parkinson et al, 1999), micro-scale (∼10 m) plasma turbulence, and electric field variations in the Pc 1-2 frequency range, may all play a possible role in increasing the radar spectral widths. However, the large spectral widths encountered in the auroral and cusp ionosphere cannot be explained by large-scale variations in the convection pattern (André et al, 2000b).…”

Section: Introductionmentioning

confidence: 99%

Magnetic local time, substorm, and particle precipitation-related variations in the behaviour of SuperDARN Doppler spectral widths

et al. 2004

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Abstract. Super Dual Auroral Radar Network (DARN) radars often detect a distinct transition in line-of-sight Doppler velocity spread, or spectral width, from <50 m s −1 at lower latitude to >200 m s −1 at higher latitude. They also detect a similar boundary, namely the range at which ionospheric scatter with large spectral width suddenly commences (i.e. without preceding scatter with low spectral width). The location and behaviour of the spectral width boundary (SWB) (and scatter boundary) and the open-closed magnetic field line boundary (OCB) are thought to be closely related. The location of the nightside OCB can be inferred from the poleward edge of the auroral oval determined using energy spectra of precipitating particles measured on board Defence Meteorology Satellite Program (DMSP) satellites. Observations made with the Halley SuperDARN radar (75.5 • S, 26.6 • W, geographic; −62.0 • ) and the Tasman International Geospace Environment Radar (TIGER) (43.4 • S, 147.2 • E; −54.5 • ) are used to compare the location of the SWB with the DMSP-inferred OCB during 08:00 to 22:00 UT on 1 April 2000. This study interval was chosen because it includes several moderate substorms, whilst the Halley radar provided almost continuous high-time resolution measurements of the dayside SWB location and shape, and TIGER provided the same in the nightside ionosphere. The behaviour of the day-and nightside SWB can be understood in terms of the expanding/contracting polar cap model of high-latitude convection change, and the behaviour of the nightside SWB can also be organised according to substorm phase. Previous comparisons with DMSP OCBs have proven that the radar SWB is often a reasonable proxy for the OCB from dusk to just past midnight . However, the present case study actually suggests that the nightside SWB is often a better proxy for the poleward edge of Pedersen conductance enhanced by hot particle precipitation in the auroral zone. Simple modeling implies that the large spectral widths must be caused by ∼10-km scale velocity fluctuations.

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Signatures of the ionospheric cusp in digital ionosonde measurements of plasma drift above Casey, Antarctica

Cited by 11 publications

References 31 publications

Parametric dependence of electric field variability in the Sondrestrom database: A linear relation with Kp

Parametric dependence of electric field variability in the Sondrestrom database: A linear relation with Kp

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

Magnetic local time, substorm, and particle precipitation-related variations in the behaviour of SuperDARN Doppler spectral widths

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