Search

Recent studies reveal that midlatitude ionospheric irregularities are less understood due to lack of models and observations that can explain the characteristics of the observed wave structures. In this paper, the cascading processes of both the temperature gradient instability (TGI) and the gradient drift instability (GDI) are investigated as the cause of these irregularities. Based on observations obtained during a coordinated experiment between the Millstone Hill incoherent scatter radar and the Blackstone Super Dual Auroral Radar Network radar, a time series for the growth rate of both TGI and GDI is calculated for observations in the subauroral ionosphere under both quiet and disturbed geomagnetic conditions. Recorded GPS scintillation data are analyzed to monitor the amplitude scintillations and to obtain the spectral characteristics of irregularities producing ionospheric scintillations. Spatial power spectra of the density fluctuations associated with the TGI from nonlinear plasma simulations are compared with both the GPS scintillation spectral characteristics and previous in situ satellite spectral measurements. The spectral comparisons suggest that initially, TGI or/and GDI irregularities are generated at large-scale size (kilometer scale), and the dissipation of the energy associated with these irregularities occurs by generating smaller and smaller (decameter scale) irregularities. The alignment between experimental, theoretical, and computational results of this study suggests that in spite of expectations from linear growth rate calculations, cascading processes involving TGI and GDI are likely responsible for the midlatitude ionospheric irregularities associated with GPS scintillations during disturbed times.

Transionospheric radio signals in the high-latitude polar cap are susceptible to degradation when encountering sharp electron density gradients associated with discrete plasma structures, or patches. Multi-instrument measurements of polar cap patches are examined during a geomagnetic storm interval on 22 January 2012. For the first time, we monitor the transportation of patches with high spatial and temporal resolution across the polar cap for 1–2 h using a combination of GPS total electron content (TEC), all-sky airglow imagers (ASIs), and Super Dual Auroral Radar Network (SuperDARN) HF radar backscatter. Simultaneous measurements from these data sets allow for continuous tracking of patch location, horizontal extent, and velocity despite adverse observational conditions for the primary technique (e.g., sunlit regions in the ASI data). Spatial collocation between patch-like features in relatively coarse but global GPS TEC measurements and those mapped by high-resolution ASI data was very good, indicating that GPS TEC can be applied to track patches continuously as they are transported across the polar cap. In contrast to previous observations of cigar-shaped patches formed under weakly disturbed conditions, the relatively narrow dawn-dusk extent of patches in the present interval (500–800 km) suggests association with a longitudinally confined plasma source region, such as storm-enhanced density (SED) plume. SuperDARN observations show that the backscatter power enhancements corresponded to the optical patches, and for the first time we demonstrate that the motion of the optical patches was consistent with background plasma convection velocities.

[1] The Super Dual Auroral Radar Network (SuperDARN) is a worldwide chain of HF radars which monitor plasma dynamics in the ionosphere. Autocorrelation functions are routinely calculated from the radar returns and applied to estimate Doppler velocity, spectral width, and backscatter power. This fitting has traditionally been performed by a routine called FITACF. This routine initiates a fitting by selecting a subset of valid phase measurements and then empirically adjusting for 2π phase ambiguities. The slope of the phase variation with lag time then provides Doppler velocity. Doppler spectral width is found by an independent fitting of the decay of power to an assumed exponential or Gaussian function. In this paper, we use simulated data to assess the performance of FITACF, as well as two other newer fitting techniques, named FITEX2 and LMFIT. The key new feature of FITEX2 is that phase models are compared in a least-squares fitting sense with the actual data phases to determine the best fit, eliminating some ambiguities which are present in FITACF. The key new feature of LMFIT is that the complex autocorrelation function (ACF) itself is fit, and Doppler velocity, spectral width, and backscatter power are solved simultaneously. We discuss some of the issues that negatively impact FITACF and find that of the algorithms tested, LMFIT provides the best overall performance in fitting the SuperDARN ACFs. The techniques and the data simulator are applicable to other radar systems that utilize multipulse sequences to make simultaneous range and velocity determinations under aliasing conditions.

[1] The Super Dual Auroral Radar Network (SuperDARN) is a chain of HF radars for monitoring plasma flows in the high and middle latitude E and F regions of the ionosphere. The targets of SuperDARN radars are plasma irregularities which can flow up to several kilometers per second and can be detected out to ranges of several thousand kilometers. We have developed a simulator which is able to model SuperDARN data realistically. The simulation system comprises four separate parts: model scatterers, model collective properties, a model radar, and post-processing. Importantly, the simulator is designed using the collective scatter approach which accurately captures the expected statistical fluctuations of the radar echoes. The output of the program can represent either receiver voltages or autocorrelation functions (ACFs) in standard SuperDARN file formats. The simulator is useful for testing and implementation of SuperDARN data processing software and for investigation of how radar data and performance change when the nature of the irregularities or radar operation varies. The companion paper demonstrates the application of simulated data to evaluate the performance of different ACF fitting algorithms. The data simulator is applicable to other ionospheric radar systems.

We compare measurements of polar cap ionospheric plasma flow over Resolute Bay, Canada, made by a digital ionosonde using the Doppler drift technique with simultaneous measurements at the same location made by the first operational pair of SuperDARN HF radars. During the 3-hour comparison interval the flow varied widely in direction and from 100 to 600 m/s in speed. The two measurement techniques show very good agreement for both the speed and direction of flow for nearly all of the samples in the interval. The difference between the velocities determined by the two techniques has a scatter of about ±35° in direction and ±30% in speed, with no systematic difference above the level of the scatter. The few samples which strongly disagreed were usually associated with strong spatial structure in the flow pattern measured by SuperDARN in the vicinity of the comparison point. The drift speed measured by the ionosonde was independently verified by observing the time taken for polar cap F layer ionization patches to drift between ionosondes sited at Eureka and Resolute Bay. These results confirm that the speed and direction of the polar cap ionospheric convection can be reliably monitored by the ionosonde Doppler drift technique.

The theory of auroral coherent echoes developed for VHF scattering by Uspensky et al. (1988, 1989) is applied to the interpretation of intensity and Doppler velocity slant range profiles of HF radar aurora. The theoretical model includes the effects of irregularity aspect sensitivity, ionospheric refraction of the radar beam, and the reception of signals from different heights. The predicted profiles of HF radar aurora are compared with Schefferville HF radar observations in the frequency interval of 9–18 MHz. Satisfactory agreement is found between theory and experiment for the intensity profiles. However, there are significant discrepancies for the Doppler velocity profiles. We discuss this lack of agreement in light of other recent observations.

Meridional radar scans of electron density from the Sondrestrom incoherent scatter radar (Greenland, 66.99°N, 50.95°W) have been used to identify latitudinally narrow, field-aligned depletions of the auroral F region ionosphere. Observations of these so-called auroral cavities have been reported in earlier case studies in close proximity to E layer arcs at the poleward edge of the nightside oval (Doe et al. 1993). These radar data indicated that the cavities and arcs remained as collocated pairs for periods as long as an hour, while coordinated imaging and satellite measurements indicated that the pairs were extended in magnetic local time

[1] The Super Dual Auroral Radar Network (SuperDARN) is a network of HF radars that are traditionally used for monitoring phenomena in the Earth's ionosphere at high latitudes. The radar backscatter is due primarily to reflections from plasma irregularities in the ionosphere, known as ionospheric scatter, and to signal reflected from the ground, known as ground scatter. In recent years, SuperDARN has expanded to midlatitudes to provide improved coverage of the auroral region during times of enhanced geomagnetic activity. In addition to high-speed auroral flows, the radars commonly see a variety of low-velocity plasma drift associated with the quiet time midlatitude ionosphere. The traditional method of distinguishing between scatter types in SuperDARN data was developed for high latitudes and depends solely on the Doppler velocity and Doppler spectral width of each data point. This method has proven inadequate for identifying quiet time midlatitude ionospheric scatter. In this paper, we present a new technique for the classification of SuperDARN data, which operates on a distributed range time basis and involves procedures similar to “depth first search.” Using the new method for classification of ground and ionospheric scatter, we show a dramatic improvement in the determination of ionospheric scatter within extended (>1 h) events. Compared to the traditional method, the number of ionospheric measurements resolved increases by more than 50%. The new classification algorithm identifies discrete events of ionospheric scatter and can be applied to statistical analysis of event occurrence and characteristics.

The first results of an investigation of the altitude characteristics of auroral echoes at 398 MHz are presented. The data were collected over two nights in the spring of 1973 with a phased array radar operated at Homer, Alaska. Heights of maximum backscattered power can be determined with an accuracy approaching 2 km, a temporal resolution as short as 20 s, and a horizontal spatial resolution of 40 km. The spatial distributions of the height of echoing in two premidnight periods are shown to be consistent with a model of scattering from a continuous range of heights between 97 and 117 km; within this interval, the height tends to change in such a way that the echoes come from directions nearly perpendicular to the earth's magnetic field. In a postmidnight period, the echo activity was confined to a region of considerably more restricted (5–10 km) vertical extent. In all cases, the echo region was sharply bounded from below at 96–98 km. The heights may have short-term (minutes) and small-scale (< 100 km) structure. Adjacent structures are sometimes observed to differ in height by as much as 10 km.