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  1. Abstract

    The Super Dual Auroral Radar Network (SuperDARN) is a collection of radars built to study ionospheric convection. We use a 7‐year archive of SuperDARN convection maps, processed in 3 different ways, to build a statistical understanding of dusk‐dawn asymmetries in the convection patterns. We find that the data set processing alone can introduce a bias which manifests itself in dusk‐dawn asymmetries. We find that the solar wind clock angle affects the balance in the strength of the convection cells. We further find that the location of the positive potential foci is most likely observed at latitudes of 78° for long periods (>300 min) of southward interplanetary magnetic field (IMF), as opposed to 74° for short periods (<20 min) of steady IMF. For long steady dawnward IMF the median is also at 78°. For long steady periods of duskward IMF, the positive potential foci tends to be at lower latitudes than the negative potential and vice versa during dawnward IMF. For long periods of steady Northward IMF, the positive and negative cells can swap sides in the convection pattern. We find that they move from ∼0–9 MLT to 15 MLT or ∼15–23 MLT to 10 MLT, which reduces asymmetry in the average convection cell locations for Northward IMF. We also investigate the width of the region in which the convection returns to the dayside, the return flow width. Asymmetries in this are not obvious, until we select by solar wind conditions, when the return flow region is widest for the negative convection cell during Southward IMF.

     
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  2. Abstract

    Propagation of high‐frequency (HF) radio signals is strongly dependent on the ionospheric electron density structure along a communications link. The ground‐based, HF space weather radars of the Super Dual Auroral Radar Network (SuperDARN) utilize the ionospheric refraction of transmitted signals to monitor the global circulation ofE‐ andF‐region plasma irregularities. Previous studies have assessed the propagation characteristics of backscatter echoes from ionospheric irregularities in the auroral and polar regions of the Earth's ionosphere. By default, the geographic location of these echoes are found using empirical models which estimate the virtual backscattering height from the measured range along the radar signal path. However, the performance of these virtual height models has not yet been evaluated for mid‐latitude SuperDARN radar observations or for ground scatter (GS) propagation modes. In this study, we derive a virtual height model suitable for mid‐latitude SuperDARN observations using 5 years of data from the Christmas Valley East and West radars. This empirical model can be applied to both ionospheric and GS observations and provides an improved estimate of the ground range to the backscatter location compared to existing high‐latitude virtual height models. We also identify a region of overlapping half‐hopF‐region ionospheric scatter and one‐hopE‐region GS where the measured radar parameters (e.g., velocity, spectral width, elevation angle) are insufficient to discriminate between the two scatter types. Further studies are required to determine whether these backscatter echoes of ambiguous origin are observed by other mid‐latitude SuperDARN radars and their potential impact on scatter classification schemes.

     
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  3. Abstract

    This paper presents updated methods for locating the Poleward and Equatorward Auroral Luminosity Boundaries (PALB and EALB) directly from IMAGE Far UltraViolet (FUV) images of the Northern Hemisphere auroral oval. Separate boundaries are determined from images measured at different FUV wavelengths. In addition, new methods for indirectly estimating the Open‐Closed magnetic field line Boundary (OCB) and the Equatorward Precipitation Boundary (EPB) locations are presented; these new boundaries are derived from a combination of the auroral luminosity boundary estimates with statistical latitudinal offsets derived from comparisons with low‐altitude spacecraft Particle Precipitation Boundaries (PPBs). Subsequently, we derive new circle model fits for all these boundary data sets, as well as new quality control criteria for these model fits. The suitability of circle fits for each of the data sets is discussed, and the OCB and PALB circle fits are validated against the Convection Reversal Boundary (CRB), as measured by low‐altitude in situ spacecraft. All the new boundary data sets, covering the epoch May 2000 to October 2002, are freely available online.

     
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  4. Abstract

    The Super Dual Auroral Radar Network (SuperDARN) is a network of High Frequency (HF) radars that are typically used for monitoring plasma convection in the Earth's ionosphere. A majority of SuperDARN backscatter can broadly be divided into three categories: (a) ionospheric scatter due to reflections from plasma irregularities in the E and F regions of the ionosphere, (b) ground scatter caused by reflections from the ground/sea surface following reflection in the ionosphere, and (c) backscatter from meteor trails left by meteoroids as they enter the Earth's atmosphere. Due to the complex nature of HF propagation and mid‐latitude electrodynamics, it is often not straightforward to distinguish between different modes of backscatter observed by SuperDARN. In this study, we present a new two‐stage machine learning algorithm for identifying different backscatter modes in SuperDARN data. In the first stage, a neural network that “mimics” ray‐tracing is used to predict the probability of ionospheric and ground scatter occurring at a given location along with parameters like the elevation angles, reflection heights etc. The inputs to the network include parameters that control HF propagation, such as signal frequency, season, UT time, and geomagnetic activity levels. In the second stage, the output probabilities from the neural network and actual SuperDARN data are clustered together to determine the category of the backscatter. Our model can distinguish between meteor scatter, 1/2 hop E‐/F‐region ionospheric as well as ground/sea scatter. We validate our model by comparing predicted elevation angles with those measured at a SuperDARN radar.

     
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  5. Abstract

    The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. Alongside software developments, this has resulted in many different versions of the convection maps data set being available. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the StormDARN radars. This enables us to simulate how much information was missing from older SuperDARN research. We study changes in the Heppner‐Maynard boundary (HMB), the cross polar cap potential (CPCP), the number of backscatter echoes (n) and theχ2/nstatistic which is a measure of the global agreement between the measured and fitted velocities. We find that the CPCP is reduced when the PolarDARN radars are introduced, but then increases again when the StormDARN radars are added. When the background model is changed from the RG96 model, to the most recent TS18 model, the CPCP tends to decrease for lower values, but tends to increase for higher values. When comparing to geomagnetic indices, we find that there is on average a linear relationship between the HMB and the geomagnetic indices, as well asn, which breaks when the HMB is located at latitudes below ∼50° due to the low observational density. Whilstnis important in constraining the maps (maps withn > 400 data points are unlikely to differ), it is insufficient as the sole measure of quality.

     
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  6. Abstract

    Lobe reconnection is usually thought to play an important role in geospace dynamics only when the Interplanetary Magnetic Field (IMF) is mainly northward. This is because the most common and unambiguous signature of lobe reconnection is the strong sunward convection in the polar cap ionosphere observed during these conditions. During more typical conditions, when the IMF is mainly oriented in a dawn‐dusk direction, plasma flows initiated by dayside and lobe reconnection both map to high‐latitude ionospheric locations in close proximity to each other on the dayside. This makes the distinction of the source of the observed dayside polar cap convection ambiguous, as the flow magnitude and direction are similar from the two topologically different source regions. We here overcome this challenge by normalizing the ionospheric convection observed by the Super Dual Aurora Radar Network (SuperDARN) to the polar cap boundary, inferred from simultaneous observations from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). This new method enable us to separate and quantify the relative contribution of both lobe reconnection and dayside/nightside (Dungey cycle) reconnection during periods of dominating IMFBy. Our main findings are twofold. First, the lobe reconnection rate can typically account for 20% of the Dungey cycle flux transport during local summer when IMFByis dominating and IMFBz ≥ 0. Second, the dayside convection relative to the open/closed boundary is vastly different in local summer versus local winter, as defined by the dipole tilt angle.

     
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  7. Abstract

    Super Dual Auroral Radar Network (SuperDARN) radars operate in a coordinated but monostatic configuration whereby high‐frequency (HF) signals scattered from ionospheric density irregularities or from the surface of the Earth return to the transmitting radar where Doppler parameters are then acquired. A bistatic arrangement has been developed for SuperDARN radars in which HF signals transmitted from one radar are received and analyzed by another radar that is separated by a large distance (>1,000 km). This new capability was developed and tested on radars located in Oregon and Kansas. Numerous 3‐day bistatic campaigns have been conducted over a period extending from September 2019 through March 2020. During these campaigns three distinct bistatic propagation modes have been identified including a direct mode in which signals are transmitted and received through the radar side lobes. Direct mode signals propagate along the great‐circle arc connecting the two bistatic radar sites, reflecting from the ionosphere at bothEregion andFregion altitudes. Two additional modes are observed in which HF signals transmitted from one radar scatter from either ionospheric density irregularities or from the surface of the Earth before propagating to the bistatic receiving radar. Ray tracing simulations performed for examples of each mode show good agreement with observations and confirm our understanding of these three bistatic propagation modes. Bistatic campaigns continue to be scheduled in order to improve technical aspects of this new capability, to further explore the physical processes involved in the propagation and scattering of HF bistatic signals and to expand the coverage of ionospheric effects that is possible with SuperDARN.

     
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  8. Abstract

    Super Dual Auroral Radar Network (SuperDARN) ionospheric convection maps are a powerful tool for the study of solar wind‐magnetosphere‐ionosphere interactions. SuperDARN data have high temporal (approximately minutes) and spatial (∼45 km) resolution, meaning that the convection can be mapped on fine time scales that show more detail than the large‐scale changes in the pattern. The Heppner‐Maynard boundary (HMB) defines the low‐latitude limit of the convection region, and its identification is an essential component of the standard SuperDARN convection mapping technique. However, the estimation of the latitude of this boundary is dependent on ionospheric scatter availability. Consequentially it is susceptible to nonphysical variations as areas of scatter in different latitude and local time regions appear and disappear, often due to changing propagation conditions. In this paper, the HMB is compared to an independent field‐aligned current data set from the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE). A linear trend is found between the HMB and the boundary between the AMPERE Region 1 and Region 2 field‐aligned currents in the Northern Hemisphere, at both solar minimum and solar maximum. The use of this trend and the AMPERE current data set to predict the latitude position of the HMB is found to improve the interpretation of the SuperDARN measurements in convection mapping.

     
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