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An annular solar eclipse was visible on 14 October 2023 from 15:00–21:00 UT as its path traveled across North, Central, and South America. In this letter, we present the first multi‐frequency Super Dual Auroral Radar Network (SuperDARN) observations of the bottomside ionospheric response to a solar eclipse using a novel experimental mode designed for the October 2023 annular eclipse. We compare our results from the mid‐latitude Christmas Valley East radar with measurements of the vertical electron density profile from the nearby Boulder Digisonde, finding the changes in 1‐ and 2‐hop ground scatter skip distance are well correlated with the F2 ${F}_{2}$‐layer density response, which lags the peak obscuration by ∼ ${\sim} $30 min. Changes in the line‐of‐sight Doppler shifts are better aligned with the time derivative of eclipse obscuration. Plain Language Summary: During a solar eclipse when the moon passes between our planet and the sun, the amount of incoming solar extreme ultraviolet radiation is reduced over the shadowed region of Earth. As a result, temperatures can become cooler and the rate of plasma production in the ionized layers of the Earth's upper atmosphere, known as the ionosphere, can also decrease. Users of high‐frequency radio systems, such as over‐the‐horizon radar and amateur radio, depend on knowledge of the ionospheric plasma density, and are therefore susceptible to abrupt changes due to space weather phenomena such as a solar eclipse. While not attracting as much media attention as the total solar eclipses over North America in August 2017 and April 2024, the annular solar eclipse of October 2023 nevertheless presented a unique opportunity to study the response of Earth's upper atmosphere using a diverse array of ground‐based instruments in a similar region but at a different time of day. For this event, we designed a new experimental mode for a pair of space weather radars located in central Oregon to transmit signals at a range of frequencies in the HF band to monitor their evolution as the eclipse shadow passed nearby. Key Points: A novel multi‐frequency experiment was conducted with the Christmas Valley East SuperDARN radar during the 14 October 2023 annular eclipseOur comparison with the nearby Boulder Digisonde shows a strong correlation in 1‐hop skip distance with F2‐layer critical frequencyThe transition from negative to positive Doppler shifts is clearly aligned with the time derivative of eclipse shadow [ABSTRACT FROM AUTHOR]

The path of totality of the 8 April 2024 solar eclipse traversed the fields‐of‐view of four US SuperDARN radars. This rare scenario provided an excellent opportunity to monitor the large‐scale ionospheric response to the eclipse. In this study, we present observations made by the Blackstone (BKS) SuperDARN radar and a Digisonde during the eclipse. Two striking effects were observed by the BKS radar: (a) the Doppler velocities associated with ground scatter coalesced into a pattern clearly organized by the line of totality, with a reversal in sign across this line, and, (b) a delay of ∼ ${\sim} $45 min between time of maximum obscuration and maximum effect on the skip distance. The skip distance estimated using a SAMI3 simulation of the eclipse did not however capture the asymmetric time‐delay. These observations suggest that the neutral atmosphere plays an important role in controlling ionospheric plasma dynamics, which were missing in SAMI3 simulations. Plain Language Summary: The total solar eclipse on 8 April 2024 was the last one to be observed over the continental United States until 2045. In addition to blocking the visible light from the Sun over a swath ranging a few hundred kilometers, a solar eclipse will also partially obscure the Sun's extreme ultraviolet radiation. As a result, an eclipse can drive significant changes in the ionosphere, a charged region in the Earth's upper atmosphere that is predominantly ionized by solar radiation. A unique feature of this eclipse was that the path of totality traversed the fields‐of‐view of three Super Dual Auroral Radar Network (SuperDARN) radars–Fort Hays East, Blackstone, and Wallops Island. SuperDARN radars operate in the High Frequency (HF) range, and radio waves in this frequency range are particularly sensitive to changes in the ionosphere. In this study, we use observations provided by SuperDARN radars alongside a Digisonde to determine the temporal response of the different ionospheric layers to the eclipse and compare these observations with modeled behavior. Key Points: We present observations made by the Blackstone SuperDARN radar, a Digisonde, and SAMI3 simulations to analyze the eclipsed ionosphereSuperDARN Doppler velocities cohered into a pattern clearly organized by the line of totality with a reversal in sign across the lineSuperDARN skip distance and Digisonde derived foF2 show a delayed response to the shadow, suggesting slower response at higher altitudes [ABSTRACT FROM AUTHOR]

The phenomenon known as strong thermal emission velocity enhancement (STEVE) is a narrow optical structure that may extend longitudinally for thousands of kilometers. Initially observed by amateur photographers, it has recently garnered researchers' attention. STEVE has been associated with a rapid westward flow of ions in the ionosphere, known as subauroral ion drift (SAID). In this work, we investigate three occurrences of STEVE, using data from one of the Time History of Events and Macroscale Interactions during Substorms (THEMIS) ground-based all-sky imagers (ASIs) located at Pinawa, Manitoba, and from the Super Dual Auroral Radar Network (SuperDARN). This approach allows us to verify the correlation between STEVE and SAID, as well as analyze the temporal variation of SAID observed during STEVE events. Our results suggest that the SAID activity starts before the STEVE, and the magnitude of the westward flow decreases as the STEVE progresses toward the end of its optical manifestation. [ABSTRACT FROM AUTHOR]

The ground‐based, high‐frequency radars of the Super Dual Auroral Radar Network (SuperDARN) observe backscatter from ionospheric field‐aligned plasma irregularities and features on the Earth's surface out to ranges of several thousand kilometers via over‐the‐horizon propagation of transmitted radio waves. Interferometric techniques can be applied to the received signals at the primary and secondary antenna arrays to measure the vertical angle of arrival, or elevation angle, for more accurate geolocation of SuperDARN observations. However, the calibration of SuperDARN interferometer measurements remains challenging for several reasons, including a 2π phase ambiguity when solving for the time delay correction factor needed to account for differences in the electrical path lengths between signals received at the two antenna arrays. We present a new technique using multi‐frequency ionospheric and ground backscatter observations for the calibration of SuperDARN interferometer data, and demonstrate its application to both historical and recent data. Key Points: Calibration of Super Dual Auroral Radar Network (SuperDARN) interferometer angle of arrival data remains an outstanding challengeAnalysis of data at multiple frequencies can overcome the inherent 2π measurement ambiguity in the time delay correction factor (tdiff)Example applications are shown for historical and contemporary multi‐frequency SuperDARN observations [ABSTRACT FROM AUTHOR]

Medium‐scale Traveling Ionospheric Disturbances (MSTIDs) are prominent and ubiquitous features of the mid‐latitude ionosphere, and are observed in Super Dual Auroral Radar Network (SuperDARN) and high‐resolution Global Navigational Satellite Service (GNSS) Total Electron Content (TEC) data. The mechanisms driving these MSTIDs are an open area of research, especially during geomagnetic storms. Previous studies have demonstrated that nightside MSTIDs are associated with an electrodynamic instability mechanism like Perkins, especially during geomagnetically quiet conditions. However, dayside MSTIDs are often associated with atmospheric gravity waves. Very few studies have analyzed the mechanisms driving MSTIDs during strong geomagnetic storms at mid‐latitudes. In this study, we present mid‐latitude MSTIDs observed in de‐trended GNSS TEC data and SuperDARN radars over the North American sector, during a geomagnetic storm (peak Kp reaching 9) on 7–8 September 2017. In SuperDARN, MSTIDs were observed in ionospheric backscatter with Line of Sight (LOS) velocities exceeding 800 m/s. Additionally, radar LOS velocities oscillated with amplitudes reaching ±500 m/s as the MSTIDs passed through the fields‐of‐view. In detrended TEC, these MSTIDs produced perturbations reaching ∼50 percent of background TEC magnitude. The MSTIDs were observed to propagate in the westward/south‐westward direction with a time period of ∼15 min. Projecting de‐trended GNSS TEC data along SuperDARN beams showed that enhancements in TEC were correlated with enhancements in SuperDARN SNR and positive LOS velocities. Finally, SuperDARN LOS velocities systematically switched polarities between the crests and the troughs of the MSTIDs, indicating the presence of polarization electric fields and an electrodynamic instability process during these MSTIDs. Key Points: Medium‐scale Traveling Ionospheric Disturbance (MSTID) signatures were observed in Global Navigational Satellite Service Total Electron Content and Super Dual Auroral Radar Network (SuperDARN) ionospheric backscatter during a strong geomagnetic stormMSTID characteristics were broadly consistent between the data sets, with periods of 10–20 min and phase speeds of ∼800 m/sSuperDARN Line of Sight velocities systematically switched polarities between MSTID crests and troughs, indicating polarization electric fields [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: The Super Dual Auroral Radar Network (SuperDARN) is an international network of radars that operate in the High Frequency (HF) range (between 8 and 18 MHz). The radars are primarily used for monitoring the motion of plasma in the charged portion of Earth's upper atmosphere, called the ionosphere. A key feature of HF radio waves is that they are refracted or "bent" by the ionosphere. As a result, these frequencies are usually reflected back by decameter‐scale density structures in the ionosphere or by the ground, depending on the density of the ionosphere and operational characteristics of the radar. SuperDARN data is therefore mostly composed of measurements from the ionosphere, ground/sea, and meteor trails. At high latitudes, it is usually straightforward to distinguish between fast‐moving ionospheric and the slow‐moving ground observations. However, at mid‐latitudes, due to the similarities between ionospheric and ground measurements it is usually difficult to distinguish between these two types of measurements. In this study, we present a new methodology that uses a physics‐based approach to encode certain HF propagation characteristics into a machine learning model that can: (a) provide the ability to classify between different types of measurements, and (b) determine the uncertainties in the model ionosphere used to characterize HF propagation. Key Points: We developed a new machine learning model that is guided by ray‐tracing and the International Reference Ionosphere (IRI) to examine SuperDARN backscatter modesOur model can be used to classify SuperDARN backscatter into different categories such as meteor, E‐/F‐region ionosphere and ground/seaThe model's error rate is lowest in winter and highest in summer, suggesting uncertainties in the IRI ionosphere are larger in summer [ABSTRACT FROM AUTHOR]

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 of E‐ and F‐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‐hop F‐region ionospheric scatter and one‐hop E‐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. Key Points: We derive a new empirical virtual height model suitable for improved geolocation of mid‐latitude Super Dual Auroral Radar Network high‐frequency radar observationsThe new model provides the first characterization of ground scatter (GS) propagation modesCharacteristics of half‐hop F‐region ionospheric scatter and one‐hop E‐region GS are examined [ABSTRACT FROM AUTHOR]

Evolution of large‐scale and fine‐scale plasmaspheric plume density structures was examined using space‐ground coordinated observations of a plume during the 7–8 September 2015 storm. The large‐scale plasmaspheric plume density at Van Allen Probes A was roughly proportional to the total electron content (TEC) along the satellite footprint, indicating that TEC distribution represents the large‐scale plume density distribution in the magnetosphere. The plasmaspheric plume contained fine‐scale density structures and subauroral polarization streams (SAPS) velocity fluctuations. High‐resolution TEC data support the interpretation that the fine‐scale plume structures were blobs with ∼300 km size and ∼500–800 m/s in the ionosphere (∼3,000 km size and ∼5–8 km/s speed in the magnetosphere), emerging at the plume base and drifting to the plume. The short‐baseline Global Navigation Satellite System receivers detected smaller‐scale (∼10 km in the ionosphere, ∼100 km in the magnetosphere) TEC gradients and their sunward drift. Fine‐scale density structures were associated with enhanced phase scintillation index. Velocity fluctuations were found to be spatial structures of fine‐scale SAPS flows that drifted sunward with density irregularities down to ∼10 s of meter‐scale. Fine‐scale density structures followed a power law with a slope of ∼−5/3, and smaller‐scale density structures developed slower than the larger‐scale structures. We suggest that turbulent SAPS flows created fine‐scale density structures and their cascading to smaller scales. We also found that the plume fine‐scale density structures were associated with whistler‐mode intensity modulation, and localized electron precipitation in the plume. Structured precipitation in the plume may contribute to ionospheric heating, SAPS velocity reduction, and conductance enhancements. Plain Language Summary: A plume of cold plasma circulates in the system during geomagnetic storms, and it is important for global positioning system (GPS) signal scintillation at mid‐latitudes of the Earth. We show that the plume contains fine‐scale density structures across multiple‐scales, and reveal their 2‐d structure and motion using GPS remote sensing and multiple satellites. The network of GPS receivers showed that the fine‐scale plume structures were blobs with hundreds of km size in the ionosphere, and GPS signal scintillation was highly correlated with the fine‐scale density structures. Radar observations identified a close relation between the fine‐scale density and fast plasma streams. The plume density structures formed first at large‐scales and then small‐scale density structures emerged near the peak of the geomagnetic storm. We suggest that fast plasma streams created fine‐scale density structures and their turbulent cascading to smaller scales. Key Points: Two dimensional structure and motion of fine‐scale plume density has been revealed by Van Allen Probes‐defense meteorological satellite program‐Swarm‐global positioning system conjunctionFine‐scale subauroral polarization streams flows are related to fine‐scale density and are suggested to create turbulent density cascadingFine‐scale density contributes to waves, precipitation, heating, and scintillation [ABSTRACT FROM AUTHOR]

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 both E region and F region 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. Key Points: Bistatic capability has been developed and demonstrated using two midlatitude SuperDARN radarsThree distinct propagation modes were commonly observed during bistatic campaignsGood agreement between observations and ray tracing using the IRI model is obtained [ABSTRACT FROM AUTHOR]

Increased electron density in the ionosphere due to photoionization by radiation emitted during a solar X‐ray flare impacts high‐frequency (HF) radio wave propagation. Shortwave fadeout (SWF) due to the enhanced D region absorption that results is characterized by the level of cosmic radio noise attenuation derived from riometer measurements. SWF impacts HF radio propagation and has been identified in the Super Dual Auroral Radar Network (SuperDARN) data. An X2.1 solar X‐ray flare that erupted on 11 March 2015 is examined to determine its effects on HF radio propagation. Riometer data indicate a sharp enhancement in absorption, which falls off with increasing solar zenith angle. SuperDARN radars observed a suppression of both ground scatter and ionospheric echoes. Ground scatter data indicated a rapid weakening of signal from far to near ranges followed by a ~20‐min interval of complete signal loss. Recovery lasted ~30 min and proceeded from near to far ranges. Prior to the complete signal loss, an apparent sharp velocity impulse (Doppler flash) lasting 1–2 min was observed in the ground scatter data. The peak of this flash preceded the onset of enhanced absorption. The onset of signal loss by SuperDARN preceded the onset of enhanced absorption observed by riometers. Both data sets observed a positive correlation between increasing delay in onset and increasing solar zenith angle with onset progressing at an average rate of 16.7°/min (0.060 min/°). Agreement between riometer and SuperDARN indicates the possibility of using a joint data set for improved monitoring of the space weather impact of solar X‐ray flares. Key Points: Solar X‐ray flares may impact HF radio wave propagation on the dayside, to which riometers and SuperDARN radars are sensitiveRiometer and SuperDARN instruments demonstrate a solar zenith angle dependence on the onset time of the observed response to the solar X‐ray flareA velocity impulse observed by SuperDARN radars prior to complete signal loss may serve as a warning that shortwave fadeout is imminent [ABSTRACT FROM AUTHOR]

Regions of persistent westward directed flows are often observed equatorward of the auroral oval in the dusk‐midnight sector. In general, the midnight narrow flows are termed as subauroral ion drifts and the duskside broader flows are termed subauroral polarization streams (SAPS). SAPS/subauroral ion drift electric fields play an important role in controlling the dynamics of the midlatitude ionosphere. In this paper we analyze longitudinally extended observations of SAPS measured by midlatitude Super Dual Auroral Radar Network (SuperDARN) radars under varied geomagnetic conditions. We find that SAPS speeds exhibit a strong dependence on geomagnetic activity, with flows exceeding 1,500 m/s during geomagnetic storms and dropping to 100 m/s during periods of geomagnetic quiet. Moreover, SAPS flows turn increasingly poleward when moving from the midnight sector toward dusk and this effect is more pronounced during disturbed geomagnetic conditions. The variations in SAPS speeds with magnetic local time (MLT) are also found to be strongly dependent on geomagnetic conditions. Specifically, SAPS speeds increase quasilinearly with MLT during disturbed geomagnetic conditions, whereas during relatively quiet geomagnetic conditions there is no discernible trend. This behavior suggests the possibility of different mechanisms influencing SAPS during geomagnetically quiet conditions. Average cross‐SAPS potentials increase with geomagnetic activity and typically vary between 15 and 45 kV. Finally, a new empirical model of SAPS potentials has been developed parameterized by Asy‐H index, MLT, and magnetic latitude. Key Points: We present a new empirical model of SAPS potentials parameterized by Asy‐H, MLT, and magnetic latitudeSAPS speeds exhibit considerable differences during storm time and non‐storm time conditionsSAPS speeds increase quasilinearly with MLT during disturbed geomagnetic conditions; no trend is seen for quiet times [ABSTRACT FROM AUTHOR]

The international scientific radars known as the Super Dual Auroral Radar Network (SuperDARN) are designed to primarily measure plasma convection at ionospheric altitudes over a large region of the Northern and Southern Hemispheres. SuperDARN radars are equipped with a secondary interferometry array that is used to measure the elevation angle ( α) of signals. These values of α have been used in relatively few studies; however, they are important for estimating ionospheric quantities and for accurate geolocation of the ionospheric source region of backscattered signals. The majority of SuperDARN radars are constructed with interferometers that are separated from their main array in one or two dimensions, and a relatively straightforward algorithm gives reasonably accurate results. A solution to the more general case, where offsets in all three dimensions are present, is desirable for future designs and necessary for at least one operational radar. Details of such an algorithm are described here and applied to phase measurements from several radars. For radars with interferometers offset only along the radar boresight and vertical directions, small differences of up to ∼1.5° in α are observed and negative values of α, which are deemed unphysical, are no longer produced. For the radar interferometer that is offset in all three dimensions the resulting values of α are consistent with expected behavior. The algorithm presented here provides a technique for accurately determining α from SuperDARN radars with offsets in all three dimensions and significantly reduces constraints placed on the positioning of interferometers for future SuperDARN radars. [ABSTRACT FROM AUTHOR]