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Abstract Joule heating is a major energy sink in the solar wind‐magnetosphere‐ionosphere system and modeling it is key to understanding the impact of space weather on the neutral atmosphere. Ion drifts and neutral wind velocities are key parameters when modeling Joule heating, however there is limited validation of the modeled ion and neutral velocities at mid‐latitudes. We use the Blackstone Super Dual Auroral Radar Network radar and the Michigan North American Thermosphere Ionosphere Observing Network Fabry‐Perot interferometer to obtain the local nightside ion and neutral velocities at ∼40° geographic latitude during the nighttime of 16 July 2014. Despite being a geomagnetically quiet period, we observe significant sub‐auroral ion flows in excess of 200 ms⁻¹. We calculate an enhancement to the local Joule heating rate due to these ion flows and find that the neutrals impart a significant increase or decrease to the total Joule heating rate of >75% depending on their direction. We compare our observations to outputs from the Thermosphere Ionosphere Electrodynamic General Circulation Model (TIEGCM). At such a low geomagnetic activity however, TIEGCM was not able to model significant sub‐auroral ion flows and any resulting Joule heating enhancements equivalent to our observations. We found that the neutral winds were the primary contributor to the Joule heating rates modeled by TIEGCM rather than the ions as suggested by our observations. 

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 Sporadic‐E (Es) are thin layers of enhanced ionization observed in the E‐region, typically between 95 and 120 km altitude. Es plays an important role in controlling the dynamics of the upper atmosphere and it is necessary to understand the geophysical factors influencing Es from both the scientific and operational perspectives. While the wind‐shear theory is widely accepted as an important mechanism responsible for the generation of Es, there are still gaps in the current state of our knowledge. For example, we are yet to determine precisely how changes in the dynamics of horizontal winds impact the formation, altitude, and destruction of Es layers. In this study, we report results from a coordinated experimental campaign between the Millstone Hill Incoherent Scatter Radar, the SuperDARN radar at Blackstone, and the Millstone Hill Digisonde to monitor the dynamics of mid‐latitude Es layers. We report observations during a 15‐hr window between 13 UT on 3 June 2022 and 4 UT on 4 June 2022, which was marked by the presence of a strong Es layer. We find that the height of the Es layer is collocated with strong vertical shears in atmospheric tides and that the zonal wind shears play a more important role than meridional wind shears in generating Es, especially at lower altitudes. Finally, we show that in the presence of Es, SuperDARN ground backscatter moves to closer ranges, and the height and critical frequency of the Es layer have a significant impact on the location and intensity of HF ground scatter. 

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. 

Abstract Sudden enhancement in high‐frequency absorption is a well‐known impact of solar flare‐driven Short‐Wave Fadeout (SWF). Less understood, is a perturbation of the radio wave frequency as it traverses the ionosphere in the early stages of SWF, also known as the Doppler flash. Investigations have suggested two possible sources that might contribute to it’s manifestation: first, enhancements of plasma density in the D‐and lower E‐regions; second, the lowering of the F‐region reflection point. Our recent work investigated a solar flare event using first principles modeling and Super Dual Auroral Radar Network (SuperDARN) HF radar observations and found that change in the F‐region refractive index is the primary driver of the Doppler flash. This study analyzes multiple solar flare events observed across different SuperDARN HF radars to determine how flare characteristics, properties of the traveling radio wave, and geophysical conditions impact the Doppler flash. In addition, we use incoherent scatter radar data and first‐principles modeling to investigate physical mechanisms that drive the lowering of the F‐region reflection points. We found, (a) on average, the change in E‐ and F‐region refractive index is the primary driver of the Doppler flash, (b) solar zenith angle, ray’s elevation angle, operating frequency, and location of the solar flare on the solar disk can alter the ionospheric regions of maximum contribution to the Doppler flash, (c) increased ionospheric Hall and Pedersen conductance causes a reduction of the daytime eastward electric field, and consequently reduces the vertical ion‐drift in the lower and middle latitude ionosphere, which results in lowering of the F‐region ray reflection point. 

Abstract Over‐the‐Horizon communication is strongly dependent on the state of the ionosphere, which is susceptible to solar flares. Trans‐ionospheric high frequency (HF, 3–30 MHz) signals can experience strong attenuation following a solar flare that lasts typically for an hour, commonly referred to as shortwave fadeout (SWF). In this study, we examine the role of dispersion relation and collision frequency formulations on the estimation of SWF in riometer observations using a new physics‐based model framework. The new framework first uses modified solar irradiance models incorporating high‐resolution solar flux data from the GOES satellite X‐ray sensors as input to compute the enhanced ionization produced during a flare event. The framework then uses different dispersion relation and collision frequency formulations to estimate the enhanced HF absorption. The modeled HF absorption is compared with riometer data to determine which formulation best reproduces the observations. We find the Appleton‐Hartree dispersion relation in combination with the averaged collision frequency profile reproduces riometer observations with an average skill score of 0.4, representing 40% better forecast ability than the existing D‐region Absorption Prediction model. Our modeling results also indicate that electron temperature plays an important role in controlling HF absorption. We suggest that adoption of the Appleton‐Hartree dispersion relation in combination with the averaged collision frequency be considered for improved forecasting of ionospheric absorption following solar flares. 

Abstract Trans‐ionospheric high frequency (HF: 3–30 MHz) signals experience strong attenuation following a solar flare‐driven sudden ionospheric disturbance (SID). Solar flare‐driven HF absorption, referred to as short‐wave fadeout, is a well‐known impact of SIDs, but the initial Doppler frequency shift phenomena, also known as “Doppler flash” in the traveling radio wave is not well understood. This study seeks to advance our understanding of the initial impacts of solar flare‐driven SID using a physics‐based whole atmosphere model for a specific solar flare event. First, we demonstrate that the Doppler flash phenomenon observed by Super Dual Auroral Radar Network (SuperDARN) radars can be successfully reproduced using first‐principles based modeling. The output from the simulation is validated against SuperDARN line‐of‐sight Doppler velocity measurements. We then examine which region of the ionosphere, D, E, or F, makes the largest contribution to the Doppler flash. We also consider the relative contribution of change in refractive index through the ionospheric layers versus lowered reflection height. We find: (a) the model is able to reproduce radar observations with an root‐median‐squared‐error and a mean percentage error (δ) of 3.72 m/s and 0.67%, respectively; (b) the F‐region is the most significant contributor to the total Doppler flash (∼48%), 30% of which is contributed by the change in F‐region's refractive index, while the other ∼18% is due to change in ray reflection height. Our analysis shows lowering of the F‐region's ray reflection point is a secondary driver compared to the change in refractive index. 

Abstract We utilized citizen scientist photographs of subauroral emissions in the upper atmosphere and identified a repeatable sequence of proton aurora and subauroral red (SAR) arc during substorms. The sequence started with a pair of green diffuse emissions and a red arc that drifted equatorward during the substorm expansion phase. Simultaneous spectrograph and satellite observations showed that they were subauroral proton aurora, where ion precipitation created secondary electrons that illuminated aurora in green and red colors. The ray structures in the red arc also indicated existence of low‐energy electron precipitation. The green diffuse aurora then decayed but the red arc (SAR arc) continued to move equatorward during the substorm recovery phase. This sequence suggests that the SAR arc was first generated by secondary electrons associated with ion precipitation and may then transition to heat flux or Joule heating. Proton aurora provides observational evidence that ion injection to the inner magnetosphere is the energy source for the initiation of the SAR arc.