We report a citizen science-motivated study on the cause of an unusually bright red aurora as witnessed from Hokkaido, Japan during a magnetic storm on December 1, 2023. Such an intense red aurora event has occurred in the Halloween 2003 super storm, but the Dst index peak of this December 2023 storm was only -107 nT. In spite of the moderate storm amplitude, the extremely high solar wind density of >50 /cc caused the aurora oval extension to 53 MLAT (L=2.8). We discuss that the drift loss of the ring current particles across the small-size magnetopause is important, and Hokkaido was at the right position to see the direct effect of the large particle injection of the storm-time substorm.

On 15 January 2022, the submarine volcano on the southwest Pacific island of Tonga violently erupted. Thus far, the ionospheric oscillation features caused by the volcanic eruption have not been identified. Here, observations from the Super Dual Auroral Radar Network (SuperDARN) radars and digisondes \change{are}{were} employed to analyze ionospheric oscillations in the Northern Hemisphere caused by the volcanic eruption in Tonga. Due to the magnetic field conjugate effect, the ionospheric oscillations were observed much earlier than the arrival of surface air pressure waves, and the maximum negative line-of-sight (LOS) velocity of the ionospheric oscillations exceeded 100 m/s in the F layer. After the surface air pressure waves arrived, the maximum LOS velocity in the E layer approached 150 m/s. A maximum upward displacement of 100 km was observed in the ionosphere. This work provides a new perspective for understanding the strong ionospheric oscillation caused by geological hazards observed on Earth.

The Super Dual Auroral Radar Network (SuperDARN) currently consists of more than thirty high-frequency (HF, 3–30 MHz) radars covering mid-latitude to polar regions in both hemispheres. Their major task is to map ionospheric plasma circulation which provides information about the interactions between the solar wind and the near-Earth’s space plasma environment. One of the major factors defining radar data quality is the signal-to-noise ratio (SNR), which requires an accurate characterisation of the HF noise. The standard SuperDARN data analysis software uses the SNR as part of a set of empirical procedures designed to remove low-quality data from further analysis. In this study we found that the currently used empirical algorithm systematically underestimates the noise level by up to 40%. Based on comparison of theoretical and observational noise statistics, we resolve this issue by designing and validating a procedure for accurate background noise level estimation. We then propose a simple SNR threshold to replace the existing criteria for excluding low-quality data. In addition, we show that several aspects of the radar operational regime design, as well as short-lived anthropogenic radio interference, can adversely affect the quality of the noise estimates at selected radar sites, and we propose ways to mitigate these problems.

An interplanetary shock can abruptly compress the magnetosphere, excite magnetospheric waves and field-aligned currents, and cause a ground magnetic response known as a sudden commencement (SC). However, the transient (<~1 min) response of the ionosphere-thermosphere system during an SC has been little studied due to limited temporal resolution in previous investigations. Here, we report observations of a global reversal of ionospheric vertical plasma motion during an SC on 24 October 2011 using ~6 s resolution SuperDARN ground scatter data. The dayside ionosphere suddenly moved downward during the magnetospheric compression due to the SC, lasting for only ~1 min before moving upward. By contrast, the post-midnight ionosphere briefly moved upward then moved downward during the SC. Simulations with a coupled geospace model suggest that the reversed E X B vertical drift is caused by a global reversal of ionospheric zonal electric field induced by magnetospheric compression during the SC.

Over–the–Horizon (OTH) communication is strongly dependent on the state of the ionosphere, which is susceptible to solar flares. Trans–ionospheric high frequency (HF) signals experience a strong attenuation following a solar flare, commonly referred to as Short–Wave Fadeout (SWF). In this study, we examine the role of dispersion relation–collision frequency formulations on the estimation of flare–driven HF absorption seen in Riometer observation using a data assimilation framework. Specifically, the framework first uses modified solar irradiance models (such as EUVAC, FISM), which incorporate high–resolution solar flux data from GOES satellite X-ray sensors, to compute the enhanced ionization produced during the flare events. The framework then uses different dispersion relation–collision frequency formulations to estimate enhanced HF absorption. Finally, the modeled HF absorption is compared against the data to determine which combination of dispersion relation–collision frequency formulation best reproduces the Riometer observations. From the modeling work, we find that the Appleton–Hartree dispersion relation in combination with Schunk–Nagy collision frequency profile produces the best agreement with Riometer data.