Direct Forcing of the Collisional Auroral Ionosphere by Kinetic Alfvén Turbulence

TL;DR

This work investigates how magnetospheric forcing imprints a kinetic Alfvén turbulence cascade in the collisional auroral ionosphere, spanning scales from ~20 m to ~100 km. By constructing a novel composite power spectrum from icebear radar and GPS phase fluctuations, the authors reveal a $P(k) \propto k^{-8/3}$ scaling that persists as the turbulence propagates into the E-region and is modulated by precipitating electron flux. Across multiple conjunctions with Swarm and Arase spacecraft, the spectral slope steepens with energy input, echo altitudes cluster near 102 km, and low-altitude turbulence reaches down to ~80 km, indicating a coupling between magnetospheric drivers and low-altitude instabilities. The study proposes a dual forcing-seeding mechanism, where structured precipitation and dispersive Alfvén waves seed and sustain turbulence while collisional damping and electron heating regulate the cascade, offering a potential proxy for space weather dynamics.

Abstract

The structure of the auroral ionosphere is ascribed to local plasma instabilities. However, we report turbulence extending below 90 km altitude, where particle collisions act to stabilize the plasma. Using a composite radar-GPS spectrum, we resolve a scale-invariant cascade in the 80 km-120 km altitude layer. We identify a characteristic kinetic Alfvénic k^{-8/3} scaling, spanning four orders of magnitude in k, that tracks precipitating energy flux. This reveals a chemical and electric imprint of magnetohydrodynamic turbulence, seeding and driving local instability processes.

Figures (6)

• Figure 1: A space-ground conjunction between the icebear radar and the inner-magnetosphere spacecraft Arasemiyoshi_erg_2018miyoshi_geospace_2018, that took place on 13 March 2021. Panel a) shows auroral images from the trex rgbgilliesApparentMotionSTEVE2020 all-sky-imager at Rabbit Lake, with radar echo locations in red and Arase's ionospheric footprint as a cyan star. Panel b) shows the upper and lower envelope of the electrojet index, demonstrating the onset of a moderate magnetospheric substorm newellSubstormMagnetosphereCharacteristic2011. Panel c) shows the combined precipitating electron energy flux through the LEP-e kazama_low-energy_2017-1, MEP-e kasahara_medium-energy_2018, and HEP mitani_high-energy_2018 instruments (pitch-angles lower than 5$^\circ$ and $10^\circ$), which we take as a proxy for the real precipitating energy flux). Panel d) compares the inferred ionization altitude profile from Arase (green), based on the accumulative precipitating energy flux through the interval, with the altitude distribution of radar echoes superposed (black), ignoring echoes with extreme azimuths, whose altitudes are anomalous ivarsenAlgorithmSeparateIonospheric2023. Panel e) shows the median precipitating electron spectra, while panel f) show altitude-time-intensity point-clouds of echoes, color-coded by signal-to-noise ratio (SNR). Green and black lines indicate the peak ionization altitude (thick line) and a single standard deviation (thin lines). See the Supplementary Materials for an additional eight such conjunctions.
• Figure 2: Panel a) shows the average composite spectrum for the five-minute interval starting at 11:06 UT on 6 May 2023 (Black line). The normalized spectrum of eastward magnetic fluctuations measured by Swarm C is shown with a green line. A five-component piecewise log-log linear fit is shown above the spectra (solid red line) while a single-slope fit is shown below the spectrum (dashed red line). Spectral indices are indicated in red lettering while two prominent spatial scales (break-points) are indicated with black lettering. Panel b) shows eastward magnetic (red, right axis) and northward electric (black, left axis) fields measured by Swarm A five minutes later ('$\rho$' being Pearson correlation), while panel c) shows the coherence between the two signals. Panel d) shows the composite icebear-chain spectrum measured during the 17-minute interval starting at 13:02 UT on 2 August 2023, akin to panel a). Panel e) shows the average precipitating electron spectrum measured by Arase during the interval, while panel f) shows (in green) the plasma density column created by the particles, using the E-CHAIM model themensEmpiricalCanadianHigh2017. Panel g) shows timeseries of spectral index values measured by icebear (red) and chain (green) individually during the interval 13:02 UT--13:19 UT, segmented in 1-minute bins. On the right axis we show the observed low-pitch angle ($\leq5^\circ$) flux of electrons measured in the $6$ keV channel of the low-energy particle detector onboard Arase, and '$\rho$' indicates Pearson correlation at zero lag. See Figures S2 and S3 in the Supplementary Materials for furtehr details.
• Figure 3: Panel a) shows all 10 composite icebear-chain spectra (solid black line), with a linear log-log fit (black dashed line) and a -8/3-slope (red dashed line) indicated. Panel b) compare the icebear-chain spectra (green line) with a statistical aggregate of 7,700 icebear echo clustering spectra (red line) observed during 2020, 2021 (the database that was analyzed in Ref. ivarsenMeasuringSmallscalePlasma2023). Panel c) shows the median distributions in HR radar Doppler speeds, while panel d) treats echo altitudes. A green line in panel d) indicates the assumed GPS pierce-point locations (with shaded green region giving upper/lower quartile distributions), whereas a green line in panel c) shows the derived phase screen speed.
• Figure 4: Panel a) shows a sample 6-second radar point-cloud cluster, while Panel b) shows the two-point correlation function based on that point-cloud (Eq. \ref{['eq:twopoint']})
• Figure 5: Example phase (green), IFLC (black), and TEC (red) spectra, with a piecewise linear fit shown with a blue line, and with the Fresnel scale (wavenumber) shown with a red, dashed line.