Recurrent high-speed solar wind co-rotating interaction region imprint on the ionosphere and atmosphere: GPS TEC variations and atmospheric gravity waves
Bibliographic record
Abstract
High-speed streams (HSS) from coronal holes dominate solar wind structure in the absence of coronal mass ejections during solar minimum and the descending branch of solar cycle. Prominent and long-lasting coronal holes produce intense co-rotating interaction regions (CIR) on the leading edge of high-speed plasma streams that cause recurrent ionospheric disturbances and geomagnetic storms. Through solar wind coupling to the magnetosphere-ionosphere-atmosphere (MIA) system they affect the ionosphere and neutral atmosphere at high latitudes, and, at mid to low latitudes, by the transmission of the electric fields [1] and propagation of atmospheric gravity waves from the high-latitude lower thermosphere [2]. The high-latitude ionospheric structure, caused by precipitation of energetic particles, strong ionospheric currents and convection, results in changes of the GPS total electron content (TEC) and rapid variations of GPS signal amplitude and phase, called scintillation [3]. The GPS phase scintillation is observed in the ionospheric cusp, polar cap and auroral zone, and is particularly intense during geomagnetic storms, substorms and auroral breakups. Phase scintillation index is computed for a sampling rate of 50 Hz by specialized GPS scintillation receivers from the Canadian High Arctic Ionospheric Network (CHAIN). A proxy index of phase variation is obtained from dual frequency measurements of geodetic-quality GPS receivers sampling at 1 Hz, which include globally distributed receivers of the RT-IGS network that are monitored by the Canadian Geodetic Survey in near-real-time [4]. Temporal and spatial changes of TEC and phase variations following the arrivals of HSS/CIRs [5] are investigated in the context of ionospheric convection and equivalent ionospheric currents derived from a ground magnetometer network using the spherical elementary current system method [6,7]. The Joule heating and Lorentz forcing in the high-latitude lower thermosphere have long been recognized as sources of internal atmospheric gravity waves (AGWs) [2] that propagate both upward and downward, thus providing vertical coupling between atmospheric layers. In the ionosphere, they are observed as traveling ionospheric disturbances (TIDs) using various techniques, e.g., de-trended GPS TEC maps [8]. In this paper we examine the influence on the Earth’s ionosphere and atmosphere of a long-lasting HSS/CIRs from recurrent coronal holes at the end of solar cycles 23 and 24. The solar wind MIA coupling, as represented by the coupling function [9], was strongly increased during the arrivals of these HSS/CIRs. [1] Kikuchi, T. and K. K. Hashimoto, Geosci. Lett. , 3:4, 2016. [2] Hocke, K. and K. Schlegel, Ann. Geophys., 14, 917–940, 1996. [3] Prikryl, P., et al., J. Geophys. Res. Space Physics, 121, 10448–10465, 2016. [4] Ghoddousi-Fard et al., Advances in Space Research, 52(8), 1397-1405, 2013. [5] Prikryl et al. Earth, Planets and Space, 66:62, 2014. [6] Amm O., and A. Viljanen, Earth Planets Space, 51, 431–440, 1999. [7] Weygand J.M., et al., J. Geophys. Res., 116, A03305, 2011. [8] Tsugawa T., et al., Geophys. Res. Lett., 34, L22101, 2007. [9] Newell P. T., et al., J. Geophys. Res., 112, A01206, 2007.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".