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Electron density irregularities in the ionosphere can give rise to scintillations, affecting radio wave phase and amplitude. While scintillations in the cusp and polar cap regions are commonly associated with mesoscale density inhomogeneities and/or shearing, the auroral regions exhibit a strong correlation between scintillation and density structures generated by electron precipitation (arcs). We aim to examine the impact of electron precipitation on the formation of scintillation‐producing density structures using a high‐resolution physics‐based plasma model, the “Geospace Environment Model of Ion‐Neutral Interactions,” coupled with a radio propagation model, the “Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere.” Specifically, we explore the effects of varying spatial and temporal characteristics of the precipitation, including electron total energy flux and their characteristic energies, obtained from the all‐sky‐imagers and Poker Flat Incoherent Scatter Radar observations, on auroral scintillation. To capture small‐scale structures, we incorporate a power‐law turbulence spectrum that induces short wavelength features sensitive to scintillation. Finally, we compare our simulated scintillation results with satellite‐observed scintillations, along with spectral comparisons.

 

We present a binary hypothesis test for detecting clear sky in auroral all‐sky images based on single‐wavelength keograms. The coefficient of variationc, the ratio of the sample standard deviation to the mean over elevation angle along the meridian, is the test statistic. After image‐correcting keograms and excluding dark sky intervals, detection performance is compared to true conditions as determined by Advanced Very High Resolution Radiometer satellite imagery. The cloud mask, an index of cloud cover, is selected at the corresponding nearest time and location to the site of a meridian spectrograph at Poker Flat Research Range. With training data from 2014 to 2016, theoretical Rayleigh distributions fit to the histograms show a decision threshold of 0.40 could yield an accuracy of about 80%. Separately, we numerically compute the false alarm and missed detection statistics of the greenline 557.7 nm emission and of the redline 630.0 nm emission. We find a threshold of 0.25 for the greenlinecmaximizes the percent of events correctly identified at 76%. Applied to testing data from 2015 to 2017, the 0.25 threshold yields an accuracy of 68%. Diffuse aurora can have coefficient of variation around 0.2 to 0.5, which would be included by the numerical minimum, but partly excluded by the theoretical model obtained. Numerical results are a few percent worse for the redline emission.

 

Electron density irregularities in the ionosphere modify the phase and amplitude of trans-ionospheric radio signals. We aim to characterize the spectral and morphological features of E- and F-region ionospheric irregularities likely to produce these fluctuations or “scintillations”. To characterize them, we use a three-dimensional radio wave propagation model—“Satellite-beacon Ionospheric scintillation Global Model of upper Atmosphere” (SIGMA), along with the scintillation measurements observed by a cluster of six Global Positioning System (GPS) receivers called Scintillation Auroral GPS Array (SAGA) at Poker Flat, AK. An inverse method is used to derive the parameters that describe the irregularities by estimating the best fit of model outputs to GPS observations. We analyze in detail one E-region and two F-region events during geomagnetically active times and determine the E- and F-region irregularity characteristics using two different spectral models as input to SIGMA. Our results from the spectral analysis show that the E-region irregularities are more elongated along the magnetic field lines with rod-shaped structures, while the F-region irregularities have wing-like structures with irregularities extending both along and across the magnetic field lines. We also found that the spectral index of the E-region event is less than the spectral index of the F-region events. Additionally, the spectral slope on the ground at higher frequencies is less than the spectral slope at irregularity height. This study describes distinctive morphological and spectral features of irregularities at E- and F-regions for a handful of cases performed using a full 3D propagation model coupled with GPS observations and inversion. 

In this work we enable the data assimilation algorithm Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE) to estimate global neutral winds. EMPIRE corrects the ion drifts and neutral winds from background models using electron density in the F region derived mainly from total electron content measurements. The new EMPIRE basis functions for the neutral winds are vector spherical harmonics, enforcing the field to be smooth and continuous globally. Global basis functions allow us to estimate the horizontal wind vector from time‐varying plasma densities. The geomagnetic storm on 25 October 2011 is studied to investigate the global implementation of neutral wind estimation. During this storm, the estimates are also compared to those of the old method of estimation using power series and to Fabry‐Perot interferometer (FPI) measurements for validation at three different sites: Pisgah, Cariri, and Nasca. The new global estimation is 10%–20% closer to the FPI measurements than the model and than the old method for most of the viewing directions of the sites, in terms of root‐mean‐square residuals. In the northward direction at Pisgah the estimates using either the old or new implementation disagree with the model, and might be related to an insufficiently small temporal scale used in EMPIRE.

 

This paper surveys six years of Global Positioning System (GPS) L1 and L2C ionospheric scintillation in the auroral zone and, with a collocated incoherent scatter radar, hypothesizes the ionospheric irregularity layer. The Scintillation Auroral GPS Array of six scintillation receivers is sited at Poker Flat Research Range, Alaska, as is the Poker Flat incoherent scatter radar (PFISR). Scintillation intervals are identified across at least four receivers of the array using S4 and sigma phi (σ_ϕ) indices at 100 s cadence. Classification as “amplitude,” “phase,” or “both‐phase‐and‐amplitude” scintillation is performed by analyzing common time intervals of elevated S4 andσ_ϕ. Scattering of Global Navigation Satellite System (GNSS) waves by refractive or diffractive effects is hypothesized to occur in the E or F layer, or a transition layer in between, based on the PFISR peak density altitude at the time of the scintillation event. We analyze the statistics of the irregularity layer from 2014 to 2019, spanning solar maximum to solar minimum. We find fewer scintillation events per day with the waning solar cycle, nearly all of them phase scintillations. We also find that the percentage of events hypothesized to be caused by irregularities in the E layer increases with the declining solar cycle. The local time dependence of phase scintillations is primarily at night and in the E layer. Phase scintillation events occurring during daytime occur at solar maximum and are nearly all in the F layer. The majority of the events containing amplitude scintillations are daytime F layer at solar maximum (2014).