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Abstract As Global Navigation Satellite System electromagnetic waves pass through the ionosphere, especially in auroral zones, ionospheric irregularities cause the waves to scintillate. Identification of the ionosphere scattering layer is an important factor in understanding the cause of scintillation. This work implements two techniques to determine whether signal scattering for Global Positioning System L1 and L2C signals might be in the E‐ or F‐layer. The first technique used is an updated process of Sreenivash et al. (2020, https://doi.org/10.1029/2018RS006779), in which the Poker Flat Incoherent Scatter Radar (PFISR) maximum electron densities and their uncertainties hypothesize the layer in which scattering has occurred. The density‐based method predicts a majority of F‐region scintillation events for 2014, with a majority of E‐region events found for 2015 to 2019. The second technique consists of using the ratio of the 630 (red) to the 428 nm (blue) intensity in optical all‐sky images (ASIs) to hypothesize the scattering layer with ASI. The decision threshold is set to 1.35 based on the GLobal airglOW model. From 2014 to 2018 174 events have both PFISR data and ASIs with clear viewing conditions and alignment to within 25° of magnetic zenith. There is an agreement between the two methods for 128 (74%) events.

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.

The Ionospheric Data Assimilation Four-Dimensional (IDA4D) technique has been coupled to Sami3, which is another model of the ionosphere (SAMI3). In this application, ground-based and space-based GPS total electron content (TEC) data have been assimilated into SAMI3, while in-situ electron densities, autoscaled ionosonde NmF2, and reference GPS stations have been used for validation. IDA4D/SAMI3 shows that night-time ionospheric localized enhancements (NILE) are formed following geomagnetic storms in November 2003 and August 2018. The NILE phenomenon appears as a moderate, longitudinally extended enhancement of NmF2 at 30°-40°N MLAT, occurring in the late evening (20-24 LT) following much larger enhancements of the equatorial anomaly crests in the main phase of the storms. The NILE appears to be caused by upward and northward plasma transport around the dusk terminator, which is consistent with eastward polarization electric fields. Independent validation confirms the presence of the NILE, and indicates that IDA4D is effective in correcting random errors and systematic biases in SAMI3. In all cases, biases and root-mean-square errors are reduced by the data assimilation, typically by a factor of 2 or more. During the most severe part of the November 2003 storm, the uncorrected ionospheric error on a GPS 3D position at 1LSU (Louisiana) is estimated to exceed 34 m. The IDA4D/SAMI3 specification is effective in correcting this down to 10 m., (© 2021. The Authors.)

We show that inter-model variation due to under-constraint by observations impacts the ability to predict material transport in the lower thermosphere. Lagrangian coherent structures (LCSs), indicating regions of maximal separation (or convergence) in a time-varying flow, are derived in the lower thermosphere from models for several space shuttle water vapor plume events. We find that inter-model differences in thermospheric transport manifest in LCSs in a way that is more stringent than mean wind analyses. LCSs defined using horizontal flow fields from the Specified Dynamics version of the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (SD-WACCMX) at 109 km altitude are compared to Global Ultraviolet Imager (GUVI) observations of the space shuttle main engine plume. In one case, SD-WACCMX predicts an LCS ridge to produce spreading not found in the observations. LCSs and tracer transport from SD-WACCMX and from data assimilative WACCMX (WACCMX + DART) are compared to each other and to GUVI observations. Differences in the modeled LCSs and tracer positions appear between SD-WACCMX and WACCMX + DART despite the similarity of mean winds. WACCMX + DART produces better tracer transport results for a July 2006 event, but it is unclear which model performs better in terms of LCS ridges. For a February 2010 event, when mean winds differ by up to 50 m/s between the models, differences in LCSs and tracer trajectories are even more severe. Low-pass filtering the winds up to zonal wavenumber 6 reduces but does not eliminate inter-model LCS differences. Inter-model alignment of LCSs improves at a lower 60 km altitude., (© 2021. The Authors.)

The energetic particle precipitation (EPP) indirect effect (IE) refers to the downward transport of reactive odd nitrogen (NO x  = NO + NO 2 ) produced by EPP (EPP-NO x ) from the polar winter mesosphere and lower thermosphere to the stratosphere where it can destroy ozone. Previous studies of the EPP IE examined NO x descent averaged over the polar region, but the work presented here considers longitudinal variations. We report that the January 2009 split Arctic vortex in the stratosphere left an imprint on the distribution of NO near the mesopause, and that the magnitude of EPP-NO x descent in the upper mesosphere depends strongly on the planetary wave (PW) phase. We focus on an 11-day case study in late January immediately following the 2009 sudden stratospheric warming during which regional-scale Lagrangian coherent structures (LCSs) formed atop the strengthening mesospheric vortex. The LCSs emerged over the north Atlantic in the vicinity of the trough of a 10-day westward traveling planetary wave. Over the next week, the LCSs acted to confine NO-rich air to polar latitudes, effectively prolonging its lifetime as it descended into the top of the polar vortex. Both a whole atmosphere data assimilation model and satellite observations show that the PW trough remained coincident in space and time with the NO-rich air as both migrated westward over the Canadian Arctic. Estimates of descent rates indicate five times stronger descent inside the PW trough compared to other longitudes. This case serves to set the stage for future climatological analysis of NO transport via LCSs., (© 2021. The Authors.)

We introduce and analyze the first data from an array of closely spaced Global Positioning System (GPS) scintillation receivers established in the auroral zone in late 2013 to measure spatial and temporal variations in L band signals at 100-1000 m and subsecond scales. The seven receivers of the Scintillation Auroral GPS Array (SAGA) are sited at Poker Flat Research Range, Alaska. The receivers produce 100 s scintillation indices and 100 Hz carrier phase and raw in-phase and quadrature-phase samples. SAGA is the largest existing array with baseline lengths of the ionospheric diffractive Fresnel scale at L band. With an initial array of five receivers, we identify a period of simultaneous amplitude and phase scintillation. We compare SAGA power and phase data with collocated 630.0 nm all-sky images of an auroral arc and incoherent scatter radar electron precipitation measurements, to illustrate how SAGA can be used in multi-instrument observations for subkilometer-scale studies., Key Points: A seven-receiver Scintillation Auroral GPS Array (SAGA) is now at Poker Flat, Alaska SAGA is the largest subkilometer array to enable phase/irregularities studies Simultaneous scintillation, auroral arc, and electron precipitation are observed.