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Anomalous long distance reports of Automatic Identification System (AIS) shipping transmissions were received by a United States Coast Guard terrestrial monitoring network in the eastern United States and Puerto Rico. 6677 signals were identified from ships located over 1000-km from the ground stations between 13 and 14 July 2021, with almost no long-distance links received at night or at any time on 15 July. The cause appears to be sporadic-E layers identified by Digisonde and satellite radio occultation data. The density of these layers cannot be accurately determined, but might exceed 27 MHz, or 9x1012 el. m3. AIS transmissions potentially provide an excellent means of identifying dense sporadic-E layers globally.

We investigate the response of the mid-latitude thermospheric neutral winds to a sub-auroral polarisation stream (SAPS) event. Using red-line (F-region) airglow data from two Fabry-Perot interferometers (FPIs), and F-region ionospheric flow velocities from four Super Dual Auroral Radar Network (SuperDARN) radars, the drivers behind changes seen in the neutral winds are explored within the context of the larger SAPS structure. Different, although strong, neutral wind responses to the SAPS are seen at the two FPI sites, even though they are relatively close geographically. We attribute the wind differences to the varying balance of pressure gradient, ion-drag, and Coriolis forces, which ultimately depend on proximity to the SAPS. At the FPI site equatorward of the SAPS, pressure-gradient and Coriolis forces drive the winds equatorward and then westward. At the FPI site co-located with the SAPS, ion-drag is strong and results in the winds surging westward, before turning eastward when becoming influenced by dawnside sunward plasma convection drifts.

During extreme ionospheric storms, plasma behaves very differently than current physics models predict, such as by forming a nighttime ionospheric localized enhancement (NILE). Aiming to decrease the gap between the real measurements and background model estimation, we propose using a data assimilation tool: Estimating Model Parameters Reverse Engineering (EMPIRE) with Kalman filter implementation to ingest ion drift measurements to enable the estimation of electric potential and neutral winds. In this preliminary work, we show results for one storm-time event of EMPIRE estimating global winds and electric potential when augmenting the linear system of observations with measurements of LOS ion drift. We first assimilate Global Navigation Satellite System (GNSS)-based total Electron Content (TEC) measurements with the Sami3 is Another Model of the Ionosphere (SAMI3) first-principles background using the Ionospheric Data Assimilation 4-Dimensional (IDA4D) algorithm. IDA4D yields estimates of plasma density globally at 3-degree resolution and at 5-minute intervals. We then time difference the plasma densities and assimilate those, plus observations of ion drifts speeds from incoherent scatter radar (ISR) located at Massachusetts institute of Technology (MIT) Haystack Observatory. We compare the difference in results between a solution that does not assimilate ion drift (relying on density rates alone versus a solution that does assimilate the ion drift). Three analysis locations are selected: the location of ISR, the location of the NILE, and a site near the magnetic equator along the same longitude line. From the assimilated results, we show that new augmentation of ion velocity measurements impacts the estimated ion motions at all three locations. Further investigation is required to determine the extent to which the ingestion improves the estimation.

A new technique has been developed in which the high-latitude electric potential is determined from field-aligned current observations from the Active Magnetosphere and Planetary Electrodynamics Re...

The Ionospheric Data Assimilation Four-Dimensional (IDA4D) technique has been coupled to Sami3 is Another Model of the Ionosphere (SAMI3). In this application, ground- 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.

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.

We present the first observations from a new low-cost oblique ionosonde located in Antarctica. The transmitter is located at McMurdo Station, Ross Island, and the receiver at Amundsen–Scott Station, South Pole. The system was demonstrated successfully in March 2019, with the experiment yielding over 30 000 ionospheric echoes over a 2-week period. These data indicate the presence of a stable E layer and a sporadic and variable F layer with dramatic spread F of sometimes more than 500 km (in units of virtual height). The most important ionospheric parameter, NmF2, validates well against the Jang Bogo Vertical Incidence Pulsed Ionospheric (VIPIR) ionosonde (observing more than 1000 km away). GPS-derived TEC data from the Multi-Instrument Data Analysis Software (MIDAS) algorithm can be considered necessary but insufficient to predict 7.2 MHz propagation between McMurdo and the South Pole, yielding a true positive in 40 % of cases and a true negative in 73 % of cases. The success of this pilot experiment at a total grant cost of USD 116 000 and an equipment cost of ∼ USD 15 000 indicates that a large multi-static network could be built to provide unprecedented observational coverage of the Antarctic ionosphere.

We present the first observations from a new low-cost oblique ionosonde located in Antarctica. The transmitter is located at McMurdo Station, Ross Island and the receiver at Amundsen-Scott Station, South Pole. The system was demonstrated successfully in March 2019, with the experiment yielding over 30 000 ionospheric echoes over a two-week period. These data indicate the presence of a stable E-layer and a sporadic and variable F-layer with dramatic spread-F of sometimes more than 500 km (in units of virtual height). The most important ionospheric parameter, NmF2, validates well against the Jang Bogo VIPIR ionosonde (observing more than 1000 km away). GPS-derived TEC data from the MIDAS algorithm can be considered necessary but insufficient to predict 7.2 MHz propagation between McMurdo and South Pole, yielding a true positive in 40 % of cases and a true negative in 73 % of cases. The success of this pilot experiment at a total grant cost of $116k and an equipment cost of ~$15k indicates that a large multi-static network could be built to provide unprecedented observational coverage of the Antarctic ionosphere.

Past extreme geomagnetic storms have been known to produce not only dayside storm-enhanced density (SED) and SED plumes, but also in a number of cases an nighttime ionospheric localized enhancement (NILE), also known as the “Florida effect.” In this work, we apply data assimilation to adjust a background model to better capture the NILE enhancement. We use the SAMI3 (SAMI3 is Another Model of the Ionosphere) model for an extreme storm as the background model in Ionospheric Data Assimilation 4-Dimensional (IDA4D) to produce plasma density estimates across the NILE feature. IDA4D ingests GPS-based total electron content (TEC) to reconstruct ionospheric plasma densities over space and time. Simulating the November 20-21, 2003, extreme geomagnetic storm, we show that the SAMI3 model alone underestimates the magnitude of positioning errors for fictitious receivers in the Caribbean, Gulf coast, and Rocky Mountains, subjected to the dayside SED by as much as a factor of 3. During the nighttime data assimilation of SAMI3 with IDA4D shows uplift in the peak densities. The day following the storm shows a negative phase (depressed TEC) relative to SAMI3 alone.

Thermospheric winds and temperatures must be correctly specified to understand the impacts of lower atmosphere processes on the upper atmosphere and to measure the global effects of high-latitude magnetospheric processes. Fabry-Perot interferometers can estimate these parameters by measuring the characteristic 630.0 nm emission that is produced at around 250 km altitude. These sophisticated instruments exist at only a few locations globally, so models are often employed to provide wind and temperature estimates elsewhere. This study is composed of two parts. First, observing system simulation experiments estimate the accuracy of Fabry-Perot interferometer observations using the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM) and the Whole Atmosphere Community Climate Model eXtended (WACCM-X). Atmospheric observational error sources are found to be very small across two test periods (September 2000 and September 2010) and using two different “truth” models. The largest magnitude wind observation error is found to be 16.9 m/s, root-mean-square errors are 2.3 m/s, and the bias is 0.9 m/s. The largest-magnitude temperature observation error is found to be 63.7 K, root-mean-square errors over the test period are 6.7 K, and the bias is 2.8 K. Modeled redline emission altitudes vary by over 100 km, far more than was expected. Second, several models (TIEGCM, WACCM-X, the Horizontal Wind Model, and the Mass Spectrometer Incoherent Scatter model) are assessed using interferometer winds and temperatures from Cariri and Cajazeiras, Brazil, as ground truth. In the best cases, the models reproduce wind variability without systematic biases but show no ability to predict instantaneous values, although temperatures are modeled more accurately.

Global Navigation Satellite System (GNSS) signals exhibit rapid fluctuations at high and low latitudes as a consequence of propagation through drifting ionospheric irregularities. We focus on the high latitude scintillation problem, taking advantage of a conjunction of EISCAT Incoherent Scatter Radar (ISR) observations and a GPS scintillation monitor viewing the same line-of-sight. Just after 20:00 UT on 17 October 2013, an auroral E-region ionization enhancement occurred with associated phase scintillations. This investigation uses the scintillation observations to estimate the ionospheric electron density distribution beyond the spatial resolution of the ISR (5 - 15 km along the line-of-sight in this case). Following the approach of Deshpande et al. [2014], signal propagation is modeled through a specified density distribution. A multiple phase screen propagation algorithm is applied to irregularities conforming to the description of Costa and Kelley [1977] and constrained to match the macroscopic conditions observed by the ISR. A 50-member ensemble of modeled outputs is approximately consistent with the observations according to the standard deviation of the phase (σp). The observations have σp = 0.23 radians, while the ensemble of modeled realizations has σp = 0.23 + 0.04 -0.04. By comparison of the model output with the scintillation observations, we show that the density fluctuations cannot be a constant fraction of the mean density. The model indicates that E-region density fluctuations whose standard deviation varies temporally between 5 - 25% of the mean (ISR-observed) density are required to explain the observed phase scintillations.

Data assimilation in conventional meteorological applications uses measurements in conjunction with a physical model. In the case of the ionised region of the upper atmosphere, the ionosphere, assimilation techniques are much less mature. The empirical model known as the International Reference Ionosphere (IRI) could be used to augment data-sparse regions in an ionospheric now-cast and forecast system. In doing so, it is important that it does not introduce systematic biases to the result. Here, the IRI model is compared to ionospheric observations from the Global Positioning System satellites over Europe and North America. Global Positioning System data are processed into hour-to-hour monthly averages of vertical Total Electron Content using a tomographic technique. A period of twelve years, from January 1998 to December 2009, is analysed in order to capture variations over the whole solar cycle. The study shows that the IRI model underestimates Total Electron Content in the daytime at solar maximum by up to 37% compared to the monthly average of GPS tomographic images, with the greatest differences occurring at the equinox. IRI shows good agreement at other times. Errors in TEC are likely due to peak height and density inaccuracies. IRI is therefore a suitable model for specification of monthly averages of Total Electron Content and can be used to initialise a data assimilation process at times away from solar maximum. It may be necessary to correct for systematic deviations from IRI at solar maximum, and to incorporate error estimation into a data assimilation scheme.

The Multi Instrument Data Analysis system, MIDAS is an algorithm that images the ionosphere in three or four dimensions and was originally developed by Mitchell and Spencer (2003) [1]. MIDAS often operates using GPS measurements of slant Total Electron Content, but Chartier et al. [2012] [2] showed that incorporating ionosonde data into the algorithm could improve imaging of the ionosphere in the vertical dimension. Here we extend the technique to incorporation of multiple ionosondes, the key problem is to transition horizontally between regions of different peak height and changing densities. This approach is validated via comparisons with independent satellite data.

The impact of space weather events on satellitebasedtechnologies (e.g. satellite navigation and precise positioning)is typically quantified on the basis of the total electroncontent (TEC) and temporal fluctuations associated withit. GNSS (global navigation satellite systems) TEC measurementsare integrated over a long distance and thus may includecontributions from different regions of the ionised atmospherewhich may prevent the resolution of the mechanismsultimately responsible for given observations. The purposeof the experiment presented here was to compare TECestimates from EISCAT and GPS measurements. The EISCATmeasurements were obtained along the same line ofsight of a given GPS satellite observed from Tromsø. Thepresent analyses focussed on the comparison of temporalfluctuations in the TEC between aligned GPS and EISCATmeasurements. A reasonably good agreement was found betweentemporal fluctuations in TEC observed by EISCATand those observed by a co-located GPS ionospheric monitoralong the same line of sight, indicating a contributionfrom structures at E and F altitudes mainly to the total TECin the presence of ionisation enhancements possibly causedby particle precipitation in the nighttime sector. The experimentsuggests the great potential in the measurements to beperformed by the future EISCAT 3D system, limited only inthe localised geographic region to be covered.

[1] A new technique is presented for the incorporation of ionosonde observations into GPS ionospheric tomography. This approach greatly improves the vertical resolution of the images when using independent incoherent scatter radar observations as ground truth, addressing a traditional weakness of tomographic techniques. Ionosonde observations are used to set vertical basis functions adaptively within the inversion as well as providing electron density information for direct assimilation. The technique also improves slant total electron content (TEC) accuracy in the vicinity of the ionosonde. An experiment was performed in the equatorial region of South America as a 6-day case study due to the availability of incoherent scatter and ionosonde data during this period. Preliminary results were validated with the Jicamarca incoherent scatter radar and independent GPS slant TEC observations. Using the incoherent scatter radar as ground truth for the vertical profile, the new technique reduces mean NmF2 error to −0.07 × 1011 electrons/m3 compared with 0.27 × 1011 electrons/m3 in a control run with no ionosonde data, while root-mean square error is now 0.5 × 1011 electrons/m3 compared with 1.0 × 1011 electrons/m3 in the control. The new technique also results in 0.1 km mean error in hmF2, compared with −3.9 km in the control, while root-mean square hmF2 error is around 40 km in both cases. Using independent slant TEC observations, the mean error is −0.36 TECU compared with 0.64 TECU in the control run, while root-mean square error is 3.55 TECU down from 4.02 TECU, suggesting the new technique also improves TEC values.