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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.

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.

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.