On the Electron Temperature in the Topside Ionosphere as Seen by Swarm Satellites, Incoherent Scatter Radars, and the International Reference Ionosphere Model

The global statistical median behavior of the electron temperature (Te) in the topside ionosphere was investigated through in-situ data collected by Langmuir Probes on-board the European Space Agency Swarm satellites constellation from the beginning of 2014 to the end of 2020. This is the first time that such an analysis, based on such a large time window, has been carried out globally, encompassing more than half a solar cycle, from the activity peak of 2014 to the minimum of 2020. The results show that Swarm data can help in understanding the main features of Te in the topside ionosphere in a way never achieved before. Te data measured by Swarm satellites were also compared to data modeled by the empirical climatological International Reference Ionosphere (IRI) model and data measured by Jicamarca (12.0°S, 76.8°W), Arecibo (18.2°N, 66.4°W), and Millstone Hill (42.6°N, 71.5°W) Incoherent Scatter Radars (ISRs). Moreover, the correction of Swarm Te data recently proposed by Lomidze was applied and evaluated. These analyses were performed for two main reasons: (1) to understand how the IRI model deviates from the measurements; and (2) to test the reliability of the Swarm dataset as a new possible dataset to be included in the underlying empirical dataset layer of the IRI model. The results show that the application of the Lomidze correction improved the agreement with ISR data above all at mid latitudes and during daytime, and it was effective in reducing the mismatch between Swarm and IRI Te values. This suggests that future developments of the IRI Te model should include the Swarm dataset with the Lomidze correction. However, the existence of a quasi-linear relation between measured and modeled Te values was well verified only below about 2200 K, while for higher values it was completely lost. This is an important result that IRI Te model developers should properly consider when using the Swarm dataset.

A Global Empirical Model of the Ion Temperature in the Ionosphere for the International Reference Ionosphere

This study presents a suggestion for improvement of the ion temperature (Ti) model in the International Reference Ionosphere (IRI). We have re-examined ion temperature data (primarily available from NASA’s Space Physics Data Facility (SPDF)from older satellites and combined them with newly available data from the Defense Meteorological Satellite Program (DMSP), the Communication Navigation Outage Forecasting System (C/NOFS), and from the recently launched Ionospheric Connection Explorer (ICON). We have compiled these data into a unified database comprising in total Ti data from 18 satellites. By comparisons with long term records of ion temperature from the three incoherent scatter radars (ISRs) (Jicamarca, Arecibo, and Millstone Hill), it was found that an intercalibration is needed to achieve consistency with the ISR data and among individual satellite data sets. This database with thus corrected data has been used for the development of a new global empirical model of Ti with inclusion of solar activity variation. This solar activity dependence is represented by an additive correction term to the Ti global pattern. Due to the limited data coverage at altitudes above 1000 km, the altitude range described by the model ranges from 350 km to 850 km covering only the region where generally Ti is higher than the neutral temperature (Tn) and lower than the electron temperature (Te). This approach is consistent with the current description of Ti in the IRI model. However, instead of one anchor point at 430 km altitude as in the current IRI, our approach includes anchor points at 350, 430, 600, and 850 km. At altitudes above 850 km Ti is merged using a gradient derived from the model at 600 and 850 km, with the electron temperature described by the IRI-2016/TBT-2012 option. Comparisons with the ISR data (Jicamarca, Arecibo, Millstone Hill, and Kharkiv) for high and low solar activity and equinox show that the proposed Ti model captures local time variation of Ti at different altitudes and latitudes better than the current IRI-2016 Ti model.

Towards a Real-Time Description of the Ionosphere: A Comparison between International Reference Ionosphere (IRI) and IRI Real-Time Assimilative Mapping (IRTAM) Models

This paper focuses on a detailed comparison, based on the F2-layer peak characteristics foF2 and hmF2, between the International Reference Ionosphere (IRI), which is a climatological empirical model of the terrestrial ionosphere, and the IRI Real-Time Assimilative Mapping (IRTAM) procedure, which is a real-time version of IRI based on data assimilation from a global network of ionosondes. To perform such a comparison, two different kinds of datasets have been considered: (1) foF2 and hmF2 as recorded by 40 ground-based ionosondes spread all over the world from 2000 to 2019; (2) foF2 and hmF2 from space-based COSMIC/FORMOSAT-3 radio occultation measurements recorded from 2006 to 2018. The aim of the paper is to understand whether and how much IRTAM improves IRI foF2 and hmF2 outputs for different locations and under different diurnal, seasonal, solar and magnetic activity conditions. The main outcomes of the study are: (1) when ionosonde observations are considered for validation, IRTAM significantly improves the IRI foF2 modeling both in accuracy and precision, while a slight improvement in the IRI hmF2 modeling is observed for specific locations and conditions; (2) when COSMIC observations are considered for validation, no noticeable improvement is observed from the IRTAM side for both foF2 and hmF2. Indeed, IRTAM can improve the IRI foF2 description only nearby the assimilated ionosonde locations, while the IRI hmF2 description is always more accurate and precise than IRTAM one.

Predictability of Ionosphere using Assimilative Empirical Model IRTAM

<p>Real-time assimilative <em>empirical </em>models based on the International Reference Ionosphere (IRI) [1], a 3D quiet-time climatology model of the ionospheric plasma density, provide prompt weather specification by adjusting IRI definitions into a better match with the available measurements and geospace activity indicators [2]. The IRI-based Real-Time Assimilative Model (IRTAM) [3] is one of such Real-Time IRI operational ionospheric weather models based on the low-latency sensor inputs from the Global Ionosphere Radio Observatory (GIRO) [4].</p><p>IRTAM leverages predictive properties of the underlying IRI expansion basis formalism [5] that treats dynamics of the ionospheric plasma in terms of its harmonics, both temporal and spatial. It uses Non-linear Error Compensation Technique with Associative Restoration (NECTAR) technique [6] to first detect multi-scale inherent diurnal periodicity of the differences between GIRO measurements and the underlying IRI climatology. Then, under the assumption that variations in time at periodic, planetary-scale <em>Eigen</em> scales (diurnal, half-diurnal, 8-hour, etc.) translate to their spatial properties, it globally interpolates and extrapolates each diurnal harmonic individually. This approach allowed NECTAR to associate observed fragments of the activity at GIRO locations with the unveiling grand-scale weather processes of the matching variability scales, as the ground observatories co-rotate with the Earth.</p><p>Predictive properties of IRTAM are discussed in order to establish the baseline predictability of the ionospheric dynamics that analyzes only the latest 24-hour history of its deviation from the expected behavior. Concepts for the next generation empirical forecast models are outlined that would leverage the same principle of associative restoration to evaluate the geospace activity timeline and its subtle associations with subsequent storm-time behavior of the ionosphere.</p><p><strong>References</strong></p><p>[1] Bilitza, D. (ed.) (1990), International Reference Ionosphere 1990, 155 pages, National Space Science Data Center, NSSDC/WDC-A-R&S 90-22, Greenbelt, Maryland, November 1990.</p><p>[2] Bilitza, D., D. Altadill, V. Truhlik, V. Shubin, I. Galkin, B. Reinisch, and X. Huang (2017), International Reference Ionosphere 2016: From ionospheric climate to real-time weather predictions, Space Weather, 15, 418-429, doi:10.1002/2016SW001593.</p><p>[3] Galkin, I. A., B. W. Reinisch, X. Huang, and D. Bilitza (2012), Assimilation of GIRO Data into a Real-Time IRI, Radio Sci., 47, RS0L07, doi:10.1029/2011RS004952.</p><p>[4] Reinisch, B.W. and I.A. Galkin (2011), Global Ionospheric Radio Observatory (GIRO), Earth Planets Space, vol. 63 no. 4 pp. 377-381, doi:10.5047/eps.2011.03.001</p><p>[5] International Telecommunications Union (2009), ITU-R reference ionospheric characteristics, Recommendation P.1239-2 (10/2009). Retrieved from http://www.itu.int/rec/R-REC-P.1239/en.</p><p>[6] Galkin, I. A., B. W. Reinisch, A. Vesnin, et al., (2020) Assimilation of Sparse Continuous Near-Earth Weather Measurements by NECTAR Model Morphing, Space Weather, 18, e2020SW002463, doi:10.1029/2020SW002463.</p>

Accuracy Analysis of International Reference Ionosphere 2016 and NeQuick2 in the Antarctic

Global navigation satellite system (GNSS) can provide dual-frequency observation data, which can be used to effectively calculate total electron content (TEC). Numerical studies have utilized GNSS-derived TEC to evaluate the accuracy of ionospheric empirical models, such as the International Reference Ionosphere model (IRI) and the NeQuick model. However, most studies have evaluated vertical TEC rather than slant TEC (STEC), which resulted in the introduction of projection error. Furthermore, since there are few GNSS observation stations available in the Antarctic region and most are concentrated in the Antarctic continent edge, it is difficult to evaluate modeling accuracy within the entire Antarctic range. Considering these problems, in this study, GNSS STEC was calculated using dual-frequency observation data from stations that almost covered the Antarctic continent. By comparison with GNSS STEC, the accuracy of IRI-2016 and NeQuick2 at different latitudes and different solar radiation was evaluated during 2016–2017. The numerical results showed the following. (1) Both IRI-2016 and NeQuick2 underestimated the STEC. Since IRI-2016 utilizes new models to represent the F2-peak height (hmF2) directly, the IRI-2016 STEC is closer to GNSS STEC than NeQuick2. This conclusion was also confirmed by the Constellation Observing System for Meteorology Ionosphere and Climate (COSMIC) occultation data. (2) The differences in STEC of the two models are both normally distributed, and the NeQuick2 STEC is systematically biased as solar radiation increases. (3) The root mean square error (RMSE) of the IRI-2016 STEC is smaller than that of the NeQuick2 model, and the RMSE of the two modeling STEC increases with solar radiation intensity. Since IRI-2016 relies on new hmF2 models, it is more stable than NeQuick2.

Investigation of the ionosphere over Antarctica under quiet space weather conditions: results of vertical sounding of the ionosphere September 14–24, 2020

We present observational results of variations in the ionospheric parameters hmF2 and NmF2 over the Ukrainian Antarctic station “Akademik Vernadsky” for magnetically quiet conditions. The results of comparative analysis of observational data and the International Reference Ionosphere-2016 model predictions are presented. The main objective of this study is to investigate the temporal variations of two key ionospheric parameters – the F2 layer peak height and electron density – during very quiet space weather conditions using data of vertical sounding of the ionosphere obtained over the Ukrainian Antarctic station “Akademik Vernadsky” and comparison the observation results with model values. Methods: The temporal variations of the F2 layer peak height and electron density were calculated from ionograms obtained with ionosonde installed at the Ukrainian Antarctic station “Akademik Vernadsky” with subsequent electron density profile inversion. Diurnal variations of hmF2 and NmF2 were calculated using a set of sub-models of the IRI-2016 model for comparison with results of observational studies. Results: We found that for the Antarctic region option of IRI-2016 model for the F2 layer peak height SHU-2015 provides a better fit for hmF2 through the investigated period compare to the AMTB-2013 model predictions. Electron density models (URSI, CCIR) generally well reproduce the observed variations of NmF2 during periods of absence non-standard manifestations of space weather, which are possible for quiet conditions too. Hypotheses regarding the possible reasons for experimental and model differences in variations of NmF2 are discussed. The analysis of effect of geomagnetic storm on September 24, 2020 on NmF2 variations was carried out. Conclusions: The obtained results demonstrate peculiarities of the state of the ionosphere-plasmasphere system over Antarctica under very quiet space weather conditions and provide evaluation of predictive capabilities of modern international reference ionosphere models. New knowledge about the features of electron density variations in the ionosphere for magnetically quiet conditions over the Antarctic region has practical value for specialists which are engaged in the study of the near-Earth space environment, in particular, at high latitudes, and also work on correction of global ionospheric models. Keywords: electron density, F2 layer peak height, ionosonde, quiet space weather, models of the ionosphere, downward plasma flux

Ionospheric Behavior of foF2 over Chinese EIA Region and Its Comparison with IRI-2016

The ionograms, which were recorded by the ionosonde located at Pu’er station (PUR, 22.7° N, 101.05° E, Dip Latitude 12.9° N) in the Southwest of China in the year of 2016, were used to study the ionospheric behavior of the ordinary critical frequency of the F2 layer (foF2) in the region of the northern equatorial ionization anomaly. To verify the performance of the International Reference Ionosphere (IRI) over the Southwest of China, a comparative study of the observed foF2 and the latest version of the International Reference Ionosphere (IRI-2016) was carried out. We found that the foF2 in equinox months is greater than summer and winter. Moreover, a higher frequency of the observed bite-out of foF2 in January and April than other months and the IRI-2016 cannot represent the bite-out of foF2 in diurnal variations. Compared to the observations at Pu’er Station, the IRI-2016 underestimated foF2 for most time of the year. The IRI with the International Radio Consultative Committee (CCIR) option overestimated foF2 is higher than that with the International Union of Radio Science (URSI) option. Furthermore, the normalized root mean square error of foF2 from the IRI-2016 with the CCIR option is less than that with the URSI.