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

Abstract

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.

ARTIST Ionogram Autoscaling Confidence Scores: Best Practices

“…Finally, for hmF2, confidence scores of 75, 80, 90, and 95 provide excellent skill with respect to climatology, but all other scores provide limited skill improvement or, in the case of scores 0, 40, and 55, actively produce worse estimates of hmF2 than the climatological IRI. Circumstances like this may account for some of the reduced performance of the Real Time IRI (IRTAM), which assimilates these GIRO data, with respect to the climatological IRI in terms of hmF2 found in [14].…”

A‐CHAIM: Near‐Real‐Time Data Assimilation of the High Latitude Ionosphere With a Particle Filter

“…This is problematic, as the distribution of ionosondes is severely limited at high latitudes, and this approach precludes using more widely distributed GNSS data. Pignalberi et al (2021) show that while IRTAM improves the representation of foF2 in the regions covered by data, it degrades performance in regions away from the ionosondes. Its reliance on ionosonde data also results in limited performance in hmF2, not just in regions away from data, but also in their vicinity.…”

The International Reference Ionosphere Model: A Review and Description of an Ionospheric Benchmark

“…An assessment of the plasmaspheric contribution to vTEC was presented by Cherniak and Zakharenkova (2016). Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation (RO) data have been used for global modeling of hm F2 (Shubin, 2015) and there have also been many comparisons of the IRI electron density F2‐peak parameters with RO data from COSMIC and other satellites (e.g., H. Huang et al., 2021; Moses et al., 2021; Pignalberi, Pietrella, & Pezzopane, 2021). However, the inherent assumption of spherical symmetry makes RO analysis difficult in regions of sharp gradients as for example, the equatorial ionization anomaly (EIA) region (e.g., Wu et al., 2009; Yue et al., 2010).…”

“…Pignalberi, Pietrella, and Pezzopane (2021) performed a detailed comparison between IRI and IRTAM, based on the F2‐layer peak characteristics fo F2 and hm F2 recorded by 40 ground‐based ionosondes spread all over the world from 2000 to 2019 and from COSMIC satellites from 2006 to 2018. The main outcome of their study is that nearby the assimilated ionosonde locations, IRTAM improves the IRI fo F2 and hm F2 modeling, especially fo F2, while away from the participating stations, the IRI and IRTAM outputs for fo F2 are similar and the IRI hm F2 description is always more accurate and precise than the IRTAM one.…”

“…A large availability of data at mid latitudes assures a corresponding good accuracy, while the performance is not so good in regions at high (auroral and polar) and low (equatorial) latitudes, where the data availability is not comparable to that at mid latitudes. Model accuracy is also affected by the hemispheric imbalance in ground station coverage, with a much denser network of stations in the Northern hemisphere (Arikan et al., 2019; Pignalberi, Pietrella, & Pezzopane, 2021). The next section discusses the most important data sources for the IRI model development.…”