# Towards a Real-Time Description of the Ionosphere:
## 6 Validation Results for _fo_F2 Based on Radio Occultation Observations
Specifically, the actual ionospheric conditions are better represented by IRTAM over those areas where a high concentration of ionosondes is available for data assimilation. Specifically, a clear improvement in the _f_oF2 modeling is observed over Europe, South Africa, North America, and Brazil, where the _RMSPE_ percentage error is remarkably reduced when IRTAM is run. Vice versa, over the oceans, deserts (e.g., Sahara, Gobi, Kalahari) and Antarctica as well, a better performance from the IRI side is observed. These circumstances can explain why the results of Figure 19 show a global balance between the two models. As expected from an assimilative model, IRTAM improves considerably IRI predictions over those regions where it is possible to assimilate a large number of data. However, a little unexpected is the observed situation that IRTAM does not seem to reproduce the IRI background in areas very far away from the assimilation sites, which is a constraint that it is usually requested by an assimilative model (see, for example, [11; 14]). In fact, since IRTAM works on the residuals between measured values and IRI values through NECTAR (see Section 2.2), it should correct the background model close to assimilation sites and relax to the background far away from assimilation sites. This is not the case represented in Figure 20. A possible explanation of this could lay on the global nature of the correction made by IRTAM to URSI coefficients. In fact, even if the diurnal correction is maximum at assimilation sites (Section 2.2), corrected diurnal coefficients are used to calculate the corrected spatial coefficients through the Jones and Gallet procedure; as a consequence, the correction affects the spatial harmonic functions that have a global nature. Because of this, the effect of the correction at one assimilation site can influence also a very distant location. On the one hand, this is a clear advantage because the correction has a global nature and is robust against sporadic data outliers but, on the other hand, the quality of the procedure critically depends on the spatial distribution of assimilation sites. It is clear from Figure 20 that the current Digisondes' global distribution is an important constraint for IRTAM. This accounts for the IRTAM performances that are better at mid latitudes than at low latitudes, as visible in Figures 20-23. Figure 21 shows that IRI and IRTAM _RMSPE_ maps obtained as a function of modify and local time are very similar: (a) both IRI and IRTAM show the best performance during daytime hours at northern high latitudes; (b) a worsening of both IRI and IRTAM performance is detected during the central hours of the day around 30\({}^{\circ}\) N; (c) the highest absolute and percentage errors occur in the latitudinal band (30\({}^{\circ}\) S, 30\({}^{\circ}\) N) around sunrise hours. This last circumstance was somehow expected from the IRI side because, being an empirical climatological model, IRI can have some limitations in describing the variability of the ionospheric characteristics when they present wide variations in a relatively small time window, as is the case at solar terminator hours. Nonetheless, the bottom panel of Figure 21 tells us that between 30\({}^{\circ}\) S and 30\({}^{\circ}\) N IRI performance was noticeably improved by IRTAM around sunrise hours. This fact constitutes a clear evidence of how data assimilation can play a key role in improving _f_oF2 modeling in certain situations. Both models exhibit quite large errors during nighttime at mid-low latitudes, as already evidenced by Jicamarca and Ascension Islands grids (Figures 4-9). Figure 22 shows that from a seasonal point of view the performances of IRI and IRTAM are similar. Both models show most of the problems at low/equatorial latitudes throughout the year, especially in correspondence to the crests of the equatorial ionospheric anomaly, mostly the southern one. For what concerns the northern crest the output of IRI seems to be better than the IRTAM one.