## 5 Conclusions  
In this study, the main statistical median features of the topside ionosphere \(T_{\rm e}\) were investigated on a global basis through data collected by LPs on-board Swarm satellites from the beginning of 2014 to the end of 2020. Swarm \(T_{\rm e}\) measured data were compared with corresponding values modeled by IRI, and with data measured by Jicamarca, Arecibo, and Millstone Hill ISRs, to evaluate the reliability of both Swarm data and IRI model in the description of the spatial, diurnal, and seasonal trends of \(T_{\rm e}\) in the topside ionosphere. We also investigated the effectiveness of the correction to Swarm \(T_{\rm e}\) values proposed by [PERSON] et al. [24] through comparison with IRI-modeled data and ISRs-measured ones. Specifically, we found that the application of the Lomidze correction:  
* improves the agreement between Swarm data and corresponding ones modeled by IRI when the entire dataset is considered, for every Swarm satellite. This is attested by the average 400 K improvement in the mean residuals between Swarm and IRI after the Lomidze correction application;
* does not alter either the dispersion of Swarm data around the mean and the correlation between Swarm and IRI, due to the linear character of the correction;
* reduces the Swarm data RMSE from about 690-780 K to about 440-530 K, and RRMSE from about 27-29% to about 20-23%, when compared to IRI data;
* generally improves the agreement between Swarm and ISR data. The improvement is particularly evident at Millstone Hill while it is lower at Arecibo and even lower at Jicamarca. Moreover, the correction is more effective during daytime than nighttime;
* does not alter the linear relation trend between measured and modeled \(T_{\rm e}\) values in the range below 2200 K, but it improves the corresponding slope (closer to 1) and intercept (closer to 0) values. The results obtained with ISRs data suggest that the calibration of Swarm \(T_{\rm e}\) data made by [PERSON] et al. [24] is heavily biased towards mid latitudes and daytime hours due to the ISRs dataset they used, and to the fact that they cumulated the data of the three ISRs to derive a single calibration curve. As a consequence, the accuracy of Swarm \(T_{\rm e}\) data would benefit from the inclusion of the latitudinal and diurnal dependence in the calibration procedure. Swarm \(T_{\rm e}\) data are very valuable to study the relative changes of \(T_{\rm e}\), but a more detailed correction is needed to obtain more reliable absolute values of \(T_{\rm e}\) especially at low and equatorial latitudes. Moreover, to better describe the high \(T_{\rm e}\) values, the inclusion of data recorded by high-latitude ISRs in the Lomidze dataset is advisable. The orbital configuration of Swarm satellites and the extension of the dataset are very tailored for the study of the global features of \(T_{\rm e}\) with a spatial and time resolution hardly accessible in the past. Because of this, we were able to study the median spatial, diurnal, and seasonal trends of \(T_{\rm e}\) in the topside ionosphere in a very accurate fashion. Moreover, this allowed implementing an important statistical comparison between measured data and corresponding ones modeled by IRI. This comparison is beneficial both to validate the IRI model and to unveil the most important departures between measured and modeled data for a future inclusion of the Swarm \(T_{\rm e}\) dataset in the IRI model. The statistical comparison between Swarm and IRI evidenced that:  
* the largest differences emerge at magnetic equator latitudes at dawn, and at low and mid latitudes during daytime and nighttime, respectively;
* IRI needs to be improved in the description of the morning peak at low latitudes.