## 3 Results
### Statistical Comparison against ISRs Data
It is the same for Swarm after applying the Lomidze correction; in this case the agreement with ISR's data is remarkable for both the representation of the diurnal and seasonal trends and the accuracy of the absolute values; only a slight overestimation is visible during nighttime particularly at December solstice. It has to be considered that the Lomidze correction, aside from being based on the same three ISRs here studied, is heavily biased toward Millstone Hill ISR data that were more represented in the [PERSON] et al. [24] dataset than Arecibo data and above all Jicamarca. As a consequence, since [PERSON] et al. [24] cumulated the data of the three ISRs to derive a single calibration curve, it should be expected that the correction is more effective at Millstone Hill than at Arecibo and Jicamarca. This agrees very well with the results shown in Figures 4-6. Moreover, the Lomidze correction does not discriminate between daytime and nighttime or between different seasons. Our results show that the Lomidze correction has the best performance for daytime hours and the worst for nighttime hours, with no distinct seasonal difference. This suggests that a latitudinal and day/night dependence should be included in the Lomidze correction when enough data become available in the future. As we can see from Figures 4-6, the daily \(T_{\text{e}}\) profile varies with the ISR geographic location. For example, at Jicamarca, which is at the magnetic equator, \(T_{\text{e}}\) shows a single sharp maximum around dawn that can be associated with the well-known morning overshoot. This feature is characteristic of low latitudes, and in fact is present also in the daily profiles acquired at Arecibo. Here, and at Millstone Hill (middle and sub-auroral latitudes), the increase of \(T_{\text{e}}\) in the dayside is due to the increased sunlight and a second hump at dusk marks the decrease of \(T_{\text{e}}\) in passing from day to night. At Millstone Hill, an increased \(T_{\text{e}}\) during nighttime is recorded at the December solstice, mainly due to the decrease of plasma density in the F layer and the following reduction of the collisional cooling effect,and also to the conjugate heating. To better highlight and describe all of these different spatial features exhibited by the topside \(T_{\rm e}\), in the next section, the main spatial trends of \(T_{\rm e}\) will also be investigated, in both geographic and magnetic coordinates. Statistical Trends of Swarm-Measured Electron Temperature Values and Comparison with IRI-Modeled Ones  
The results of Section 3.1 and 3.2 demonstrate that the application of the Lomidze correction improves the agreement between Swarm data and those modeled by IRI and measured by different ISRs. This is why, in the following analyses, we focus only on Swarm B data corrected according to [PERSON] et al. (2014). Swarm B data from 2014 to 2020, and corresponding IRI-modeled values, were binned as a function of the geographic coordinates with bins \(2.5^{\circ}\)-wide in latitude and \(5^{\circ}\)-wide in longitude. For each bin, the median value was considered, as representative of the main statistical trend, after discarding the outliers through the Median Absolute Deviation statistical procedure (see Section 3.3 by [PERSON] et al. (2016) for a detailed description). The binning was first performed on the entire dataset and then by selecting MLT (in QD coordinates) sectors representative of the dawn (5-7 MLT), daytime (12-15 MLT), and nighttime (0-3 MLT) conditions. This was done because at a fixed altitude, the \(T_{\rm e}\) diurnal variations are known to be the most important along with the latitudinal ones ([PERSON] _et al._, 2016; [PERSON] _et al._, 2017; [PERSON] _et al._, 2018). Figure 7 shows the corresponding results considering all the MLTs and the different MLT sectors, for both Swarm-measured and IRI-modeled data, and the corresponding percentage of the normalized residuals between them.