# A High Latitude Model for the E Layer Dominated Ionosphere
## 2 Data  
We used vertical electron density profiles derived from IRO observations onboard the COSMIC satellites. The profile files contained in our dataset cover a period from April 2006 to December 2018 and were obtained from the COSMIC Data Analysis and Archive Center [22]. First, we filtered out all those profile files that could either not be opened or whose contents were corrupted. For each profile, we then performed the computations listed in the following paragraph. The information derived through this process was later used for the computation of the model coefficients and of the model observable trends.  
To obtain the ELDI state \(ELDI_{st}\) of a profile, which indicates whether the profile represents an ELDI event or not, and to obtain the three E layer observables, we proceeded similarly as described in [8]. In this regard, we first divided the height range of the profile into an E layer segment extending from 90 to 150 km and an F2 layer segment located above 150 km. Thereafter, we determined the maximum electron density \(NmrF2\) and the associated height \(hmF2\) within the F2 layer segment. Fitting a Chapman layer function to the F2 layer topside electron density and extrapolating it into the bottomside ionosphere yielded the F2 layer contribution to the profile. Next, we subtracted the F2 layer contribution from the observed profile in order to extract the E layer. Subsequently, we fit a Gaussian function to the E layer. Profiles for which any of these fitting steps failed were ignored from here on. The magnitude, position and full width at half maximum (FWHM) of the Gaussian resulted in the E layer observables \(NmE\), \(hmE\) and \(wvE\), respectively. Via a comparison of \(NmE\) with \(NmF2\) and additional filter steps outlined in [8], we determined the ELDI state of the profile. The day of year \(DOY\), which represents seasonal variation, and the local time \(LT\) were taken from the profile's timestamp information. The observational data for the solar radio flux index \(F10.7\), which we used as a measure for solar activity, were downloaded from the Space Physics Data Facility (SPDF) website of the Goddard Space Flight Center [23]. Following other ionosphere models previously developed in Neustrelitz, as presented in [PERSON] et al. [19] and Hoque and Jakowski [20; 21], we computed the geomagnetic latitude \(MLAT\) of the profile from its geographic latitude and longitude by means of the dipole magnetic field model based on a formula described in [PERSON] [1]. Furthermore, we computed the convection electric field magnitude \(E_{Conv}\) as discussed in [PERSON] et al. [9] according to a formula given in [PERSON] [24] from observational solar wind speed data (\(v_{sw}\)) and interplanetary magnetic field data (\(B_{sw}\)) downloaded from the SPDF website. Overall, performing the aforementioned processing steps resulted in the following information for each profile: \(ELDI_{st}\), \(NmE\), \(hmE\), \(wvE\), \(MLAT\), \(LT\), \(DOY\), \(F10.7\) and \(E_{Conv}\). The flowchart in Figure 1 summarizes the steps involved in the data pre-processing.  
After completion of the data pre-processing, our resulting final dataset contains the information about the ELDI state, the E layer observables and the model drivers for about 2.3 million profiles in total. To compute the model coefficients and to validate the model, we randomly split the dataset into a modeling dataset and a test dataset. In order to increase the quality of the model coefficients, the modeling dataset contains 90% of the total data, whereas the test dataset contains 10% of it.  
Figure 1: Flowchart of the data pre-processing steps.