Incoherent Scatter Radar (ISR) measurements are a crucial component of many space weather studies, as they provide multiple ionosphere parameters, including electron density, ion/electron temperature, and ion velocity. However, these parameters are inferred from the incoherent scatter spectrum, assuming certain a priori parameters, most notably the ratio of atomic oxygen ion (O+) density to the electron density, Ne. It has been shown in the past that the assumed ion composition has a considerable effect on the electron and ion temperature measurements e.g.. Hence, the measurement reliability is strongly affected by the accuracy of the a priori modeled O+ ratio profile.

The most commonly applied empirical ionosphere model is the International Reference Ionosphere IRI,. gives an overview of the different IRI versions and applied parameterizations. They note that the accuracy of empirical ion composition models is significantly limited by the scarcity of measurements, especially for statistically rare conditions, e.g. during geomagnetic storms. Physics-based thermosphere-ionosphere models obtain the ion composition by solving the continuity and momentum equations of the ionosphere . However, though the ion chemistry in the F region is considerably simpler than in the D and E regions , plasma dynamics and thermosphere-ionosphere coupling affect the accuracy of the modeled ion composition e.g.. Nevertheless, physics-based ionosphere models are likely to cover the variability of the F region ion composition better than empirical models for geomagnetically active periods.

To assess the effects of empirical and physics-based model ion compositions, we reevaluate the ISR measurements with the EISCAT Svalbard Radar during the major geomagnetic storm in May 2024 . For this reevaluation, we replace the O+ ratios given by the default ionosphere a priori model (IRI2020) of the EISCAT analysis with the O+ ratios as given by the physics-based Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension (WACCM-X). Different high-latitude drivers of the WACCM-X model are compared.

Section  gives an overview of the applied measurements and models. Section  shows the reevaluated plasma parameters and relates them to the model differences in O+ ratio. Section  discusses the obtained results, and the advantages and disadvantages of the technique applied in this paper compared to previous solutions of the ion composition issue. Section  summarizes the main conclusion and gives an outlook on future work.

The major geomagnetic storm of May 2024 was the strongest space weather event in two decades and reached the maximum possible Kp=9 index (the Kp-similar Hp30 index, for which no upper limits apply, reached up to 11.33). A complete overview of the storm impact at high latitudes can be found in . In addition, studied the polar ionosphere-thermosphere coupling using multiple observations. They showed that both Ti increases and neutral composition changes are important for F region recombination and hence result in electron density depletion and ion composition changes in the polar region. The geomagnetic storm started at about 17:00 UTC on 10 May and reached its maximum during the night from 10–11 May. On 11 and 12 May, and showed a strongly pronounced negative storm phase, indicating significant thermospheric upwelling and consequent disturbances of the chemical composition at the thermosphere/ionosphere. Figure  shows the EISCAT ESR measurements of electron density Ne, electron temperature Te, and ion temperature Ti from 10–13 May 2024.

As described in Sect.  and , the plasma parameters in Fig.  are inferred from the incoherent scatter spectrum assuming certain a priori parameters from the empirical IRI 2020 and NRLMSIS 2.1 models. Figure a shows the O+-to-Ne ratio rO+ as given by the IRI model from 10–13 May 2024. It can be seen that IRI provides the diurnal variation of rO+ but no variations as expected from the varying geomagnetic conditions during this period. The Heelis- and AMIE-driven WACCM-X O+ ratios in Fig. b and c show this variation of rO+ with geomagnetic activity. The low rO+ well up into the F region at around 08:00 UTC on 11 May, presumably connected to the uplift of molecular atmospheric constituents following the main phase of the storm, can be seen in both WACCM-X runs. However, the variability of rO+ is distinctly lower in the Heelis-driven model run, as expected due to the driving with the 3-hourly Kp index. Since the data assimilative AMIE method is expected to cover the actual geomagnetic forcing better than the empirical Heelis model , the further analysis in this paper will be conducted using the AMIE-driven WACCM-X model results. Due to the limited availability of AMIE results, the Heelis-driven model rO+ is more widely applicable for the reevaluation of EISCAT measurements demonstrated below, e.g. from .

The GUSIDAP software for inferring EISCAT plasma parameters contains a subroutine ionomodel.m which, by default, calls upon the IRI 2020 model to give a priori estimates of the fitted plasma parameters as well as an a priori O+ ratio that is assumed as true during the fitting of plasma parameters. We adjusted this subroutine and opened a path to directly read the O+ ratio from the prepared WACCM-X run. The adjusted ionomodel.m routine as well as the WACCM-X data files for Heelis- and AMIE-driven model runs are provided in a software and data repository . We would like to emphasize again that all results shown below are obtained by applying the AMIE-driven model results.

Figure a shows the difference of O+ ratio ΔrO+ between WACCM-X and IRI during the May 2024 storm. Figure b–d show the percentage changes 1dX=Xreevaluation-XoriginalXoriginal⋅100 of Ne, Te, and Ti in the reevaluation using WACCM-X rO+ compared to the original EISCAT parameters. It can be seen that for all three parameters dX has a negative correlation with ΔrO+. While dNe is limited to about ±10% at maximum deviation, dTi can reach up to ±30% and dTe even up to ±40%.

Figure  illustrates the correlation of ΔrO+ and dX throughout all times and altitudes shown in Fig. . We distinguish two altitude regimes, above and below the transition altitude z50, as applied by , where half of the ionospheric plasma consists of atomic oxygen ions, i.e. rO+(z50)=0.5. It can be seen that the percentage change between original analysis and reevaluation is strongly negatively correlated (R<-0.9) in all cases, except for dNe below the transition altitude. This indicates the potential to develop a simple, linear correction model which would allow to de-bias EISCAT measurements without needing to repeat the incoherent scatter analysis. For the case of dTe above z50, which has the highest correlation with ΔrO+, we determine a linear function dTe=A⋅ΔrO++B, so that 2Te,reevaluated=Te,o⋅A⋅ΔrO+100+B100+1.

We find that A=-74.8138 and B=0.2261 (hence B/100≪1 can be neglected) for this case.

However, a reliable correction model that can be applied to other EISCAT measurements would require a statistical analysis of EISCAT measurements, including quiet-time campaigns. The idea of a correction function was already suggested by , but the significant increase in ISR measurements since then would allow for a statistically more sound evaluation. Also, non-linear relations, as already discussed by , should be considered. The scope of this paper is the May 2024 superstorm, but the development of such a correction model might prove useful in the future.

Figure a–c show the analogous percentage changes of the plasma parameter uncertainties dδX. For all three parameters, the percentage change between reevaluation and the original analysis is below 10%. However, it becomes apparent that the correlation with ΔrO+ is not as straightforward as with dX in Fig. .

In Fig. , the transition altitudes given by the IRI and WACCM-X models, interpolated to EISCAT measurement altitudes, are shown as solid (WACCM-X) and dashed (IRI) lines. The percentage change of the parameter uncertainties has an opposite sign above, and below the smaller of the two compared transition altitudes, i.e. it depends on whether the altitude h is larger or smaller than min{z50,WACCM-X,z50,IRI}. Table  summarizes the relations of ΔrO+, h, and dδX. To our understanding, the origin of the relations in Table  is rather a mathematical consequence of the incoherent scatter analysis than an actual physical process, though no evidence can be provided.

To obtain an impression of how the impact of the reevaluation, Figs.  and show the vertical profiles of Ne, Te, and Ti for 11 May 08:00 UTC and 12 May 22:10 UTC, which are the times of minimum/maximum ΔrO+ respectively.

It can be seen that the deviation of the original and reevaluated profiles is mostly larger than the uncertainty range at around 200–300 km altitude. This demonstrates the usefulness of such a reevaluation, especially for studies investigating plasma temperatures.

This section discusses alternative approaches to constrain/determine the O+ ratio before or during the analysis process, in addition to the default GUSIDAP analysis, using IRI rO+, and the WACCM-X-based reevaluation presented in this paper. The advantages and disadvantages of each method will be compared.

A reevaluation of EISCAT plasma parameters during the May 2024 geomagnetic storm was conducted, assuming O+ ratios from an AMIE-driven SD-WACCM-X run. We showed that under extreme storm conditions, the EISCAT electron density measurements deviate up to 15 % compared to the standard analysis assuming IRI O+ ratios. Electron and ion temperatures were shown to deviate even stronger, up to 40 % and 30 %, respectively. We showed a very high linear correlation of electron temperature deviations and rO+ in the applied a priori models, opening the possibility to introduce a simple correction function. The uncertainties in the plasma parameters were impacted by the reevaluation, increasing by about 5 %–10 %. However, whether the uncertainty is increased or decreased due to the reevaluation depends on the transition altitudes of the two a priori models. However, the deviations of F1 region plasma parameters between the original analysis and reevaluation are notably larger than the uncertainty range.

As discussed in Sect. , the main advantage of an ISR measurement reevaluation based on the ion composition given by a physics-based thermosphere-ionosphere model is the possibility to extend the method into a correction model. Due to the limited availability of AMIE results coinciding with EISCAT measurements, a correction model would have to be based on standard high-latitude drivers of WACCM-X, i.e. the Heelis and Weimer empirical convection models. Existing WACCM-X long-runs, such as , can be applied. Such a correction model would be quickly and easily applicable to all researchers, regardless of their proficiency with incoherent scatter analysis software. However, extended studies including ISR campaigns during different levels of geomagnetic activity are required to verify the possibility of inferring a correction model, and it needs to be determined under what conditions physics-based models actually capture the ionosphere composition better than empirical models.