Skip to main content
SearchLoginLogin or Signup

Ionospheric Electron Temperature and Density Variations during Extreme Geomagnetic Storms

Presentation #405.01 in the session Drivers and Dynamics of the Coupled Ionosphere-thermosphere-mesosphere-atmosphere System II.

Published onOct 20, 2022
Ionospheric Electron Temperature and Density Variations during Extreme Geomagnetic Storms

Ionospheric electron density (Ne) and temperature (Te) are sensitive indicators of coupling between magnetospheric energy into the upper atmosphere as well as forcing from the lower atmosphere. During geomagnetic storms, there is a complex interplay of various drivers which lead to anomalous Te and Ne gradients. In the present study, high resolution in-situ measurements of Te and Ne obtained from the Langmuir Probe (LP) on board DE2 are compared with the simulations of Global Ionosphere Thermosphere Model, to study 2 major storms that occurred during solar cycle 21. The super storm of 14 July 1982 registered a minimum Dst of -436 nT while the storm of 22 September 1982 recorded a minimum Dst of -230 nT. Although the solar drivers of the solstice storm were stronger (southward excursion of Bz value to -31.8 nT) than the equinoctial storm (Bz of -10.1 nT), perturbation was observed to be larger during the storm of September 1982. The maximum Te recorded by the LP was 5386K for the July storm whereas for the September storm, it shot up beyond 6000K. Corresponding decrease in the Ne values to 104 /cm3 and 103 /cm3 were observed for the July and September storms respectively. Elevated temperatures over southern hemisphere for both the storms is also intriguing. The storms were simulated using GITM to validate its performance at capturing the response of IT region to extreme storm events. Simulated Te and Ne follow the same overall patterns of decrease and increase for both storms. However, the peak values of Te and Ne did not match the observed values. In order to identify the regions and times when GITM either overestimated or underestimated storm time features, the entire data set was subsetted to identify where the model performed best and worst. The different subsets include Northern/Southern Hemisphere; day/night; top/bottom side F region; high/low levels of Kp and SME indices and high/low geomagnetic latitude regions. GITM simulated Te and Ne matched best with the observed values over the bottom side F region of the high latitudes over northern hemisphere during daytime of low activity levels of Kp. However, over the low latitude of southern hemisphere, especially during high geomagnetic activity levels, there seems to be a discord between simulated and observed values. This is corroborated using a robust set of metrics to identify the errors, bias and the prediction efficiency of the model, which helps to pin down the region/time that warrants further improvement in the identification of various heat sources and sinks along with the transport mechanisms incorporated in the model, leading to better forecast capabilities.


No comments here