A comparative assessment of the distribution of Joule heating in altitude as estimated in TIE-GCM and EISCAT over one solar cycle

Abstract

During geomagnetically active times, Joule heating in the Lower Thermosphere - Ionosphere is a significant energy source, greatly affecting density, temperature, composition and circulation. At the same time, Joule heating and the associated Pedersen conductivity are amongst the least known parameters in the upper atmosphere in terms of their quantification and spatial distribution, and their parameterization by geomagnetic parameters shows large discrepancies between estimation methodologies, primarily due to a lack of comprehensive measurements in the region where they maximize. In this work we perform a long-term statistical comparison of Joule heating as calculated by the NCAR Thermosphere - Ionosphere - Electrodynamics General Circulation Model (TIE-GCM) and as obtained through radar measurements by the European Incoherent Scatter Scientific Association (EISCAT). Statistical estimates of Joule heating and Pedersen conductivity are obtained from a simulation run over the 11 year period spanning from 2009 until 2019 and from radar measurements over the same period, during times of radar measurements. The results are statistically compared in different Magnetic Local Time sectors and Kp level ranges in terms of median values and percentiles of altitude profiles. It is found that Joule heating and Pedersen conductivity are higher on average in TIE-GCM than in EISCAT for low Kp and are lower than EISCAT for high Kp. It is also found that neutral winds cannot account for the discrepancies between TIE-GCM and EISCAT. Comparisons point towards the need for a Kp-dependent parameterization of Joule heating in TIE-GCM to account for the contribution of small scale effects.

Evaluation of the Empirical Scaling Factor of Joule Heating Rates in TIE‐GCM With EISCAT Measurements

“…The factor f = 1.5 has been implemented in the TIE‐GCM as the default factor and, as shown in this study, seems to be appropriate as average factor for all convection models, magnetic local times and geophysical conditions. The general trend that the largest q J occurs around midnight and the lowest q J is observed around noon magnetic local time agrees well with previous studies (e.g., Baloukidis et al., 2023; Rodger et al., 2001). The exception is that when applying EISCAT plasma parameters at Kp > 4, the strongest Joule heating is found in the dusk MagLT sector.…”

“…It has been reported previously that the Joule heating rate varies strongly with the magnetic local time (Baloukidis et al., 2023; Foster et al., 1983). We will therefore investigate the Joule heating rates separately for four MagLT bins covering the dawn sector (03–09 MagLT), the noon sector (09–15 MagLT), the dusk sector (15–21 MagLT), and the midnight sector (21–03 MagLT).…”

“…The vertical profile of the neutral wind u ( z ) in Equations and is always taken from TIE‐GCM. Especially for periods of low geomagnetic activity, the neutral wind contribution to the Joule heating rate can not be neglected (Baloukidis et al., 2023; Vickrey et al., 1982).…”

“…Since the TIE‐GCM can be driven by both the Heelis and the Weimer convection models, we will compare the performance of both models within TIE‐GCM to obtain Joule heating rates for different forcing conditions. It has been shown that the Joule heating rate strongly depends on the magnetic local time (MagLT) (Baloukidis et al., 2023; Foster et al., 1983) and therefore we will also investigate how the required f factor varies with MagLT.…”

A Comparative Assessment of the Distribution of Joule Heating in Altitude as Estimated in TIE‐GCM and EISCAT Over One Solar Cycle

“…Data processing source code: The processing of TIE-GCM output data and EISCAT data was done using the code that can be found at: https://github.com/baldimitris/TIEGCM_Statistics (Baloukidis et al, 2023).…”