| 17 Sep 2025
Storm-time Energy Budget in the High Latitude Lower Thermosphere-Ionosphere: Quantification of Energy Exchange and Comparison of Different Drivers in TIE-GCM
Abstract. The energy flow and energy balance in the Lower Thermosphere-Ionosphere (LTI) is governed by a number of processes that are driven by interactions between ions, neutrals and electrons. Even though these processes are well understood theoretically, and even though the framework to implement these processes exists in current global circulation models, the energy estimates for the different processes show large discrepancies between models, in large part because of limitations in available data sets. In this study, we explore numerically the energy inputs and energy transfer between ions, neutrals and electrons during the 2015 St. Patrick’s day geomagnetic super-storm. We use NCAR’s Thermosphere Ionosphere Electrodynamics General Circulation Model, version 2.0 (TIE-GCM 2.0) for estimating energy sources and sinks, energy transfer rates and the energy partitioning between species. Two independent TIE-GCM runs were executed: the first one used the Weimer 2005 empirical model, and the second used the Assimilative Mapping of Ionospheric Electrodynamics (AMIE) data assimilative technique. The resulting energy budget and the corresponding partitioning of energy between species are inter-compared between the two runs, before and at the peak of the storm. Discrepancies between the model runs are discussed and the way forward to close the gaps in present knowledge is highlighted.
The paper "Storm-time energy budget in the high latitude lower thermosphere-ionosphere: Quantification of energy exchange and comparison of different drivers in TIE-GCM" provides a detailed assessment of TIE-GSM heating and cooling terms relevant for neutrals, ions, and electrons, during a major geomagnetic storm. Two simulation runs are compared, one driven by the Weimer (2005) model of high latitude electric potential, the other by AMIE data.
Understanding and properly quantifying the energy budget in the ionosphere-thermosphere is certainly a major topic, likewise the related improvement of the simulation codes and boundary conditions. As soon as the few issues listed below and in the attached annotated manuscript are fixed, I shall be happy to recommend publication.
1. As far as I can judge, the main point that requires clarification is the direct Joule heating of the neutrals. This is invoked several times, as well as indicated in Figures 2 and 3. I am a bit confused, since Joule heating implies the effect of the electric field, which is obviously not directly felt by the neutrals. As aptly mentioned by the authors, the energy is passed to the ions by Joule heating, then transferred to the neutrals by collisions. But obviously there is also another mechanism, indicated in Figure 2 by the direct red arrow between the q_J box (q_\Omega in the figure - typo?) and in Figure 3 by the gray 'Joule heating' box (incidentally, the 'Joule heating' and 'Ions' boxes have somewhat different mutual roles in Figure 3 compared to Figure 2). I presume that the 'direct Joule heating' to neutrals and the Joule heating via ions are indeed related to specific terms of TIE-GCM. Perhaps the 'direct Joule heating' is related to the neutral wind term of Eq. (5), u_n \times B, i.e., to the (macroscopic) convection motion of the neutrals, whereas the ion term, related to the temperature difference (pointed out by the authors), is rather a (microscopic) conduction effect? Or, as suggested by Eq. (11), there is a ‘prompt’ energy transfer (the ‘direct’ Joule heating of neutrals?) versus a ‘delayed’ transfer (see the annotated pdf)? Please clarify.
2. Another point that I regard as important is the reason behind the difference of the Weimer and AMIE results, in particular at / near the maximum phase of the storm (Figure 1). This is attributed mainly to the sub-grid variability, apparently better captured by AMIE, because of better spatial resolution (e.g., L567-569, 576-578). The better capturing of the actual conditions by AMIE is at least as important and should be emphasized better. To my understanding, AMIE takes (much?) better into account the actual conditions, as compared to a statistical model, like Weimer (2005), which provides some sort of 'average ' behavior. The more disturbed are the conditions, the farther off are the various parameters from some 'average' and the more important is to drive the simulation by (as close as possible to) actual boundary conditions. I think that some elaboration of the discussion and conclusions would be welcomed.
3. Besides the two points above, please see the annotated manuscript, attached, for various other remarks, mostly minor issues.