the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Oct 2024
Effects of sudden stratospheric warmings on the global ionospheric total electron content using a machine learning analysis
Abstract. A sudden stratospheric warming is a breakdown of winter stratospheric polar vortex. It has atmospheric effects in both the Northern and Southern hemispheres, leading to disturbances in the whole ionosphere. Previous works with case studies have shown that SSW effect is mainly in low-latitude ionosphere and each SSW event may have a different effect on the ionosphere due to complex dynamics from solar/geomagnetic activities and seasonal changes. However, the SSW induced tidal variability in mid to high-latitude ionosphere is only identified for several events and its behaviour is not well understood. Here we analyze SSWs’ influences on diurnal/semidiurnal variations of global ionosphere with the global maps of total electron content (TEC) from 1998 to 2022. We use machine learning (ML) with neural network to establish the TEC (ML-TEC) model related to the solar/geomagnetic activities and seasonal change from the long-term global TEC data. The TEC variations due to SSWs are extracted by subtracting the ML-TEC from the observed TEC. Comprehensive composite analysis of 18 SSW events shows for the first time a globally SSW-induced enhancement in diurnal/semidiurnal TEC variations. The enhancement is the strongest at equatorial ionospheric anomaly (EIA) crests, moderate in mid-latitude and vague in high-latitude ionosphere. It also exhibits hemispheric asymmetry and longitudinal differences. While the semidiurnal enhancement starts earlier and peaks at ~8 days after SSW onset, the diurnal one starts on the SSW onset day and peaks around 20–30 days after SSW onset. The enhancement of both semidiurnal and diurnal TEC variations lasts to about 50 days after SSW onset. The SSW related E-region dynamo is likely the dominant mechanism which is not strong enough to produce discernible TEC variations in high-latitude ionosphere. ML-TEC does not contain the SSW effect and is thus a valuable reference for the ionospheric state without an SSW.
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RC1: 'Comment on egusphere-2024-3177', Anonymous Referee #1, 15 Dec 2024
Tidal changes in the ionosphere during SSW has been focused for a decade of years. Although it is believed that the changes are global, most of the studies were concerned mainly in the ionospheric variation the low latitudes. Based on the global TEC map data with resolution of 2 hour, and 2.5° latitude *5° longitude, the ionospheric background morphology has been obtained using a neural network algorithm. Further the global distribution of the diurnal and semidiurnal tide components was analyzed using the residual of the TEC data focused on 18 major SSW events in northern winter hemisphere. This study can provide a comprehensive understanding of the global effects on the ionosphere due to SSW. On the whole, the obtained results are clear. But there are still some unclear situations and some discussions about the results are needed further.
Comments:
1, The TEC map data used here are obtained with interpolation algorithm based on about 300 GNSS stations that are very unevenly distributed. Very limited GNSS data can used in the ocean region especially in the southern hemisphere. Usually, the TEC map with such low spatial and temporal resolution are used for revealing the ionospheric background morphology and large ionosphere disturbance, such as ionospheric storm. So it is better to give some analysis about the availability of such TEC data for deriving the tidal components in the study.
2，What is the criteria for the SSW events in Table 1 as MAJOR?
In general, the major SSW event mainly occurs in the winter period of the Northern Hemisphere, which is manifested by the reversal from eastwards to westwards of the zonal wind zonal mean and the increase of the stratospheric temperature in the polar region.
How is the Central date determined, and is it the same time as the SSW onset in Figure 4? The date of the SSW event in 2010 and 2020 is 20100323 and 20200322. Strictly speaking, these two events should be classified as Final Warming, and the background condition of the zonal wind zonal mean during this kind of warming is different with the normal SSW event occurred in winter period.
3， The input layer of the neural network algorithm shown in Figure 1 only takes into account the annual and diurnal variations of the ionosphere. Why doesn't consider the seasonal variation, i.e., the 180-day period variation? The selected SSW events happened in the northern winter period, whether this collection of input layer without seasonal variation component affect the final results?
4，Why the sites of diurnal tidal and semidiurnal tidal component given in figure 3 are different? It may be better to give the diurnal and semidiurnal tidal components during the same event at same site.
5， Figure 6 and Figure 7 give the latitudinal distribution of the diurnal and semidiurnal components at certain meridian line during SSW period, respectively. Why are there no results for the same longitude? It is suggested to provide the latitudinal distribution of the diurnal and semidiurnal component at each meridian lines. In addition, little observational data in the southern hemisphere in the sector of 80 E meridian line, and the map data in this region is basically interpolated, the result in this meridian line is it reliable?
By the way, the vertical line in each figure is not clear.
6， In the discussion section, it is necessary to analyze why the semi-diurnal tides in the mid-latitudes of the Southern Hemisphere are stronger than those in the mid-latitudes of the Northern Hemisphere, and what are the possible mechanisms. In addition, it has been suggested that the semi-diurnal tidal component is probably related to the enhanced semi-lunar tidal (M2) during the SSW, and the discussion about the M2 component enhancement in the Northern and Southern Hemisphere during SSW should be added in the discussion section. The following related papers can be referred.
Goncharenko, L. P., Harvey, V. L., Randall, C. E., Coster, A. J., Zhang, S.-R., Zalizovski, A., et al. (2022). Observations of Pole-to-Pole, Stratosphere-to-Ionosphere Connection. Frontiers in Astronomy and Space Sciences, 8, 768629. https://doi.org/10.3389/fspas.2021.768629
Liu, J., Zhang, D., Goncharenko, L. P., Zhang, S., He, M., Hao, Y., & Xiao, Z. (2021). The latitudinal variation and hemispheric asymmetry of the ionospheric lunitidal signatures in the American sector during major Sudden Stratospheric Warming events. Journal of Geophysical Research: Space Physics. https://doi.org/10.1029/2020ja028859
Jing Liu, Donghe Zhang, Shuji Sun, Yongqiang Hao, Zuo Xiao, Ionospheric Semidiurnal Lunitidal Perturbations During the 2021 Sudden Stratospheric Warming Event: Latitudinal and Inter‐Hemispheric Variations in the American, Asian‐Australian, and African‐European Sectors, Journal of Geophysical Research: Space Physics, 10.1029/2022JA030313, 127, 9, (2022).
Citation: https://doi.org/10.5194/egusphere-2024-3177-RC1 -
RC2: 'Comment on egusphere-2024-3177', Anonymous Referee #2, 03 Jan 2025
The paper presents a composite analysis of ionospheric response to multiple sudden stratospheric warmings. To isolate SSW response, the authors first develop empirical model of total electron content, and use data-model differences to see SSW effects. Composite analysis of 18 SSW events is the novel aspect of the paper. Global ionospheric variations and complex latitudinal and longitudinal patterns are also new and interesting features.
Overall, the Introduction is pretty weak and does not mention several important studies that describe the state of knowledge on the topic. The new empirical model that uses machine learning approach is an interesting development. However, it would be important to demonstrate the performance of the model and discuss several performance metrics, so that the reader can be more comfortable about the attribution of the observed effects to SSW and not to the model itself. The paper would also benefit from a more extended discussion of potential mechanisms responsible for the observed features. Overall, the paper is an interesting development and will be stronger after addressing several comments. Most of them are clarifications and should not be hard to address. I recommend a minor revision.
Major comments
L. 26-28 - As there is a lot of literature on SSWs, a better reference is needed here. For example, recent review of Baldwin et al., 2021 (see suggested references below).
L. 32-33 - it has been established through multiple simulations that wind and temperature changes in the middle atmosphere are the primary reasons for the amplification of tidal modes, not mesospheric polar vortex. Please revise the Introduction.
L. 55+ - there were several other studies that investigated response to SSW at middle to high latitudes, including for multiple SSW events - for example, Liu et al., 2021. The paper would benefit from a more comprehensive description of what is known.
The GNSS receiver coverage substantially varies with latitude and longitude, and also varies in time, with earlier data containing fewer stations and hence using more interpolations. The study needs to reflect that and discuss potential implications on the results.
Table 1 presents central dates of SSWs. As there are multiple ways of defining a central day of SSW, exact dates (and hence the results of the study) can depend on the definition of central date. Please provide more details how central date was defined for this study.
Development of empirical model of TEC is an important effort that can provide background TEC for a variety of other studies. It is important to understand how good is the model and how well it describes seasonal and solar cycle variations. The paper needs to include at least some examples of this, and to include several metrics evaluating the performance of the model. If the authors are reluctant to include them in the body of the paper, they can be included as Attachment.
There were several earlier efforts to develop empirical TEC models using the same (although shorter) TEC dataset. For example, Mukhtarov et al., 2013a, b; Lean et al., 2016. They need to be mentioned for the sake of scientific objectivity. How does the model developed in this study perform compared to the earlier models?
In Figure 3, diurnal and semidiurnal components are given for the same latitude but different longitudes. What is the justification for this?
In addition, the authors attribute all the data/model differences to SSW. However, largest post-SSW difference of ~5TECu coincides with increase in solar flux due to the 27-day solar rotation, and some of the differences could be potentially attributed to the model performance for different seasons and solar flux levels. This is why it is important to present some evidence of model performance, per my earlier comment.
In Figure 4, what is the justification for showing delta S1 at 13 days before SSW? Are you implying that SSW effects start 13 days before the central date? Are these patterns statistically significant?
Describing Figure 4, the authors write ‘The largest deltaS1 enhancement is 2.25 TECU and locates at (2.5°S, 90°W)’, and several lines later they write ‘Largest deltaS1 is ~1.95 TECU and locates at 2.5N and [45°W, 50°W]’. Please clarify the meaning of this - it is not clear what the authors are trying to emphasize.
Similar comments about Figure 5 - figure 5a shows distribution of deltaS2 for 12 days before the SSW onset. Why 12 days? Why not 10 days or 15 days, and why this is different from 13 days before SSW onset for Figure 4? Are these variations statistically significant? How do they compare with, for example, 1 sigma or RMSE for the model?
Figure 6 shows deltaS1 at one longitude. Please say few words whether patterns are similar or substantially different at other longitudes.
Figure 7 shows deltaS2 at a different longitude, 80W. Why is it different from the longitude in Figure 5? Why are these specific longitudes selected?
For all figures 4-9 (or at least for some of them), it might be worthwhile to add another panel that shows variations not in absolute units of TEC, but as percentage compared to the background (model). This might help to illuminate the relative strength of SSW-related disturbances at different latitudes and longitudes.
Figure 8 shows interesting longitudinal features. The study needs to include a discussion of potential reasons for these variations.
Figure 9 - same comment as earlier; 20N is selected for figure 8, but 22.5N for figure 9. Why? As the study uses TEC maps with latitude grid of 2.5 degrees, differences at 20N and 22.5N should not be large.
In figure 9, the authors emphasize enhancement at 45-135E (note also, there is a typo there, should be 45-135E, not 45-135N). But enhancement is also seen around day -50 to -40. How confident are you that enhancements after the SSW onset in that longitude range can be truly attributed to SSW, and not to, for example, insufficient data coverage at these longitudes?
Overall, the Discussion section is pretty weak and could benefit from more extended discussion about the potential mechanisms for the observed features and comparison with available studies.
As empirical model takes substantial time to develop and can be used for other studies as a background, it would be important to provide access to model output code to the reader, as currently expected in different journals.
Acknowledgment mentions foF2 data for Okinawa and Wuhan, which is not relevant to this study.
Minor comments & language
L. 10 - ‘SSW effect is mainly in low-latitude ionosphere’ - SSW effects are observed mainly in the low-latitude ionosphere
L. 21 - ‘lasts to about 50 days after SSW onset’ - lasts for about 50 days after SSW onset?
It is better to avoid using abbreviations in the abstract, and introduce abbreviations the first time they are used. For example, ‘SSW’ is used in the abstract, but not defined.
Some references are missing in the reference list - for example, Chau et al., 2009, Goncharenko et al., 2018; Yamazaki et al., 2012. Please check the references list carefully.
L. 120 - ‘only those driven by the atmosphere below are remained’ —> ‘only those driven by the atmosphere below are retained’ or ‘only those driven by the atmosphere remain’
L. 151 - ‘In southern atmosphere’ —> In southern hemisphere?
Vertical line that marks SSW onset in figures 6-9 could be made thicker, it is barely seen now.
L. 235 - ‘is larger Northern hemisphere’ —> ‘is larger in the Northern hemisphere’
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References
Baldwin, M. P., Ayarzagüena, B., Birner, T., Butchart, N., Butler, A. H., Charlton‐Perez, A. J., ... & Pedatella, N. M. (2021). Sudden stratospheric warmings. Reviews of Geophysics, 59(1), e2020RG000708.
Liu, J., Zhang, D., Goncharenko, L. P., Zhang, S. R., He, M., Hao, Y., & Xiao, Z. (2021). The latitudinal variation and hemispheric asymmetry of the ionospheric lunitidal signatures in the American sector during major sudden stratospheric warming events. Journal of Geophysical Research: Space Physics, 126(5), e2020JA028859.
Lean, J. L., R. R. Meier, J. M. Picone, F. Sassi, J. T. Emmert, and P. G. Richards (2016), Ionospheric total electron content: Spatial patterns of variability, J. Geophys. Res. Space Physics, 121, 10,367–10,402, doi:10.1002/2016JA023210.
Mukhtarov, P., Pancheva, D., Andonov, B., & Pashova, L. (2013). Global TEC maps based on GNSS data: 1. Empirical background TEC model. Journal of Geophysical Research: Space Physics, 118(7), 4594-4608.
Mukhtarov, P., Pancheva, D., Andonov, B., & Pashova, L. (2013). Global TEC maps based on GNNS data: 2. Model evaluation. Journal of Geophysical Research: Space Physics, 118(7), 4609-4617.
Citation: https://doi.org/10.5194/egusphere-2024-3177-RC2
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