the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Apr 2026
The SuperDARN Meteor Wind Product: A 31-year archive with modeled altitude contributions and validation
Abstract. Radar echoes from meteor plasma trails constitute one of the main sources of observations of winds in the mesosphere-lower thermosphere. A new 31-year archive of meteor wind observations has been prepared from data taken at 38 Super Dual Auroral Radar Network (SuperDARN) sites, covering 1993–2024. These observations are not height-resolved, and so an empirical meteor model has been produced to estimate the altitude contribution function, in other words the meteor count distribution. The meteor count model RMSEs were estimated at 1.1 km for the peak height and 1.0 km for the full width at half maximum. Using the meteor model, the SuperDARN wind observations have been compared against nearby dedicated meteor radar data, and against JAWARA reanalysis winds. Two case-study comparisons were performed: one for the Andenes meteor radar versus Hankasalmi SuperDARN radar in 2008, and one for the McMurdo meteor radar versus McMurdo SuperDARN radar in 2019. The three datasets were found to be in reasonable agreement, with correlations ranging from 0.49–0.88 for the comparison of SuperDARN against the meteor and 0.50 – 0.72 for the comparison of SuperDARN against JAWARA. A summertime equatorward mean flow of 5–15 m/s was identified in the northern hemisphere SuperDARN data, consistent with previous reports.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2026-1634', Anonymous Referee #1, 20 May 2026
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AC3: 'Reply on RC1', Alex Chartier, 10 Jun 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1634/egusphere-2026-1634-AC3-supplement.pdf
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AC3: 'Reply on RC1', Alex Chartier, 10 Jun 2026
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AC1: 'Comment on egusphere-2026-1634', Alex Chartier, 27 May 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1634/egusphere-2026-1634-AC1-supplement.pdf
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RC2: 'Comment on egusphere-2026-1634', Anonymous Referee #2, 08 Jun 2026
This manuscript describes the work of creating a meteor count model as a function of geographic locations and time of the year and several other parameters, for the purpose of using it to calculate height averaged horizontal wind measured by meteor radars and compare that with the SuperDARN measured wind (which is not height resolved). The intention is to both examine the quality of the SuperDARN wind data against meteor radar and JAWARA model, and provide the height information of where the SuperDARN winds represent.
While the model construction and analysis procedure are described clearly, there are a few fundamental issues that need to be addressed:
- Height range of meteor trails detected by SuperDARN radars. The SuperDARN radars operate at HF (8-20MHz) while meteor radars operate at VHF (30-50MHz). They are sensitive to meteors at different altitudes. As authors point out in eq(3), the HF is expected to detect meteors at higher altitudes. This raises the question of whether meteor count distribution from meteor radars can represent meteors detected by SuperDARN radars. One study cited by the authors, Chisham & Freeman (2013) reported SuperDARN meteors peak at 102-103 km, much higher than 90-95 km detected by meteor radars.
- The comparison with meteor radar wind is insufficient. The selected site, JUL, is very close to AND. Even though it is not used in the meteor count model training, it is expected to have similar wind and meteor distributions. Real validation should be conducted with meteor radar sites far away. Note that such comparison does not require the meteor radar site to have meteor counts data, only the wind data is sufficient. Therefore, there are many sites can be used as long as they are close to a SuperDARN radar.
- The correlation coefficients are not a good measure for such comparison. There are strong seasonal and diurnal variations in wind field that will automatically give good correlation. Vice versa, poor correlation does not necessarily mean poor height representation because a weak natural variation could also result in low correlation. Furthermore, the correlation coefficients do not reveal systemic bias, nor amplitude differences. A useful validation of this work is to show whether the meteor count model has improved wind comparisons over other simpler methods, e.g. using a centroid height and width with a simple seasonal variation. Without such comparison, the correlation coefficients of 0.4 or 0.8 cannot tell whether it is a ‘good agreement.’
- The parameters chosen for the SVM model are not well justified. Although they may be considered to be potential factors that could affect the meteor distribution, there is no quantitative evaluation on model sensitivity to each of them, which can be provided after the model is trained. In addition, there are studies of other factors, such as temperature, that can also affect the meteor distribution (Kim et al, AG 2018, JGR 2021) but not included.
- The summertime equatorward flow is a common feature and can be identified from SuperDARN wind without any of the current work. It is not really related to this work.
Citation: https://doi.org/10.5194/egusphere-2026-1634-RC2 -
AC2: 'Reply on RC2', Alex Chartier, 10 Jun 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1634/egusphere-2026-1634-AC2-supplement.pdf
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This article is an advertisement of the new archive of meteor wind data obtained from 38 SuperDARN sites around the globe, covering 1993-2024. It looks like a technical report rather than a research paper. The article describes the methods for wind retrieval and presents a validation by comparing with meteor radars. For more details, codes for calculating the wind and the wind data are available at Zenodo. Potentially, such a dataset might be useful for atmospheric modelling, atmospheric research, and meteor studies.
However, the correlation 0.49-0.88 between the SuperDARN and meteor radars cannot be considered as a reasonable agreement, such that the method will need further improvements. Essential changes are hardly needed in the present paper however it would be worth discussing the issues.
Specifically: