Articles | Volume 19, issue 13
https://doi.org/10.5194/amt-19-4553-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Remote sensing of local-dust across the Canadian Arctic
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- Final revised paper (published on 10 Jul 2026)
- Preprint (discussion started on 16 Feb 2026)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2025-6037', Anonymous Referee #1, 04 Mar 2026
- AC1: 'Reply on RC1', Seyed Ali Sayedain, 05 Jun 2026
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RC2: 'Comment on egusphere-2025-6037', Anonymous Referee #2, 10 Mar 2026
- AC2: 'Reply on RC2', Seyed Ali Sayedain, 05 Jun 2026
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AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Seyed Ali Sayedain on behalf of the Authors (05 Jun 2026)
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ED: Publish subject to technical corrections (18 Jun 2026) by Sebastian Schmidt
AR by Seyed Ali Sayedain on behalf of the Authors (22 Jun 2026)
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I recommend publication after minor revisions -- specifically, the addition of certain caveats. Here is my full review:
This paper applies a collection of in situ and remote sensing observations to characterize the properties of seven dust events in the Canadian Arctic Archipelago. Surface data focuses on instruments at Eureka: the CIMEL, from which AERONET retrieval products were obtained, the Arctic HSRL, and an APS. Satellite remote sensing data include MODIS, MISR, and Sentinel-2 imagery, aerosol optical depth mapping, and from MISR, also plume heights. Wind data are obtained from MISR and from Reanalysis. The authors have built a cottage industry in studying dust in the Arctic, which is an important topic, as summarized in the paper’s introduction section; this paper aims to provide a useful addition to that literature.
A lot of careful work has gone into analyzing the seven cases presented. The value in this work is that it demonstrates techniques that could to some extent be applied more widely around the Arctic based on remote sensing data alone. Such wider application would be part of follow-on work, which is why the current paper is appropriate for AMT, as the authors indicate. The authors make a considerable effort to justify the interpretation of satellite remote-sensing signals in the seven cases as due to local dust events, and they are each quite convincing, despite very low AOD values. I note that most passive satellite remote-sensing observations in the Arctic remain extremely difficult to interpret. My primary recommendation is that in the Abstract and especially in the Conclusions, caveats might be provided that make clear the seven cases presented here are all distinct, narrow plumes, at least partly over dark water, downwind of likely dust sources, under contemporaneous high-wind conditions, and that interpreting MODIS and MISR data as indicating local dust plumes more generally must be done with similar care. Some further notes are included below.
Notes
Lines 182-184. As this study uses primarily MODIS DT over water, in interpreting the FMF product, one needs to consider that sea spray can also be a “coarse mode” aerosol, especially in the vicinity of the high-wind events that can also be effective in mobilizing local dust. This is not a concern in the seven cases highlighted in the current paper, but caution would be needed when applying the approach more generally.
Figure 2. In itself, this is a tough measurement. All the AODs are below 0.01. I understand that the authors have done a convincing job assembling other indications that this is a dust event. However, I have to ask whether variability in the background AOD produces similar fluctuations in general, especially if the intent is to subsequently apply this technique more widely, specifically in cases lacking the distinct, narrow plumes over dark water surfaces, downwind of regions with the characteristics of likely dust sources represented by the seven cases studied in detail here.
Lines 285-288. I know it is given in the publication cited in the footnote, but this estimate of MOIDS sensitivity to AOD seems *extremely* optimistic, especially when applied in the Arctic. Consider the further, extenuating conditions at high latitudes – low sun angle, very bright snow or ice-covered surfaces that can affect the recorded signal in nearby dark-water areas due to latency, internal reflections, or other instrumental effects, and possible thin cirrus contamination. I guess, for wider application of the approach, it would strengthen the case to show that, in non-dust circumstances (based on verifiable surface measurements where available), such remote-sensing signals are unlikely to occur. I.e., characterize as much as possible the likelihood of false positives.
Figure 4. Another thought, given the challenges involved in applying this technique more widely. Conditions for mobilizing dust would include sufficiently high wind (which is considered for the cases included in the paper), the availability upwind of loose surface dust that is not snow-, ice-, or vegetation-covered (also considered in the paper for the case studies), and usually some surface roughness to mix momentum downward. At least some locations of surface dust deposits have already been mapped across the Arctic, based on the identification of dry river deposits, mountain talus accumulations, etc. in seasons when those surfaces are snow- and ice-free. The exposure of such upwind surfaces at the specific time of dust-plume observation could be verified with contemporaneous satellite imagery. These considerations would be especially important when interpreting possible remote-sensing local dust-plume detections in general, in the absence of ground-truth data. (I agree that the seven specific cases presented in the current paper are convincing.)
Page 18, footnote 34. I’m not sure what “…neither the plume height nor the plume speed sampling trajectories are subject to any objective sampling protocol…” means. As I understand, the MISR MINX retrievals are done on all 1 km pixels within a user-defined aerosol plume region where the spatial contrast relative to surrounding pixels in the multi-angle images is sufficiently above the noise to produce a geometric height retrieval.
Generally, it would be helpful to have a more complete list of Symbols and Abbreviations. I know there is a list in Appendix B, but many are missing, such as, tco, tcp, tcl, VDR, etc. It is a long article, and there are many non-standard abbreviations; searching for the meaning of some abbreviation becomes tedious.