the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Feb 2025
Siberian wildfire smoke observations from space-based multi-angle imaging: A multi-year regional analysis of smoke particle properties, their evolution, and comparisons with North American boreal fire plumes
Abstract. The physical and chemical properties of biomass burning (BB) smoke particles vary with fuel type and burning conditions, greatly affecting their impact on climate and air quality. However, the factors affecting smoke particle properties are not well characterized on a global scale, and the factors controlling their evolution during transport are not well constrained. From observations of the Multi-Angle Imaging Spectrometer (MISR) instrument aboard NASA’s Terra satellite, smoke aerosol optical depth (AOD) can be retrieved, along with constraints on near-sourced plume vertical extent, smoke age, and particle size, shape, light-absorption, and absorption spectral dependence. Previous work demonstrated the robust, statistical characterization of BB particles across Canada and Alaska using MISR and other remote sensing data. Here we expand upon this work, studying over 3,600 wildfire plumes across Siberia. We leverage the MISR Research Aerosol (RA) algorithm to retrieve smoke particle properties and the MISR Interactive Explorer (MINX) tool to retrieve plume heights and the associated wind vectors. These results are compared statistically to available observations of fire radiative power (FRP), land cover characteristics, and meteorological information. Correlations appear between the retrieved smoke particle properties, smoke age, local ambient conditions, and fuel type, allowing us in many cases to infer the dominant aging mechanisms and the timescales over which they occur. Specifically, we find that plumes located in areas with higher peat content are subject to less oxidation and condensation/hydration compared to other plume types (e.g., forest and grassland), and are predominantly affected by dilution instead.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-395', Anonymous Referee #1, 18 Feb 2025
Using MISR and MERRA2 products, the authors extend previous analyses of Canada and Alaska wildfires to include those in Siberia. This is a generally excellent paper. It’s timely, insightful, and informative. But my recommendation to the editor is a straightforward rejection because of Code/Data Availability concerns (see my fuller comment below). If the authors address these concerns, I will be happy to take another look. I very much like the rest of the manuscript; if it weren’t for the Code/Data Availability, I would’ve recommended it for publication as-is (comments below are non-blocking).
Comments I wrote while (re)reading the manuscript:
L29: I think the word “however” is likely the wrong word here
L32: I think man-made may require qualification or even better a citation
L80: Still not really clear which study exactly examined the Canada and Alaska wildfires? Which one is it? Maybe just cite it here!
L86: And here!
L137: is the geometric standard deviation designated as well?
L140: citation (or link?) for may be needed for “publicly available”
L255: I didn’t check, but I assume that’s the same way you also defined it in the other study for the sake of consistency?
Figure 4: I found this figure hard to decipher (panels are too small, etc.). Consider improving. You can unify the titles (N=22, …) and labels (Forest, Woody, …) on top of the first row; you can use just on y-axis label (and include with it the a) median plume height, etc. info. Then, you may have enough space to showcase the figures themselves instead of the BIG words. See Figure 5, 6, 7 for inspiration :)
Table 3: I find tables in general hard to read. Is there a better way to showcase this data-rich info?
Table 4: this is a productive usage of the table format. Note a minor typo “but it’s AOD does” should be “but its AOD does” in the 4th row of the Fall column.
L511: The analysis and data are consistent across datasets/studies, right? If so, I would assure the readers here by stating that.
Section 3.6: I understand the authors plan to release more work with further and more in-depth analyses, but I think this manuscript will benefit from further contextualization and/or speculation. My comment here is vague, but it simply an invitation for the authors to do more here if they think it is warranted.
Code/Data Availability: After reading this manuscript, I got pretty excited about potentially using the data and/or taking a look the amazing underlying dataset. In my opinion, this Code/Data Availability section is unacceptable and as such I don’t think this work can be published without better disclosure of the underlying data AND some reproducibility code (to reproduce figures and tables in this manuscript). My request here, of course, does not apply to the noted propriety algorithm; you can keep that secret all you want. It applies to the raw data produced by this work, and especially the raw data used to make the scientific statements in this work. Also, please explicitly cite and point the reader to where they can find the "user-friendly" MINX. Anything short of full disclosure, the manuscript should be rejected and other reviewers shouldn’t waste time on it. I understand the authors wrote “[final URL is TBD]" but I am sorry, let’s not waste reviewers' time before it is “determined”
Supplement: same comment regarding tables and figures as I made regarding Figure 4 and Table 3 above.
Citation: https://doi.org/10.5194/egusphere-2025-395-RC1 -
RC2: 'Comment on egusphere-2025-395', Anonymous Referee #2, 04 Mar 2025
I think this is overall an excellent paper that provides interesting, useful, and sometimes surprising (and thus even more valuable) insights into the properties and ageing processes of Siberian biomass burning plumes. The findings, especially in the context of the broader goal of performing this analysis in different BB regions of the world (of which two – North America and Siberia have already been processed), have a great potential to contribute to better understanding and modeling of biomass burning aerosol emission processes. The goals stated in the introduction were reached by the work and well discussed in the conclusions.
Several items below would make the presented information clearer, in my opinion, but I did understand the message and the presentation well in its current form.
L33 – I would have liked to see a reference to a study (or several) linking aspects of climate change to changes in fires to support this important claim.
L55 – the use of “flame front” brought up the question if all the fires considered here were actively burning. Seeing a significant number of peatland fires – were any of these smoldering fires? Is this important here? It may be not, so either clarify, or maybe use another term here that indicates the location/source/point of combustion, but not paints the image of flame front.
L57 – “…and alter particle scattering as well as CCN efficiency, especially…” – you may want to add absorption after scattering here. You show that absorption profile changes with aging as well.
L59, also L52 and L68 – there are a lot of references in this list at the end of the paragraph, that are relevant to different parts of the paragraph. For example, Dalirian et al, 2018 is about CCN, so I would much prefer it to be mentioned as a stand-alone reference after CCN are mentioned in L57 than in a long list of other references about everything in the paragraph. This referring to works where they belong makes it a lot more convenient for the reader to get additional information on the point of interest right there, rather than going through the entire list.
L78 – In the sentence “In previous work…” do you mean Jungen Noyes at al., 2022? It is again cited in the end of the paragraph, so I was wondering all the way there, since line 78. Please move the reference to immediately after “In previous work…”
Table 2 – are the plumes above 2 km AGL a subset of Plumes above MERRA-2 PBL? I guessed that yes, but didn’t find a confirmation to it in the text.
Section 2.2 – Is this plumes dataset available somewhere? If it is a part of the bigger dataset of digitized plumes, from which you selected a subset of 3,716, then it would be helpful to know. If this has been created for this study specifically then it looks like a valuable set for the scientific community. Please create a supplemental table or a link to a text or ncdf or any other format file with geographic coordinates and relevant information for each plume, like, height, length, age, FRP, vegetation type… - pretty much whatever relevant information was used to produce tables and figures in this paper but for each plume. It will likely be a big table, but valuable for scientific community, and also solidify reproducibility of your results, should anyone wish to do any complimentary studies.
Fig 3 and Fig 4 – labels on individual graphs are very small and difficult to read especially in printed version. I had to magnify the digital copy. Every little graph in this figure has “N=” a few times above it. These are unnecessary and can be removed, just make a note in the table description that these digits are number of cases. In most graphs the numbers themselves could be moved inside the rectangle. These would free up some space to “stretch” the graph rectangles to make them more legible.
Fig. 5 – yellow axis labels are impossible to read in the printed version. Maybe, axes and labels can be black, while the data remains depicted in the color it is now. And, again, the labels are very small. There is no reason the graph can’t take up the whole page. If you transpose rows and columns, and represent the same data as 3 columns with 5 rows, it should fit nicely onto a vertical letter page.
Fig 6 and 7 – same comment as for Fig. 5 about difficult to read small color labels on axes, especially in printed version.
Citation: https://doi.org/10.5194/egusphere-2025-395-RC2
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