the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Oct 2024
Impacts of Sea Ice Leads on Sea Salt Aerosols and Atmospheric Chemistry in the Arctic
Abstract. Sea salt aerosols (SSA) alter Arctic climate through interactions with radiation and clouds. The processes contributing to Arctic cold season (November–April) SSA remain uncertain. Observations from coastal Alaska suggest emissions from open leads in sea ice, which are not included in climate models, may play a dominant role. Their Arctic-wide significance has not yet been quantified. Here, we combine satellite data of lead area (the AMSR-E product) and a chemical transport model (GEOS-Chem) to quantify pan-Arctic SSA emissions from leads during the cold season from 2002–2008 and predict their impacts on atmospheric chemistry. Lead emissions vary seasonally and interannually. Total monthly SSA emissions increase by 1.0–1.8 % (≥60° N latitude) and 5.8–8.4 % (≥75° N). The AMSR-E product detects at least 50 % of total lead area as compared to optical MODIS satellite images. SSA concentrations increase primarily at the location of leads, where standard model concentrations are low. GEOS-Chem overestimates SSA concentrations at Arctic sites even when lead emissions are not included, suggesting underestimation of SSA sinks and/or uncertainties in SSA emissions from blowing snow and open leads. Multi-year monthly mean surface bromine atom (Br) concentrations increase 2.8–8.8 % due to SSAs from leads. Changes in ozone concentrations are negligible. While leads contribute <10 % to Arctic-wide SSA emissions in the years 2002–2008, these emissions occur in regions of low background aerosol concentrations. Leads are also expected to increase in frequency under future climate change. Thus, lead SSA emissions could have significant impacts on Arctic climate.
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Status: open (until 28 Nov 2024)
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RC1: 'Comment on egusphere-2024-3147', Anonymous Referee #1, 07 Nov 2024
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General impressions:
This work uses satellite-based information on sea ice leads in the Arctic combined with GEOS-Chem model information to estimate the contribution of leads to the sea salt aerosol budget and bromine concentrations during November to April. It is a fairly straightforward study, and was relatively easy to follow. The contribution will be useful. However, I think it would be work further emphasizing the limitations of their approach, and under-emphasizing the links to climate, which I felt were a bit too bold. My impression is also that the writing and figures in the manuscript are not yet of sufficient quality for ACP. I recommend that the authors do several more rounds of editing before resubmission, since I only had time to point out some of the issues below. After addressing these issues, I would re-consider recommending it for ACP.
Specific comments:I recommend that the authors further clarify, and when appropriate, emphasize the limitations of their approach in detecting leads. For example,
L146: "The lead area fraction includes open water leads and thin ice-covered leads 3 km and wider." Please discuss with references the portion of leads that are are smaller than 3 km. This information was briefly touched on in the methods and conclusions, but should be further clarified and expanded upon. Depending on how many leads are being missed, it may merit that the authors clearly state in the title, abstract, introduction and conclusions that they are only focusing on large leads, to avoid misleading readers (no pun intended) about the meaning of their findings.
L152: "more than 50% of the total lead area visible in 500 m MODIS images was detected" Please address what fraction of leads will be missed with a 500 m resolution (or at least what is known about that question).I was unconvinced about the links to climate, and felt they were over-emphasized as written. For example:
Abstract: “Thus, lead SSA emissions could have significant impacts on Arctic climate.” There is a missing step in the logic here. Just because leads are increasing and they emit SSA doesn’t mean that there will be significant impacts on Arctic climate. What is the evidence for a link here?
Relatedly, L. 484: "...could also affect aerosol-cloud interactions, which largely have a warming effect in the Arctic from trapping of longwave radiation during the cold season (Cox et al., 2015; Stramler et al., 2011)." As written, this statement is not correct. Clouds have a warming effect in the Arctic from trapping of longwave radiation during the cold/dark season, but the warming vs. cooling effect from aerosol-cloud interactions in the Arctic is not well understood (e.g., Morrison et al., 2012; Schmale et al., 2021; Tan et al., 2023; Zamora and Kahn, 2024). Some studies suggest aerosol-cloud interactions can actually cool the surface during winter (e.g., Villanueva et al., 2022), although others disagree.I recommend that the authors either include in the analysis or cite other relevant datasets. For example:
L421: "This further highlights the need for observations in other regions to better understand the impacts of lead emissions." I believe there are other observations. For example, Villum Research Station has historic Na data. The 2008 NASA ARCTAS campaign has Br concentrations. There may also be data from ship campaigns and other aircraft campaigns as well.
L. 467: I am pretty sure there have been other relevant studies, e.g., from the MOSAiC field campaign.
L. 504: "To better constrain lead impacts on SSA and reduce uncertainty in the SSA size distribution, additional ground observations with size distribution information in the Canadian archipelago, such as off the northern coast of Baffin Island and the eastern coast of Victoria Island, would be beneficial." I recommend that the authors more throughly check to see what data in this area are already available. The NETCARE campaign, for example, took place in that region.The abstract needs some work. Regarding, “Total monthly SSA emissions increase by 1.0-1.8% (≥60°N latitude) and 5.8-8.4% (≥75°N),” please state the time frame that the increase refers to (Nov-April? 2002-2008? Something else?). Please also state the information this finding is based on. Also, from reading the abstract alone, it is unclear how the studies can show that GEOS-Chem overestimates SSA concentrations at Arctic sites. The reader is left guessing whether this is based on some ground data or something else. L 126-130: This information should also be in the abstract.
The paragraph starting on L 75 reads like a collection of facts. It would help to re-write it to emphasize just the relevant information a reader needs to know, and to clarify how the different facts are relevant.
L95: can you please clarify for the reader how snow becomes saline in the first place?
L 101, “Incorporating… ” please clarify how incorporating blowing snow SSA emissions into models has a significant impact on atmospheric chemistry
L142: “This method of detection can only be applied to the Arctic freezing season (November-April) due to surface melt of the sea ice May-October.” Please state why that is.
L153: Please specify more clearly how this information on MODIS is relevant
L172: Probably worth mentioning here that in the wintertime Arctic, there isn't a lot of rain deposition or convective precipitation. Also probably worth mentioning that precipitation is notoriously hard to predict correctly in the Arctic. Please comment on how this latter fact might influence your findings.
L185-191: It is not clear why this information is in the manuscript. Also, please state the reasoning for choosing the Jaegle et al. (2011) parameterization instead of the Nilsson et al. (2001) or Ioannidis et al. (2022) parameterizations.
Section 2.3: Please clarify what years the samples at Utqiaġvik, Zeppelin, and Alert were taken. Were they taken during the full time period of the study?
In Section 3, for Table 1: relative increases are more meaningful when placed in context of what they are relative to, so I recommend adding in monthly total SSA emissions to this Table. For example, a 1% increase in SSA emissions of 10 mg/m2/day might be more meaningful than an 8% increase in emissions of 0.1 mg/m2/day. This information is sort of present in Figure 3, but the information is presented later and in different units. So right now when a reader first sees Table 1, they are left wondering whether leads are really most important in January than November when freeze is still happening. Also, I would think that in January when sea ice is thicker and more compact, leads are possibly less common (not a sea ice expert here). Is that the case?
L. 255: "Total emissions are resolution independent" Why is that? Wouldn't there be more relevant information at a higher model resolution?
L 274: "Poleward..." can you speculate as to why this is? Presumably in April at lower latitudes melt is already occurring in some places, but what is going on in January?
Supplement L28: Which value for theta did the authors use? They only say the recommended value.
L.287: Please clarify the logic here instead of referencing section 2.2. Why would monthly total lead emissions and lead area having a low correlation mean that variance in monthly total lead emissions is dominated by the nonlinear dependencies on wind speed and sea surface temperature?
L. 324: It is important to say whether this "slight decreasing trend" is statistically significant. Based on the SD, it doesn't look like it is. If so, the authors should take that part of the sentence out. Same with the statement, "Changes in SSA mass concentration are also higher poleward of 75°N."Figs. 5 and 6: As stated before, I don't find the percent increase due to leads very meaningful. Please either convincingly explain what scientific process this metric is meaningful for, or remove the figure, or relate it more clearly to something like absolute concentrations.
Paragraph starting on L. 435: It reads strangely to have this much text referencing a figure in the supplement. I recommend either moving the supplement figure to the main text, or moving the paragraph to the supplement, and just summarizing the paragraph in a sentence or two in the main text.
L. 474: "We find that lead SSA emissions occur primarily in regions where other SSA emissions sources are very low, mainly within the Canadian archipelago and the eastern Greenland Sea." From Fig. 2, the lead emissions are higher in the Nares St. and in the Bering Strait than over the Canadian archipelago.
L. 493: Please add uncertainty estimates here.
L. 494: "The percent increase due to leads in SSA and Br concentrations are spatially coherent." Please clarify what this means.
The figures need some work. Here are some suggestions:
Fig. 1: There is not enough contrast between the white background and the light blue colors. Please redo the figure so that a reader can clearly see the lead area fraction and related percentages. Maybe a rainbow color scheme instead of just a blue-based color scheme would help?
Figure 1: You might consider changing the month to January from November, so people can compare lead fraction in January to the data shown in Figs. 2 and 4.
Fig. S1: Please increase the font size of the color bar
Fig. 4: Please make the sites have larger point sizes and larger fonts. It's really hard to see them, and I could barely find Alert at all. Also, I think the Utqiaġvik, Alaska point is currently placed in the figure in Russia, so please check the coordinates.
Figs. 4, 6, S5, and S7: Please enhance the contrast in the land border color in the figures relative to the figure colors. Right now the black thin borders cannot be easily seen, making it harder to distinguish feature locations.
Fig. 7: The current color scheme and shaded areas make it very difficult to distinguish between the Observations and the Standard run. Please fix.
Fig. S6: Please increase font of the months in the key.
Figs. S4, S8 are blurry. Please increase resolution.
Fig. S8: The color contrast between the blues and the oranges are hard to distinguish. Please fix.
Technical comments:
L 75: “lead-based SSA” would it be more accurate to say something like, “emissions of SSA from leads”?
L105: “incorporates” should be changed to “incorporated”
109: “analysis” should be changed to “analyses”
123: should be “produces”
L162: "(Community, 2021)" This isn't the correct citation
L166: "from the NASA"
L168: "wind-" not "wind"
Paragraph starting on L168 should be broken up into several paragraphs
L169: "sea-surface-temperature-dependent"
L182: " The AMSR-E satellite data is regridded to 0.5°x0.625° from 6.25x6.25 km using a distance-weighted average remapping." This sentence seems out of place.
L183: "This is..." Please specify what "this" refers to
L100 in Supplement: "updates"
L105 in Supplement: "running" not "run"?
L 490: "the standard concentration " of what? SSA?
References:
Morrison, H., de Boer, G., Feingold, G., Harrington, J., Shupe, M. D., & Sulia, K. (2012). Resilience of persistent Arctic mixed‐phase clouds. Nature Geoscience, 5(1), 11–17. https://doi.org/10.1038/ngeo1332
Schmale, J., Zieger, P., & Ekman, A. (2021). Aerosols in current and future Arctic climate. Nature Climate Change, 11(2), 95–105. https://doi.org/ 10.1038/s41558‐020‐00969‐5
Tan, I., Sotiropoulou, G., Taylor, P. C., Zamora, L., & Wendisch, M. (2023). A review of the factors influencing arctic mixed‐phase clouds: Progress and outlook. In Clouds and their climatic impacts: Radiation, circulation, and precipitation (pp. 103–132). American Geophysical Union (AGU). https://doi.org/10.1002/9781119700357.ch5
Villanueva, D., Possner, A., Neubauer, D., Gasparini, B., Lohmann, U., & Tesche, M. (2022). Mixed‐phase regime cloud thinning could help restore sea ice. Environmental Research Letters, 17(11), 114057. https://doi.org/10.1088/1748‐9326/aca16d
Zamora, L. M., & Kahn, R. A. (2024). First observational evidence that dust‐driven cloud phase changes cool the surface over summertime Arctic sea ice. Geophysical Research Letters, 51, e2024GL110423. https://doi.org/10.1029/2024GL110423
Citation: https://doi.org/10.5194/egusphere-2024-3147-RC1 -
RC2: 'Comment on egusphere-2024-3147', Anonymous Referee #2, 08 Nov 2024
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Summary
The paper presents a detailed study on the contribution of sea ice leads to sea salt aerosol (SSA) emissions and their impact on atmospheric chemistry in the Arctic. The authors utilize satellite data and the GEOS-Chem chemical transport model to quantify these emissions and assess their significance. The combination of satellite observations with a chemical transport model is an approach that can improve the understanding of SSA emissions from sea ice leads. The SSA emissions associated with sea ice leads are generally not well known and this approach may be a good approach to help solve this problem. A clearer focus of the paper would be helpful. There are discussions of climatological scale change, but results are based on a relatively short AMRS-E dataset. If the aim is to present climate scale change, the inclusion of AMRS-2 data and/or IR based lead detections would be necessary. If the intention is only to focus on presented dataset, then it would seem better to limit discussion to the observed inter-annual variability and save discussion of climate scale change for a larger study.
Specific comments
- Line 57: There would not be any scattering of incoming solar radiation during the season when there is no incoming solar radiation. Or at least the impact would be small given the darkness dominates the region in the winter season.
- Section 2.1: It would be helpful to include a description of the operational lifespan of AMSR-E and how that is a constraint on the period of study. Also, the study seems quick to dismiss the use of thermal IR techniques for lead detection. While it is true that microwave bands are less sensitive to clouds, the IR sensors have higher spatial resolution. There could be more discussion on the lifespan of SSA in the atmosphere and the relationship between SSA and clouds. For example, it would seem that SSA would have negligible radiative forcing when under a canopy of opaque clouds, the observation of cloud may be larger SSA sink than a source (even if there are leads under cover of clouds), and how does the lifespan of SSA in the atmosphere compare to clouds (if they are on the same order of magnitude, then detection of SSA under clouds may be irrelevant)?
- Line 153: There is mention that 50% of the total lead area visible in MODIS is detected by AMSR-E. But presumably the AMRS-E would have a bias towards detected the wider leads. Has there been any work to study a correlation between lead with and SSA emission? There seems to be an assumption that leads emit SSA at an equal rate as a function of width. However, I would suspect that narrow leads are more likely to emit SSA at a higher rate per area because there would be more thermal contrast (and convective mixing) associated with narrow leads and a lower rate of SSA emission for wider leads. But this is my own speculation, and a literature review on this may be necessary to see if there have been any studies on this.
- Line 155: The reference to the Hoffman et al 2022 paper does not seem appropriate here. That paper uses the Level 1 brightness temperatures for the lead detection not the Level 2 SST product. The SST product is in fact limited to clear sky conditions. But lead detection in Hoffman et al ’22 is possible under optically thin cloud conditions (under a wider range of conditions where a sea surface temperature retrieval is possible).
- Line 262: It would be helpful to identify regions by the name of the sea rather than location relative to a country.
- Line 277: Is there a trend in the inter-annual viability? If so, could results be presented as a slope rather than a constant?
- Line 279: It might be helpful to show the corresponding lead area, mean wind, and mean SST to get a better sense of how these relate to the plotted SSA emissions.
- Line 305: It seems surprising that the largest increase in SSA appears in the Canadian Archipelago, but Figure 1 did not show this region to have especially high lead fractions. There is a brief mention of this in the conclusion, but more explanation may be appropriate in Section 3.2. For example, is the lead fraction low in this region because the denominator includes water area plus land area; would the lead fraction be higher if the denominator is only water area?
- Line 392, 399, and 400: given the ranges of uncertainty, 2 significant digits may be more appropriated than the 3 digits that are given.
- Line 428: This may be a reason to use IR based lead detections and focus on lead emissions under clear sky conditions. Might your bias be because clouds are a net sink for SSA – even if leads are occurring under opaque clouds?
- Line 451: Replace “too-low” with “under predicted”.
- Line 452: How good of an observation site can a station on land be for an observation of oceanic processes? For example, if you have a land-breeze the station might not be representative of the air over the ocean. Have you filtered the observations to only include observations when the wind is in the direction of the ocean and/or exclude observations wind the wind is coming from the continent?
Citation: https://doi.org/10.5194/egusphere-2024-3147-RC2
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