the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 May 2022
Modelling wintertime Arctic Haze and sea-spray aerosols
Abstract. Anthropogenic and natural emissions contribute to enhanced concentrations of aerosols, so-called Arctic Haze in the Arctic winter and early spring. Models still have difficulties reproducing available observations. Whilst most attention has focused on the contribution of anthropogenic aerosols, there has been less focus on natural components such as sea-spray aerosols (SSA), including sea-salt sulphate and marine organics, which can make an important contribution to fine and coarse mode aerosols, particularly in coastal areas. Models tend to underestimate sub-micron and overestimate super-micron SSA in polar regions, including in the Arctic region. Quasi-hemispheric runs of the Weather Research Forecast model, coupled with chemistry model (WRF-Chem) are compared to aerosol composition data at remote Arctic sites to evaluate the model performance simulating wintertime Arctic Haze. Results show that the model overestimates sea-salt (sodium and chloride) and nitrate and underestimates sulphate aerosols. Inclusion of more recent wind-speed and sea-surface temperature dependencies for sea-salt emissions, as well as inclusion of marine organic and sea-salt sulphate aerosol emissions leads to better agreement with the observations during wintertime. The model captures better the contribution of SSA to total mass for different aerosol modes, ranging from 20–93 % in the observations. The sensitivity of modelled SSA to processes influencing SSA production are examined in regional runs over northern Alaska (United States) where the model underestimates episodes of high SSA, particularly in the sub-micron, that were observed in winter 2014 during field campaigns at the Barrow Observatory, Utqiaġvik. A local source of marine organics is also included following previous studies showing evidence for an important contribution from marine emissions. Model results show relatively small sensitivity to aerosol dry removal with more sensitivity (improved biases) to using a higher wind speed dependence based on sub-micron data reported from an Arctic cruise. Sea-ice fraction, including sources from open leads, is shown to be a more important factor controlling modelled super-micron SSA than sub-micron SSA. The findings of this study support analysis of the field campaign data pointing out that open leads are the primary source of SSA, including marine organic aerosols during wintertime at the Barrow Observatory, Utqiaġvik. Nevertheless, episodes of high observed SSA are still underestimated by the model at this site, possibly due to missing sources such as SSA production from breaking waves. An analysis of the observations and model results does not suggest an influence from blowing snow and frost flowers to SSA during the period of interest. Reasons for the high concentrations of sub-micron SSA observed at this site, higher than other Arctic sites, require further investigation.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(31007 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(31007 KB) - Metadata XML
- BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
CC1: 'Review of egusphere-2022-310', Øystein Hov, 23 Jun 2022
Title: Modelling wintertime Arctic Haze and sea-spray aerosols
Author(s): Eleftherios Ioannidis, Kathy S. Law, Jean-Christophe Raut, Louis Marelle, Tatsuo Onishi, Rachel M. Kirpes, Lucia Upchurch, Andreas Massling, Henrik Skov, Patricia K. Quinn, and Kerri A. Pratt
MS No.: egusphere-2022-310
MS type: Research articleOverall review based on the principal criteria:
Does the manuscript represent a substantial contribution to scientific progress within the scope of Atmospheric Chemistry and Physics (substantial new concepts, ideas, methods, or data)? FAIR
Are the scientific approach and applied methods valid? Are the results discussed in an appropriate and balanced way (consideration of related work, including appropriate references)? GOOD
Are the scientific results and conclusions presented in a clear, concise, and well-structured way (number and quality of figures/tables, appropriate use of English language)? FAIR
The findings and conclusions are not clear. In my opinion the approach taken in the paper precludes clarity as references to literature findings are continuously introduced interrupting the flow of a consistent argument based on the data material of the study to attempt to answer a few scientific questions (which need to be posed), like what are the relative importance of the removal processes and dispersion for the aerosol concentrations calculated at the observational site?
Some comments:
On l. 85-87 the purpose of the paper is stated: «In this study, the performance of the Weather Research Forecast model, coupled with chemistry (WRF-Chem), is examined with regard to its ability to simulate Arctic Haze composition as well as SSA components, including ss-SO2− 4 and marine organics.» This is done by comparing model results for two five-day periods in January-February 2014 with observations taken close to Barrow in Alaska. This means that the paper takes the “model for science”-approach, while in a model evaluation requires more of a “science for model” approach. How is the model diagnosing the processes that affect the calculated concentrations?
The paper is to a large extent a review of literature of observations of aerosols in the Arctic. The number of references is very large, while the understanding communicated from them in the paper is more limited. It does not present the picture of the mechanisms and processes – and their variability with time and in space - that modify the aerosol amount and composition from the source to the receptor, no discussion of lifetime regimes for aerosols of different size and age, even though the field of aerosols is quite old with numerous studies of processes that influence aerosols also in the Arctic and including SSA, since the 1970s. The model results are only discussed in terms of the concentrations calculated, while the diagnostics - why the results ended up in the way they did, is not known. This limits the learning from the results.
One would think that anthropogenic aerosol (fractions) and SSA have quite different lifecycles in the Arctic. In particular super-micron SSA is probably rather local and depending in a quite non-linear way on the upwind wind speed, and depending on the the air masses passing over open leads in sea ice upwind of the observation site. While the concentration of anthropogenic aerosols at a surface site like the one used here, would depend strongly on the synoptic weather situation. Was the site inside or outside of the polar vortex? Are there anthropogenic sources that can emit aerosols or precursors that can be transported close to the surface to the site? To what extent is the calculated aerosol concentration at the Alaska site a small number which is the difference between two much larger numbers? (The concentration field calculated with really slow loss mechanisms compared with a concentration field with a realistic loss processes.) (In this case a factor of 2 or even 5 “error” in calculated concentration near Barrow would be quite a success.)
Even though the agreement between observed and calculated wind speed is very high at the measurement site (Figure D2) (is that due to the nudging?) one would think that in particular for super-micron SSA the concentrations are quite sensitive to the upwind wind velocity close to the ground, as well as the sea ice conditions when the air passes over the ocean. This calls for high resolution limited area modelling of a coupled NWP-sea ice model data assimilation, of the type now available at some meteorological centres. 2-3 km resolution is often routinely available. The 20 and 100 km resolution used for atmospheric physics and dynamics and no mention of data assimilation, seem to inject a fairly large uncertainty into a decisive part of the data set that the WRF-chem calculations are based on?
The illustrations are quite straight forward comparisons of calculations and observations while the text in quite long sections is a description of what the figures show. Perhaps it is possible to convey more understanding thorugh the illustrations? Model diagnostics?
Citation: https://doi.org/10.5194/egusphere-2022-310-CC1 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
RC1: 'Comment on egusphere-2022-310', Anonymous Referee #1, 06 Aug 2022
This work applies the WRF-Chem model to the Arctic and compares with observations, from January and February, 2014, in an effort to evaluate and improve the model’s capabilities to represent the atmospheric aerosol over the Arctic with a particular focus on the modelling the main chemical components of sea spray.
Comparisons of simulations from a “Control” version of the model and from an updated version (“HEM_NEW)” are drawn with coarse particle observations of nitrate, sulphate, chloride, ammonium and sodium from Alert, Villum and Zeppelin. The domain, d1 shown in Figure 1, is simulated at a resolution of 100x100 km. Then, ‘Control’ and ‘HEM_NEW’ comparisons are made with fine particle observations from Simeonof and Gates of the Arctic, for the same suite of chemical components. In this case, the model domain (d2) is nested within the d1 domain, and the simulations are a resolution of 20x20 km. (Note: in Figure 1, Simeonof is shown outside of d2, but in Figure 3 it appears that the model resolution is the same for both Simeonof and Gates of the Arctic; please clarify). Subsequently, comparison of ‘Control’ and ‘HEM_NEW’ are drawn with observations of both super-micron and sub-micron particle composition measurements from the Barrow Observatory within d2 at 20x20 km resolution. The differences between “’Control’ and ‘HEM_NEW’ could be more clearly delineated, perhaps in a Table. I understand them to be the addition of marine organics, the addition of a sea-surface temperature component for sea spray emissions, application of satellite data to improve the whitecap fraction and the addition of a sea-salt sulphate component.
In section 5, Table 3 is a bit confusing, but it appears that ‘HEM_NEW’ run at 20x20 km resolution over Alaska becomes the “Alaska_Control” and “NEW_Alaska” is ‘Alaska_Control’ with updated dry deposition code, a local source of marine organics, a modified sub-micron particle dependence on wind-speed and increased resolution of sea-ice fractions.
Overall, the paper is an important document of justified changes to a model, made to improve its ability to represent the Arctic aerosol. The paper is long, a bit repetitious in a few spots, and reasonably well organized. It could benefit from a careful look at little details, including some of the figures. I have one major concern and a number of minor comments.
Major
1. Sea-spray aerosol (SSA) is a major component of this paper, and I agree that it is an important topic. However, Arctic Haze is in the title and nss-sulphate has been the major component of Arctic Haze. The deficiency in modelled submicron sulphate at Barrow is substantial (Fig. 4b and 11), but little discussion is given to it. The sulphate time series is relatively flat in Figure 4b, which seems unrealistic. Sub-micron aerosol at Alert, Villum and Zeppelin is neither shown nor discussed, aside from the reference to OM at Alert on line 429. My concern here is that if the model does not simulate Arctic Haze well, that transport of sea spray from more distant sources may be a problem as well. If so, this could jeopardize your conclusion about open leads as the major source of SSA. On the other hand, sub-micron nss-SO4= at Alert during January and February, 2014 was unusually low, and may be more consistent with your simulations. Do you have any references that indicate the model does well with Arctic Haze, or would you show comparisons of submicron sulphate from the model with observations at Alert, Villum and Zeppelin? This issue needs to be dealt with in the paper.
Minor comments
2. Line 4 – Concerning organics, you might consider here the paper by Mungall et al.: Microlayer source of oxygenated volatile organic compounds in the summertime marine Arctic boundary layer, P. Natl. Acad. Sci. USA, 114, 6203, https://doi.org/10.1073/pnas.1620571114, 2017.
3. Line 16 – Maybe reduced biases, instead of improved biases.
4. Line 31 – “mid-latitude”
5. Line 55 – Also important to further knowledge about the vertical extent of SSA.
6. Line 110 – Instead of “All the various processes”, maybe “The well-known processes” or “Basic processes”
7. Line 112-113 – What about dust? It can be an important factor in the Arctic.
8. Section 3.1 – With respect to Alert, I suspect the coarse-particle chemistry is based on the difference between high-volume (essentially TSP) filters collected outside and submicron filters collected inside. The high uncertainties may be related to uncertainty in cut size of the submicron filters. Also, the high-volume filters are susceptible to blowing snow, which may (on occasion) bias concentrations a bit high.
9. Line 224 – “long-raNge”
10. Lines 228-229 – The sea around Alert is also frozen in winter.
11. Figure 2 – I suggest only showing the weekly-averaged model points to enable the scale be expanded to show the proper comparisons better.
12. Figure 6 and like figures – Can you place the labels horizontally above or below the globes?
13. Figure 3 - What is the difference between the blue crosses and the grey dots in SO4= in Figure?
14. Lines 401-403 – This may be too simple a solution. The aqueous phase is unlikely at Alert in winter, unless in fine haze particles (possibly quite acidic). Transport to Alert through liquid clouds at more southern latitudes is possible, but then some sunlight might be a factor too.
15. Line 407 - It is not so easy to see this for NH4+, since the concentrations of NH4+ are quite small. What is the uncertainty in the NH4+ measurements?
16. Line 415 and Figure 4b - It is very difficult to tell from this figure that lower concentrations are better represented by HEM_NEW.
17. Line 418 – Modelled sub-micron OA…
18. Line 429 – parenthesis after “2” not needed.
19. Line 455 – “difficulties in capturing sub-micron SSA and nss-SO4= during wintertime…”
20. Line 462 – Demonstrations of the importance of wet and dry deposition goes back further than 2007. Maybe “the importance of the formulation of wet and dry removal…”?
21. Figure 7 caption – “sub-micron aerosol mass concentrations” instead of aerosol mass concentrations for sub-micron”.
22. Line 514 – not be expected
23. Line 517 – “in clean regions of the Arctic” is a little too broad. Wasn't it near Zeppelin? Also, clean regions of the Arctic is contradicted by Arctic Haze.
24. Lines 621-622 – Maybe “Overall, the Alaska-New January simulations of sub-micron Na+ and Cl- are an improvement over the CONTROL, but still ...”
25. Line 667 – “not a significant source of SSA”
26. Lines 726-728 - This is misleading, unless you can show that submicron aerosol at other sites compares well.
27. Lines 729-730 - Not to underestimate the potential of aqueous-phase processes, I feel that the third reference to metal-catalysed aqueous-phase oxidation, without a comprehensive discussion, over-emphasizes the potential of this process.
28. Lines 766-769 – By radiative effects in the darkness of winter, I assume you are suggesting that SSA contributes to changes in longwave radiation or is somehow involved with ice crystals. A little more detail would help, including a reference or two.Citation: https://doi.org/10.5194/egusphere-2022-310-RC1 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
RC2: 'Comment on egusphere-2022-310', Anonymous Referee #2, 24 Aug 2022
The manuscript by Ioannidis et al. reports model simulations over the Arctic with the aim of improving SSA predictions. The study is a large effort trying to examine the impact of various recent parameterisations on the model output and agreement with the observations.
Despite a significant effort by the authors it falls short of advancing the understanding of processes and their impact on model output. Just for a start, the paper title emphasizes Arctic haze while the main stated purpose is to advance SSA predictions. I am not suggesting that Arctic haze is not important, but the current version if a mix of everything: mostly sea spray, but frequently interspersed by acidic components and anthropogenic sources. That does not help to deliver focused conclusions, because there are already too many issues related to sea spray alone.
However, the most significant problem is related to the implementation of the study. What was the purpose of using an outdated sea spray source function – Gong97, which is not even based on observations, but is rather a mathematical extension of an even older, although pioneering at a time, study of Monahan, combined with the slightly more contemporary observational data of O’Dowd et al. 1997? Being instrumentally limited, even O’Dowd et al. size distribution stopped at 0.1um in diameter when there are plenty of recent papers providing evidence of large numbers of sea spray particles down to 10nm (L. Cravigan et al. 2015 JGR, A. Schwier et al. 2015 ACP, J. Ovadnevaite et al. 2014 ACP, W. Xu et al., 2022 Nature Geoscience just to name a few). Surprisingly, none of the above papers are mentioned despite a clear contextual value. That is even more surprising given the choice of the state-of-the-art WRF-Chem model. If sea spray model output so outdated and diverging with observations, how can anyone trust inferences on marine organic matter, ssSO4 and processes taking place in internally mixed particles?
I wonder why the authors did not make an attempt to compare with size distribution data. That is a critical aspect, because focusing on mass balance does not advance process understanding and produces little value when it comes to studying aerosol-cloud interactions and predicting CCN. Mass balance is dominated by supermicron fraction in sea spray while the number is dominated by the submicron fraction.
The paper is very long and well organized, but suffers from lack of focus. For example, take dry deposition section. There is no context of reason given why the impact of dry deposition is explored given the fact that the model generally underestimates SSA and larger dry deposition is only making matters worse. The other example is sulphate. Although there is a clear distinction between ssSO4 and nssSO4, the model comparison only deals with total SO4 making all findings or inferences vague as those species come from entirely different sources. The authors devote a large section on neutralization factor, but use total sulphate in calculations despite the fact that only nssSO4 is making aerosol acidic. By contrast, ssSO4 is balanced by sea salt cations.
Conclusions are a compilation of mostly speculative statements. Some of them are pure speculations as to suggesting what was not included in the model and what impact it would have had if it was (anyone’s guess really), some are speculative in a sense that no quantitative support is given. If something improved the simulations, then by how much? Was better agreement marginal or significant? Same criticism applies to Abstract where there is a single number to illustrate the results.
Although the value of the paper would not dramatically improve, a reorganisation of the paper by dropping anthropogenic components and by providing better context, reasoning and the outcome of specific parameterisations would make it more readable and useful.
Other comments as they appeared
Line 2. Models will always have difficulties reproducing observations, because they are just model approximations. Model agreement does not need to be perfect if it captures key processes consistently.
Line 8. The statement that the model overestimates sea salt is contradicted by all further results where model consistently underestimates sea salt.
Line 10. Sea salt sulphate is part of sea salt, why is it included second time? Please clarify if not.
Line 21. Breaking waves (open ocean or open leads) are the main source of SSA, how can it be missing?
Line 55. How come open ocean be a new SSA source if it was always the main one? The statement is either completely wrong or should be rephrased/clarified.
Line 129. Sea spray is not just Na and Cl. Sea spray is sea salt (including sea salt sulphate) and primary organic matter. Those early SSA functions were derived from physical particle measurements, not chemical measurements. This aspect is crucial for comparing model and observations which often report just Na and Cl and rarely sea salt sulphate, other major ions and almost never OM.
How Gong et al. source function was translated into Na and Cl emissions? Was it necessary at all, because it is rather straightforward to split sea salt into major components, like Na, Cl, ssSO4, etc.
What was the rationale to improve model simulations by using three decades old source function alongside with newly discovered SSA sources from open leads and frost flowers?
Line 187. It is crucial to acknowledge and discuss sampling loses in sea salt observations, because models do not take into consideration of sampling inlets and other sampling artefacts. Sampling losses are mostly related to super-micron range, but depend on specific inlets or samplings ducts.
Therefore, given the fact, that the model is generally underestimating observations, sampling losses would make underestimation even more dramatic.
Figure 2. HEM_NEW or CONTROL simulations were not introduced up to this point.
Line 217. How could Fuentes parameterisation for sub100nm be fully utilized if Gong97 or its extension based on O'Dowd97 stopped at 100nm?
Line 224. 20% of ss-SO4 is not a small fraction.
Line 233. I am not sure that anthropogenic Na was properly estimated given Cl depletion in anthropogenic air masses, which tends to be translated into excess Na and thus anthropogenic source. The authors do not discuss Cl/Na ratio which would be informative and also considering derivation of ssSO4 as 0.25xNa.
Line 259. What was the degree of neutralization considering the fact that NH3 neutralizes the stronger sulphuric acid and only then the nitric acid?
Line 278. The authors missed to mention earlier pioneering studies of Blanchard 1976, O'Dowd et al. 2004 Nature and later Ovadnevaite et al. 2011 GRL, 2014 JGR. The authors have a justified liberty of choosing parameterization, but the acknowledgement of earlier studies is advisable.
Line 316. Wind speed is indeed an oversimplified dependency most importantly not accounting for increasing and decreasing wind speed relationships. This aspect as well SST dependence together with a new sea salt source function accounting for the sea state was introduced by Ovadnevaite et al. in 2014 ACP.
Line 331. Na, Cl, ss-SO4 and OM does not capture full sea spray as Mg, Ca, K are missing. How was the ss-SO4 fraction of 9.9% obtained, especially that 7% is arising from basic sea water composition?
Line 356. Basic inorganic chemistry mandates that NH3 is first neutralising sulphuric acid (stronger acid) and producing either ammonium bisuphate or sulphate. Only a leftover producing ammonium nitrate which is pretty stable in polar areas.
Line 360. f=1 is representing fully neutralized aerosol, not "more". More importantly, only nss-SO4 (and NO3) should be used for assessing neutralization, because ss-SO4 is balanced by other cations in sea water (salt).
Line 378. Sulphate and nitrate mass is conserved and has nothing to do with chlorite depletion reactions as model simulation do not output masses of specific salts like Na2SO4 or NaNO3 to attempt Na mass balance.
Line 480. If model underestimates SSA in general, higher dry deposition only makes matters worse. Clearly larger dry deposition is studied not for the better agreement, but simply for theoretical reasons. Better justification and context is needed in this section.
Line 558. SSA - win speed relationship is nonlinear (power of 2-3) with Gong97 on a high end of values. What is the purpose of comparing with linear dependences?
Citation: https://doi.org/10.5194/egusphere-2022-310-RC2 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
Interactive discussion
Status: closed
-
CC1: 'Review of egusphere-2022-310', Øystein Hov, 23 Jun 2022
Title: Modelling wintertime Arctic Haze and sea-spray aerosols
Author(s): Eleftherios Ioannidis, Kathy S. Law, Jean-Christophe Raut, Louis Marelle, Tatsuo Onishi, Rachel M. Kirpes, Lucia Upchurch, Andreas Massling, Henrik Skov, Patricia K. Quinn, and Kerri A. Pratt
MS No.: egusphere-2022-310
MS type: Research articleOverall review based on the principal criteria:
Does the manuscript represent a substantial contribution to scientific progress within the scope of Atmospheric Chemistry and Physics (substantial new concepts, ideas, methods, or data)? FAIR
Are the scientific approach and applied methods valid? Are the results discussed in an appropriate and balanced way (consideration of related work, including appropriate references)? GOOD
Are the scientific results and conclusions presented in a clear, concise, and well-structured way (number and quality of figures/tables, appropriate use of English language)? FAIR
The findings and conclusions are not clear. In my opinion the approach taken in the paper precludes clarity as references to literature findings are continuously introduced interrupting the flow of a consistent argument based on the data material of the study to attempt to answer a few scientific questions (which need to be posed), like what are the relative importance of the removal processes and dispersion for the aerosol concentrations calculated at the observational site?
Some comments:
On l. 85-87 the purpose of the paper is stated: «In this study, the performance of the Weather Research Forecast model, coupled with chemistry (WRF-Chem), is examined with regard to its ability to simulate Arctic Haze composition as well as SSA components, including ss-SO2− 4 and marine organics.» This is done by comparing model results for two five-day periods in January-February 2014 with observations taken close to Barrow in Alaska. This means that the paper takes the “model for science”-approach, while in a model evaluation requires more of a “science for model” approach. How is the model diagnosing the processes that affect the calculated concentrations?
The paper is to a large extent a review of literature of observations of aerosols in the Arctic. The number of references is very large, while the understanding communicated from them in the paper is more limited. It does not present the picture of the mechanisms and processes – and their variability with time and in space - that modify the aerosol amount and composition from the source to the receptor, no discussion of lifetime regimes for aerosols of different size and age, even though the field of aerosols is quite old with numerous studies of processes that influence aerosols also in the Arctic and including SSA, since the 1970s. The model results are only discussed in terms of the concentrations calculated, while the diagnostics - why the results ended up in the way they did, is not known. This limits the learning from the results.
One would think that anthropogenic aerosol (fractions) and SSA have quite different lifecycles in the Arctic. In particular super-micron SSA is probably rather local and depending in a quite non-linear way on the upwind wind speed, and depending on the the air masses passing over open leads in sea ice upwind of the observation site. While the concentration of anthropogenic aerosols at a surface site like the one used here, would depend strongly on the synoptic weather situation. Was the site inside or outside of the polar vortex? Are there anthropogenic sources that can emit aerosols or precursors that can be transported close to the surface to the site? To what extent is the calculated aerosol concentration at the Alaska site a small number which is the difference between two much larger numbers? (The concentration field calculated with really slow loss mechanisms compared with a concentration field with a realistic loss processes.) (In this case a factor of 2 or even 5 “error” in calculated concentration near Barrow would be quite a success.)
Even though the agreement between observed and calculated wind speed is very high at the measurement site (Figure D2) (is that due to the nudging?) one would think that in particular for super-micron SSA the concentrations are quite sensitive to the upwind wind velocity close to the ground, as well as the sea ice conditions when the air passes over the ocean. This calls for high resolution limited area modelling of a coupled NWP-sea ice model data assimilation, of the type now available at some meteorological centres. 2-3 km resolution is often routinely available. The 20 and 100 km resolution used for atmospheric physics and dynamics and no mention of data assimilation, seem to inject a fairly large uncertainty into a decisive part of the data set that the WRF-chem calculations are based on?
The illustrations are quite straight forward comparisons of calculations and observations while the text in quite long sections is a description of what the figures show. Perhaps it is possible to convey more understanding thorugh the illustrations? Model diagnostics?
Citation: https://doi.org/10.5194/egusphere-2022-310-CC1 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
RC1: 'Comment on egusphere-2022-310', Anonymous Referee #1, 06 Aug 2022
This work applies the WRF-Chem model to the Arctic and compares with observations, from January and February, 2014, in an effort to evaluate and improve the model’s capabilities to represent the atmospheric aerosol over the Arctic with a particular focus on the modelling the main chemical components of sea spray.
Comparisons of simulations from a “Control” version of the model and from an updated version (“HEM_NEW)” are drawn with coarse particle observations of nitrate, sulphate, chloride, ammonium and sodium from Alert, Villum and Zeppelin. The domain, d1 shown in Figure 1, is simulated at a resolution of 100x100 km. Then, ‘Control’ and ‘HEM_NEW’ comparisons are made with fine particle observations from Simeonof and Gates of the Arctic, for the same suite of chemical components. In this case, the model domain (d2) is nested within the d1 domain, and the simulations are a resolution of 20x20 km. (Note: in Figure 1, Simeonof is shown outside of d2, but in Figure 3 it appears that the model resolution is the same for both Simeonof and Gates of the Arctic; please clarify). Subsequently, comparison of ‘Control’ and ‘HEM_NEW’ are drawn with observations of both super-micron and sub-micron particle composition measurements from the Barrow Observatory within d2 at 20x20 km resolution. The differences between “’Control’ and ‘HEM_NEW’ could be more clearly delineated, perhaps in a Table. I understand them to be the addition of marine organics, the addition of a sea-surface temperature component for sea spray emissions, application of satellite data to improve the whitecap fraction and the addition of a sea-salt sulphate component.
In section 5, Table 3 is a bit confusing, but it appears that ‘HEM_NEW’ run at 20x20 km resolution over Alaska becomes the “Alaska_Control” and “NEW_Alaska” is ‘Alaska_Control’ with updated dry deposition code, a local source of marine organics, a modified sub-micron particle dependence on wind-speed and increased resolution of sea-ice fractions.
Overall, the paper is an important document of justified changes to a model, made to improve its ability to represent the Arctic aerosol. The paper is long, a bit repetitious in a few spots, and reasonably well organized. It could benefit from a careful look at little details, including some of the figures. I have one major concern and a number of minor comments.
Major
1. Sea-spray aerosol (SSA) is a major component of this paper, and I agree that it is an important topic. However, Arctic Haze is in the title and nss-sulphate has been the major component of Arctic Haze. The deficiency in modelled submicron sulphate at Barrow is substantial (Fig. 4b and 11), but little discussion is given to it. The sulphate time series is relatively flat in Figure 4b, which seems unrealistic. Sub-micron aerosol at Alert, Villum and Zeppelin is neither shown nor discussed, aside from the reference to OM at Alert on line 429. My concern here is that if the model does not simulate Arctic Haze well, that transport of sea spray from more distant sources may be a problem as well. If so, this could jeopardize your conclusion about open leads as the major source of SSA. On the other hand, sub-micron nss-SO4= at Alert during January and February, 2014 was unusually low, and may be more consistent with your simulations. Do you have any references that indicate the model does well with Arctic Haze, or would you show comparisons of submicron sulphate from the model with observations at Alert, Villum and Zeppelin? This issue needs to be dealt with in the paper.
Minor comments
2. Line 4 – Concerning organics, you might consider here the paper by Mungall et al.: Microlayer source of oxygenated volatile organic compounds in the summertime marine Arctic boundary layer, P. Natl. Acad. Sci. USA, 114, 6203, https://doi.org/10.1073/pnas.1620571114, 2017.
3. Line 16 – Maybe reduced biases, instead of improved biases.
4. Line 31 – “mid-latitude”
5. Line 55 – Also important to further knowledge about the vertical extent of SSA.
6. Line 110 – Instead of “All the various processes”, maybe “The well-known processes” or “Basic processes”
7. Line 112-113 – What about dust? It can be an important factor in the Arctic.
8. Section 3.1 – With respect to Alert, I suspect the coarse-particle chemistry is based on the difference between high-volume (essentially TSP) filters collected outside and submicron filters collected inside. The high uncertainties may be related to uncertainty in cut size of the submicron filters. Also, the high-volume filters are susceptible to blowing snow, which may (on occasion) bias concentrations a bit high.
9. Line 224 – “long-raNge”
10. Lines 228-229 – The sea around Alert is also frozen in winter.
11. Figure 2 – I suggest only showing the weekly-averaged model points to enable the scale be expanded to show the proper comparisons better.
12. Figure 6 and like figures – Can you place the labels horizontally above or below the globes?
13. Figure 3 - What is the difference between the blue crosses and the grey dots in SO4= in Figure?
14. Lines 401-403 – This may be too simple a solution. The aqueous phase is unlikely at Alert in winter, unless in fine haze particles (possibly quite acidic). Transport to Alert through liquid clouds at more southern latitudes is possible, but then some sunlight might be a factor too.
15. Line 407 - It is not so easy to see this for NH4+, since the concentrations of NH4+ are quite small. What is the uncertainty in the NH4+ measurements?
16. Line 415 and Figure 4b - It is very difficult to tell from this figure that lower concentrations are better represented by HEM_NEW.
17. Line 418 – Modelled sub-micron OA…
18. Line 429 – parenthesis after “2” not needed.
19. Line 455 – “difficulties in capturing sub-micron SSA and nss-SO4= during wintertime…”
20. Line 462 – Demonstrations of the importance of wet and dry deposition goes back further than 2007. Maybe “the importance of the formulation of wet and dry removal…”?
21. Figure 7 caption – “sub-micron aerosol mass concentrations” instead of aerosol mass concentrations for sub-micron”.
22. Line 514 – not be expected
23. Line 517 – “in clean regions of the Arctic” is a little too broad. Wasn't it near Zeppelin? Also, clean regions of the Arctic is contradicted by Arctic Haze.
24. Lines 621-622 – Maybe “Overall, the Alaska-New January simulations of sub-micron Na+ and Cl- are an improvement over the CONTROL, but still ...”
25. Line 667 – “not a significant source of SSA”
26. Lines 726-728 - This is misleading, unless you can show that submicron aerosol at other sites compares well.
27. Lines 729-730 - Not to underestimate the potential of aqueous-phase processes, I feel that the third reference to metal-catalysed aqueous-phase oxidation, without a comprehensive discussion, over-emphasizes the potential of this process.
28. Lines 766-769 – By radiative effects in the darkness of winter, I assume you are suggesting that SSA contributes to changes in longwave radiation or is somehow involved with ice crystals. A little more detail would help, including a reference or two.Citation: https://doi.org/10.5194/egusphere-2022-310-RC1 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
RC2: 'Comment on egusphere-2022-310', Anonymous Referee #2, 24 Aug 2022
The manuscript by Ioannidis et al. reports model simulations over the Arctic with the aim of improving SSA predictions. The study is a large effort trying to examine the impact of various recent parameterisations on the model output and agreement with the observations.
Despite a significant effort by the authors it falls short of advancing the understanding of processes and their impact on model output. Just for a start, the paper title emphasizes Arctic haze while the main stated purpose is to advance SSA predictions. I am not suggesting that Arctic haze is not important, but the current version if a mix of everything: mostly sea spray, but frequently interspersed by acidic components and anthropogenic sources. That does not help to deliver focused conclusions, because there are already too many issues related to sea spray alone.
However, the most significant problem is related to the implementation of the study. What was the purpose of using an outdated sea spray source function – Gong97, which is not even based on observations, but is rather a mathematical extension of an even older, although pioneering at a time, study of Monahan, combined with the slightly more contemporary observational data of O’Dowd et al. 1997? Being instrumentally limited, even O’Dowd et al. size distribution stopped at 0.1um in diameter when there are plenty of recent papers providing evidence of large numbers of sea spray particles down to 10nm (L. Cravigan et al. 2015 JGR, A. Schwier et al. 2015 ACP, J. Ovadnevaite et al. 2014 ACP, W. Xu et al., 2022 Nature Geoscience just to name a few). Surprisingly, none of the above papers are mentioned despite a clear contextual value. That is even more surprising given the choice of the state-of-the-art WRF-Chem model. If sea spray model output so outdated and diverging with observations, how can anyone trust inferences on marine organic matter, ssSO4 and processes taking place in internally mixed particles?
I wonder why the authors did not make an attempt to compare with size distribution data. That is a critical aspect, because focusing on mass balance does not advance process understanding and produces little value when it comes to studying aerosol-cloud interactions and predicting CCN. Mass balance is dominated by supermicron fraction in sea spray while the number is dominated by the submicron fraction.
The paper is very long and well organized, but suffers from lack of focus. For example, take dry deposition section. There is no context of reason given why the impact of dry deposition is explored given the fact that the model generally underestimates SSA and larger dry deposition is only making matters worse. The other example is sulphate. Although there is a clear distinction between ssSO4 and nssSO4, the model comparison only deals with total SO4 making all findings or inferences vague as those species come from entirely different sources. The authors devote a large section on neutralization factor, but use total sulphate in calculations despite the fact that only nssSO4 is making aerosol acidic. By contrast, ssSO4 is balanced by sea salt cations.
Conclusions are a compilation of mostly speculative statements. Some of them are pure speculations as to suggesting what was not included in the model and what impact it would have had if it was (anyone’s guess really), some are speculative in a sense that no quantitative support is given. If something improved the simulations, then by how much? Was better agreement marginal or significant? Same criticism applies to Abstract where there is a single number to illustrate the results.
Although the value of the paper would not dramatically improve, a reorganisation of the paper by dropping anthropogenic components and by providing better context, reasoning and the outcome of specific parameterisations would make it more readable and useful.
Other comments as they appeared
Line 2. Models will always have difficulties reproducing observations, because they are just model approximations. Model agreement does not need to be perfect if it captures key processes consistently.
Line 8. The statement that the model overestimates sea salt is contradicted by all further results where model consistently underestimates sea salt.
Line 10. Sea salt sulphate is part of sea salt, why is it included second time? Please clarify if not.
Line 21. Breaking waves (open ocean or open leads) are the main source of SSA, how can it be missing?
Line 55. How come open ocean be a new SSA source if it was always the main one? The statement is either completely wrong or should be rephrased/clarified.
Line 129. Sea spray is not just Na and Cl. Sea spray is sea salt (including sea salt sulphate) and primary organic matter. Those early SSA functions were derived from physical particle measurements, not chemical measurements. This aspect is crucial for comparing model and observations which often report just Na and Cl and rarely sea salt sulphate, other major ions and almost never OM.
How Gong et al. source function was translated into Na and Cl emissions? Was it necessary at all, because it is rather straightforward to split sea salt into major components, like Na, Cl, ssSO4, etc.
What was the rationale to improve model simulations by using three decades old source function alongside with newly discovered SSA sources from open leads and frost flowers?
Line 187. It is crucial to acknowledge and discuss sampling loses in sea salt observations, because models do not take into consideration of sampling inlets and other sampling artefacts. Sampling losses are mostly related to super-micron range, but depend on specific inlets or samplings ducts.
Therefore, given the fact, that the model is generally underestimating observations, sampling losses would make underestimation even more dramatic.
Figure 2. HEM_NEW or CONTROL simulations were not introduced up to this point.
Line 217. How could Fuentes parameterisation for sub100nm be fully utilized if Gong97 or its extension based on O'Dowd97 stopped at 100nm?
Line 224. 20% of ss-SO4 is not a small fraction.
Line 233. I am not sure that anthropogenic Na was properly estimated given Cl depletion in anthropogenic air masses, which tends to be translated into excess Na and thus anthropogenic source. The authors do not discuss Cl/Na ratio which would be informative and also considering derivation of ssSO4 as 0.25xNa.
Line 259. What was the degree of neutralization considering the fact that NH3 neutralizes the stronger sulphuric acid and only then the nitric acid?
Line 278. The authors missed to mention earlier pioneering studies of Blanchard 1976, O'Dowd et al. 2004 Nature and later Ovadnevaite et al. 2011 GRL, 2014 JGR. The authors have a justified liberty of choosing parameterization, but the acknowledgement of earlier studies is advisable.
Line 316. Wind speed is indeed an oversimplified dependency most importantly not accounting for increasing and decreasing wind speed relationships. This aspect as well SST dependence together with a new sea salt source function accounting for the sea state was introduced by Ovadnevaite et al. in 2014 ACP.
Line 331. Na, Cl, ss-SO4 and OM does not capture full sea spray as Mg, Ca, K are missing. How was the ss-SO4 fraction of 9.9% obtained, especially that 7% is arising from basic sea water composition?
Line 356. Basic inorganic chemistry mandates that NH3 is first neutralising sulphuric acid (stronger acid) and producing either ammonium bisuphate or sulphate. Only a leftover producing ammonium nitrate which is pretty stable in polar areas.
Line 360. f=1 is representing fully neutralized aerosol, not "more". More importantly, only nss-SO4 (and NO3) should be used for assessing neutralization, because ss-SO4 is balanced by other cations in sea water (salt).
Line 378. Sulphate and nitrate mass is conserved and has nothing to do with chlorite depletion reactions as model simulation do not output masses of specific salts like Na2SO4 or NaNO3 to attempt Na mass balance.
Line 480. If model underestimates SSA in general, higher dry deposition only makes matters worse. Clearly larger dry deposition is studied not for the better agreement, but simply for theoretical reasons. Better justification and context is needed in this section.
Line 558. SSA - win speed relationship is nonlinear (power of 2-3) with Gong97 on a high end of values. What is the purpose of comparing with linear dependences?
Citation: https://doi.org/10.5194/egusphere-2022-310-RC2 -
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
-
AC1: 'Comment on egusphere-2022-310', Eleftherios Ioannidis, 17 Dec 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-310/egusphere-2022-310-AC1-supplement.zip
Peer review completion
Journal article(s) based on this preprint
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 673 | 229 | 13 | 915 | 12 | 9 |
- HTML: 673
- PDF: 229
- XML: 13
- Total: 915
- BibTeX: 12
- EndNote: 9
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Cited
1 citations as recorded by crossref.
Eleftherios Ioannidis
Jean-Christophe Raut
Louis Marelle
Tatsuo Onishi
Rachel M. Kirpes
Lucia Upchurch
Andreas Massling
Henrik Skov
Patricia K. Quinn
Kerri A. Pratt
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(31007 KB) - Metadata XML