the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol-climate model ECHAM6.3–HAM2.3
Abstract. Primary marine organic aerosol (PMOA) contributes significantly to the aerosol loading over remote oceanic regions, where sea spray dominates aerosol production in the lower troposphere, and plays an important role in aerosol-cloud-climate interactions. The sea-atmosphere transfer of organic components depends on their abundance at the ocean surface and their physicochemical characteristics. We introduce a novel approach for representing the ocean concentration of the most abundant organic groups in seawater that are relevant to aerosols. By apportioning the phytoplankton exuded dissolved organic carbon, modelled in the biogeochemistry model FESOM2.1-REcoM3, three biomolecule groups are computed (dissolved carboxylic acidic containing polysaccharides (PCHO), dissolved combined amino acids (DCAA), and polar lipids (PL)). The transfer of these marine groups to the atmosphere is represented by the OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) parameterization which is implemented in the aerosol-climate model ECHAM6.3–HAM2.3 to represent the emission and transport processes in the atmosphere. The concentration of biomolecules in the ocean serves as the bottom boundary condition for the PMOA simulation within the aerosol model. Among the simulated organic groups in seawater, modelled PCHO is the most prevalent, followed by DCAA and PL. Conversely, PL contributes the most to the organic matter in aerosols, given the high air-seawater affinity of lipids compared to the other groups. Biomolecules exhibit minor variations in Equatorial waters, whereas strong seasonal patterns are observed towards the polar regions. The global aerosol model simulations indicate that PMOA emission fluxes are primarily influenced by marine biological activity and surface wind conditions. Based on the most comprehensive evaluation to date, the computed levels of biomolecules in the ocean and species-resolved PMOA concentrations are compared with ground-based measurements across the globe. The comparison shows a strong agreement, given the uncertainties in model assumptions and measurements. Since PMOA is emitted together with sea salt, model biases in the representation of the marine organic aerosol groups are caused by uncertainties in the simulated sea salt concentrations. A comparison with a set of long-range in-situ aircraft measurements indicates that by including PMOA in the model, the representation of organic aerosols in the Southern Oceans is significantly improved.
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RC1: 'Comment on egusphere-2024-2917', Anonymous Referee #1, 24 Oct 2024
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Review of “Modelling emission and transport of key components of primary marine organic aerosol using the global aerosol-climate model ECHAM6.3–HAM2.3” by Leon-Marcos et al. (egusphere-2024-2917)
This work by Leon-Marcos et al. presents the implementation and evaluation in ECHAM-HAM of a parameterization of marine organics in sea water and the associated aerosol emissions. It constitutes a very important contribution for the climate community as it addresses one of the critical aspects of marine aerosol emissions, which are often not represented in models despite the major implications of marine organics for clouds and climate representation. The manuscript is well written, thoroughly addresses the topic and I recommend its publication in GMD. I provide below a few propositions to improve the manuscript.
General commentThe will of the authors to be very thorough is good, but the manuscript is very long and dense as a consequence. I recommend the authors try to trim down the manuscript by removing parts that are non-essential. As an example, the sentences line 265-266 are simply a repletion/reformulation of the previous sentence line 264-265, while that first sentence contains already all the information needed on how the module represents aerosols. There are several such examples throughout the manuscript and I trust the authors can reduce the manuscript length without losing any information by removing statements that would be obvious to GMD readers.
Minor commentsThe wording in the Abstract is sometimes too strong, e.g.
“The comparison shows a strong agreement, given the uncertainties in model assumptions and measurements.” - Seeing your results, I would not call this a strong agreement, especially in the Northern Hemisphere compared to Atom.
“model biases in the representation of the marine organic aerosol groups are caused by uncertainties in the simulated sea salt concentrations” - as mentioned below in another comment, I do not think you can attribute the model biases solely to sea salt aerosol based on what you showSection 3.3 - It is unclear why you cannot simply use the SIC and SST from FESOM-REcoM to force ECHAM-HAM. Instead you use this “SIC and SST mask”, where you sometimes use AMIP data and sometimes replace it with FESOM-RECoM, that I do not fully understand. What is the reason for not using SIC and SST from FESOM-REcoM always?
L.519-527: here is another example of text that could be taken out. This paragraph is solely a description of the values in the measurements, without reference to modelled values. Although this bit of analysis is not uninteresting, I think it is unnecessary and contributes to making the manuscript too dense.
L.584-587: According to Equation 10, the ratio of PMOA to SS should be the sum of OMFi/(1-OMFi), right? But then OMFi does not depend on the sea salt source function according to the formulas provided. Therefore I am not sure your explanation is actually valid, unless I missed something.
L.588-593: I do not follow the argument here. What is the basis for saying that when you compare a chl-a based OMF and yours the difference in the results is still more driven by the sea salt than by the fundamental differences in modeling OMF?
Figure 6: why do you mask out land on the total burden panel (b)? It would be very interesting to see how far inland PMOA can be transported in your model and evaluate if they can affect atmospheric composition and clouds over continental areas.
L.632-637: here is another unnecessary paragraph. The limitations of comparing coarse resolution models to observations are well-known and do not need to be explained in a GMD article.
Section 6.2.1: here too you could merge the first 2 paragraphs to improve readability.
L.744-746: SST is usually a 2nd-order driver of sea salt emissions, compared to the more important wind speed. I would take this discussion out, as surely the regional differences can be better explained by the ability of the model to represent winds in different regions.
L.801-802: could you illustrate this statement with references? I think it is a little bold to suggest that PMOA do not matter in the Arctic solely based on your comparison with observations. Biases in your simulation could also explain the loss of correlation, like transport and removal, or the oceanic biogeochemistry in the Arctic ocean that can be challenging to represent. Please moderate the message here or provide references that support this claim.
Figures C1-C2: the figures would be easier to read if instead of letters for panel titles you put directly the month of the data as the title of the panel.
Citation: https://doi.org/10.5194/egusphere-2024-2917-RC1 -
CEC1: 'Comment on egusphere-2024-2917: No compliance with the policy of the journal', Juan Antonio Añel, 29 Oct 2024
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Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.htmlYou have archived your code on repositories that are not acceptable for long-term archival in scientific research. For example, you have posted the FESOM2.1-REcoM3 model in GitHub. However, GitHub is not a suitable repository for scientific publication. GitHub itself instructs authors to use other long-term archival and publishing alternatives, such as Zenodo. Regarding the ECHAM6.3–HAM2.3 code, you have linked a server managed by the ETH. This is not an acceptable repository neither.
Therefore, please publish your code in one of the appropriate repositories (you can find suggestions in our policy) and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible, as we can not accept manuscripts in Discussions that do not comply with our policy. Therefore, the current situation with your manuscript is irregular.
Please, note that if you do not fix this problem, we will have to reject your manuscript for publication in our journal.
Also, you must include the modified 'Code and Data Availability' section in a potentially reviewed manuscript, with the DOI of the new repositories for the code.
Juan A. Añel
Geosci. Model Dev. Executive EditorCitation: https://doi.org/10.5194/egusphere-2024-2917-CEC1 -
AC1: 'Reply on CEC1', Anisbel Leon, 19 Nov 2024
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Dear editor Juan A. Añel,
Thank you for your feedback and for pointing out the issues with our manuscript's compliance with the "Code and Data Policy".
We would like to inform you that we have resolved the concerns. The FESOM2.1-REcoM3 and the ECHAM6.3–HAM2.3 models have been archived in an appropriate long-term repository. The relevant links are as follows:FESOM2.1-REcoM3: https://doi.org/10.5281/zenodo.14017536
ECHAM6.3–HAM2.3: https://doi.org/10.5281/zenodo.14169999
We will also update the 'Code and Data Availability' section in the manuscript to reflect these changes.
Thank you for your guidance, and we look forward to your feedback.
Best regards,
The authorsCitation: https://doi.org/10.5194/egusphere-2024-2917-AC1 -
CEC2: 'Reply on AC1', Juan Antonio Añel, 19 Nov 2024
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Dear authors,
Unfortunately, your action does not solve the problem I pointed out. Our policy (which I recommend you to read carefully) establishes that the repositories can not be restricted, and that contacting authors to get access to the code is not an option. This is not the case for the second repository you have posted. I have to highlight again that all the code that is used for a submitted manuscript must be published openly and without restrictions before submitting the manuscript, and that no manuscript can be accepted in Discussions without being fully compliant with this policy. Your manuscript is now in Discussions, despite being not compliant with our policy, which is irregular. We are conceding not to reject your manuscript to allow you to solve this situation. Despite it, it has taken to you three weeks to address my previous comment.
Therefore, I insist that you must publish the code openly, without restrictions on its access or use, and in a long-term repository we can accept, without delay. For other issues, I recommend you to read our policy carefully.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-2917-CEC2 -
AC2: 'Reply on CEC2', Anisbel Leon, 21 Nov 2024
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Dear editor Juan A. Añel,
Thank you for your feedback regarding the compliance of our manuscript with the journal's Code and Data Policy, and appreciate once again the opportunity to address this matter.
We regret that our previous actions have not fully resolved the concerns you raised. However, due to the strict licensing terms governing the ECHAM-HAM model under the HAMMOZ Software Licence Agreement, it is unfortunately beyond the authors control to make the full source code openly available. The ECHAM-HAM code is accessible only through registration with HAMMOZ, as mandated by the licence (https://redmine.hammoz.ethz.ch/projects/hammoz/wiki/1_Licencing_conditions).
We have reviewed the policy carefully again (https://www.geoscientific-model-development.net/policies/code_and_data_policy.html) and we are committed to facilitating transparency and reproducibility within the constraints of these licensing restrictions. Specifically:
Reviewer Access: We can provide the code for reviewers' use via a restricted repository hosted on https://gitlab.dkrz.de, facilitated through the editor. We believe it could balance the policy's intent and our licensing obligations.
Public Code Access on Zenodo: While the full source model code, including the marine aerosol component, is governed by the HAMMOZ Licence Agreement (https://doi.org/10.5281/zenodo.14193491), we have taken steps to ensure compliance with the journal's requirements. Specifically, we have made publicly available on Zenodo the portion of the code directly relevant to the manuscript. This includes the implementation of primary marine organic aerosol emissions as a patch file, which can be applied to other versions of the HAM module. Furthermore, we have also provided the files necessary to reproduce the model experiments, including the complete model setup (https://doi.org/10.5281/zenodo.14192909, Version 1.1_revision).
We understand the importance of fully complying with the policy and are willing to explore additional solutions within the constraints of the HAMMOZ Licence Agreement if the actions we have provided here are not sufficient. Kindly let us know if there are further steps we can take to meet the journal's standards.
We greatly appreciate your understanding, patience and the opportunity you are giving us to resolve this issue.
Best regards,
The authorsCitation: https://doi.org/10.5194/egusphere-2024-2917-AC2 -
CEC3: 'Reply on AC2', Juan Antonio Añel, 21 Nov 2024
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Dear authors,
Thanks for this reply. We understand that you have chosen to work with a model that has severe limitations regarding compliance with scientific replicability, caused by the license that the original authors of the model impose. This is unfortunate, but we understand that at this point publishing it is out of your control. With these conditions, we agree that in your case this could qualify for a exception to our policy. However, to store a copy of the code, which could serve to give access to the editors and reviewers, we can not accept a Git repository from the DRKZ, you need to deposit the full model code in a permanent repository that we can trust, in this case with the access restricted. In this way, both all the code necessary to reproduce your work is permanently stored in a trusted repository, and you keep the control on who can access to it.
If the full ECHAM6.3–HAM2.3 model was not stored in your previously shared restricted repository, please, proceed to solve this issue following these instructions. Also, reply to this comment with the corresponding explanations regarding the availability of the code used in the work presented in your manuscript.
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-2917-CEC3 -
AC3: 'Reply on CEC3', Anisbel Leon, 22 Nov 2024
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Dear editor Juan A. Añel,
Thank you for your feedback and for granting an exception to the policy under the current circumstances. We understand the importance of ensuring scientific replicability, and we appreciate your flexibility given the model licence limitations.
To address the issue of code availability, we have archived the full ECHAM6.3–HAM2.3 model code, including the marine aerosol component, in the Zenodo repository (https://doi.org/10.5281/zenodo.14193491). Access can be provided to reviewers through the editor. This repository offers permanent, trusted storage with the required restricted access.
The pertinent details will also be updated in the "Code and Data Availability" section of our manuscript as follows:
"Code and data availability. The source code of FESOM2.1-REcoM3 model is available at https://doi.org/10.5281/zenodo.14017536. The
ECHAM–HAM model is accessible to the scientific community under the HAMMOZ Software Licence Agreement, which specifies the
terms of use for the model (https://redmine.hammoz.ethz.ch/projects/hammoz/wiki/1_Licencing_conditions, last accessed: 22 November
2024). The model version used in the current study, including the implementation of primary marine organic aerosols' emission, is archived
on Zenodo (https://doi.org/10.5281/zenodo.14193491). Setting files for the simulation experiments and the code of the primary marine
aerosol implementation into the model is also documented at https://doi.org/10.5281/zenodo.14203456. The biogeochemistry model tracers
to compute the marine biomolecules groups, the ocean biomolecule concentration and results of the aerosol-climate model simulations
are accessible at https://zenodo.org/records/13235178. The seawater and aerosol measurement data sets were derived from the referenced
literature or requested directly to the authors. The in-situ aircraft observations were acquired as a data collection shared at The Oak Ridge
National Laboratory Distributed Active Archive Center (ORNL DAAC) https://doi.org/10.3334/ornldaac/1925, last accessed: 22 November 2024. The model evaluation with
observations was performed with python3 (Python Software Foundation) with available interpolation functions in the module SciPy. In
addition, to handle the model data and visualize the results, other python3 libraries such as xarray, pandas, cartopy, and matplotlib were used.
Climate Data Operators (cdo) version 2.2.4 were used for adapting the bottom boundary condition data to the ECHAM6.3–HAM2.3 grid and
for the posterior interpolation of the aerosol model results to a regular vertical and horizontal grid."We hope this solution meets your requirements, but please let us know if further adjustments or clarifications are needed.
Best regards,
The authors
Citation: https://doi.org/10.5194/egusphere-2024-2917-AC3 -
CEC4: 'Reply on AC3', Juan Antonio Añel, 22 Nov 2024
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Dear authors,
Many thanks for the reply. Provided that after checking the repository it is verified that the code is stored, we can consider the current submitted version your manuscript in compliance with our policy.
Regards,
Juan A. Añel
Geosci. Model Dev. Executive Editor
Citation: https://doi.org/10.5194/egusphere-2024-2917-CEC4 -
AC4: 'Reply on CEC4', Anisbel Leon, 25 Nov 2024
reply
Dear editor Juan A, Añel,
We are pleased to hear that our manuscript is now in compliance with the code and data availability policy.
Thank you once again for the opportunity to clarify this issue.
Regards,
The authors
Citation: https://doi.org/10.5194/egusphere-2024-2917-AC4
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AC4: 'Reply on CEC4', Anisbel Leon, 25 Nov 2024
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CEC4: 'Reply on AC3', Juan Antonio Añel, 22 Nov 2024
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AC3: 'Reply on CEC3', Anisbel Leon, 22 Nov 2024
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CEC3: 'Reply on AC2', Juan Antonio Añel, 21 Nov 2024
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AC2: 'Reply on CEC2', Anisbel Leon, 21 Nov 2024
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CEC2: 'Reply on AC1', Juan Antonio Añel, 19 Nov 2024
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AC1: 'Reply on CEC1', Anisbel Leon, 19 Nov 2024
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RC2: 'Review of the manusript by Leon-Marcos et al.', Anonymous Referee #2, 13 Dec 2024
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The modelling study by Leon-Marcos et al. addresses very important topic of primary marine organic matter in global ocean and atmosphere by incorporating the most advanced and further updated schemes into the global model. The paper is very well written and easy to follow, however, still requires some organisation to have more logical flow. The most disappointing aspect of the study, and not of the authors effort, is very poor representation of sea salt in sea spray. That does not undermine the authors efforts, but places low credibility on quantitative aspect of the results. If there is no agreement on the most basic species of submicron sea salt, how could we trust aerosol PMOA mass concentrations? Overall, the paper is a very significant contribution and representation of the state-of-the-art development of PMOA emission schemes and I, therefore, recommend publication of the study, but with a pinch of salt.
The major organisational comment relates to the sea salt comparison. It appears in various places and when suites the authors narrative, despite being the key species and the most basic parameter of the modelling effort, because PMOA is emitted by sea spray source function. BTW is it unclear what sea salt source function is used in the model in the first place. Whatever it was it should probably be avoided in the future? I suggest consolidating all sea salt comparison and information at the start of chapter 6.2 before discussing individual PMOA species.
Other comments as they appeared:
Line 81. This paragraph ideally suites to start the follow up section.
Equation 3. notation g m-3
Line 159. Line 299 refers to 2009-2019 period. Clarification or correction for consistency needed.
Line 262. What SS source function is used in the model?
Line 269. Soluble and insoluble aerosol particles are introduced without the substance what biomolecule species would be contributing to each. Or not contributing? Many studies consider lipids as insoluble material, although OCEANFILMS treat all biomolecules as dissolved organic carbon species. More detailed description is needed here considering the above. Later in the text it mentioned OC from other than marine sources, so perhaps insoluble material is entirely anthropogenic. However, it confusing to say the least.
Line 279. Since HAM is using M7 aerosol model which does not consider Aitken sea spray the study is missing out on recent observational evidence of multiple submicron sea spray modes. Aitken sea spray with OM may not contribute significantly to the fine particle mass fraction, but it can have profound effect on cloud activation. It worth mentioning here that the modelling study utilised the very state-of-the-art of PMOA in the ocean, but not state-of-the-art of sea spray generation, including temperature-flux relationship.
Line 302. Does that mean that SPMOAoff is only accounting for sea salt in sea spray?
Line 320. There has to be a consideration what impact proximity of the stations to the continents or islands would have in comparison to modelled open ocean.
Line 355. This is consistent with the results of the O'Dowd et al. 2015 in Scientific Reports study where correlation between Chl-a and OMF was degrading as the time resolution increased.
Line 361. How is continental outflow treated in the model? It can be significant, especially closer to the land masses. Do I understand correctly that the model completely neglects anthropogenic OM as PMOA comes directly from OCEANFILMS and sea spray emissions? However, filter samples may have captured continental outflow, unless sector specific sampling method has been performed. If BC was modelled, its presence would indicate the amount of continental impact which would ease comparison.
Line 594. Wind is indeed the driving factor behind sea spray emissions (mind Reynolds number as a more appropriate predictor), however, the flux parametrization is the key with the magnitude of the power law controlling sea spray mass at a more significant wind speed.
Line 605. What latitude Southern Ocean is limited to? Where roaring forties and screaming fifties belong?
Section 6.2 Section should start by evaluating sea salt in aerosol phase without simulated PMOA, because sea spray emission schemes are vital for correct prognosis of PMOA. Without such a comparison, PMOA simulation results are very academic: developed a scheme, ran the model and whatever comes out of it compares with measurements were differences somewhat speculatively explained.
Line 673. As commented earlier, comparison of sea salt should be comprehensively described at the very start, instead of in places where argument is needed.
Figure 8. This is rather depressing comparison, because there is no agreement between model and observations of a key sea salt. It does not invalidate the simulation effort of PMOA using sophisticated schemes, but rather places very low credibility of modelled PMOA.
Section 6.2.4. Why there is no scatter plot for comparing total modelled and total measured OM? Is this including anthropogenic sources. I think confusion started at line 269.
Figure 9. Are Pearson coefficients statistically significant? It would best if each bar has P-value attached. It applies to all regression plots too – no regression equation or even a line should be presented unless it is statistically significant.
Citation: https://doi.org/10.5194/egusphere-2024-2917-RC2
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