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 comment

The 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 comments

The 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 show

Section 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.

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.