the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Apr 2024
Assessing the global contribution of marine, terrestrial bioaerosols, and desert dust to ice-nucleating particle concentrations
Abstract. Aerosol-cloud interactions, and particularly ice crystals in mixed-phase clouds (MPC), stand as a key source of uncertainty in climate change assessments. State-of-the-art laboratory-based parameterizations were introduced into a global chemistry-transport model to investigate the contribution of mineral dust, marine primary organic aerosol (MPOA), and terrestrial primary biological aerosol particles (PBAP) to ice nucleating particles (INP) in MPC. INP originating from PBAP (INPPBAP) are found to be the primary source of INP at low altitudes between -10 °C and -20 °C, particularly in the tropics, with a pronounced peak in the Northern Hemisphere (NH) during boreal summer. INPPBAP contributes about 27 % (in the NH) and 30 % (in the SH) of the INP population. Dust-derived INP (INPD) show a prominent presence at high altitudes in all seasons, dominating at temperatures below -25 °C, constituting 68 % of the INP average column burden. MPOA-derived INP (INPMPOA) dominate in the Southern Hemisphere (SH), particularly at subpolar and polar latitudes at low altitudes for temperatures below -16 °C, representing approximately 46 % of INP population in the SH. When evaluated against available global observational INP data, the model achieves its highest predictability across all temperature ranges when both INPD and INPMPOA are included. The additional introduction of INPPBAP slightly reduces model skills for temperatures lower than -16 oC; however, INPPBAP are the main contributors to warm-temperature ice nucleation events. Therefore, consideration of dust and marine and terrestrial bioaerosol as IPN precursors is required to simulate ice nucleation in climate models. In this respect, emissions, ice-nucleating activity of each particle type and its evolution during atmospheric transport require further investigations.
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RC1: 'Comment on egusphere-2024-952', Anonymous Referee #1, 06 Jun 2024
Review of “Assessing the global contribution of marine, terrestrial bioaerosols, and desert dust to ice-nucleating particle concentrations” by Chatziparaschos and co-authors in ACPD.
Summary:
In this study the authors use a global chemical-transport model driven by reanalysis meteorology to simulate the global distribution of ice nucleating particles (INPs) over a period of 6/7 years. The authors build upon the previous study of Chatziparaschos et al. (2023) who considered INPs from quartz- and K-feldspar-containing mineral dust particles. In this study the authors include two new INP types (collectively referred to as bioaerosols): primary marine organic aerosol (PMOA) associated with sea spray aerosol, and primary biological aerosol particles (PBAPs). The PBAPs considered in this study include terrestrial bacteria and fungal spores. Though INP sources of PBAPs can also include pollen, the authors choose to not represent this class due to uncertainties with its treatment, and a likelihood of low concentrations when compared to the other classes. The authors have put effort into sufficiently representing the emissions of the bioaerosols and their subsequent evolution in the atmosphere. Methods for representing the ice-nucleating ability of each INP species are based on existing parameterizations from literature. The model simulation is run from 2009 to 2016 to obtain temporally and spatially collocated INP concentrations for comparison with a global database of INP measurements. The authors compare the global (and seasonal) distributions of simulated INP from the three INP sources, highlighting locations and seasons in which each displays particular importance or sensitivity. Dust is particularly important in the northern hemisphere, especially at higher altitudes, and PMOA is important in the lower atmosphere of the southern hemisphere towards the polar region. This is consistent with other studies. The INP sourced from PBAPs shows particular importance at warmer freezing temperatures (when compared to dust) and across much of the lower latitudes where there is considerable (seasonally dependent) productivity from vegetation. Finally, the authors compare the simulated INP distributions with a global dataset of observations. The authors report that the model is most representative when dust and PMOA are considered the only sources of INP, whereas the addition of PBAPs to either dust or dust+PMOA acts to worsen the comparison. Reasons for this are discussed, including the potential for an over-estimation in the sensitivity of PBAPs to act as INPs. The authors conclude from this that although dust and PMOA produces the best representation for INPs in the climate system (as a whole), the inclusion of PBAPs is still recommended given their likely strong spatial and seasonal variability. I thoroughly enjoyed reading this and believe it will be a valuable addition for the community, but feel it needs restructuring into a more logical and meaningful sequence. I also believe a small amount of extra analysis in the simulated-vs-observed comparisons could be beneficial in drawing out the impact of PBAPs at warmer temperatures (which is where they display the most importance). I therefore recommend minor revisions before being accepted for publication. I have provided more details below.
Major comments:
I have three primary areas of concern.
#1. To trust the simulated INP concentrations the reader must believe that the model is able to capture the precursor aerosol species, which in this case includes dust, sea spray / PMOA, and PBAPs. The evaluation of dust and PMOA is referred to as having occurred, but the reader is redirected to previous studies. There is no evaluation of PBAP concentrations, and no discussion as to whether the simulated concentrations are appropriate. There may be no observations to compare to, and in this case should be stated as such. I strongly recommend that the authors include a sentence or two for dust and PMOA that provides a quantitative summary of what the evaluations show. What is the RMSE for the comparison to observations? Does it display any particular bias? Did the evaluation show the model is representative of the distribution and seasonal cycle? I also recommend the authors include an evaluation (or reasons for its omission) of the simulated PBAP concentrations/distribution.
#2. This is my primary concern. The current structure of the results section is: Figures 2 – 4 present the relative importance of each INP species; Figure 5 establishes the global distribution of INPs in the model; and Figure 6 validates the INP model. At the moment this is backwards. The logical order is:
- Here is our simulated INP model in its complete form (Figure 5; simulated INP distribution presented)
- This is how it compares to the observations (Figure 6; INP model evaluated / validated)
- Now we dig deeper into the relative importance of each species (Figures 2 – 4)
In this order the reader can then appreciate from the outset that the inclusion of PBAPs does not, in fact, tend to improve the representation of the global dataset of measured INP concentrations. This then has implications for the relative importance of PBAPs as is concluded from Figures 2 – 4. If, as suggested by the INP model evaluation, PBAP concentrations are too high or too ice-active, then this may suggest the ‘relative-importance’ analysis is biased towards INPs from PBAPs. The authors do a fantastic job at explaining the possible reasons why PBAPs do not improve the evaluation and I do not think that this means the relative-importance analysis needs to be removed. I think it is still entirely valid, but it should be highlighted that there is an associated uncertainty. The restructuring also applies to the abstract and conclusions section. I agree with the author’s conclusions but feel they should be re-ordered for clarity.
#3. In-line with comment #2 above I believe the INP model evaluation (Figure 5) would benefit from additional analysis. It is clear that PBAPs are active at warmer temperatures than dust. Therefore, if the INP model evaluation of dust+PMOA+PBAPs is made in binned temperature regimes does this show better performance (when compared to dust+PMOA only) in the warmer temperature regimes? If so, this would strengthen the hypothesis that PBAPs are indeed important at warm temperatures. Also, the INP measurement database doesn’t show particularly great global coverage. Given that the strongest signal from PBAPs is likely in low latitudes / boreal regions during the summer months, could the authors subset the comparison to these particular regions and seasons? This would provide a good basis for testing the importance of PBAPs.
Minor comments:
Throughout: degree symbols are sometimes not superscript.
L30. As discussed in comment #2 the INP model evaluation should precede the more detailed analysis. Also, given the uncertainties I recommend changing “INP originating from PBAP…” to “The model suggests INP originating from PBAP…”
L50. MPC not yet defined in the manuscript.
L54. “As a result, they significantly impact precipitation rates and radiative energy balance on both regional and global scales” Please include references to support this statement.
L56. Collection/collisional processes are also an ice-liquid interaction in MPCs. Can you expand to include other processes?
L71. “..via the WBF process and multiply via SIP… affecting precipitation ranges, cloud properties, and albedo”. Please include references to support his statement.
L80. Could you expand to describe the ‘seeder-feeder’ mechanism?
L85. “In the absence of a well-established theory for heterogeneous ice nucleation…”. What about classical nucleation theory?
L127. “…with INP concentrations estimated at approximately 1 to 2 per litre”. Would be useful to have some context - how does this compare to dust?
L134. SIP yet to be defined.
L137. “..warm parts of the mid-latitude clouds..”. I do not understand what this is referring to. Please can you rewrite for clarity?
L137. “..with about 1x10^-5 % of the global average ice nucleation rates..” this is also a confusing statement. Please can you rewrite for clarity?
L139. “..altitudes between 400 and 600 hPa..”. Please use consistent quantities/units.
L181. “bioaerosols”. This term hasn’t been defined yet.
L191. The model is very coarse, both horizontally and vertically. Do the authors think this will have implications for the emission and dispersion of aerosols and modelled INP concentrations?
L205. Please expand this sentence to briefly say what drives the dust emission sensitivity – i.e., wind speeds, surface moisture, etc
L215. As per comment #1 please expand and provide a short quantitative summary of the evaluation.
L245. “FNG are assumed to be … 3um diameter with 1000 kgm-3 density”. Is this appropriate? Do the authors have a sense of the uncertainty of this and its variability across the globe?
Did the authors evaluate the simulated bacteria + fungal spore concentrations against observations? Is this a key observational dataset we are missing?
L278. As per comment #1 please expand and provide a short quantitative summary of the evaluation.
L298. Please include some statistics that summarise the evaluation. This evaluation is actually shown in Figure 6a so could be referenced.
L370. Missing minus sign.
L372. Specific to this line but more general. How relevant are the tropical and subtropical atmospheres for MPCs? Are they commonly observed here or more prevalent in the higher latitudes?
L404. I suggest adding a value that signifies a threshold for “high pressure levels”.
L497. “Even if dust is the most abundant… cannot predict the observed INP, especially at high temperatures”. Is this consistent with other studies?
L502/3. “…largely in agreement with literature and have been thoroughly discussed in ..”. This shouldn’t be redirected to a different study. Please summarise the discussion from Chatziparaschos et al. 2023.
L505. “… increasing the predictability of the model to 70%..”. Recommend including “increasing the predictability of the model FROM XX% FOR DUST to 70%...”
L506. I think this is where the additional analysis suggested in comment #3 would fit – and enhance the rigor of the evaluation.
L511/2. “The model tends to slightly overpredict INP only in the temperature range around -25C”. Could the parameterisation exhibit an incorrect temperature-dependence?
L532. Have you tried looking at only-fungal-spore INPs vs only-bacteria INPs? Would this help identify which sub-species of bioaerosol is driving the discrepancy?
L600 onwards. In this paragraph the authors list a number of potential sources of uncertainty and reasons for model bias. What is required in order to constrain or address these? More laboratory measurements? More in-situ observations? More locations? Additional techniques to establish particle composition at sampling site? It would be good to identify what is currently lacking and is needed in future studies/campaigns.
Missing data availability statement.
Figure 1. Reference to different methods of calculating INP concentration depending on convective state. This is not discussed in the manuscript, and therefore is quite confusing. Please include an explanation of this in the text. Also consider removing this figure as it does not add much to the manuscript and is only briefly referred to.
Figure 2. Viewing this figure feels like an eye test. Please increase the font size of all elements. Also, this would greatly benefit from distinct colormaps for the two rows. One for concentrations, the other for percentage contributions. The same comments apply to Figures S2 and S3 in the supporting information.
References:
Chatziparaschos, M., Daskalakis, N., Myriokefalitakis, S., Kalivitis, N., Nenes, A., Gonçalves 685 Ageitos, M., Costa Surós, M., Pérez Garc\’\ia-Pando, C., Zanoli, M., Vrekoussis, M., and Kanakidou, M.: Role of K-feldspar and quartz in global ice nucleation by mineral dust in mixed-phase clouds, Atmos. Chem. Phys., 23, 1785–1801, https://doi.org/10.5194/acp-23-1785-2023, 2023
Citation: https://doi.org/10.5194/egusphere-2024-952-RC1 -
AC2: 'Reply on RC1', Maria Kanakidou, 05 Nov 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-952/egusphere-2024-952-AC2-supplement.pdf
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RC2: 'Review of "Assessing the global contribution of marine, terrestrial bioaerosols, and desert dust to ice-nucleating particle concentrations" by Chatziparaschos et al.', Anonymous Referee #2, 09 Jul 2024
Summary:
This study by Chatziparaschos et al. examines the spatial and vertical distribution of ice nucleating particles (INPs) from three different sources: dust (D), marine organics (MPOA), and terrestrial bioaerosols (PBAP) through simulations using the TM4-ECPL global chemistry-transport model. They find dust are the dominant INPs at high altitudes/cold temperatures north of ~ 40°S, and across all seasons. PBAP are the most important INP species at warm temperatures (>-16 °C), especially in the Northern Hemisphere summer. Marine organic INPs are found to have minor contributions in the Northern Hemisphere, but to dominate in the Southern Hemisphere across all seasons. Overall, these results are in agreement with prior observational and modeling studies. The best agreement between simulated and observed INP concentrations across the entire temperature range (-5 to -35 °C) are found when both dust and MPOA INPs are included, but not PBAP. All simulations including PBAP INPs have a high bias relative to observations, which may point to an overactive parameterization for this species, which should be explored in future studies.
I found the article easy to read, and the figures are well-labeled and clear. However, the discussion needs to be re-structured into a more logical flow so the conclusions build on each other. This will help reduce some of the repetition of results between paragraphs and different sections. Overall, this work provides a valuable addition to the INP community, but some additional analyses in the comparison between simulated and observed INPs would be valuable and improve the manuscript greatly, so I am recommending minor revisions. Details are provided below:
Major Comments:
- The structure of the discussion is confusing, and lead to a lot of repetition of results, as well as mentioning results before the corresponding figure was presented. Additionally, the evaluation of the model against observations should come earlier in the discussion, since it impacts how the reader interprets the rest of the simulated results. A suggested order is listed below:
- Figure 1 (schematic representation of ice nucleation). This can also be removed, as it does not add much to the discussion and is only briefly mentioned. The two types of INP concentration metric indicated in the schematic are not well explained (see major comment #2).
- Presentation of the global model results (Figure 5)
- Comparison of the model against observations (Figure 6)
- Additional figures looking at specific aspects of the model (Fig. 2-4)
- Figure 1 presents two different ways in which INP concentrations can be calculated/presented: the concentration which reaches a specific model level/altitude and are active at the model temperature, and the concentration at a specific model level which are active at a different temperature of interest. Since these numbers can be quite different, it would be helpful to the reader to have a description of what these values are and how they differ in the main text instead of just a very brief sentence in the caption for Figure 1. And then the INP metric plotted in each figure needs to be clarified in the main text and/or figure caption. I suspect the difference between these two metrics is driving the very different patterns seen between Fig. 3 and Fig. 4, for example, but this is not clear from either the text or figures.
- The model simulation of the aerosol types underlying the INP simulation, in this case, dust, sea spray, and PBAPs, are either only briefly mentioned as having previously occurred (dust, marine organics) or not covered at all (PBAPs). While reproducing these prior validation studies is unnecessary and impractical, I suggest adding a few sentences where the major conclusions, any biases, etc. of the previous evaluation studies (if any) are discussed. This would allow the reader to understand whether any of these biases may impact the INP results presented here.
- The model validation against observations (Figure 6) could be improved in a few ways. First, based on Figure S1, the datasets used for evaluation are strongly biased towards the Northern Hemisphere, and the Arctic in particular. There is only one oceanic dataset included, and it occurs in a region where Saharan dust and possibly PBAP emissions are expected to dominate over marine INPs, so there are none or very few observations where MPOA INPs would be expected to be the dominant contribution. Oceanic INP measurements have been compiled in Welti et al. (2020), and many of them are from within the 2009-2016 period simulated here. Adding some of these to the evaluation would improve confidence in the simulated MPOA INP concentrations, in particular. More recent measurements of both PBAP and marine INPs exist as well, but would be more difficult to directly compare to the simulations due to the temporal offset In addition, while the contribution of different model INP species are separated out and assessed, there appears to be no attempt to classify or separate the observations into either measured or expected dominant INP type. Why would you expect a PBAP-only parameterization to correctly simulate dust INP concentrations, for example? The fact that it is still overestimating concentrations when only PBAP are included (Fig. 6c) strongly suggests either the underlying PBAP aerosol emissions are too large and/or the INP parameterization is too active. Not all observations make measurements of INP species/type, but comparing the single-INP type simulations (Fig. 6a-c) to only observations where the INP type is known or can be reasonably estimated would improve confidence in the accuracy of the simulations. This then has direct bearing on the percent contributions of each type calculated and shown in Fig. 2-4 and S2.
Minor Comments:
- Throughout the text, degree symbols are not always superscripted, and the 1 and 1.5 in Pt1 and Pt1.5 are not always subscripted.
- Throughout text: what is meant by INP “precursor”. Based on context, it seems like INP “species” or “type” would be more appropriate and consistent with the language used by the community.
- Line 26: replace ice “crystals” with ice “processes”.
- Line 41: replace “dust and marine and” with “dust, marine, and”
- Line 42-44: the last sentence of the abstract does not fit with rest of the paragraph. I suggest just removing it.
- Line 49: define mixed-phase clouds as MPC here, otherwise you do not define the acronym before you use it.
- Line 50-51: The sentence “A significant feature…” is confusing. What do you mean by this/why is it important?
- Line 60: remove “saturation” from “saturation water vapor pressure”. You appear to be discussing factors that alter ambient vapor pressure and not the saturation value, which is an intrinsic value characteristic of a set of environmental conditions.
- Line 61: add “area” after “ice crystal surface”
- Line 69-71: Please include references to support that SIP influences “precipitation ranges, cloud properties, and albedo.” What are precipitation ranges?
- Line 117: “INP contributor” should be “INP contribution”
- Line 117: “Nevertheless, there are other minerals” should be changed to something like “There are also other minerals”
- Line 131-132: “Recent advances in remote sensing and model/sensor fusion have enabled the presence of secondary ice in clouds, revealing that this process holds…” should be changed to “Recent advances in remote sensing and model/sensor fusion have enabled detection of secondary ice processes in clouds, revealing that they hold…”
- Line 137: “,with about” should be “, accounting for”
- Line 149: typo in “sea spay”, should be “sea spray”
- Line 152: Burrows et al. (2013) and DeMott et al. (2016), in addition to Wilson et al. (2015) are more appropriate references instead of Mitts et al. (2021), as they are some of the first studies to suggest this idea.
- Line 153: MPOA and SS should be reversed in this sentence.
- Line 167-170: This entire sentence is almost word for word copied from Wilson et al. (2015). Either indicate it is a direct quotation, or rephrase in your own words.
- Line 179-180: This sentence is a bit misleading. The simulations are based on others’ work identifying major INP types, which you (reasonably) take advantage of. Please rephrase to more accurately describe your contribution.
- Lines 239-241: How representative are “diverse locations across Europe” for PBAP emissions globally? Especially since Fig. 5 indicates the PBAP INP simulations peak in Africa and South America? Can you comment on how representative the Global Land Cover database from 2000 is for simulations that occur 1-2 decades later?
- Line 269: Are MPOA and SS internally or externally mixed in the model? This will impact what diameters are simulated.
- Line 288: What is meant by “the spectrum of ice nucleation properties”?
- Line 317-318: The sentence “Additionally, observations…” does not fit well in this paragraph.
- Line 330: In equation 3, is CMPOA meant to be CTOC?
- Line 340: Simulated INP concentrations were compared to measurements at the same temperature and date. Were the lat/lon and altitude of the measurements also matched?
- Paragraph beginning with line 347: This paragraph jumps around and is hard to follow. The altitudes, temperatures, latitudes, and INP type discussed vary from sentence to sentence. It would be helpful to discuss Figure 2 for all INP types, then move on to figure S2 and the seasonality of the simulations, instead of sprinkling that into some of the paragraphs and then repeating much of that information later in the discussion. Focus this first paragraph on dust and move the couple of sentences about PBAP and MPOA to the next 2 paragraphs.
- Line 358: “amount of minerals” should be changed to something like “type and fraction of different minerals”
- Line 361-362: The statement that “PBAP are the primary source of INP between −12°C and −20°C.” should come after the evaluation of model results demonstrating the overestimation of PBAP by the model. See major comment #1.
- Line 372-373: The sentence “INPPBAP mainly affect…” simply repeats what was already said and is unnecessary.
- Line 374: “(Fig. 2S)” is actually Fig. S2.
- Paragraph beginning with line 369 needs some work, which will be helped by restructuring the discussion in line with major comment #1. The sentence beginning with “In boreal summer…” belongs with a discussion of Fig. S2 and not Fig. 2, and the one beginning “Our results suggest that PBAP…” with the discussion of Fig. 5. The last two sentences of this paragraph jump around between INP types and repeat things that were said in the preceding paragraph.
- Line 383: Clarify that the “concentration range shown in Wilson et al. (2015)…” are, in fact, simulated concentrations and not actual observations.
- Line 387: Chubb et al. (2013) presented measurements of SLW and not INPs. Either clarify this, or cite something specific to INPs, such as McCluskey, Hill, et al. (2018) or Welti et al. (2020).
- Line 391: What models or types or models (ie global, cloud resolving) are you referring to? There have been significant improvements in many models between CMIP5 and CMIP6, also.
- Line 395: See Gettelman et al. (2020) and Bodas-Salcedo et al. (2019) for improvements in radiation budgets following an increase in SLW in two different models, in contrast to Huang et al. (2018).
- Line 395-397: See also McCluskey et al. (2023), which shows significant differences in CAM6 between two dust parameterizations, one of which was used in Huang et al. (2018) and overpredicts dust INP in the Southern Ocean, at least. I am not familiar with the validation of the ECHAM6-HAM2 model used in Huang et al. (2018), but simulated dust concentrations will also strongly impact these results because of the large discrepancy in freezing efficiency between marine and dust aerosol.
- Line 402: “figure 2c” should be capitalized. Also, it is not obvious in Fig. 2c that MPOA are enhanced at the surface, especially not in the Arctic. Please specify exactly what is plotted in Fig. 2- are the concentrations showing only INP active at the model temperature level, such that MPOA do not appear enhanced at the surface because they are not active at very warm temperatures? Please also check the colorbar scale for Fig. 2d-f. Based on Fig. S2, I would expect the MPOA % contribution to be higher in Fig. 2f, since it dominates from 60-90 °S and up to ~500 hPa during all seasons.
- Line 404: Replace “high pressure levels” with “warmer temperatures” for clarity.
- Line 407-410: Note Fig. S3 in addition to S2, otherwise it is not referenced anywhere in the main text. The statement about PBAP concentrations refers to S3, for example, but is not listed. This location may change if the discussion is re-structured.
- Line 411-412: PBAP INPs appear to dominate at low altitudes in the Northern Hemisphere year-round, based on S2, and likewise for MPOA INPs in the Southern Hemisphere. The seasonality is not clear in Fig. S2, except for >60 °N. Also, what is meant by “showing alternating patterns influenced by vegetation and ocean biota”?
- Line 415-417: It is a little difficult to directly compare Fig. S2 and S3 to observational data which was all made at the surface. The concentration of marine INPs active at any given temperature would be expected to be higher near the surface, since that's the source. But since I think you have plotted the number contributing at a seasonally averaged isotherm, your percentages will be very sensitive to the exact parameterization used to determine the temperature dependence. Please clarify if what is being plotted is the INP concentration at the model temperature and altitude. If not, have you explored why the MPOA and PBAP do not appear to peak at the surface? You should also clarify that the region you are discussing here is the Arctic (ie >60 °N), and the altitude/temperature range you are referring to. Could the fact that PBAP appear to contribute more than MPOA in summer be related to the apparent overestimation of INP PBAP by the model (Fig. 6)?
- Line 431-432: Capitalize F in figure 3, replace “INP total number concentration column” with “total INP column (number) concentration”. Can you also clarify what INP metric is plotted in Fig. 3? Is it the concentration of INPs active at each temperature which reach the range of temperatures listed (ie the -40 to -30°C values are at higher altitudes and the -10 to -20°C values are from near the surface) or the "potential" total concentration active at each temperature, regardless of whether they reach the altitude corresponding to the listed temperature range?
- Line 434: Is the annual mean % contribution listed also from 2015? How much annual variability is simulated by the model?
- Line 444: “INP sources” is more correctly “INP types” or “INP species”
- Line 444-445: Please clarify what is meant by “correlation between the percentage contribution of each INP type and the concentration ranges of INP.” What is a concentration range? The % contribution is calculated from the concentration of one species divided by the total, so must mathematically be correlated with the species concentration.
- Line 457-458: Is 27% the annual average of INPPBAP, if so, for which year? The fall INPPBAP contribution is 45%, but it is lower in the summer, ~30%. Provide an average if you wish to talk about both together.
- Line 466 and 472: Do you mean the spatial “distributions of INPs”? Either clarify or just replace with concentration.
- Line 467: Why was 600 hPa chosen as an example pressure level? Most of the observations you compare to later (Table S1) appear to be from ground sites, so surface concentrations at any temperature of interest would seem more appropriate. Also, Fig, 4a appears to show INP concentrations below detection limit between ~30 °S and 30 °N at 600hPa. How do you have almost global coverage in Fig. 3 and 5? It is not clear in most of the figures which metric of INP concentration you are plotting, and it is difficult to decipher why there are large differences between the maps.
- Line 468-469: What is meant by “allow all species to activate and act as INP”?
- Paragraph beginning with line 474: You don’t really explain what is meant by INPD-20 or INPPBAP-20, etc, consider replacing with, eg, “INPD at -20 °C”.
- Lines 475-476: The phrasing “transport patterns from sources that favour 475 dust present in the NH.” is confusing. The wording used in the conclusion is clearer.
- Line 482: How is the upper troposphere a “marine environment”? In addition to the possible influence of PBAP in marine environments, dust INPs contribute significantly in many areas. This is particularly clear over the central Atlantic, downwind of the Sahara, where dust INP concentrations are larger than both MPOA and PBAP. And dust also contributes significantly over the N Pacific down wind of continental outflow.
- Line 484: It would be appropriate to add somewhere a discussion of the observations, and the mix of INP types observed or expected to be observed in those locations. There are no observations included, for example, where MPOA are expected to be the dominant INP type, since the only cruise included is immediately down wind of Africa, where significant dust and PBAP emissions are expected. See Major Comment #4.
- Line 488-489: What altitude/pressure were the simulated concentrations in Fig. 6? If the 600 hPa from Fig. 5, why, when the majority of observations are surface measurements? Did the lat/lon and altitude of the simulated values match each observation?
- Line 495: Simulating dust INPs alone appears to compare quite well against the observations below ~-25 °C.
- Line 501: “PBAP onto mineral” should be “PBAP on mineral”
- Line 507: Isn’t is more likely the discrepancy between the MPOA-only simulation and the observations is due to the observations containing (mostly) measurements that are not MPOA? It would be informative to separate these single-INP type comparisons (Fig. 6a-c) and compare to similar observations. See Major Comment #4.
- Line 509: Wilson et al. (2015) did not use Chl-a to parameterize MPOA. SML INP concentrations were scaled by measured TOC, and this scaling factor was applied to modeled organic matter in sea spray.
- Line 509-512: The overestimation of Wilson et al. (2015) seen in McCluskey, Ovadnevaite, et (2018) was specific to observations of marine aerosol. Why would you expect a MPOA-only parameterization to overpredict total INP, when dust is much more IN-active? Are the observations around -25 °C expected to be MPOA INPs?
- Line 515: I think you mean the McCluskey, Ovadnevaite, et (2018) parameterization here, not Wilson et al. (2015).
- Line 517-520: This sentence requires more explanation or clarification. Why does sea spray surface area require detailed organic composition information? What do you mean by "SS size variability that occurred due to marine biological processes"? SS will change size once in the atmosphere, but the only direct link to marine biology after emission would be through condensation of emitted gases. What "process is not parameterized in McCluskey et al. (2018)" that is needed? Since you do not implement or otherwise discuss the McCluskey, Ovadnevaite, et (2018) parameterization, this sentence can probably be removed.
- Line 523-527: See Raman et al. (2023) for a more nuanced discussion of why equating SML and SS INPs may be a poor assumption. Organic enrichment factors between the SML and SS are hugely variable based on the specific organic composition, in addition to the aerosol production mechanism. The evaluation of TM4-ECPL OC in Myriokefalitakis et al. (2010) indicated a general underestimation of POC, and virtually no seasonality in the model. Even if the Wilson et al. (2015) relationship (which included only Arctic measurements) between SML TOC and atmospheric INPs is globally applicable to SS, you have not evaluated any other parameterization(s), and so have not provided any direct evidence your model is "more realistic". And indeed, the studies which have evaluated both the Wilson (2015) and McCluskey, Ovadnevaite, et (2018) parameterizations generally find the latter works better. An overactive Wilson (2015) parameterization may be counteracting the underestimation of OC by the model. The more complicated approach may be theoretically more realistic, but only if all the component parameterizations are very accurate. Can you comment on this at the fairly coarse model resolution used here?
- Line 533: Could this discrepancy also be attributed to comparing with observations that are not dominated by PBAP INPs?
- Line 536: Replace “ice efficiency” with “ice nucleating efficiency”
- Line 537-539: A similar limitation is true of the Wilson (2015) parameterization, which uses data from a small number of Arctic SML samples and then generates a global parameterization using simulated (not observed) atmospheric INP concentrations. Some caveats or discussion is warranted in the preceding paragraph or in the methods, as was given here for the Tobo et al. (2013) parameterization for PBAP.
- Line 544: “highest correlation is found” should be replaced by “highest correlation between simulated and observed INP concentrations is found”.
- Line 549: Add “of” between “correlation coefficient” and “0.88”. Remove the reference to Fig. 6c, the correct Fig. 6d is referenced earlier in the sentence. Add “in addition to dust” in between “MPOA” and “improves”.
- Line 550-552: The sentence beginning with “Model results are more consistent…” simply repeats what was just said and is unnecessary.
- Line 554: “contributor” should be plural, “contributors”
- Line 573: Can you expand on what you mean by “model performance”?
- Line 580: add “, but not INPPBAP” after “are included”.
- Line 591-594: Did you show a relationship between PBAP and “regional weather patterns” somewhere? Or one between MPOA and “regions of high sea spray and phytoplankton activity”?
- Line 599: remove “at” between “mainly” and “low altitudes”.
- Line 600-601: This paragraph would flow better if you remove the first sentence beginning with “Therefore, we propose…” and combine the rest of the paragraph with the very short one in lines 595-599.
- Line 602: replace “could” with “can likely”, since you do not show any evidence for this, it is your speculation.
- Line 611: Does “sulfate acids” mean “sulfuric acid”?
Figure Notes:
- Are all the data in the figures (except for Fig. 6) from 2015? What is the annual variability between the concentrations and percentages shown, if so?
- Consider removing Fig. 1, since you barely mention it in the discussion. And/or, add some explanation to the main text to describe the different INP concentration metrics shown in the upper right.
- Please clarify which INP concentration metric you are plotting in every figure. See Major Comment #2.
- I’m not sure Fig. 4 adds much to the discussion. Could you instead do the seasonal pie charts currently in Fig. 4 for Fig. 3? Between Fig. 2 and 3, the main conclusions from Fig. 4 have already been discussed.
- Separating the pie charts in Fig. 3 and 4 into only NH and SH are a bit oversimplified if you want to discuss dominant INP sources/types. As you mentioned, the main sources of PBAP are equatorial. The Southern Ocean and Arctic are very small sources of INPs overall, but also have very different clouds (height, temperatures, SLW) than in the tropics and mid-latitudes. Perhaps having 3 categories, one from 60 °S to 60 °N, plus the Arctic (>60 °N) and Southern Ocean/Antarctic (<60 °S) would make the most sense in terms of INP sources and also cloud regimes.
- Caption for Fig. 6:
- Line 1075: add “simulated” between “accounting for” and “mineral dust”
- Line 1076-1078: the dashed lines are hard to see, perhaps replace with “shaded region” in the text, since you also shade the Pt1 and Pt1.5 regions.
- Pt1.5 appears to be missing from the legends
- Line 1079: the error bars are the uncertainty on the observed values and not the simulated ones? What kind of uncertainty measurement is plotted (standard error, 90% confidence interval, etc)?
- Line 1080: The 1 and 1.5 in Pt1 and Pt1.5 should be subscripted.
- Line 1081: Do the Pt1 and Pt1.5 values consider the error bar on the simulated value, or just the monthly mean when considering whether they agree with the observations?
7. Figure S1 caption: Did you mean to reference Fig. 6 instead of Fig. 4?
8. The colorbar scale on Fig. S3 may be a little too large. It's difficult to tell that dust is significantly more prevalent than PBAP.
References:
Bodas-Salcedo, A., Mulcahy, J. P., Andrews, T., Williams, K. D., Ringer, M. A., Field, P. R., & Elsaesser, G. S. (2019). Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3. Journal of Advances in Modeling Earth Systems, 11(6), 1735–1758. https://doi.org/10.1029/2019MS001688
Burrows, S. M., Hoose, C., Pöschl, U., & Lawrence, M. G. (2013). Ice nuclei in marine air: biogenic particles or dust? Atmospheric Chemistry and Physics, 13(1), 245–267. https://doi.org/10.5194/acp-13-245-2013
Chubb, T. H., Jensen, J. B., Siems, S. T., & Manton, M. J. (2013). In situ observations of supercooled liquid clouds over the Southern Ocean during the HIAPER Pole-to-Pole Observation campaigns. Geophysical Research Letters, 40(19), 5280–5285. https://doi.org/10.1002/grl.50986
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Gettelman, A., Bardeen, C. G., McCluskey, C. S., Järvinen, E., Stith, J., Bretherton, C., et al. (2020). Simulating Observations of Southern Ocean Clouds and Implications for Climate. Journal of Geophysical Research: Atmospheres, 125(21), e2020JD032619. https://doi.org/10.1029/2020JD032619
Huang, W. T. K., Ickes, L., Tegen, I., Rinaldi, M., Ceburnis, D., & Lohmann, U. (2018). Global relevance of marine organic aerosol as ice nucleating particles. Atmospheric Chemistry and Physics, 18(15), 11423–11445. https://doi.org/10.5194/acp-18-11423-2018
McCluskey, C. S., Ovadnevaite, J., Rinaldi, M., Atkinson, J., Belosi, F., Ceburnis, D., et al. (2018). Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses. Journal of Geophysical Research: Atmospheres, 123(11), 6196–6212. https://doi.org/10.1029/2017JD028033
McCluskey, C. S., Hill, T. C. J., Humphries, R. S., Rauker, A. M., Moreau, S., Strutton, P. G., et al. (2018). Observations of Ice Nucleating Particles Over Southern Ocean Waters. Geophysical Research Letters, 45(21), 11,989-11,997. https://doi.org/10.1029/2018GL079981
McCluskey, C. S., Gettelman, A., Bardeen, C. G., DeMott, P. J., Moore, K. A., Kreidenweis, S. M., et al. (2023). Simulating Southern Ocean Aerosol and Ice Nucleating Particles in the Community Earth System Model Version 2. Journal of Geophysical Research: Atmospheres, n/a(n/a), e2022JD036955. https://doi.org/10.1029/2022JD036955
Mitts, B. A., Wang, X., Lucero, D. D., Beall, C. M., Deane, G. B., DeMott, P. J., & Prather, K. A. (2021). Importance of Supermicron Ice Nucleating Particles in Nascent Sea Spray. Geophysical Research Letters, 48(3), e2020GL089633. https://doi.org/10.1029/2020GL089633
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Tobo, Y., Prenni, A. J., DeMott, P. J., Huffman, J. A., McCluskey, C. S., Tian, G., et al. (2013). Biological aerosol particles as a key determinant of ice nuclei populations in a forest ecosystem. Journal of Geophysical Research: Atmospheres, 118(17), 10,100-10,110. https://doi.org/10.1002/jgrd.50801
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Wilson, T. W., Ladino, L. A., Alpert, P. A., Breckels, M. N., Brooks, I. M., Browse, J., et al. (2015). A marine biogenic source of atmospheric ice-nucleating particles. Nature, 525(7568), 234–238. https://doi.org/10.1038/nature14986
Citation: https://doi.org/10.5194/egusphere-2024-952-RC2 -
AC1: 'Reply on RC2', Maria Kanakidou, 05 Nov 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-952/egusphere-2024-952-AC1-supplement.pdf
- The structure of the discussion is confusing, and lead to a lot of repetition of results, as well as mentioning results before the corresponding figure was presented. Additionally, the evaluation of the model against observations should come earlier in the discussion, since it impacts how the reader interprets the rest of the simulated results. A suggested order is listed below:
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