the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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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Status: open (until 05 Jul 2024)
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RC1: 'Comment on egusphere-2024-952', Anonymous Referee #1, 06 Jun 2024
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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
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