the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Lidar estimates of birch pollen number, mass and related CCN concentrations
Abstract. Accurate representation of microphysical properties of atmospheric aerosol particles – such as number, mass and cloud condensation nuclei (CCN) concentration – is key to constraining climate forcing estimations and improving weather and air quality forecasts. Lidars capable of vertically resolving aerosol optical properties have been increasingly utilized to study aerosol-cloud interactions, allowing for estimations of cloud-relevant microphysical properties. Recently, lidars have been employed to identify and monitor pollen particles in the atmosphere, an understudied aerosol particle with health and possibly climate implications. Lidar remote sensing of pollen is an emerging research field, and in this study, we present for the first time retrievals of particle number, mass, CCN, giant CCN (GCCN) and ultra–giant CCN (UGCCN) concentration estimations of birch pollen derived from polarization lidar observations and specifically from a Vaisala CL61 ceilometer.
A pivotal role in these estimations is played by the conversion factors necessary to convert the optical measurements into microphysical properties. This set of conversion parameters for birch pollen is derived from in situ observations of major birch pollen events in Vehmasmäki station in Eastern Finland in 2021. Then, the conversion factors are applied to ground-based lidar observations and compared against in situ measurements of aerosol and pollen particles. In turn, this demonstrates the potential of ground-based lidars such as a ceilometer network with polarization capacity to document large-scale birch pollen outbursts in detail and thus to provide valuable information for climate, cloud, and air quality modeling efforts, elucidating the role of pollen within the atmospheric system.
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RC1: 'Comment on egusphere-2024-3032', Anonymous Referee #1, 16 Oct 2024
This paper presents, for the first time, estimations of particle number, mass, CCN, giant CCN (GCCN), and ultra-giant CCN (UGCCN) concentrations derived from polarization lidar observations of birch pollen, going beyond the traditional distribution and classification of aerosol types in the atmosphere. Although there are still many aspects that need to be improved when compared to in-situ measurements at ground level, this study is deemed necessary from the perspective of extending lidar technology and making new attempts.
Therefore, it is judged appropriate for this paper to be published in the respective journal.
However, there is one important question. When discussing the particle size distribution and concentration, as shown in Figure 3, you compare the particle size of birch pollen using results obtained from the Burkard sampler and ICEMET. At this point, it is necessary to confirm whether the particle sizes reported by each instrument refer to aerodynamic particle size or geometric particle size. It seems that the particle size from the Burkard sampler is reported as the geometric particle size, but I am unsure about the particle size reported by ICEMET. If it is the aerodynamic particle size, it may require adjustments to compare the particle sizes derived from the two instruments.
Additionally, although it was mentioned that wind direction and wind speed were measured using a Doppler lidar, no results related to these measurements are presented in the paper. There is only a reference stating that it was used to identify the mixed layer and that data below 200 m were not used in the analysis. When comparing lidar measurements with in-situ measurements, as in Figure 7, it seems necessary to check whether meteorological conditions, especially wind speed or diffusion coefficients at different altitudes, had any effect. In this context, Doppler lidar data could be utilized.
Other revisions or questions are as follows:
-
The CL 61 instrument is said to have a full overlap at 300 m, but in the study, data measured at 200–250 m are analyzed. Please provide an explanation for this.
-
The lowest observation altitude for the Doppler lidar is indicated, but the highest observation altitude is not. Please also indicate the highest observation altitude.
Citation: https://doi.org/10.5194/egusphere-2024-3032-RC1 - AC2: 'Reply on RC1', Maria Filioglou, 09 Dec 2024
-
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RC2: 'Comment on egusphere-2024-3032', Anonymous Referee #2, 01 Nov 2024
The authors present a study to retrieve extinction-to-microphysics conversion parameters of pollen aerosol. These conversion parameters can be applied to profiles of pollen aerosol-optical properties derived by polarization lidar observations in order to estimate profiles of cloud-relevant properties, in this case pollen cloud condensation nuclei concentrations. The presented method is analogous to the well-established POLIPHON (Polarization Lidar Photometer Networking) method, however it is using ceilometer with polarization capability and ground-based in situ observations instead of long-term AERONET sun photometer observations to link particle extinction with particle size distributions. This link is then exploited to retrieve abovementioned conversion parameters.
Such novel (in terms of aerosol type) conversion parameters are always sought-after for the application to lidar profiles all over the world, either from ground-based long-term observations or networks, or from space-borne lidars, which allows to retrieve climatologies of microphysical and cloud-relevant properties. Furthermore, very special observations periods at specific sites equipped with appropriate instrumentation are needed to perform such correlation studies.
Therefore, the manuscript is suited for publication in Atmospheric Chemistry and Physics and can be published almost as is after addressing rather minor comments/questions listed below.
Major comment:
My main question following hereafter is with regard to wavelengths and wavelength conversion. 355 and 532 nm are much more common lidar wavelengths (of ground-based but also space-borne systems, which you mention in your conclusion), especially concerning polarization capability. I believe it would be worth adding some statements to the manuscript regarding this topic.
There is a PollyXT is at this site (Line 75)? Does it have near-range Raman capability? Its data are obviously not used in this study. Is there a specific reason for that? I see that there would be potentially two problems: first, the pollen being present at very low ranges below the overlap region of that larger lidar; and second, potentially the polar day at these high latitudes in summer (already in May?) impairs Raman retrieval due to background light.
At least in e.g., Bohlmann et al. (2019, 2021), this seemed to be not a significant problem, and at least backscatter and depolarization profiles down to low ranges at low vertical averaging would be retrievable by Raman method (at nighttime), even lower using near-range capability, including extinction, however missing depolarization, if I understand the (obviously various) PollyXT setups correctly.
Could/did you compare nighttime Raman extinctions (at 355 and 532 nm) to the Klett-retrieved extinction (from backscatter, at 910 nm)? What about somehow verify the choice of the lidar ratio (of 60 sr at 910 nm) or discuss the sensitivity of the retrieved conversion parameters on that choice?
As Bohlmann et al. (2019, 2021), Shang et al. (2020, 2022) and Filioglou et al. (2023) nicely discussed pollen lidar ratios, depolarization ratios, however, for 355 and 532 nm wavelength, and maybe most importantly in this context here, also some Ångström exponents (also backscatter-related 532/1064 and 532/910, respectively), it would be very beneficial at least to discuss/provide some more literature values or methods/ideas/suggestions helping in the wavelength conversion of your results.
Minor comments:
Line 58: I urgingly suggest to add e.g., in front of He et al. (2023), or add other studies. It has been done many more times and before than only He et al. (2023).
Line 133/Fig. 3: Is this software what is used to produce these blue lines in Fig. 3? It is not clear from the caption what these lines are (indicated length and text are written in a much too small font). Please, include it.
Line 360: Concerning the log-log regression in the relationship between number concentration and extinction, usually Shinozuka et al. (2015, https://doi.org/10.5194/acp-15-7585-2015) is given as a reference. At least log-log regression is nowadays commonly done when using AERONET to retrieve conversion parameters (for number concentrations), however, usually rather for the smaller particles (r>50 nm and 100 nm, i.e., marine, continental/pollution) than for the larger particles (r>250 nm, i.e., dust) (e.g., Mamouri and Ansmann, 2016).
It is correctly stated in the abstract and in Sect. 3.2.1. that the conversion parameters are only retrieved from 2021 measurements. This becomes clear as ICEMET data were only available in 2021 and 2023 (Line 160), but missing in 2022, and on the other hand, ceilometer data were not available in 2023 (Line 104). It might be helpful to make this fact a bit clearer by explicitly stating that, despite the fact that impressive multiyear pollen observations are available, the concurrent measurements are only available for 2021.
Line 416: Here, I would recommend to repeat that statement from the abstract regarding ceilometer-networks. Of course, they are meant inclusively in lidar-networks, but one could highlight the advantage of the dense coverage of such systems/networks, even if they are not yet throughout equipped with polarization capability.
Also Line 416: There is no reason to restrict it to space-borne backscatter lidars. I see that this could be meant as the minimum requirement, but I suggest to just state “space-borne lidars”.
Minor comments on style and spelling:
There are many cases of missing dots after Fig. etc., not abbreviated Section or Figure(s), missing s for plural Equations/Figrues, one missing ~ or \, after Sect. (Line 100-101), comma after “e.g.”. Generally, it would also be beneficial to make figure and section references clickable by using \ref{label}.
There are many hyphens mixed up. Use “--” for intervals, maybe for things like aerosol--cloud interaction, but not for things like aerosol-type-dependent.
In equations/formulas, generally, do not use italics for indices, use for example $_{\mathrm{index}}$. I suggest to do the same as well for units, only put the exponents in math mode cm$^{-3}$ (consistently), and use \textmu for micrometer.
Line 103: I suggest to add “those”: “therefore those data were omitted”. The sentence before is also quite incomprehensible. I suggest to change it like that by adding two commas: “We only considered observations during 2021 and 2022, since during the birch pollen period in May 2023, the instrument experienced…”.
Line 114: use \citep[e.g.,][]{Vakkari_2015} to avoid double )).
Line 139: Kaikkonen et al. (2020) refers to ICEMET only? Then, also add it like this: \citep[hereafter ICEMENT; University of Oulu, Finland][]{Kaikkonen_2020}.
Line 207: Tesche et al. (2009) with \citet{} instead of \citep{}.
Line 374: “CCN concentrations […] are caused” instead of “is caused”.
Line 378: “model-based” instead of “modeled--based”.
Line 379: Wozniak et al. (2018) with \citet{} instead of \citep{}.
Line 388: “coastal” instead of “Coastal”.
Fig. 1: Last access date of that web page has to be stated. And a comma added: “In close proximity,”.
Figs. 2 and 7: I would state “number concentration” and “Mass concentration”, respectively, at least in the captions.
Fig. 4: Add spaces or hyphens between 2 and h, “2-h” or “2 h” (actually, in the whole manuscript). Furthermore, I would not write “perfect fit” but “1:1 reference line”, “identity line” or “line of equality”.
References:
Generally, it would be useful to have the references clickable in the text (copernicus class should do this automatically, though).
Generally, consistently use either full journal name or abbreviation (e.g., Lines 496, 520, 546, 556, 654).
Generally, remove all double https://doi.org/ in https://doi.org/https://doi.org/.
Lines 454 and 455: some strange line breaks (in Baars et al., 2016).
Lines 466, 507, 587, 590, 593: no space between pages and hyphen.
Line 479: In Buters et al. (2018), Galán is not correctly parsed.
Line 486: The degree sign in the title is missing (Cholleton et al., 2022).
Lines 521, 522: Why are two urls given? And last access date of both should be given.
Lines 553, 554 and 579, respectively: Last access dates have to be stated in the same format.
Line 561: In Lewis and Schwartz (2004), the doi seems to be not working (besides the issue with double https://doi.org/), even though it is stated as well on this url: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/9781118666050.ch5. I do not know how to deal with this issue. I leave it to the copy editors.
Line 627: Journal name has to be written in capitals, or as abbreviation (also in capitals).
Line 629: In Tesche et al. (2009), Müller is not correctly parsed.
Line 635: Fernández Rodríguez and Ángela Gonzalo Garijo are not correctly parsed, and no hyphens in the names should be written. (author={Tormo Molina, R. and Maya Manzano, J. M. and Fern\'andez Rodr\'iguez, S. and Gonzalo Garijo, \'A and Silva Palacios, I.})
Citation: https://doi.org/10.5194/egusphere-2024-3032-RC2 - AC4: 'Reply on RC2', Maria Filioglou, 09 Dec 2024
-
RC3: 'Comment on egusphere-2024-3032', Anonymous Referee #3, 14 Nov 2024
The manuscript presents a multi-disciplinary study that combines in-situ and remote sensing data to provide newly derived extinction to concentration conversion factors for Birch Polen particles at 905 nm. Such factors are of high importance toin the lidar and ceilometer communities as they can be used for the monitoring of the vertical distribution of pollen concentration that is in-turn important for public-health and for studying aerosol-cloud interactions. The manuscript is well structured and clear. The techniques are described sufficiently. I recommend the publication of the manuscript after some minor revisions according to the comments below.
Lines 98-100: Is this uncertainty related only to the calibration? is the uncertainty due to lidar ratio biases taken into account too? If not please add the anticipated uncertainty if the lidar ratio is not 60 sr.
Lines 101-102: Is an overlap correction being applied down to 300 m (or 200 m). If yes, which is the real distance of full overlap where the correction starts? Please specify.
Lines 179-181: In section 2.5.1 a size limit of 5.3 μm is reported for ICEMET. This seems to be in conflict with the 12-35 μm range mentioned here. The different values probably refer to different types of size distribution (number concentration and volume concentration) but this is not clearly mentioned. Please add a brief explanation.
Lines 207-208: What are the two components? Is it pollen and water solubles (sulfate, nitrate organics)?
Lines 205-207: From which instrument/wavelength? Is this still the ceilometer?
Lines 211-212: Here it is implied, that a MLH ensures well mixed conditions up to 200 m so that the in-situ and the remote sensing retrievals can be combined. Is this the case? Please elaborate more as this is a key part of this study.
Lines 211-212: Does the birch share correspond to volume or number concentration fraction? Please specify. Recommendation: It would be interesting to know how does 90% contribution to the volume (or number) concentration translate to extinction (or backscatter) contribution? This can be estimated with the same methodology described here.
Lines 215-218: Is the LR of birch particles 60 sr or is this a general climatological value? Please specify and add a reference here.
Lines 215-218: According to section 2.2 the ceilometer full overlap is 300 m. How much is the systematic uncertainty due to the incomplete overlap at 200 m? Is an overlap correction being applied between 200 and 300 m. Please specify
Lines 221-222: Please don't forget to mention which concentration is being used each time, number or volume?
Lines 236-238: Suggestion: Move this sentence higher up in this section so that the readers can follow more easily the discussion.
Lines 225-226: As this is a multi-disciplinary study, it would be beneficial to provide a brief explanation of what kappa-value is for non CCN experts.
Lines 243-250: The factor f_ss, birch is never introduced. Please add a description.
Lines 240-261: Most of the factors/variables here were never properly introduced. Please add a discription of what each factor corresponds too. The subscripts are not sufficient to deduce the variable's role.
Lines 284-285: Are sea salt particles expected at the site?Citation: https://doi.org/10.5194/egusphere-2024-3032-RC3 -
AC1: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
Publisher’s note: the content of this comment was removed on 11 December 2024 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/egusphere-2024-3032-AC1 - AC3: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
-
AC1: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
Status: closed
-
RC1: 'Comment on egusphere-2024-3032', Anonymous Referee #1, 16 Oct 2024
This paper presents, for the first time, estimations of particle number, mass, CCN, giant CCN (GCCN), and ultra-giant CCN (UGCCN) concentrations derived from polarization lidar observations of birch pollen, going beyond the traditional distribution and classification of aerosol types in the atmosphere. Although there are still many aspects that need to be improved when compared to in-situ measurements at ground level, this study is deemed necessary from the perspective of extending lidar technology and making new attempts.
Therefore, it is judged appropriate for this paper to be published in the respective journal.
However, there is one important question. When discussing the particle size distribution and concentration, as shown in Figure 3, you compare the particle size of birch pollen using results obtained from the Burkard sampler and ICEMET. At this point, it is necessary to confirm whether the particle sizes reported by each instrument refer to aerodynamic particle size or geometric particle size. It seems that the particle size from the Burkard sampler is reported as the geometric particle size, but I am unsure about the particle size reported by ICEMET. If it is the aerodynamic particle size, it may require adjustments to compare the particle sizes derived from the two instruments.
Additionally, although it was mentioned that wind direction and wind speed were measured using a Doppler lidar, no results related to these measurements are presented in the paper. There is only a reference stating that it was used to identify the mixed layer and that data below 200 m were not used in the analysis. When comparing lidar measurements with in-situ measurements, as in Figure 7, it seems necessary to check whether meteorological conditions, especially wind speed or diffusion coefficients at different altitudes, had any effect. In this context, Doppler lidar data could be utilized.
Other revisions or questions are as follows:
-
The CL 61 instrument is said to have a full overlap at 300 m, but in the study, data measured at 200–250 m are analyzed. Please provide an explanation for this.
-
The lowest observation altitude for the Doppler lidar is indicated, but the highest observation altitude is not. Please also indicate the highest observation altitude.
Citation: https://doi.org/10.5194/egusphere-2024-3032-RC1 - AC2: 'Reply on RC1', Maria Filioglou, 09 Dec 2024
-
-
RC2: 'Comment on egusphere-2024-3032', Anonymous Referee #2, 01 Nov 2024
The authors present a study to retrieve extinction-to-microphysics conversion parameters of pollen aerosol. These conversion parameters can be applied to profiles of pollen aerosol-optical properties derived by polarization lidar observations in order to estimate profiles of cloud-relevant properties, in this case pollen cloud condensation nuclei concentrations. The presented method is analogous to the well-established POLIPHON (Polarization Lidar Photometer Networking) method, however it is using ceilometer with polarization capability and ground-based in situ observations instead of long-term AERONET sun photometer observations to link particle extinction with particle size distributions. This link is then exploited to retrieve abovementioned conversion parameters.
Such novel (in terms of aerosol type) conversion parameters are always sought-after for the application to lidar profiles all over the world, either from ground-based long-term observations or networks, or from space-borne lidars, which allows to retrieve climatologies of microphysical and cloud-relevant properties. Furthermore, very special observations periods at specific sites equipped with appropriate instrumentation are needed to perform such correlation studies.
Therefore, the manuscript is suited for publication in Atmospheric Chemistry and Physics and can be published almost as is after addressing rather minor comments/questions listed below.
Major comment:
My main question following hereafter is with regard to wavelengths and wavelength conversion. 355 and 532 nm are much more common lidar wavelengths (of ground-based but also space-borne systems, which you mention in your conclusion), especially concerning polarization capability. I believe it would be worth adding some statements to the manuscript regarding this topic.
There is a PollyXT is at this site (Line 75)? Does it have near-range Raman capability? Its data are obviously not used in this study. Is there a specific reason for that? I see that there would be potentially two problems: first, the pollen being present at very low ranges below the overlap region of that larger lidar; and second, potentially the polar day at these high latitudes in summer (already in May?) impairs Raman retrieval due to background light.
At least in e.g., Bohlmann et al. (2019, 2021), this seemed to be not a significant problem, and at least backscatter and depolarization profiles down to low ranges at low vertical averaging would be retrievable by Raman method (at nighttime), even lower using near-range capability, including extinction, however missing depolarization, if I understand the (obviously various) PollyXT setups correctly.
Could/did you compare nighttime Raman extinctions (at 355 and 532 nm) to the Klett-retrieved extinction (from backscatter, at 910 nm)? What about somehow verify the choice of the lidar ratio (of 60 sr at 910 nm) or discuss the sensitivity of the retrieved conversion parameters on that choice?
As Bohlmann et al. (2019, 2021), Shang et al. (2020, 2022) and Filioglou et al. (2023) nicely discussed pollen lidar ratios, depolarization ratios, however, for 355 and 532 nm wavelength, and maybe most importantly in this context here, also some Ångström exponents (also backscatter-related 532/1064 and 532/910, respectively), it would be very beneficial at least to discuss/provide some more literature values or methods/ideas/suggestions helping in the wavelength conversion of your results.
Minor comments:
Line 58: I urgingly suggest to add e.g., in front of He et al. (2023), or add other studies. It has been done many more times and before than only He et al. (2023).
Line 133/Fig. 3: Is this software what is used to produce these blue lines in Fig. 3? It is not clear from the caption what these lines are (indicated length and text are written in a much too small font). Please, include it.
Line 360: Concerning the log-log regression in the relationship between number concentration and extinction, usually Shinozuka et al. (2015, https://doi.org/10.5194/acp-15-7585-2015) is given as a reference. At least log-log regression is nowadays commonly done when using AERONET to retrieve conversion parameters (for number concentrations), however, usually rather for the smaller particles (r>50 nm and 100 nm, i.e., marine, continental/pollution) than for the larger particles (r>250 nm, i.e., dust) (e.g., Mamouri and Ansmann, 2016).
It is correctly stated in the abstract and in Sect. 3.2.1. that the conversion parameters are only retrieved from 2021 measurements. This becomes clear as ICEMET data were only available in 2021 and 2023 (Line 160), but missing in 2022, and on the other hand, ceilometer data were not available in 2023 (Line 104). It might be helpful to make this fact a bit clearer by explicitly stating that, despite the fact that impressive multiyear pollen observations are available, the concurrent measurements are only available for 2021.
Line 416: Here, I would recommend to repeat that statement from the abstract regarding ceilometer-networks. Of course, they are meant inclusively in lidar-networks, but one could highlight the advantage of the dense coverage of such systems/networks, even if they are not yet throughout equipped with polarization capability.
Also Line 416: There is no reason to restrict it to space-borne backscatter lidars. I see that this could be meant as the minimum requirement, but I suggest to just state “space-borne lidars”.
Minor comments on style and spelling:
There are many cases of missing dots after Fig. etc., not abbreviated Section or Figure(s), missing s for plural Equations/Figrues, one missing ~ or \, after Sect. (Line 100-101), comma after “e.g.”. Generally, it would also be beneficial to make figure and section references clickable by using \ref{label}.
There are many hyphens mixed up. Use “--” for intervals, maybe for things like aerosol--cloud interaction, but not for things like aerosol-type-dependent.
In equations/formulas, generally, do not use italics for indices, use for example $_{\mathrm{index}}$. I suggest to do the same as well for units, only put the exponents in math mode cm$^{-3}$ (consistently), and use \textmu for micrometer.
Line 103: I suggest to add “those”: “therefore those data were omitted”. The sentence before is also quite incomprehensible. I suggest to change it like that by adding two commas: “We only considered observations during 2021 and 2022, since during the birch pollen period in May 2023, the instrument experienced…”.
Line 114: use \citep[e.g.,][]{Vakkari_2015} to avoid double )).
Line 139: Kaikkonen et al. (2020) refers to ICEMET only? Then, also add it like this: \citep[hereafter ICEMENT; University of Oulu, Finland][]{Kaikkonen_2020}.
Line 207: Tesche et al. (2009) with \citet{} instead of \citep{}.
Line 374: “CCN concentrations […] are caused” instead of “is caused”.
Line 378: “model-based” instead of “modeled--based”.
Line 379: Wozniak et al. (2018) with \citet{} instead of \citep{}.
Line 388: “coastal” instead of “Coastal”.
Fig. 1: Last access date of that web page has to be stated. And a comma added: “In close proximity,”.
Figs. 2 and 7: I would state “number concentration” and “Mass concentration”, respectively, at least in the captions.
Fig. 4: Add spaces or hyphens between 2 and h, “2-h” or “2 h” (actually, in the whole manuscript). Furthermore, I would not write “perfect fit” but “1:1 reference line”, “identity line” or “line of equality”.
References:
Generally, it would be useful to have the references clickable in the text (copernicus class should do this automatically, though).
Generally, consistently use either full journal name or abbreviation (e.g., Lines 496, 520, 546, 556, 654).
Generally, remove all double https://doi.org/ in https://doi.org/https://doi.org/.
Lines 454 and 455: some strange line breaks (in Baars et al., 2016).
Lines 466, 507, 587, 590, 593: no space between pages and hyphen.
Line 479: In Buters et al. (2018), Galán is not correctly parsed.
Line 486: The degree sign in the title is missing (Cholleton et al., 2022).
Lines 521, 522: Why are two urls given? And last access date of both should be given.
Lines 553, 554 and 579, respectively: Last access dates have to be stated in the same format.
Line 561: In Lewis and Schwartz (2004), the doi seems to be not working (besides the issue with double https://doi.org/), even though it is stated as well on this url: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/9781118666050.ch5. I do not know how to deal with this issue. I leave it to the copy editors.
Line 627: Journal name has to be written in capitals, or as abbreviation (also in capitals).
Line 629: In Tesche et al. (2009), Müller is not correctly parsed.
Line 635: Fernández Rodríguez and Ángela Gonzalo Garijo are not correctly parsed, and no hyphens in the names should be written. (author={Tormo Molina, R. and Maya Manzano, J. M. and Fern\'andez Rodr\'iguez, S. and Gonzalo Garijo, \'A and Silva Palacios, I.})
Citation: https://doi.org/10.5194/egusphere-2024-3032-RC2 - AC4: 'Reply on RC2', Maria Filioglou, 09 Dec 2024
-
RC3: 'Comment on egusphere-2024-3032', Anonymous Referee #3, 14 Nov 2024
The manuscript presents a multi-disciplinary study that combines in-situ and remote sensing data to provide newly derived extinction to concentration conversion factors for Birch Polen particles at 905 nm. Such factors are of high importance toin the lidar and ceilometer communities as they can be used for the monitoring of the vertical distribution of pollen concentration that is in-turn important for public-health and for studying aerosol-cloud interactions. The manuscript is well structured and clear. The techniques are described sufficiently. I recommend the publication of the manuscript after some minor revisions according to the comments below.
Lines 98-100: Is this uncertainty related only to the calibration? is the uncertainty due to lidar ratio biases taken into account too? If not please add the anticipated uncertainty if the lidar ratio is not 60 sr.
Lines 101-102: Is an overlap correction being applied down to 300 m (or 200 m). If yes, which is the real distance of full overlap where the correction starts? Please specify.
Lines 179-181: In section 2.5.1 a size limit of 5.3 μm is reported for ICEMET. This seems to be in conflict with the 12-35 μm range mentioned here. The different values probably refer to different types of size distribution (number concentration and volume concentration) but this is not clearly mentioned. Please add a brief explanation.
Lines 207-208: What are the two components? Is it pollen and water solubles (sulfate, nitrate organics)?
Lines 205-207: From which instrument/wavelength? Is this still the ceilometer?
Lines 211-212: Here it is implied, that a MLH ensures well mixed conditions up to 200 m so that the in-situ and the remote sensing retrievals can be combined. Is this the case? Please elaborate more as this is a key part of this study.
Lines 211-212: Does the birch share correspond to volume or number concentration fraction? Please specify. Recommendation: It would be interesting to know how does 90% contribution to the volume (or number) concentration translate to extinction (or backscatter) contribution? This can be estimated with the same methodology described here.
Lines 215-218: Is the LR of birch particles 60 sr or is this a general climatological value? Please specify and add a reference here.
Lines 215-218: According to section 2.2 the ceilometer full overlap is 300 m. How much is the systematic uncertainty due to the incomplete overlap at 200 m? Is an overlap correction being applied between 200 and 300 m. Please specify
Lines 221-222: Please don't forget to mention which concentration is being used each time, number or volume?
Lines 236-238: Suggestion: Move this sentence higher up in this section so that the readers can follow more easily the discussion.
Lines 225-226: As this is a multi-disciplinary study, it would be beneficial to provide a brief explanation of what kappa-value is for non CCN experts.
Lines 243-250: The factor f_ss, birch is never introduced. Please add a description.
Lines 240-261: Most of the factors/variables here were never properly introduced. Please add a discription of what each factor corresponds too. The subscripts are not sufficient to deduce the variable's role.
Lines 284-285: Are sea salt particles expected at the site?Citation: https://doi.org/10.5194/egusphere-2024-3032-RC3 -
AC1: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
Publisher’s note: the content of this comment was removed on 11 December 2024 since the comment was posted by mistake.
Citation: https://doi.org/10.5194/egusphere-2024-3032-AC1 - AC3: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
-
AC1: 'Reply on RC3', Maria Filioglou, 09 Dec 2024
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