the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Sep 2023
The uncertainties in the laboratory-measured short-wave refractive indices of mineral dust aerosols and the derived optical properties: A theoretical assessment
Abstract. Mineral dust particles are typically nonspherical and inhomogeneous; however, they are often simplified as homogeneous spherical particles for retrieving the refractive indices from laboratory measurements of scattering and absorption coefficients. This study theoretically investigated uncertainties in refractive indices and corresponding optical properties resulting from this simplification at various sizes within the wavelength range of 355 to 1064 nm. Different numerical experiments were conducted under both ideal and realistic scenarios, taking into account instrumental bias in the realistic scenarios. In the numerical experiments, the inhomogeneous super-spheroid models were considered as the dust samples, while the homogeneous super-spheroid models and sphere models were used to retrieve the refractive indices. Under the ideal scenario, the look-up tables for the homogeneous super-spheroid models satisfactorily covered the measurements at any size and wavelength, while those for the sphere models failed when considering large sizes. Under the realistic scenario, both the homogeneous super-spheroid models and sphere models were ineffective for large sizes due to discrepancies in size distribution resulting from the measurements using an optical particle counter. Nevertheless, it was possible to retrieve the imaginary parts of the refractive indices based solely on the absorption coefficients. The imaginary parts obtained from the sphere models were generally consistent with those from the super-spheroid models under ideal conditions, while the former was significantly smaller than the latter under the realistic conditions. In addition, the retrieved imaginary parts were found to be size-dependent, which could be attributed to the inherent limitations of homogeneous models in characterizing inhomogeneous particles. Results showed that the uncertainties in the imaginary part and single scattering albedo should be smaller than 0.002 (0.0007) and 0.03 (0.01), respectively, under conditions of high (low) absorption. The sphere models tended to overestimate the asymmetry factor. The uncertainty in the asymmetry factor exhibited a significant variation, reaching up to 0.04 or even larger. Nonetheless, the uncertainties in the phase matrices resulting from the uncertainties in refractive indices were generally acceptable within a specific model.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1849', Anonymous Referee #1, 25 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1849/egusphere-2023-1849-RC1-supplement.pdf
- AC1: 'Reply on RC1', Lei Bi, 16 Mar 2024
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RC2: 'Comment on egusphere-2023-1849', Anonymous Referee #2, 18 Dec 2023
General comments.
This manuscript describes a method to apply the super-spheroid model to simulated aerosol particles and investigate their non-sphericity. To this aim, the authors draw on their previous work and assess the uncertainties introduced by model-dependent data interpretation. In this case, they could explain their contribution to aerosol science more clearly. The authors use the super-spheroid model to mimic experimental data, then proceed to interpret such data with a look-up table (LUT) generated with the same model while comparing the results with those obtained with a LUT based on the spherical model. Although mentioned in the introduction, other numerical models are not considered for data analysis. I am not sure how generalizable the results of this work actually are. The main weaknesses I see in the work are that it uses the same model as an input and an interpretation framework and that it does not directly confront the spheroidal model. Even though the spherical model is the benchmark for interpreting experimental data, going one step further would make this simulation work more complete. Overall, I am afraid that several (key) parts of the manuscript are not clear enough and would suggest revising its written form. I would also suggest, to improve readability, revising the use of the past tense (it is sometimes hard to tell what precedes this work and what is part of it) and the typesetting of equations and variables. I address the manuscript's sections with some comments followed by a selection of notes on specific lines.
Abstract.I believe it is longer than it needs to be while not serving its purpose quite effectively. After the first few introductory lines, it reads more like an excerpt of a discussion section than a concise synopsis of the authors' work. A key point is that the manuscript is about numerical rather than experimental results, which is not clear from either the abstract or the title.
lines 15) If the authors want to elaborate on the 'realistic' and 'ideal' scenarios in the abstract, a brief explanation of these terms should be given.line 17) discrepancies among which distributions?
line 23) why should they?
line 25) I am not sure it fits in the abstract, but the authors should discuss somewhere what they consider a large variation in the asymmetry factor.
line 26) I am afraid this sentence may be misleading as it can be understood only after having read the whole article.
Introduction.Overall, the contextualization of the models mentioned here could be improved. There are too few references about the state of the art the authors are motivated to expand upon.
When reading the central body of this section, many references point to the limitations of the spheroid model applied to experimental data: one could expect this to be the main motivation of this work. Yet the matter is not elaborated further. The authors should state more clearly what they mean by 'revisiting the laboratory measurements' using a numerical method. Since they are producing simulated data, they can control every parameter involved in the study, therefore, they can check the assumptions they make as to why some results are inconsistent.
line 36) please shortly define the 'super-spheroid model' and the rationale behind its introduction. The super-spheroid model requires more parameters than the spherical model, therefore, it can better fit experimental data by design. Its advantages should be better argued, given the aim of this work.
line 45) I assume the authors mean the volume-equivalent diameter, but many definitions of this parameter are possible.
line 55) more recent studies might be drawn to support this statement.
line 58) please provide more examples of studies on this topic.
line 82) this assertion may need further elaboration.
Experimental design.The fact that this work does not involve actual measurements but consists of numerical calculations is a defining feature. This paper should, in my opinion, state its scope more clearly. I am fully persuaded of the importance of simulative research, which is why I would advise against using the name "dust sample" or "measurement" for what is a numerical model. While I share the authors' point of view, I'm afraid that obtaining experimental data with the instruments they mention involves more than just truncating the integration interval or tuning some parameters to address a non-ideal scenario. I would go into greater detail about the assumptions the authors make to generate the population of particles they then proceed to study.
The authors might consider moving lines 156–175 at the beginning of the 'Experimental Design' section.
line 99) please explain what 'inhomogeneous' stands for.
line 118, 230–235) I believe that the process of changing or correcting the size distribution requires some more explanation.
line 124) here the authors refer to unavoidable technical limitations that are easily taken care of rather than defects. On the other hand, modeling possible stochastic or systematic experimental errors would be surely interesting.
figure 1) I am not sure how fair it is to compare results from the spherical-based LUT with those from the super-spheroid LUT since the input dust itself is generated with the super-spheroidal model. Alternatively, an ellipsoid-based LUT would be interesting.
line 137) why were these specific aspect ratios (geometries) chosen?
line 159) please provide some references supporting this statement and some further comments on how the refractive index distributions were set.
line 197) the geometric diameter should be defined earlier in the text.
line 204) the retrieval of the size distribution is a crucial step of data inversion and should be considered as a factor influencing final results. Given the numerical nature of the work, this could be investigated.
line 216) please describe more in depth the observed biases.
Results and discussion.I would be more cautious about the generality of the conclusions that may be drawn from this work, having its design in mind. It is certainly valuable to provide some links to experimental work by adapting the premises and parameters of the simulations, yet I wouldn't say the E4 case covers them completely. The authors state that defining the size of irregular particles necessarily leads to discrepancies. I see it is a critical step but it lacks the insights it deserves. With all the input parameters being known (unlike field measurements), the analysis could be more aware and detailed than it is at present. This comes to mind when they attribute the observed discrepancies to differences in the size distribution, for instance.
line 316) the authors point out the limited range of the LUT more than once. Is this a critical limitation? If so, would it be feasible to extend it, even if it were to include unlikely values of the refractive index or size?
line 318) why are the uncertainties this large?
lines 322 and ff) it might be redundant to mention a model that gives even larger discrepancies, I would rather try to quantify the extent to which the definition of size could affect the results.
lines 336–350) given the lack of literature on the refractive index of goethite and its prominent role in determining the refractive index of the ensemble of particles, why did the authors include it in the simulations? How do the results change if they don't?
line 368 and ff.) the spherical model and the super-spheroid model give very close results, particularly considering the error bars. Do the authors have any hypotheses or explanations as to this matter?
line 384-389) the argument being made here could be clearer, I believe it’s important to go into greater detail about such differences. Since these are simulations, these parameters are under control and are available for analysis.
line 390) I think this is a central point that should be investigated further, especially because of their great effect on optical properties.
lines 410 and ff) this appears to be a significant limitation of the method: what are these very strict conditions required to accurately retrieve n?
line 455) this is one of the main weaknesses of the spherical approximation. How does the phase function of super-spheroids compare to laboratory measurements? Some information about how they were calculated would be helpful (e.g. possible rotational averages).
line 459) although I share the authors’ concern, it should be noted that considerable progress has been made since the literature cited here was first published.
line 461) ‘simplify’?
line 462) ‘are’?
line 485) please expand the caption of Figure 11 with the information included in the main text.
line 508) I would recommend that the reasons for these difficulties be probed deeper and discussed in this section more thoroughly.
Summary.I appreciate the purpose of this section, also in light of the length of the manuscript. I wonder if it would not be more effective to move its content partly into the introduction and partly into the discussion.
References.I find the bibliography skewed toward less recent results in some sections of the text. Some updates would be beneficial, specifically because of the rapid scientific advances in the field of simulations. It would also be worth double-checking how relevant some of the self-citations are to the discussion and the points being made by the authors.
Citation: https://doi.org/10.5194/egusphere-2023-1849-RC2 - AC2: 'Reply on RC2', Lei Bi, 16 Mar 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1849', Anonymous Referee #1, 25 Nov 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1849/egusphere-2023-1849-RC1-supplement.pdf
- AC1: 'Reply on RC1', Lei Bi, 16 Mar 2024
-
RC2: 'Comment on egusphere-2023-1849', Anonymous Referee #2, 18 Dec 2023
General comments.
This manuscript describes a method to apply the super-spheroid model to simulated aerosol particles and investigate their non-sphericity. To this aim, the authors draw on their previous work and assess the uncertainties introduced by model-dependent data interpretation. In this case, they could explain their contribution to aerosol science more clearly. The authors use the super-spheroid model to mimic experimental data, then proceed to interpret such data with a look-up table (LUT) generated with the same model while comparing the results with those obtained with a LUT based on the spherical model. Although mentioned in the introduction, other numerical models are not considered for data analysis. I am not sure how generalizable the results of this work actually are. The main weaknesses I see in the work are that it uses the same model as an input and an interpretation framework and that it does not directly confront the spheroidal model. Even though the spherical model is the benchmark for interpreting experimental data, going one step further would make this simulation work more complete. Overall, I am afraid that several (key) parts of the manuscript are not clear enough and would suggest revising its written form. I would also suggest, to improve readability, revising the use of the past tense (it is sometimes hard to tell what precedes this work and what is part of it) and the typesetting of equations and variables. I address the manuscript's sections with some comments followed by a selection of notes on specific lines.
Abstract.I believe it is longer than it needs to be while not serving its purpose quite effectively. After the first few introductory lines, it reads more like an excerpt of a discussion section than a concise synopsis of the authors' work. A key point is that the manuscript is about numerical rather than experimental results, which is not clear from either the abstract or the title.
lines 15) If the authors want to elaborate on the 'realistic' and 'ideal' scenarios in the abstract, a brief explanation of these terms should be given.line 17) discrepancies among which distributions?
line 23) why should they?
line 25) I am not sure it fits in the abstract, but the authors should discuss somewhere what they consider a large variation in the asymmetry factor.
line 26) I am afraid this sentence may be misleading as it can be understood only after having read the whole article.
Introduction.Overall, the contextualization of the models mentioned here could be improved. There are too few references about the state of the art the authors are motivated to expand upon.
When reading the central body of this section, many references point to the limitations of the spheroid model applied to experimental data: one could expect this to be the main motivation of this work. Yet the matter is not elaborated further. The authors should state more clearly what they mean by 'revisiting the laboratory measurements' using a numerical method. Since they are producing simulated data, they can control every parameter involved in the study, therefore, they can check the assumptions they make as to why some results are inconsistent.
line 36) please shortly define the 'super-spheroid model' and the rationale behind its introduction. The super-spheroid model requires more parameters than the spherical model, therefore, it can better fit experimental data by design. Its advantages should be better argued, given the aim of this work.
line 45) I assume the authors mean the volume-equivalent diameter, but many definitions of this parameter are possible.
line 55) more recent studies might be drawn to support this statement.
line 58) please provide more examples of studies on this topic.
line 82) this assertion may need further elaboration.
Experimental design.The fact that this work does not involve actual measurements but consists of numerical calculations is a defining feature. This paper should, in my opinion, state its scope more clearly. I am fully persuaded of the importance of simulative research, which is why I would advise against using the name "dust sample" or "measurement" for what is a numerical model. While I share the authors' point of view, I'm afraid that obtaining experimental data with the instruments they mention involves more than just truncating the integration interval or tuning some parameters to address a non-ideal scenario. I would go into greater detail about the assumptions the authors make to generate the population of particles they then proceed to study.
The authors might consider moving lines 156–175 at the beginning of the 'Experimental Design' section.
line 99) please explain what 'inhomogeneous' stands for.
line 118, 230–235) I believe that the process of changing or correcting the size distribution requires some more explanation.
line 124) here the authors refer to unavoidable technical limitations that are easily taken care of rather than defects. On the other hand, modeling possible stochastic or systematic experimental errors would be surely interesting.
figure 1) I am not sure how fair it is to compare results from the spherical-based LUT with those from the super-spheroid LUT since the input dust itself is generated with the super-spheroidal model. Alternatively, an ellipsoid-based LUT would be interesting.
line 137) why were these specific aspect ratios (geometries) chosen?
line 159) please provide some references supporting this statement and some further comments on how the refractive index distributions were set.
line 197) the geometric diameter should be defined earlier in the text.
line 204) the retrieval of the size distribution is a crucial step of data inversion and should be considered as a factor influencing final results. Given the numerical nature of the work, this could be investigated.
line 216) please describe more in depth the observed biases.
Results and discussion.I would be more cautious about the generality of the conclusions that may be drawn from this work, having its design in mind. It is certainly valuable to provide some links to experimental work by adapting the premises and parameters of the simulations, yet I wouldn't say the E4 case covers them completely. The authors state that defining the size of irregular particles necessarily leads to discrepancies. I see it is a critical step but it lacks the insights it deserves. With all the input parameters being known (unlike field measurements), the analysis could be more aware and detailed than it is at present. This comes to mind when they attribute the observed discrepancies to differences in the size distribution, for instance.
line 316) the authors point out the limited range of the LUT more than once. Is this a critical limitation? If so, would it be feasible to extend it, even if it were to include unlikely values of the refractive index or size?
line 318) why are the uncertainties this large?
lines 322 and ff) it might be redundant to mention a model that gives even larger discrepancies, I would rather try to quantify the extent to which the definition of size could affect the results.
lines 336–350) given the lack of literature on the refractive index of goethite and its prominent role in determining the refractive index of the ensemble of particles, why did the authors include it in the simulations? How do the results change if they don't?
line 368 and ff.) the spherical model and the super-spheroid model give very close results, particularly considering the error bars. Do the authors have any hypotheses or explanations as to this matter?
line 384-389) the argument being made here could be clearer, I believe it’s important to go into greater detail about such differences. Since these are simulations, these parameters are under control and are available for analysis.
line 390) I think this is a central point that should be investigated further, especially because of their great effect on optical properties.
lines 410 and ff) this appears to be a significant limitation of the method: what are these very strict conditions required to accurately retrieve n?
line 455) this is one of the main weaknesses of the spherical approximation. How does the phase function of super-spheroids compare to laboratory measurements? Some information about how they were calculated would be helpful (e.g. possible rotational averages).
line 459) although I share the authors’ concern, it should be noted that considerable progress has been made since the literature cited here was first published.
line 461) ‘simplify’?
line 462) ‘are’?
line 485) please expand the caption of Figure 11 with the information included in the main text.
line 508) I would recommend that the reasons for these difficulties be probed deeper and discussed in this section more thoroughly.
Summary.I appreciate the purpose of this section, also in light of the length of the manuscript. I wonder if it would not be more effective to move its content partly into the introduction and partly into the discussion.
References.I find the bibliography skewed toward less recent results in some sections of the text. Some updates would be beneficial, specifically because of the rapid scientific advances in the field of simulations. It would also be worth double-checking how relevant some of the self-citations are to the discussion and the points being made by the authors.
Citation: https://doi.org/10.5194/egusphere-2023-1849-RC2 - AC2: 'Reply on RC2', Lei Bi, 16 Mar 2024
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Cited
Senyi Kong
Zheng Wang
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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