Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Moallemi, Alireza; Modini, Rob L.; Lapyonok, Tatyana; Lopatin, Anton; Fuertes, David; Dubovik, Oleg; Giaccari, Philippe; Gysel-Beer, Martin

doi:https://doi.org/10.5194/amt-15-5619-2022

Articles | Volume 15, issue 19

https://doi.org/10.5194/amt-15-5619-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-15-5619-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 19

Research article

|

10 Oct 2022

Research article |

| 10 Oct 2022

Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data

Alireza Moallemi, Rob L. Modini, Tatyana Lapyonok, Anton Lopatin, David Fuertes, Oleg Dubovik, Philippe Giaccari, and Martin Gysel-Beer

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Final revised paper (published on 10 Oct 2022)
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Preprint (discussion started on 14 Jun 2022)
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Interactive discussion

Status: closed

RC1:
'Comment on amt-2022-170', Reed Espinosa, 08 Jul 2022

– General Comments –

The manuscript describes a polar nephelometer information content study performed in the context of multiple polydisperse laboratory and ambient aerosols. The potential to retrieve aerosol concentration, size, spherical particle fraction and complex refractive index is evaluated for various instrument designs with different detection angles, wavelength configurations and polarization resolving capabilities. Overall, the work shows that retrievals of data from even a rudimentary polar nephelometer can theoretically provide a very significant amount of information on the sampled aerosol.

The content of the manuscript is novel, and it has the potential to be a very useful, and much needed, resource for future developers of polar nephelometer instruments. The material is inevitably a bit dense, but the text is well written, and the methods are clearly described. In my view, the manuscript could be slightly improved by the addition of a few more readily applicable results that would be more accessible to the casual reader. For example, it would be very informative to provide expected retrieval errors for the considered variables of state given the instrument configurations show in Figure 12 and the atmospheric measurement-derived a priori values. Overall though, the manuscript is clearly very appropriate for AMT, and I can recommend publication once the minor points below have been addressed.

– Specific Comments –

1. Ln 71: Phase function is sometimes normalized but I believe absolute phase function (i.e., βsca*P11, where P11 is the phase function normalized such that the integral over all angles is 4π) is used here. It would be good to expectedly state the definition and/or units used for phase function in this work.

2. Eq 2: I believe this equation is only valid for systems in which F(x) is linear everywhere, not just locally. Since Mie (and spheroid scattering) is very non-linear, I'm wondering if it is appropriate here.

3. Sec 3.1.3: Is the angular Field-Of-View (FOV) of the sensor at a given scattering angle assumed to be negligibly small? This is not always the case for real instruments and should be clarified in the text. On a side note, in the PI-Neph Δθ≈0.2° but, due to smearing of the image by imperfect optics, the FOV of each pixel ends up being about ~1°, with significant overlap between pixels. Ultimately, data is reported at 1° resolution to avoid the need for a complicated deconvolution procedure.

4. Ln 292: Covariance in polar nephelometer error can be large and quite complex, especially in imaging nephelometers. Do the authors have a sense of how sensitive their results are to this assumed covariance? How was the value ρ=0.7 selected?

5. Table 3: This table defines the PSD using GSD while the following two tables use ln(GSD). It might be clearer to use a consistent metric throughout the manuscript.

6. Ln 432: It would be good to provide a reference supporting the idea that refractive index values have significant spectral correlation. Two possible candidates would be Xu et al. (2019) and Gao et al. (2018).

7. Table 5: I'm having trouble tracking which refractive indices were used to determine the percentage-based a priori covariance values in the bottom row. Each cell of the bottom row has two values: an absolute quantity and a percentage. My understanding from Figure 5 is that the absolute quantity listed is actually used for all λ and aerosol species in the information content calculations. If so, which wavelength and species does the percentage shown apply to? Please clarify.

8. Figure 4: Would it be possible to show the σ_a values within each subplot as they are in shown in Figure 5. This would greatly ease contextualization of these results for the reader.

9. Figure 5: In the coarse, k subplot, I interpret σ_a=0.0005 and DOFS≈1 for even the single wavelength non-polarized nephelometer to mean that the corresponding instrument has the potential to retrieve k to an accuracy much better than 0.0005. Although coarse mode state may have been slightly different, prior work has not noted very significant changes in PF resulting from changes in k as small as Δk=0.0005 (e.g., see Figure 2 of Espinosa et al. (2019)). Section 4.4 and Figure S4 provide a bit more context regarding the situations in which the present authors have observed PF to change significantly with k but I'm wondering if any intuitive explanation of the exact mechanism driving this high sensitivity is available, given that this feature has not been observed in prior work.

10. Figure 6: Are these DOFS (and the results in Fig S4) based on the percentage- or atmospheric-based a priori variance values?

11. Ln 750: Do the authors know of a particular nephelometer that suffers from side angle truncation? If so, it would be good to add a reference to this instrument. If no reference is available, it may be better to soften this statement and say that some designs could potentially suffer from side angle truncations.

12. Ln 777: Intuitively, I imagine there to be two relatively separate mechanisms that lead to improvements in DOFS with increasing N_θ: (1) an improved ability to capture angular features in the PF and PPF that encode information about the aerosol and (2) an increase in measurement statistics that helps to beat down noise and effectively increase the accuracy of the measurement. The two mechanisms are likely quite difficult to disentangle but I'm wondering if the authors have any sense of their relative contributions here. If mechanism (2) was dominate, I would expect the N_θ value where "plateauing" starts to occur to be strongly dependent on the assumed error covariance (specifically the value of ρ). Is the conclusion that the plateau generally occurs 20<N_θ<40 robust to different choices of ρ? This could be quite relevant in terms of instrument design considerations where there is frequently a choice between adding more angles or increasing the accuracy in a smaller subset of angles.

13. Ln 781: I would recommend restating the sentence that begins on this line. As it is currently written, it almost sounds like the plateau in IC is more prominent with complex particles or low instrument noise, which I think is the opposite of what the authors intended.

14. Ln 784: It may be worth noting that these conclusions all apply only to polydisperse aerosols. Monodisperse aerosols, or even reactively narrow polydisperse size distributions, will have significantly more angular features and likely continue to benefit from more angles, well beyond the plateaus observed here.

– Technical Corrections –

Ln 88: "Polarized Imaging Nephelometer" should be capitalized.

Ln 290: "Wavelength" should be one word

Ln 446: This sentence contains an extra "it".

Ln 456: I might suggest something like "detection angles" in place of "sensor" since some instruments (e.g., Imaging Nephs) only have a single CCD sensor.

Ln 471: Should read "...with an increasing..."

– References –

Xu, Feng, et al. "A correlated multi-pixel inversion approach for aerosol remote sensing." Remote Sensing 11.7 (2019): 746.

Gao, M., Zhai, P.-W., Franz, B., Hu, Y., Knobelspiesse, K., Werdell, P. J., Ibrahim, A., Xu, F., and Cairns, B.: Retrieval of aerosol properties and water-leaving reflectance from multi-angular polarimetric measurements over coastal waters, Opt. Express, 26, 8968–8989, https://doi.org/10.1364/OE.26.008968, 2018.

Citation: https://doi.org/10.5194/amt-2022-170-RC1
- AC1: 'Replies to RC1 and RC2', Robin Modini, 02 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2022-170/amt-2022-170-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/amt-2022-170-AC1
RC2:
'Comment on amt-2022-170', Adam Ahern, 12 Jul 2022

The manuscript “Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data” by A. Moallemi et al. presents an evaluation of the information content of data from different polar nephelometer configurations for a variety of simple and complex aerosol models. They present a Bayesian sensitivity analysis with an appropriate discussion of the impact of prior assumptions and are deliberate in communicating the limitations of the analysis.

They use the Degree of Freedom for Signal (DOFS) to quantitatively compare polar nephelometer designs while varying amounts of signal truncation, number and position of detectors, and number of investigated wavelengths. This work represents a valuable contribution to the field because, similar to the work of Knobelspiesse et al. for remote sensing instruments, Moallemi et al. quantitatively explore the connection between in situ instrument design and the retrieved parameters. This was well-illustrated by the use of DOFS and the reductive greedy algorithm to optimize detector placement.

This manuscript is excellent and I could recommend it for publication in its current state, although I will use this opportunity to make a few small comments.

General comment:

Although the manuscript is impressive in the scope of the design permutations explored, I think that the fundamental choice of which wavelength(s), as opposed to how many wavelengths, to investigate is taken for granted. This might make an interesting addition to the supplemental material.

Minor comments:

3.1.3 Angular characteristics: number of proved angles assuming evenly distributed measurements

P10.148 Is it true that each data point represents a theoretical “sensor” that is infinitely narrow? As opposed to a sensor that has a non-zero solid angle?

3.5 Forward Model

P17.443 Besides Espinosa et al., consider including Schuster et al. (2019)

4.1 Dependence of information content on the angular configurations of previous polar nephelometer designs

P18.483 The way this is discussed is a little confusing because nDOFS is an analytical result. I wonder if another way to discuss this is that the nDOFS presented is specific to your test aerosol parameters. To extrapolate more broadly, i.e. if you want to compare which instrument provides more information about fine aerosol parameters (of which your test aerosol is a subset), then you must consider the sensitivity of nDOFS to the aerosol model parameters in the range of interest.

Fig. 5. Consistency of labels with Fig. 4 would be nice (e.g. VMR vs Median Radius)

4.4 Information content for the imaginary part of the refractive index

P26.674 where the latter is equivalent

P27.684 atmospheric-based a prior

4.8 Proof of concept for using DOFS as metric for optimizing angular sensor placement

Fig. 11 Consider using different marker shapes. The blue and black are hard to differentiate.

P33.843 Labels for Fig. 11 state PF and PPF, whereas this line states only PF.

5 Conclusion

P35.900 To assess the benefit

Dick, W. D., Ziemann, P. J., and McMurry, P. H.: Multiangle Light-Scattering Measurements of Refractive Index of Submicron Atmospheric Particles, Aerosol Sci. Technol., 41, 549–569, https://doi.org/10.1080/02786820701272012, 2007.

Li, D., Chen, F., Zeng, N., Qiu, Z., He, H., He, Y., and Ma, H.: Study on polarization scattering applied in aerosol recognition in the air, Opt. Express, OE, 27, A581–A595, https://doi.org/10.1364/OE.27.00A581, 2019.

Nakagawa, M., Nakayama, T., Sasago, H., Ueda, S., Venables, D. S., and Matsumi, Y.: Design and characterization of a novel single-particle polar nephelometer, Aerosol Sci. Technol., 50, 392–404, https://doi.org/10.1080/02786826.2016.1155105, 2016.

Schuster, G. L., Espinosa, W. R., Ziemba, L. D., Beyersdorf, A. J., Rocha-Lima, A., Anderson, B. E., Martins, J. V., Dubovik, O., Ducos, F., Fuertes, D., Lapyonok, T., Shook, M., Derimian, Y., and Moore, R. H.: A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms, Remote Sens., 11, 498, https://doi.org/10.3390/rs11050498, 2019.

Citation: https://doi.org/10.5194/amt-2022-170-RC2
- AC1: 'Replies to RC1 and RC2', Robin Modini, 02 Sep 2022
  
  The comment was uploaded in the form of a supplement: https://amt.copernicus.org/preprints/amt-2022-170/amt-2022-170-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/amt-2022-170-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Robin Modini on behalf of the Authors (02 Sep 2022) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (07 Sep 2022) by Charles Brock

Short summary

Aerosol properties (size distributions, refractive indices) can be retrieved from in situ, angularly resolved light scattering measurements performed with polar nephelometers. We apply an established framework to assess the aerosol property retrieval potential for different instrument configurations, target applications, and assumed prior knowledge. We also demonstrate how a reductive greedy algorithm can be used to determine the optimal placements of the angular sensors in a polar nephelometer.