the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Mar 2025
Scattering properties and Lidar Characteristics of Asian Dust Particles Based on Realistic Shape Models
Abstract. The lidar backscattering properties of Asian dust particles, namely the lidar ratio (𝑆) and backscattering depolarization ratio (δ), were studied using a discrete dipole approximation (DDA) model. The three-dimensional morphology of the dust particles was reconstructed in fine detail using the focused ion-beam (FIB) tomography technique. An index based on the symmetry of the scattering phase matrix was developed to assess the convergence of random orientation computation using DDA. Both the 𝑆 and δ exhibit an asymptotic trend with dust particle size: the 𝑆 initially decreases while the δ increases with size, before both approach their asymptotic values. The lidar properties were found to have statistically insignificant dependence on effective sphericity. The presence of strongly absorbing minerals, such as magnetite, can greatly reduce the dust's single-scattering albedo and δ. Utilizing the robust asymptotic trend behavior, two parameterization schemes were developed: one to estimate the δ of a single dust particle given its size, and the other to estimate the δ of dust particles with a lognormal particle size distribution given the effective radius. The parameterization scheme was compared with results based on the TAMUdust2020 database, showing hexahedrals to reasonably represent realistic geometries with similar physical properties.
- Preprint
(2565 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 07 May 2025)
-
RC1: 'Comment on egusphere-2025-1117', Anonymous Referee #1, 29 Apr 2025
reply
The study uses 14 realistic Asian dust particles with sizes from r = 0.46 to 0.93 µm and describe their scattering properties by using the discrete dipole approximation (DDA). They calculate lidar ratios and depolarization ratios at 3 commonly used lidar wavelengths based on their realistic particles with the limited size range. They reveal an asymptotic behavior of the lidar ratio and depolarization ratio with increasing size parameters and develop a parameterization for the later one. The study is interesting and contributes to the challenging task of modelling the scattering properties of irregularly shaped mineral dust particles. The DDA technique allows to create any particle shape which has advantages above predefined particles shapes. However, it is difficult to extend it to large size parameters, where the asymptotic behavior might be helpful. The manuscript can still be improved and therefore, I recommend to consider my major revisions listed below.
Major comments:
1. Size
Your studied particles range roughly between 1 – 2 µm in diameter. Is this sufficient to realistically describe atmospheric mineral dust? The fine mode or sub-micrometer mode is missing but contributes to the optical properties observed with lidar. And on the other end, the large particles are missing as well. It is a major limitation of the study and hampers a good comparison to real world observations with lidar. Please discuss how representative your particle size range is for atmospheric observations.
Because you don’t vary CRI nor shape, there is no additional information in using different wavelengths. If you would stick to one wavelength (e.g., 532 nm), you would just cover the size parameters from 5.5 to 11, this is much less than in Järvinen et al., 2016. And from this, you cannot draw the conclusions presented in Sect. 4. Now, you just add calculations at other wavelengths, in principle you could take any wavelength to cover the size parameter space from 0.1 to 20. And in fact, you’re just covering the size parameter space from 2.7 to 16.5. So, the smallest size parameters, i.e., the fine mode, is not included. Please start your figures at 0 and not at 2 (Fig. 6-8). If you take for example Fig. 12a and mark the covered size range of your particles, you will see that just a small part of the size distribution is covered.
2. CRI
If you cannot include the spectral dependence of the CRI, i.e., the increase towards the UV, I would omit the results at 355 nm. In case you want to keep the results at 355 nm, please find a way to mimic a realistic increase in the imaginary part of the CRI. Otherwise, your discussions might be misleading.
The complex refractive index (CRI) is an important quantity. However, you missed completely to set your results in the context of previous observations. The first study which comes into my mind is the one by Di Biagio et al., 2019.
3. Asian Dust
The term “Asian dust” is widely used in literature, especially to separate it from Saharan dust. However, Asia is a huge continent and at some point, you should be more specific about the source region, which is probably in the Gobi Desert. Dust from Central or West Asian (Middle Eastern, Persian or Arabian) deserts might exhibit different optical properties.
And there are differences in the optical properties, especially in the lidar ratio, between Asian and Saharan dust, which was summarized by Floutsi et al., AMT 2023 based on observations of Hofer et al., ACP 2020. A lidar ratio of 35 sr might be not that bad for Asian dust, but not for (West) Saharan dust.
4. Asymptotic Behavior
The measurements of Järvinen et al., 2016, show an asymptotic behavior for the depolarization ratio as you mentioned correctly. But you are hiding that this plateau was found at around 0.30 and not 0.41. This is a significant difference. Does your model overestimate the depolarization ratio of mineral dust? And why? What could be the reason? Asian dust was included in the study of Järvinen et al., 2016. Kahnert et al., 2020, used the laboratory results of Järvinen et al., to test various modelling parameters. Please take these two studies seriously and discuss the differences to your results.
L511-518: The asymptotic value of the depolarization ratio (0.41) is quite high compared to approximately 0.3 in Järvinen et al., 2016. How do you explain the differences? If I as a user would like to apply a parameterization like your eq 10, I would apply it rather to the measured data from Järvinen than to the purely modelled data. It is too far from the observations and maybe linked to some limitations in the model. Even if you use realistic shapes, it is still a model.
Furthermore, in Fig. 11: Why don’t we see an asymptotic behavior for the irregular hexahedra? It seems to decrease for 355 nm after reaching a maximum. This finding questions your derived plateau.
And to further add, you did the calculations up to a size parameter of 16.5 (Fig. 6). And by purely looking at Fig 6b, I would not be sure if the plateau continues to exist above x =12. Who knows what will happen for larger size parameters?I know that you are still far from lidar observations in the atmosphere. However, the spectral slope of the depolarization ratio was measured for Saharan dust (see literature, which comes close to the shape in Fig. 12) and for dust from the Taklamakan dessert by Hu et al., 2020.
5. Data availability
A statement about the data and code availability is missing although it should be included in the ACP style file. Please ensure the availability and traceability of the used data.
Minor comments
- The overall impression is that the manuscript would have benefited if the authors would have spent another month to carefully check the manuscript. There are several minor, but annoying issues which could have been eliminated, e.g., figure captions which mention different quantities than shown in the figure (e.g., Fig. 3), changing symbols for lidar ratio and depolarization ratio (Fig. 10) or color coding with the same quantity as shown on the x-axis (Fig. 8). Furthermore, a more careful literature study would have been great.
- The introduction is not really an introduction but already describes the theoretical background. I would move all equations to a separate section and keep a more clear and straight forward structure of the introduction.
- Furthermore, the first paragraph of the introduction discusses extensively the radiative forcing of mineral dust, but this is of minor importance for the presented study. Please reshape the introduction and reduce it to the parts relevant for the present study. To my opinion, the first paragraph can be reduced to 2 sentences.
- All figures missing the unit of the lidar ratio and probably some other units as well.
- The unit of the lidar ratio is sr and not sr-1 as used throughout your manuscript.
- The size parameter is defined quite late (L411) and later on defined differently (L514). Please define it earlier and keep one convention (2 pi or just pi).
- You are discussing Asian dust, but through an US American perspective (e.g., lines 51-53) omitting a long tradition of Asian dust research in Japan, but also in China and Korea, which are countries much stronger affected by Asian dust. Please add the respective literature.
- This American perspective continues when solely name MPL Net and CALIPSO omitting European and Asian lidar networks which already use much more advanced lidar systems. The new EarthCARE satellite measures not only the elastic backscatter like CALIPSO but is equipped with an HSRL channel to measure directly the extinction coefficient and so the lidar ratio. The products are described by Donovan et al., AMT 2024.
- L73-78 You’re talking about the optical properties of a single particle and at the same time introduce the bulk properties. Please keep it well separated.
- L138-141 Kemppinen et al., 2015a,b used realistic dust shapes as well for their DDA calculations. The 2 papers are cited later (L504), but should be already mentioned here.
- Fig 1: Please be sure what you want to show. 4 CALIPSO cross sections are a lot and less would be sufficient as well. The captions are not readable at all and the plots are only understandable for people familiar with CALIPSO. Which color represents dust? The dashed lines in 1a are not vertical.
- The date format is changing throughout the manuscript. MDY – Month Day Year – is not a well-defined date format, even if it is commonly used in the United States. Please choose to go from specific to general (DMY) or from general to specific (YMD).
- L365-367: Quantitatively, the same behavior for the spectral depolarization ratio and lidar ratio was measured by Haarig et al., 2022. However, the values are different.
- Eq 4,5 & 7 are not a real equation, but only a matrix. Please write them as equations.
- L393: Which dust transport region you are referring to? I would guess you are referring to Asian dust over the Pacific when you speak about dust transport region.
- L454-457: Please compare to Saito & Yang, GRL 2021 and Gasteiger et al., TellusB 2011.
- L699 ASL does not appear in the list of coauthors, probably it refers to the first author.
- L700: “ASL contributed to the methodology, data collection, interpretation and analysis and data visualization” – But who has done the data collection and analysis? If ASL just contributed to it, someone else had to do it. But who?
- It seems that the manuscript was made in word – it is recommended to use a latex environment instead. This will prevent that figure captions are given on the next page and not below the figure, and that formulas have different sizes. Furthermore, with latex the references are given in a consistent manner. In your manuscript some references are cited with the initials of the first author, e.g., L 58, but most not.
Technical corrections
- L65 gases
- L531: r_vg is not used in eq 13.
- L692: fine and coarse mode dust
- Burton et al., 2012 – the reference appears twice in your list.
References (which are not already in the paper):
Di Biagio, C.; Formenti, P.; Balkanski, Y.; Caponi, L.; Cazaunau, M.; Pangui, E.; Journet, E.; Nowak, S.; Andreae, M. O.; Kandler, K.; Saeed, T.; Piketh, S.; Seibert, D.; Williams, E. & Doussin, J.-F.: Complex refractive indices and single-scattering albedo of global dust aerosols in the shortwave spectrum and relationship to size and iron content, Atmospheric Chemistry and Physics, 2019, 19, 15503-15531
Donovan, D. P.; van Zadelhoff, G.-J. & Wang, P.: The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products, Atmospheric Measurement Techniques, 2024, 17, 5301-5340
Floutsi, A. A.; Baars, H.; Engelmann, R.; Althausen, D.; Ansmann, A.; Bohlmann, S.; Heese, B.; Hofer, J.; Kanitz, T.; Haarig, M.; Ohneiser, K.; Radenz, M.; Seifert, P.; Skupin, A.; Yin, Z.; Abdullaev, S. F.; Komppula, M.; Filioglou, M.; Giannakaki, E.; Stachlewska, I. S.; Janicka, L.; Bortoli, D.; Marinou, E.; Amiridis, V.; Gialitaki, A.; Mamouri, R.-E.; Barja, B. & Wandinger, U.: DeLiAn -- a growing collection of depolarization ratio, lidar ratio and Ångström exponent for different aerosol types and mixtures from ground-based lidar observations, Atmospheric Measurement Techniques, 2023, 16, 2353-2379.
Hofer, J.; Ansmann, A.; Althausen, D.; Engelmann, R.; Baars, H.; Fomba, K. W.; Wandinger, U.; Abdullaev, S. F. & Makhmudov, A. N.: Optical properties of Central Asian aerosol relevant for spaceborne lidar applications and aerosol typing at 355 and 532nm, Atmospheric Chemistry and Physics, 2020, 20, 9265-9280.
Hu, Q.; Wang, H.; Goloub, P.; Li, Z.; Veselovskii, I.; Podvin, T.; Li, K. & Korenskiy, M.: The characterization of Taklamakan dust properties using a multiwavelength Raman polarization lidar in Kashi, China, Atmospheric Chemistry and Physics, 2020, 20, 13817-13834
Citation: https://doi.org/10.5194/egusphere-2025-1117-RC1
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 161 | 32 | 8 | 201 | 7 | 7 |
- HTML: 161
- PDF: 32
- XML: 8
- Total: 201
- BibTeX: 7
- EndNote: 7
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1