Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm

Sinyuk, Alexander; Holben, Bent; Eck, Thomas; Giles, David; Slutsker, Ilya; Dubovik, Oleg; Schafer, Joel; Smirnov, Alexander; Sorokin, Mikhail

doi:https://doi.org/10.5194/amt-2022-60

Preprints

https://doi.org/10.5194/amt-2022-60

Preprints

15 Mar 2022

Status: this preprint is currently under review for the journal AMT.

Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm

Alexander Sinyuk^1,2, Bent Holben², Thomas Eck^3,2, David Giles^1,2, Ilya Slutsker^1,2, Oleg Dubovik⁴, Joel Schafer^1,2, Alexander Smirnov^1,2, and Mikhail Sorokin^1,2 Alexander Sinyuk et al.

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¹Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706, USA
²NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA
³University of Maryland Baltimore County (UMBC), Baltimore, MD 21250, USA
⁴Univ. Lille, CNRS, UMR 8518 – LOA – Laboratoire d’Optique Atmospherique, Lille, France

Received: 18 Feb 2022 – Discussion started: 15 Mar 2022

Abstract. In the Aerosol Robotic Network (AERONET) aerosol retrieval algorithm, smoothness constraints on the imaginary part of the refractive index (IPRI) provide control of retrieved spectral dependence of aerosol absorption by preventing the inversion code from fitting the noise in optical measurements and thus avoiding unrealistic oscillations of retrievals with wavelength. The history of implementation of the IPRI smoothness constraints in the AERONET aerosol retrieval algorithm is discussed. It is shown that the latest version of the IPRI smoothness constraints, termed standard (STD) and employed by Version 3 (V3) of aerosol retrieval algorithm, should be modified to account for strong variability of light absorption by brown carbon (BrC) containing aerosols in UV through mid-visible parts of the solar spectrum. In V3 strong spectral constraints were imposed at high values of the Angstrom Exponent (AE; 440–870 nm) since black carbon (BC) was assumed to be the primary absorber, while the constraints became increasingly relaxed as AE deceased to allow for wavelength dependence of absorption for dust aerosols. The new version of the IPRI smoothness constraints assigns different weights to different pairs of wavelengths which are the same for all values of the Angstrom Exponent. For example, in the case of four wavelength input, the weights assigned to short wavelength pairs (440–675, 675–870 nm) are small (10^-6) so that smoothness constraints do not suppress natural spectral variability of the IPRI. At longer wavelengths (870–1020 nm), however, the weight is ten times higher to provide additional constraints on the IPRI retrievals of aerosols with high AE due to low sensitivity to aerosol absorption for longer channels at relatively low aerosol optical depths for these fine mode dominated aerosols. The effect of applying the new version of the IPRI smoothness constraints, termed relaxed (REL), on retrievals of single scattering albedo (SSA) is analysed for case studies of different aerosol types: BC and BrC containing fine mode aerosols, mineral dust coarse mode aerosols and urban industrial fine mode aerosol. It is shown that for BrC containing aerosols employing the REL smoothness constraints resulted in significant reduction, compared to STD, in retrieved SSA and spectral residual errors at the short wavelengths. For example, biomass burning smoke cases show a reduction in SSA and spectral residual at 380 nm is ~0.033 and ~17 % respectively for the Rexburg site and ~0.04 and ~ 12.7 % for the Rimrock site, both AERONET sites in Idaho, USA. For a site with very high levels of BC containing aerosols (Mongu , Zambia) the effect of modification in the IPRI smoothness constraints is minor. For mineral dust aerosols at small AE values (Mezaira site, UAE) the spectral constraint on IPRI was already relaxed in V3 therefore the new REL constraint results in minimal change. In the case of weakly absorbing urban industrial aerosols at the GSFC site, there are significant changes in retrieved SSA using the REL assumption, especially reductions at longer wavelengths: ~ 0.016 and ~0.02 at 875 and 1020 nm respectively for 440 nm AOD ~0.3. Comparison of aerosol parameters retrieved by inversion using STD and REL assumptions is presented. Analysis is done for retrievals utilizing the four standard AERONET wavelengths obtained at four AERONET sites: Rexburg, Mongu, Mezaira, and GSFC. The largest difference is found for the IPRI retrievals for BrC containing biomass burning (Rexburg) and urban industrial (GSFC) aerosols in which cases employing the STD assumption in the AERONET inversion was over constraining the spectral dependence of the IPRI. The modification of smoothness constraints on the IPRI has a minor effect on retrievals of other aerosol parameters such as the real part of refractive index and parameters of the aerosol size distribution. Both SSA retrieved using STD and REL assumptions were compared to SSA derived from in situ measurements collected during the DRAGON-MD field campaign in 2011. The DISCOVER-AQ column-integrated in situ aircraft SSA data for 550 nm were compared to AERONET retrievals at 440 nm and 675 nm which were interpolated to 500 nm and showed a closer agreement between in situ SSA and SSA retrieved from inversions employing the REL assumption than between in situ SSA and SSA retrieved using STD constraints. The implementation of the relaxed smoothness constraints on the imaginary part of the refractive in the next version of the AERONET inversion algorithm will produce significant impacts at some sites with changes up to ±0.033 and ±0.017 in short wavelength channels (380 nm and 440 nm) for some biomass burning smoke cases with significant BrC content and possibly up to ±0.015 in mid-visible channels (500 nm and 675 nm) to near IR channels (870 nm to 1020 nm) for some urban industrial aerosol types while still mostly within the uncertainty of the AERONET SSA retrievals, depending on AOD level, Angstrom Exponent and wavelength. For mineral dust aerosols the impact will be insignificant, while for biomass burning aerosol dominated by BC the changes will be relatively small.

Alexander Sinyuk et al.

Status: final response (author comments only)

RC1: 'Comment on amt-2022-60', Anonymous Referee #1, 12 Apr 2022

The paper discuss an improvement of aerosol parameters retrieval algorithm from AERONET network measurements of sun and sky radiances. The authors have focused on an optimal choice of smoothness constraints on imaginary part of the refractive index. In the previous version of the retrieval algorithm, the strength of the smoothness constraints correlated with the value of the retrieved Angstrom exponent.   The authors argue that the smoothness constraints which strength depends not from the Angstrom exponent but from wavelength allow better retrieve the imaginary part of the refractive index, namely, it’s wavelength variation. Aerosol single scattering albedos has been retrieved from measurements of many observational stations, using ‘old’ and ‘new’ smoothness constraints. The authors argue that the ‘new’ approach allows better retrieve aerosol single scattering albedo wavelength dependence, especially in the presence of brown carbon, which has strong short-wave absorption.

The following improvements are suggested.

The abstract is too long and difficult to understand.

The paper is overloaded with abbreviations. Many readers who are interested in details of AERONET retrieval algorithm will want just quickly browse the paper. In this case, the text is often too difficult to understand due to abbreviations that are not very common.

Row 77. “Absorption at 380 nm is particularly important as this is the wavelength range that satellite observations and algorithms are able to retrieve atmospheric column absorption from existing (Jethva et al, 2014) and future satellite sensors (Werdell at al., 2019)” . This statement should be clarified. Is it due to low aerosol optical depths at longer wavelengths?

Equation (3) is discussed too briefly, it is better to say a few words about what each term in it represents, rather than just defining the variables.

There are two γ variables in the equation (3), Lagrange multiplier γ_n(row 149) and Lagrange multiplier γ_k (row 146). Later in the text the authors discuss the Lagrange multiplier γ₃ (row 164). It is necessary to write explicitly which one Lagrange multiplier is considered.

The authors discuss AERONET measurements from many observational places scattered throughout the world. A table with geographical coordinates of these places would be very helpful. Please check if the name Mesaira is spelled correctly (Mesairaa?).

The authors analyze the improvement achieved with use of the ‘new’ smoothness constraints by comparing the wavelength dependence of the retrieved aerosol single scattering albedo (SSA) using the ‘old’ and ‘new’ version of the constraints. They consider the dependence of SSA on wavelength for different aerosol optical depth (AOD) bins. Fig. 1 shows SSA wavelength dependences for Rexburg and Rimrock observational places. Later, wavelength dependences of SSA are presented for AOD bins only for Rimrock (4), but not for Rexburg. Tables 1-3 present further analysis only for Rexburg, but not for Rimrock. The analysis should be done in uniform manner.

Fig. 1 shows that application of the ‘new’ version of the smoothness constraints lead to smaller SSA values retrieved at short wavelengths. The authors argue that this is due to the presence of brown carbon aerosols, which have such a dependence on the wavelength. However, the retrieved absolute values of the SSA are quite high, 0.93-0.98. Are such high values typical for brown carbons? If yes then this should be said explicitly.

It is not clear how many observations are used to produce figures 1-11.

Presence of error bars on the plots would simplify its understanding.

Tables 1-3 show absolute differences between aerosol parameters retrieved using ‘old’ and ‘new’ constraints. I suggest including relative differences also because in many cases the absolute differences are too small and seeing so many zeros in the tables is not very informative.

The analysis presented in Tables 1-3 was done for wavelengths 440,675,870,1020 nm. Why is the 380 nm wavelength excluded from the analysis?

Citation: https://doi.org/10.5194/amt-2022-60-RC1
RC2: 'Comment on amt-2022-60', Anonymous Referee #3, 11 May 2022

General comments:

- This manuscript shows how much the quality of AERONET retrieval algorithm is enhanced with the usage of new relaxed smoothness constraints (REL). Anaysis looks reasonable in general. The history of treated topic and moviation of this study is well suggested in the introduction part. Theory chapter includes the explanations in detail, which looks helpful to the readers and researchers for the aerosol optical properties. So I think the publication of this manuscript will be very useful to the research community of aerosol optical properties. For the final publication, however, it seems that some revisions are needed related to the questions and comments provided as below.

Questions:

- What is the dominant aerosol component in Rexburg, Mongu, Mezaira, and GSFC, and how is it justified? Any supporting information to describe the air condition (particularly the aerosol composition) for selected cases. For example, readers do not know if BrC is really dominant for the cases treated in Fig. 1.

- Can we generalize the finding and lessons in this study based on this four sites only?

- Why this new REL only make some change for the BrC-dominated biomass burning (BB) aerosols, not the mineral dust and BC-dominated BB aerosols, which are other radiative absorbing aerosols?

- This new REL can help the retrieval of qualified SSA data in 340 nm channel?

- This new REL enable us to have SSA data more under the low AOD case; Usually the SSA analysis relates to the polluted case, at least AOD > 0.4 due to the uncertainty issue. It is curious to see if this REL can lower the uncertainty of SSA retrieval in less-polluted case. In other words, application of new REL is only helpful for the retrieval in the polluted condition (often related to the high AE because of the general contribution of find mode particle to the large air pollution), or it is also useful to improve the retrieval in the lower AOD case of polluted (urban) area where the brown carbon is dominant.

Minor and specific comments:

- Nowadays, there are so many AERONET stations and really long-term measurement data have been accumulated. In this situation, it is curious if we really can apply the analysis result only based on a several cases to the general situation (only some days were selected for the analysis even in only 'four' sites). The analysis in this study looks qualified with reliable cases showing clear dominance of a target aerosol composition, which can be a representative example for the meaningful discussion for new REL impact under the certain situation. But still, it seem the limited discussion because now we have so abundant information of AERONET measurement for several hundreds of local stations. Thus, the statistical analysis using the large number of dataset will be more expected for the generalization of findings in this work. In my opinion, this manuscript can be a good paper as a case study to show the 'possibility' for the usage of new REL for better expression of BrC optical properties. But it may be better to prepare another manuscript for the 'generalization of finding in this study'. In the second manuscript, the statistical analysis looks much required.

- Abstract seems too long, so the key point of this study is not well transferred to readers. The word number in this abstract is > 800, which looks too much compared to the general criteria (~ 200 to 300 words. I do not know the limitation of word number in ACP/AMT).

- Some sentences are too long so it is not easy to read. It will be better to have shorter length of sentence, or to use punctuation marks properly (e.g., commas for splitting the phrases).

- Line 46-50: Two sentences are not connected well (First one mentioned DRAGON campaign, but second on mentioned the DISCOVER-AQ campaign. How to connect the story here?)

- Line 56-57: How to understand this sentence? (what is the relationship between the insigficant impact for the mineral dust and relatively small impact for the BC-dominated biomass burning aerosol?)

- Line 104-106: The reference or clues are required to raise this issue about the BrC. Now there is no surporting information associated with this statement, which looks very essential for the motivation of this study.

- Line 214: => For example,

- Line 242: BrC carbon => BrC

- Line 252-255: I am not sure if this kind of discussion is possible without any fire or humidity information in this case.

- Line 270-307: I am not sure the existence of BrC in GSFC, but It may be also possible to see high amount of BrC in the urban region in the urban region, and the BrC pattern (e.g., hygroscopic growth related to the extent of aging) can be regionally different: (e.g., Zhang et al., GRL, 2011, https://doi.org/10.1029/2011GL049385). It will be useful to see if there is difference of the BrC optical pattern between the biomass burning and urban area in the further study.

- Line 360-363: This manuscript does not have the chapter of 'data description' or 'methodology'. So there is no information of SSA from in-situ measurement in DRAGON-MD campaign. A short phrase to mention Schafer et al. (2014) may not be enough because the SSA estimation using in-situ measurement itself can make the large difference from the optically measured SSA (e.g, surface representative vs. column information). so at least several statements about the data/methodology of in-situ SSA calculation looks needed.

Citation: https://doi.org/10.5194/amt-2022-60-RC2

Alexander Sinyuk et al.

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Short summary

Manuscript describes modification of smoothness constraints on imaginary part of refractive index employed in AERONET aerosol retrieval algorithm. This modification is termed relaxed due to the weaker strength of this new smoothness constraint. Applying the modified version of smoothness constraint results in significant reduction of retrieved light absorption by brown carbon containing aerosols.


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