the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Retrieval of Aerosol Properties from Direct Solar Irradiance Measurements with High Temporal Resolution and Spectral Range
Abstract. Several sun photometer networks worldwide include instruments for aerosol optical depth (AOD) observations, such as Global Atmospheric Atmosphere Watch-Precision Filter Radiometer (GAW-PFR) and Aerosol Robotic Network (AERONET). AERONET provides additional aerosol properties such as the detailed volume size distribution and the single scattering albedo through inversion modelling of sky radiance measurements. However, the data availability for such properties is limited due to the limited number of daily almucantar sky radiance scans and cloudiness. AOD measurements are significantly more frequent as they can be even every minute and are affected only by clouds being too close or covering the solar disk. The Generalized Retrieval of Atmosphere and Surface Properties (GRASP) is a flexible inversion model to retrieve aerosol properties from various observations. One of its capabilities is the retrieval of the volume concentration, the volume median radius and geometric standard deviation for each aerosol size distribution mode and the separation of AOD to each mode using only spectral AOD as an input parameter. Such properties are important for various applications, as the size of aerosols affects their interaction with solar radiation, clouds and radiative forcing modelling. Size also shows significant differences depending on the aerosol type such as dust or biomass burning. In this study, we selected four common stations of GAW-PFR and AERONET and used GRASP to retrieve the bimodal size distribution parameters from AOD measured by GAW-PFR instruments (PFRs). We assessed the homogeneity with the AERONET output parameters and investigated the effect of the spectral range and on such retrievals. We also assessed the performance for certain dust and biomass burning cases. Our results showed good agreement between PFR AOD-based and AERONET sky radiance inversions for AOD modal separation and volume concentrations. Significant improvement of the PFR-AERONET intercomparison was also possible for the fine mode volume and effective radius when restricting the datasets to AOD at 500 nm > 0.1 and Angström Exponent (AE) >1. Also, the results showed consistency with previous study regarding the validation of such retrievals using AERONET AOD. Focusing on conditions with high proportion of dust particles, we found consistent results with the general cases.
Using AOD with a larger spectral range (from BTS spectroradiometer), we found that the wavelength selection may affect the results and that using longer wavelengths can increase the sensitivity of coarse mode volume median radius to AOD and improve the correlation of the GRASP BTS AOD-based and AERONET datasets. However, the available data were limited, so it is not clear under what conditions the inclusion of such wavelengths will result in more accurate retrievals.
Finally, we were able to reproduce with GRASP the aerosol size characteristics of unusual biomass burning cases from the Canadian wildfires during 2023, but the results showed systematically increased fine mode radius and concentration compared to the AERONET output.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-2061', Anonymous Referee #1, 04 Aug 2025
- AC1: 'Reply on RC1', Angelos Karanikolas, 16 Oct 2025
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RC2: 'Comment on egusphere-2025-2061', Anonymous Referee #2, 08 Sep 2025
The manuscript describes the results of applying the GRASP-AOD inversion procedure to the PFR instrument, with the final aim to provide size distribution information to the GAW-PFR network. The writing is somewhat unwieldy, cluttered with parentheses, abbreviations and acronyms. More importantly, the methodology lacks rigor in certain aspects. A major revision would be needed for the paper to be suitable for publication in AMT. The following comments are intended to help in such revision.
Major comments
1. There is an overall strategy to "improve" the comparisons by removing "bad" data and fine-tuning the retrievals. Data in which the AOD differences are "too high" are removed. (line 271). Interpolated AOD from BTS is removed if R2<0.8. (line 268). The authors retain the best cases only, ignoring all the difficulties that yield to discrepancies and that such circumstance will always come together with real data. Line 301: how could differences be large if all discrepant data points were previously removed?
The same applies to the retrievals: thresholds to residuals are changed ad-hoc to "improve" results (Figure 1). And the initial guess (line 466, 541, 550, 594), the settings (line 495), the wavelength range (line 499) or the refractive index are changed to adapt to certain cases. Or the dataset is restricted to the most favorable conditions (line 366, 546).
And my quotes in "improve" are put to emphasize that this is not a real improvement, just artificial clean-up of presumed outliers.
2. The focus of the study gets lost throughout the text: the title speaks about "Direct Solar Irradiance Measurements with High Temporal Resolution and Spectral Range". The abstract speaks about GAW-PFR, which provides AOD at 4 spectral channels. High temporal resolution is true, but not high spectral range. And the rest of the manuscript includes a mix-up of PFR, BTS, AERONET-SDA, CIMEL in various aspects (only direct, radiances). Is the main focus the application of GRASP-AOD to the GAW-PFR network (line 138); or something else? For instance, the use of BTS could me focused to assess what is lost when using the PFR spectral range instead of a larger one. In this way, it would contribute to the main goal of the study. Instead, it seems to be an attempt to explore the performance of the GRASP-AOD itself, which in my view is a different analysis.
Why/in which aspect is relevant for the study the high temporal resolution indicated in the title?
By the way, the input for the GRASP-AOD retrieval is the AOD, not direct solar irradiance.
Other comments
Abstract
Line18: "they can be every minute" The verb is missing. Please rewrite.
L23: Size >> Particle size
L36: "GRASP-BTS AOD-based dataset": this is hard to understand. There are plenty of such acronyms in the manuscript. The GRASP papers (https://www.grasp-open.com/publications-2/) frequently adopt a nick for frequent applications: GRASP-AOD is one of them (Torres and Fuertes, 2021). And that's the application (settings included) that is used in this case. Therefore the name cannot be changed depending on the instrument (GRASP-BTS, GRASP-PFR, and so on). This creates much of confusion. Many other instances in the manuscript (e.g. line 297) are in the same direction.
Introduction
It is overall too long in providing aerosol generalities that are well known and could be much reduced by citing a few key references. Better come to the point, focus in introducing the elements that are needed in this particular study.
L65: correlates with aerosol COLUMN concentration
L66: size >> size predominance. This must be changed throughout the text (e.g. Line 113). Otherwise it would speak about a single size instead of a size distribution in which a specific size range dominates (in terms of mass or volume, by the way; not number).
L90-94: the AERONET inversion uses AOD and sky radiances (not only radiances, not only almucantar geometry). The version 3 inversions (Sinyuk et al) could be cited here.
L105: it may be worth mentioning here that index of refraction needs to be known or assumed.
L111: this is very well known since decades. A classic reference to some old book is more desirable here; otherwise it looks like a recent finding. Same for line 123.
Section 2
Line 184: the 1640nm channel is missing.
L188: 30 seconds >> 1 minute.
L190: the alignment is done by the 4 quadrant detector, not the collimator. The latter is used for straylight rejection in the sky scans.
L201: Sun angular size in 0.5deg and FOV is 3deg. It's unavoidable that some sky light leaks into the DSI.
L204: please provide a reference on the BTS calibration. Same about the AOD retrieval with BTS (line 209).
L213: not all those inputs are needed for GRASP to run. Please rewrite.
L214: the GRASP-AOD requires AOD plus the assumption of index of refraction.
L216: check repetition.
L221: exclusively >> separately?
L226: PFR AOD >> AOD obtained with the PFR (to improve readability).
Line 230: AOD500nm>0.03. Why? What do GRASP-AOD papers say about this minimum AOD?
Same about the criteria on Angstrom exponent and fine/coarse mode AOD. It brings me again to the main comment #1.
L250: Why 1.45-0.003 ? Some justification is needed. Otherwise it looks totally arbitrary. Same for line 288.
L258: the 1640nm channel (available in the Cimel) is not used in this list. Why?
Figure 1: I would recommend changing to Table format.
Section 3
L297: AER-SKY: not only radiances are used (as already mentioned). And the abbreviations are awful.
L300: "In this section": check repetitions.
L303: better quantify than give the valuation ("Excellent"). The goodness will depend on the intended application or the uncertainty estimates.
Table 1: table captions are preferably self-explicative, but this is not possible with all the abbreviations.
L345: the differences between using climatology or fix value are small. What about using the closest AERONET retrieval of the refractive index? This magnitude is very much related to aerosol composition and can depart significantly from the site average value.
L362: depend >> affect
L381: extrapolated >> interpolated?
L383: reference needed.
L399: please clarify why is this expected.
L466-467: you try to retrieve the SD, therefore you don't know it. What does it mean “using prior knowledge”? Moreover, the use of AERONET inversion information as initial guess to improve the result is a trick (main comment #1). The approach in line 564 is far more reasonable.
Figure 11: excellent example of data not fitting to the Angstrom law. Why is the fit to the Angstrom law used in the manuscript? Is it justified? Why not using just AOD observations? This is actually realized by the authors (line 618).
L500: not that unusual. See Eck et al (1999; 2023)
L572: is 1640nm channel considered in the Cimel? It's almost 2 times longer than the 862nm of the PFR.
L590: please re-think. It's obvious that the lesser number of data, the better fit. With 2 points a linear fit is just perfect. But there must be more information (lower uncertainty) if more data are used in the input. Moreover, using the Angstrom approximation makes you lose real AOD features (see my previous comment on that).
Table A1:
GRASP-BTS: ...and GRASP-AOD as retrieval.
AER-SKY: the input is AOD and radiance (almucantar or hybrid geometries).
Citation: https://doi.org/10.5194/egusphere-2025-2061-RC2 - AC2: 'Reply on RC2', Angelos Karanikolas, 16 Oct 2025
Data sets
Datasets of Aerosol properties retrieved from AOD time series at selected GAWPFR stations Angelos Karanikolas https://doi.org/10.5281/zenodo.13624808
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Given the data availability for such properties is limited due to the limited number of daily almucantar sky radiance scans and cloudiness, but AOD measurements are significantly more frequent, as they can be even every minute and are affected only by clouds being too close or covering the solar disk, so the authors selected four common stations of GAW-PFR and AERONET and used GRASP to retrieve the bimodal size distribution parameters from AOD measured by GAW-PFR instruments (PFRs). The authors assessed the homogeneity with the AERONET output parameters and investigated the effect of the spectral range on such retrievals, as well as assessed the performance for certain dust and biomass burning cases. The results showed good agreement between PFR AOD-based and AERONET sky radiance inversions for AOD modal separation and volume concentrations.
In summary, the paper proposes a method for inverting aerosol particle size distribution parameters based on high temporal resolution AOD data (GAW-PFR) and the GRASP algorithm, verifies its applicability under various aerosol conditions, and explores the impact of spectral range on inversion. The research design is rigorous and the data is detailed (long-term observations at 4 stations), which is of great value to the field of aerosol remote sensing. So, I recommend this paper to be published in AMT after minor revision, but I still have some questions that the authors should take into consideration as below: