the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Mar 2026
Validation of ceilometer aerosol profile retrievals using sun–sky photometer and balloon-borne in situ measurements
Abstract. This study evaluates two approaches for retrieving aerosol properties from ceilometer observations, using aerosol optical depth (AOD) from AERONET and synergistic aerosol profiles obtained by combining AERONET sun–sky photometer and ceilometer measurements through the GRASPpac algorithm as reference. The two retrieval techniques considered for the ceilometer retrievals are the traditional Klett-Fernald backward inversion and a forward iterative method including an independent calibration procedure. Observations collected at three European stations (Granada, Spain; Payerne, Switzerland; and Lindenberg, Germany) during 2019–2020 are analyzed to assess the performance of both approaches under a wide range of aerosol conditions. The results show that the forward iterative method systematically outperforms the Klett-Fernald backward approach. Under high aerosol load conditions, particularly during coarse-mode-dominated events, the forward retrieval reduces AOD uncertainties by ~50 % and achieves root-mean-square errors comparable to those reported in previous validation studies. Vertical comparisons against GRASPpac profiles indicate that the forward method maintains consistent accuracy throughout the troposphere, whereas the backward approach exhibits altitude-dependent biases, especially within dust layers. Additional evaluations using COBALD balloon-borne backscatter measurements confirm that the forward retrieval reproduces observed aerosol structures within 10–30~\% deviation. These results demonstrate the significant performance gains achieved by operational ceilometer networks when applying forward retrievals with independent calibration under favorable atmospheric conditions.
- Preprint
(10453 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-990', Anonymous Referee #1, 29 Apr 2026
-
RC2: 'Comment on egusphere-2026-990', Anonymous Referee #2, 03 May 2026
Review on egusphere-2026-990
Validation of ceilometer aerosol profile retrievals using sun–sky photometer and balloon-borne in situ measurements
by
Muñiz-Rosado et al.
General comments:
Paper deals with analysis of how well the wide spread ceilometers could be used fro aerosol profile characterisaiton. Taken into account that we have quite some ceilometers as compared to lidars this study can potentially significantly increase amount of available aerosol observations. The paper is generally well structured, and has its messages clear, and within the scope of ACP. However it avoids many significant “elephants in the room”, doesn’t make it clear why these specific methodology of comparison were selected, and full of inconsistencies in little details, the ones where the “devil is usually is”. I must admit it took me much longer than I anticipated to find at least some of them, that in my opinion should be addressed before the paper could be published. Below I give several insites how the paper should be improved. My overal recommendation is acceptance after major revision.
Major comments:
Statements of superiority of one method over another are not well suported, without a proper erorror analysis, i.e. quantifyeble details of possible retrieval/estimation errors of different methods. It seems that whole study either overlooks significantly many nuances of the retrievals which make direct comparisons questionable, either specifically designed to skew for one of the methods.
Whole methodology of comparison is not very well justified, averaging thousands of profiles by splitting them into specified groups won’t give any particular incentives on what is actually happening. My strongest belief is that scatter plots and correlation coefficients as well as root mean square errors and linear should be provided to support the conclusions of the paper (at least for COBALD cases and AERONET, since only these could be taken as a real validation).
Methods compared have multiple parameters that affect their performance, section of altitudes, correction of overlap, and most importantly lidar ratio selection. This should be discussed and quantified, it is not clear if 50 goes well for all the cases, GARSPpac has this parameter estimated, a comparison would be nice way to show that selection was correct, or grouping results into cases when retrieved and assumed LRs are close or very different to see the impact on the performance.
It is not very clear if methods or their realisations are authors developments or some other product, and which inputs were used, these have to be clearly stated! All the codes and products should be stated, referenced and versioned. Ideally with repository links.
Particular details of retrievals i.e., inputs, wavelengths, reference and ground altitudes selections, calibrations, sensitivity of methods to these decisions should be clearly stated, quantified and discussed.
Authors contribution is vague and lacks detail. Only 8 authors out of 18 (!sic) mentioned in dedicated paragraph. Provide detailed description of contributions or shorten the co-authors list.
Minor comments:
Line 125: solar irradiance and sky radiance at multiple wavelengths covering the 340-1640 nm range. It is not clear which channels where used, GRASPpac should follow AERONET methodology, hence using different range, please correct or provide more details.
Line 160: “obtained from numerical models.” Can authors precise, which? Are different models used, if yes, why, and under which conditions they are selected? Estimates of beta may vary a lot depending which model was used, please provide details.
Line 198: “high SNR”, please provide exact number or range of values.
Line 200: How z_0 is defined? Please provide details. Also this area will be a subject of overlap, please discuss the impact of overlap or its correction on the method.
Line 219: “the system constant CL leads to a 10–20% error in retrieved βa within the planetary boundary layer (PBL), while a similar uncertainty in the lidar ratio Sa contributes less than 5 % error.” Are these errors systematic or random? How do they add up, if both CL and LR are +10%, or one +20% and another -10%? 20% error of LR selection can be easily achieved by mismatching aerosol type, please discuss ranges of natural aerosol variability to further support the statement. These statement doesn’t provide any understanding of methods performance and its stability. Additionally dependence on z_ref and/or z_0 selection are not discussed.
Line 229: “A reference altitude z_ref is selected in the upper troposphere, where βa(zref ) = 0 is assumed”. How this altitude is selected, is there a range, specific value or a method to define?
In general it seems that backward Klett and calibration on Rayleigh are inseparable, why they are presented in different sections? Also one used LR of 52 and other assumes 50, not a big deal but an inconsistency, it impacts the retrievals, this should be discussed or even corrected. See major comments about LR selection.
Line 271: “The use of altitude-resolved Ångström exponents allows the spectral conversion to account for vertical variability in Aerosol microphysical properties.” And assumption of constant LR doesn’t. Discuss the possible concenquences of such methodological differences in the methods.
Line272: “additional uncertainty”, can this uncertainty be estimated somehow?
Line291: “In the GRASPpac (Photometer And Ceilometer) configuration” Authors continuously refer to GRASPpac, at the same time it is completely not clear how this code/configuration can be accessed, it is not a part of GRASP open repository, which is by the way not provided in the text. It is also not clear how ceilometer differs from lidars (GRASP-wise), publishing a repo link and providing brief explanations should clarify all that.
Line 300: “is discretised into 60 logarithmic altitude layers between 250 and 7000 m.” Does forward and backward used 250 and z_0 and 700m as z_ref? Theoretically if methods are compared these have to be the same, since I presume their selection may significantly impact all the retrievals. Please discuss, for e.g. Hervo et al. (2016, cited in the manuscript) demonstrated that the CHM15k overlap function is highly temperature-dependent and often incomplete below 600–1000 m. It may introduce significant error, assuming transmittance of one in high aerosol load cases.
Line 303: “In this study, AODs processed by the CAELIS system (González et al., 2020) were combined with cloud-screened, Level 2 ceilometer profiles”, I’m confused, were radiances were used too? Also provide wl set, because sun-photometer was stated to cover 340-1640 nm range in line 125. It is not clear which channels were used.
Section 3.4 How did backscatter became extinction? Description here is a bit messy, please revise. What LRs were used, and why? I mean we can select different value and get different aod, please discuss sensitivity to that selection. Were LR estimated by AERONET in the vicinity of observation checked? How fare are they from 50? It would be great and very interesting to see such a comparison.
Lines 333-338: “High-load conditions were further categorised according to the AE as a proxy for dominant particle size. Days with AE ≥ 1.2 were classified as fine-mode dominated, typically associated with anthropogenic or biomass-burning aerosols (Reid et al., 2005), whereas days with AE ≤ 0.8 were classified as coarse-mode dominated, generally linked to mineral dust. Days with intermediate AE values (0.8 <AE <1.2) were excluded from this classification, as they represent mixed aerosol conditions without a clearly dominant particle mode.” Please provide typical LR values for these 3 groups, I have serious concerns that 50 Sr will fit them all.
Line 354: “altitudes above 5 km were not considered”, but they were included in to the GRASPpac retrieval. Please discuss how avoiding 2km of the profile may affect the comparison, notably total AOD.
Line 391: “This case represents a well-documented episode of long-range Saharan dust transport” please provide references.
Line 433: ”lidar signal and can typically be retrieved with good accuracy under standard conditions ”. Define “good accuracy” and “standard conditions”. The whole paragraph is not fully correct, elastic lidar signal depends both on backscatter and extinction, theres’ no way to separate them, assume another lidar ratio and backscatter retrieval will change too, this should be properly discussed.
Line 435: “outliers, only data within the 10th–90th percentile range were retained.” What data was retained, profile as a whole or specific altitudes? Please specify. Absolutely not clear what percentiles authors are talking about, were there multiple retrievals/profiles?
Section 4.2: please, provide at least brief description of datasets, i.e. date ranges, number of profiles and how these were selected.
Section 4.2.1: how the error margin was estimated? Is it variation, is it error propagation? Please, provide explanations.
Line 454: “relative dispersion below 35 %”, why relative dispersion is provided/discussed only for this case, please provide them for all other cases too.
Line 489: “site-specific microphysical differences.” Please discuss these conditions, it is not clear for reader why stations are analysed separately. Provide some explanations why they have particularly different aerosol conditions, and why these sites where chosen out of many.
Line 543: “Comparison against GRASPpac reveals smaller dispersion for backscatter than extinction coefficients (Tables 2 and 3).” Is it about relative or absolute dispersions?
In general if theres so much discussion about LR, why not to compare them too, GRASP pac should provide some. Ideally use the LR from GRASP pac for both forward and backward methods.
Section 4.2: in general why cases are split into such specific groups: all, high load, and high fine/coarse. It is evident that klett will struggle in these cases, provide same stats for low loads of fine/coarse too.
Line 607: “covering a wide range of aerosol types, loading conditions, and meteorological regimes.” None of these were discussed.
Line 630: “At the column-integrated level, forward-derived AOD values show good agreement with AERONET observations at all sites, with mean biases close to zero and standard deviations comparable to the intrinsic uncertainty of AERONET AOD.” Would it be still the case if LR assumption will be different? I seriously doubt.
Please provide scatter plots and correlation coefficients for all the comparisons mean and std values may not represent the actual variabilities within the datasets.
Technical comments:
Figure 1 and 3. The quick look do not cover the situation around COBALD flights, consider providing them wider and marking the time periods of accumulated observations and COBALD acend times.
Figure 2 and 4. Please, Include times into the figure captions. Also it seems that profiles are in different altitude ranges, if so this should be indicated in the text, also it is not clear if the froward/backward were done for the range that is plotted in the figure, or only where all observations altitudes overlap, at least left part could be plotted for whole range for each observation, if available.
Line 4: "...synergistic aerosol profiles obtained by combining the AERONET sun–sky photometer..."
Line 64: Missing hyphen: "single-wavelength ceilometers".
Line 370: "methods show".
Line 375: "show the deviations" (Subject "Fig. 2c and d" is plural).
Line 459-460: "The big deviations... reflect"
Line 460: "inability to find an aerosol-free region".
Line 544: "attributed to".
Lines 645 and 650: Missing periods at the end of the Data Availability and Competing interests statements.
Citation: https://doi.org/10.5194/egusphere-2026-990-RC2
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 258 | 157 | 19 | 434 | 17 | 34 |
- HTML: 258
- PDF: 157
- XML: 19
- Total: 434
- BibTeX: 17
- EndNote: 34
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
This manuscript presents an evaluation of two ceilometer-based aerosol retrieval approaches, i.e. the Klett–Fernald backward inversion and a forward iterative method, using a combination of AERONET, GRASPpac, and COBALD balloon-borne observations. The study addresses an important topic in atmospheric remote sensing, particularly in the context of operational ceilometer networks, and provides a valuable multi-instrument validation across three European sites.
The work is generally well structured and demonstrates that the forward iterative method improves retrieval performance, especially under high aerosol load and coarse-mode conditions. The inclusion of independent in situ measurements (COBALD) is a notable strength and enhances the credibility of the validation.
However, some methodological limitations and missing analyses currently weaken the robustness of the conclusions. In particular, the manuscript lacks a rigorous uncertainty assessment, relies on strong assumptions (e.g., fixed lidar ratio), and occasionally overstates its findings. For these reasons, I recommend major revision before the manuscript can be considered for publication in ACP.
Major Comments
Uncertainty Quantification
A major shortcoming is the absence of a quantitative uncertainty analysis. Key sources of uncertainty, such as the assumed lidar ratio, calibration constant (CL), and spectral conversion using Ångström exponent, are only discussed qualitatively.
The forward method’s performance is strongly dependent on calibration stability, yet no uncertainty propagation is provided. Similarly, the spectral harmonization between 1064 nm and 940 nm introduces additional uncertainty that is not quantified.
I suggest to Include a sensitivity or uncertainty analysis (e.g., varying lidar ratio, calibration constant, and Ångström exponent) and assess their impact on retrieval accuracy.
Assumption of Constant Lidar Ratio
The use of a fixed lidar ratio (50–52 sr) throughout the analysis is a critical limitation. Aerosol lidar ratio varies significantly with aerosol type, and this assumption directly affects extinction profiles and derived AOD.
Provide justification for the chosen value and evaluate the sensitivity of results to realistic lidar ratio variability. This is particularly important given the study’s focus on different aerosol regimes.
Use of GRASPpac as Reference
GRASPpac retrievals are treated as a reference dataset, yet they are themselves inversion products with inherent assumptions (e.g., vertically homogeneous aerosol properties). This limitation is not sufficiently discussed.
Clarify the role of GRASPpac as a comparative dataset rather than a ground truth and discuss its uncertainties.
Statistical Analysis
The statistical evaluation is limited to mean and standard deviation. No confidence intervals, significance testing, or correlation analyses are presented. Given the variability in the results (e.g., Tables 2–3), stronger statistical support is required.
Include additional statistical metrics (e.g., confidence intervals, correlation coefficients) and assess the significance of differences between methods.
Selection Bias in Aerosol Classification
The exclusion of cases with intermediate Ångström exponent (0.8 < AE < 1.2) removes mixed aerosol conditions, which are common in real atmospheric scenarios. This may bias the conclusions.
Justify this choice or include mixed cases and assess their impact on the results.
Overinterpretation of Results
The manuscript occasionally uses strong statements such as “systematically outperforms,” despite limited sample sizes in some cases (e.g., coarse-mode events at Lindenberg). These claims should be moderated.
Minor Comments
The Introduction is somewhat lengthy and could be streamlined to better emphasize the research gap and novelty.
Some methodological choices (e.g., convergence criteria, 30-minute averaging window, cloud filtering threshold) require clearer justification.
Figures 5 and 6 are informative but overly dense; readability could be improved by splitting panels or simplifying presentation.
Terms such as “favorable atmospheric conditions” should be explicitly defined.