the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Jul 2026
LACRIT: an automated lidar framework for detecting cirrus and contrails and retrieving their radiative properties
Abstract. The accurate retrieval of radiative properties for cirrus and contrail-induced clouds remains a significant challenge, particularly in the optically thin and subvisible regimes where molecular scattering dominates and signal-to-noise constraints are critical. We present a layer-based retrieval framework for Cloud Optical Depth (COD) and Lidar Ratio (LR) utilizing complementary ground-based observations from a co-located elastic–depolarization lidar, microwave radiometer, and all-sky camera deployed in Toulouse, France. Here, COD is retrieved using a transmittance method grounded in robust log-median statistics applied to molecular reference windows. Subsequently, a modified version of the particular-integration formulation is employed to retrieve LR, ensuring consistent altitude indexing between normalized signal ratios and the physical molecular profile. The close agreement observed between transmittance-based and particular-integration CODs, with relative differences lower than 4 %, underscores the internal consistency and numerical stability of the retrieval method across a broad range of optical depths, including subvisible cloud systems with COD lower than 0.05.
When applied to representative cirrus and contrail cases, the framework reveals significant variability in retrieved LR for similar COD, highlighting the sensitivity of LR to factors such as cloud altitude which is linked with thermodynamic conditions and microphysical state of the cloud ice crystals. Nearly-fresh contrails display lower LR and depolarization around 23 % which is consistent with expected ice-particle evolution. This proposed framework offers a solid foundation for long-term monitoring of cirrus and contrail radiative properties, as well as for evaluating model parameterizations of aviation-induced cloudiness.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-3056', Anonymous Referee #1, 14 Jul 2026
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RC2: 'Comment on egusphere-2026-3056', Anonymous Referee #2, 10 Aug 2026
Summary
The authors present a new method called LACRIT for the retrieval of the cloud optical depth, lidar ratio, and volume linear depolarization ratio of cirrus clouds formed by contrails. LACRIT appears to be a synergistic retrieval using a micro-pulse lidar, an all-sky camera, and a microwave radiometer. The all-sky camera and the microwave radiometer play secondary roles. The former is used to visually verify the presence of the cirrus clouds and track their movement and the later is used as an alternative for the meteorological parameters used for the molecular profile when ERA5 reanalysis data are not available. Two cases are presenting showing an application of the LACRIT method and the results are discussed and compared with the literature.
I have focused my review on the LACRIT method as my expertise is not in cloud microphysics. I would recommend the paper for publication after dealing with some serious issues regarding the optimal estimation techniques deployed for the LACRIT retrieval and after revision section 3.
General comments:
1) The transmission method and the lidar ratio retrieval method of Cadet et al. are well established retrieval techniques for cloud properties. A big part of the novelty of this paper is the optimized retrieval of LACRIT. In its current state, the paper is lacking a proper validation of the new technique. The authors can consider applying the technique on synthetic data and compare their retrievals with the Cadet method to convince that LACRIT is indeed better or at least equally good. Moreover, the retrieval technique and the uncertainty calculation are not adequately described in section 3.1 (more specific comments below).
2) A certain amount of aerosol is always to be expected in the stratosphere. When the SNR is low they can be hidden in the noise. They can introduce a negative systematic bias to the transmission method which depends on their scattering ratio. How do the authors assess the systematic uncertainty introduced by stratospheric aerosol?
Specific comments:
Line 5-8: This part of the abstract includes technical terms which might be used by some few experts on the field but it is not intuitive for general active remote sensing readers. Please consider improving the part by using less technical, more commonly recognizable terminology to make it clearer to a bigger audience.
Line 90-91: Please mention here the distance of full overlap for each telescope. Does the receiver after each telescope include the same kind of channels (e.g. both 532 p and s and 808)? I would generally recommend to add a table with the information relevant to this study in the lidar section.
Line 107-108: Is the laser pointing at 5° off-zenith to avoid specular reflection? Please include this information in the lidar description section. If not, how do you deal with specular reflections from cirrus clouds?
Line 131-132: It is not clear what “absolute quantities” refers to here. Can you provide some examples? (e.g. COD?)
Line 128-133: Where does the normalisation take place? Can it be applied on both aerosol and molecular regions or on molecular regions only? Please specify. Identifying molecular regions in a lidar signal is not a trivial process. The technique use to identify molecular regions must be explained here. To what extend does the presence of aerosols (even in small, close to noise quantities) in the normalisation region affects your cloud retrievals?
Line 134-139: This part is not clear. The authors have to either cite parts of the technique which have been already published or, if not published yet, they should describe the layering technique in more detail. Please avoid using terms which are too ambiguous such as “residual hysteresis detection” and “adaptive thresholding” unless you describe them first. In addition, consider linking this part to the corresponding subsection if a more detailed description is provided there.
Section 3: Many different terms such as molecular baseline, molecular backscatter, molecular reference are used to describe probably the same thing: the molecular attenuated backscatter profile. Please avoid using multiple terms which introduce ambiguity, especially not clear ones such as molecular baseline, and stick to a single term and maybe an abbreviation for it for the whole manuscript. For example in line 148, does β_Ray correspond to the molecular attenuated backscatter profile or to the molecular backscatter coefficient profile? These are two different things.
Line 143-147: The transmission method is very sensitive to the molecular attenuated backscatter values before and after the cloud. How much do you expect model errors in the temperature and pressure profiles to affect your retrievals? The US standard atmosphere model can be quite inaccurate. Have you compared with radiosonde data to access the introduced systematic errors? Please also mention shortly which products do you use from the microwave radiometer and how do you apply them to calculate β_Ray.
Lines 148-149: Please mention that RCS and VLDR are provided by the lidar and also mention the wavelength (532 nm).
Lines 164-168: How do you identify the cloud core region? How big is the window?
Lines 169-171: Automatic identification of aerosol-free regions is not a trivial process. Please either cite or described the applied technique.
Lines 177-178: The molecular attenuated backscatter profile without attenuation only from molecules can be already calculated from the temperature and pressure profile and the molecular backscatter and extinction cross-sections. Please explain how SNIP is applied and what does it additionally offer.
Line 188: Median of what? Do you refer to the residuals? In which region are the residuals calculated?
Lines 191-202: Information regarding how the low and high thresholds are defined is missing here. Are the thresholds applied to the residuals? This is also not clear. This part has to be written better.
Line 205 and Eq 5: The term robust log-median statistics is not self explanatory. Please describe why the applied method is better than e.g. just calculating the two-way transmittance by averaging S inside the two windows W_t and W_b and then divide them.
Lines 213-217: It is not clear neither what the physical meaning of the offset addition is nor how transmittance is recomputed using the so called lifted signal. The transmission method is rather straightforward, it relies on finding a pure molecular region before and after the cloud. If there is aerosol contamination in one of those regions then the result will be biased. It is not possible to “tune” the result without having a priori information about the amount of aerosol contamination. At best, one can assume a conservative amount aerosols based on the RCS and its noise and use it for the error simulation. How do you control how much to “lift” the signal and when does the lifting stop?
Lines 237-246 and Eq 9: How long are the temporal intervals when you apply temporal regularization? Is it minutes, seconds, or hours?
Lines 247-252: This part is not sufficient to explain a rather complicated uncertainty schema. It is not clear to me how the uncertainty is currently assessed. It is rather important to quantify well the uncertainty of the technique because many optimization methods are applied and classical propagation of uncertainty (Monte Carlo or analytical) is no longer possible.
Lines 268-269: How can you exclude that the low variability of the lidar ratio is not due to the a-priori regularization? How much is the applied a-priori lidar ratio? Fig 4 does not show any information about the lidar ratio, were you referring to the table 1 in the text?
Technical comments:
Line 107-108: Please correct the typo “were serve”
Figure 4: I don’t see the red dashed line (baseline), is it overlapped? It is not clear why the cyan line (polynomial fit) is there and what does it show.
Line 258: What does “post-processed” here mean? Is additional processing other than LACRIT applied?
Figure 6: Which of the two cases does this figure correspond to?
Figures 5 and 7: Please mark layer 1 and layer 2 on the plots.
Citation: https://doi.org/10.5194/egusphere-2026-3056-RC2
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Please find my peer review as attached supplement