the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 28 Aug 2026
The Cloud-Aerosol Transition Zone Derived from Ground-Based and Satellite Lidars
Abstract. The contribution of Aerosol-Cloud Interactions (ACI) to the Earth’s radiative budget remains a major source of uncertainty in future climate projections. Clouds continuously interact with the surrounding non-saturated environment, forming cloud-aerosol transition zones (TZs). The suspensions in these regions are not fully assessed by cloud-cloudless distinction methodologies and have a non-negligible role in the Earth’s radiative budget, making the lack of large-scale TZ observations a challenge for full comprehension of the climate system. This study assesses TZ distributions using ground-based and spaceborne lidar observations to improve understanding of TZ conditions and evaluate the respective instrument capabilities. Ground-based Automatic low-power Lidars and Ceilometers (ALC) located at Burjassot (Spain), Gruenow (Germany), Girona (Spain) and the Cloudnet network are used, along with CALIOP observations over the region between 30°–80° N and 10° W–35° E, covering Europe. Results show that cloud-to-clear transitions are gradual, depend on detection thresholds and local climatology. Coincidental ALC and CALIOP observations are presented to assess the potential complementarity between the methods. Overall, ground-based ALCs provide high temporal and vertical resolution and are particularly effective at detecting TZs at low altitudes. In contrast, CALIOP offers global coverage and is especially useful for detecting TZs at high altitudes. Both methods show good agreement for cloud classification. However, there are some differences for aerosol and TZ detections due to instrument capabilities, altitude sensitivity, and the classification techniques. Although each approach has its individual limitations, integrating spaceborne downward-looking and ground-based upward-looking lidar observations provides a more comprehensive characterization of cloud-TZ-aerosol distribution.
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Status: open (until 09 Oct 2026)
- RC1: 'Comment on egusphere-2026-3737', Anonymous Referee #1, 13 Sep 2026 reply
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RC2: 'Comment on egusphere-2026-3737', Anonymous Referee #3, 16 Sep 2026
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The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-3737/egusphere-2026-3737-RC2-supplement.pdf
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- 1
General comments
This study compares cloud–aerosol transition zones using ground-based ALC and spaceborne CALIOP observations. The selected cases cover a range of cloud and aerosol conditions and help illustrate the complementarity and limitations of the two observing systems. I find the study valuable and consider the overall approach appropriate. A few points concerning the threshold rationale, physical interpretation of the results, and internal consistency would benefit from further clarification. I recommend publication after minor revision.
Specific comments
1. Algorithm-defined TZ and its physical interpretation
Related sections: Lines 27–29, 134–140, and 387–390; Section 2.3.
The abstract acknowledges that classification methods contribute to differences between the observations, and the introduction explains the motivation for comparing the two approaches. Lines 387–390 also note that some ALC detections may correspond to an aerosol–clear-sky boundary or noise. These explanations are helpful. Please make the implications for interpreting occurrence frequencies more explicit: features classified as TZ by the two methods do not necessarily represent the same particle populations or physical processes, and the algorithm-defined categories may not correspond exactly to physically defined cloud–aerosol transition zones. A brief clarification in the methods or conclusions would be sufficient.
2. Basis and applicability of the relaxed backscatter threshold
Related sections: Lines 246–256 and 287–309; Figure 3.
Ruiz de Morales et al. (2024) explain that the relaxed threshold of Bth = 3 × 10⁻⁶ m⁻¹ sr⁻¹ was selected near the edge of the plateau in the hit-frequency curve, with values of 2 and 4 × 10⁻⁶ m⁻¹ sr⁻¹ used to assess uncertainties associated with threshold selection and calibration. Please briefly summarize this rationale in the present manuscript. The discussion of site-dependent curve shapes and the potential effects of instrumentation and water vapour is useful. Building on this discussion, please clarify the applicability of a common backscatter threshold across the different sites and instrument types, and how differences in instrument response and calibration may affect comparisons of TZ occurrence frequencies.
3. Interpretation of the filtered TZ occurrence frequencies
Related section: Lines 317–334.
Applying quality filters to reduce artifacts is reasonable, and reporting the fractions removed helps readers understand their effects. Since strict filtering may exclude some genuine TZ layers, interpreting the filtered occurrence frequency as a conservative estimate or an approximate lower bound on the true TZ occurrence frequency is plausible. However, this interpretation assumes that residual misclassification has a limited effect and that underestimation due to missed or excluded TZ layers dominates. Please briefly explain the basis and assumptions for this interpretation in lines 333–334 and qualify the wording accordingly. For example: “Under the classification and filtering criteria used here, the resulting TZ occurrence frequency may be regarded as a conservative estimate of the true occurrence frequency and may represent an approximate lower bound.” Please also avoid implying that passing the quality filters necessarily gives every retained layer an unambiguous physical interpretation as TZ.
4. Interpretation of hygroscopic growth and regional differences
Related sections: Lines 458–459, 622–637, and 649–651.
Pollution around Paris, moisture from the Mediterranean, and Saharan dust are plausible explanations for the differences between sites. Lines 649–651 also acknowledge that strong backscatter from larger dust particles may lead to their classification as TZ. Please apply this caution consistently throughout the manuscript, particularly to the reference to “enhanced hydration” in lines 458–459. Without independent constraints on humidity or particle properties, exceeding a backscatter threshold alone cannot establish hygroscopic growth or a cloud-related transformation.
5. CALIOP grid cell assigned to GIR
Related sections: Tables 1 and B1.
Table 1 places GIR at 41.962° N, 2.829° E, whereas Table B1 lists its corresponding CALIOP grid cell as 40–45° N, −5–0° E. Based on the station coordinates, the longitude interval should be 0–5° E. Please clarify whether this is only a table-label error and confirm that the correct grid cell was used for data extraction.
Technical corrections
1.Lines 235–236 and Table 2:
The CL31 pulse repetition rate is given as 10.0 kHz in the text but 8.192 kHz in Table 2. Please check and reconcile these values.
2.Lines 299–301 and Tables B1–B2:
The ALC cloud occurrence frequencies for SFH and KEN are reported as 56.1% and 72.4% in the text, but as 58.1% and 76.6%, respectively, in both tables. Please check these values and explain any differences in processing or sampling conditions, if applicable.
3.Lines 585–587:
Please explicitly identify the nighttime and daytime values for cloud and aerosol occurrence frequencies and present them in the same order as the TZ frequencies. In particular, “64.7% and 68.1% for daytime” does not clearly identify the two corresponding periods.