the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note: comparison of manually and automatically evaluated profiles of a PollyXT multiwavelength polarization Raman lidar
Abstract. This technical note presents a comprehensive comparison of manually and automatically analyzed lidar profiles of aerosol optical properties retrieved from an 18-month measurement campaign with a continuously measuring, automated PollyXT multiwavelength polarization Raman lidar in Dushanbe, Tajikistan. The manual analysis was performed using a custom software (known as Verlauf) in multiple analyses steps based on visual inspection of the lidar signals. Its results serve as the reference dataset. The automatic analysis was performed using the PollyNET Processing Chain (PPC) (version 4.0). Retrieval parameters, derived layer-mean values, and seasonal mean and median profiles of aerosol optical properties (backscatter and extinction coefficients, particle depolarization and lidar ratios, and backscatter- and extinction-related Angstrom exponents) of the two datasets were compared. The absolute values of the percentage differences of the seasonal mean and median backscatter coefficient profiles at 1.5 km height are largely below 10 %, except at 532 nm in winter and at 1064 nm in spring and winter. The absolute values of the percentage differences of the seasonal mean and median extinction coefficient profiles at 1.5 km height are largely less than 5 %. The absolute values of the percentage differences of the seasonal mean and median particle depolarization ratios at 1.5 km are largely below 20 % at 355 and below 10 % at 532 nm wavelength. For the most part, these discrepancies are within the measurement uncertainties of the considered quantities despite challenges in the automatic retrieval such as reference height detection, depolarization calibration, and cloud screening. This supports the conclusion that the automatically analyzed profiles of aerosol optical properties are utilizable for common applications, such as extinction statistics, aerosol typing, and retrieval of microphysical and cloud-relevant aerosol properties. However, caution should be exercised when using the particle depolarization ratio at 355 nm and backscatter-related Angstrom exponents, which showed enhanced discrepancies. The results will assist further improvements of the PPC and the implementation of additional features (e.g., optimal estimation methods, retrievals of microphysics). Together with the growing network of PollyXT lidars, the automatic processing chain will remain under constant development with the goal of dissemination of near real-time data on product level with high quality to users and scientific databases.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 21 Sep 2026)
- RC1: 'Comment on egusphere-2026-3928', Anonymous Referee #1, 06 Sep 2026 reply
Data sets
Manually (Verlauf -software) and automatically analyzed (PollyNET Processing Chain) lidar profiles from the CADEX campaign (2015–2016) Hofer et al. https://doi.org/10.5281/zenodo.21023988
Model code and software
PollyNET: Pollynet Processing Chain Klamt et al. https://doi.org/10.5281/zenodo.13379737
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- 1
Multiwavelength Mie-Raman-polarization lidars have become widely used tools in aerosol studies, but the large volume of data obtained from such systems demands the development of automatic algorithms for data processing. This manuscript focuses on comparing lidar derived aerosol parameters, such as backscatter and extinction coefficients, particle depolarization ratios, lidar ratios, and Ångström exponents, obtained from manual data analysis versus automatic analysis. The dataset was provided by the PollyXT multiwavelength Raman lidar, which was operated in Dushanbe over an 18‑month period. The Leipzig group is one of the pioneers in the development of multiwavelength Raman lidars, so the authors are well aware of the challenges involved in processing such measurements. The manuscript is thoroughly and meticulously written. It contains a large amount of numerical data, which makes reading somewhat tedious. It is essentially a technical note, as it compares manual and automatic processing developed within the same group. Nevertheless, it provides useful scientific information on the seasonal variation of aerosol intensive parameters over Tajikistan. The manuscript is somewhat overloaded with figures and data, but this is acceptable for a technical note and may be of interest to numerous readers. I find the manuscript suitable for AMT and, in principle, it could be published in its current form.
I have only one question:
Line 175: “This means that the averaging duration of the manual analyses is usually 1 hour longer than that of the automatic analyses.” Why are the time intervals not exactly the same?