Validation study comparing manually and automatically evaluated PollyXT profiles
Leipzig,
09.10.2026
– Julian Hofer
open-source Python for a wider user base
The TROPOS-build PollyXT lidars (Engelmann et al., 2016) are becoming more frequently and numerously used for worldwide long-term observations as well as permanent deployments. This leads to a strongly increasing amount of data acquired within the network of PollyXT-type systems (PollyNET; Baars et al., 2016). Therefore, reliable, i.e., well-validated automatic analysis tools are necessary to provide products in near-real time to the PollyXT operators and community.
In Hofer et al. (2026), we present a validation study comparing manually and automatically analyzed lidar profiles of aerosol optical properties retrieved from an 18-month measurement campaign with a PollyXT lidar in Dushanbe, Tajikistan (Hofer et al., 2020a,b). 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 (version 4.0; Klamt et al., 2024).
Figure 1 shows a comparison of layer-mean values of aerosol optical properties from the manually and automatically analyzed profiles. The comparison shows a good agreement of most directly measured and derived quantities. 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 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.
The most recent and major change of the PollyNET Processing Chain is transferring the code from proprietary Matlab to open-source Python (https://github.com/PollyNET/PicassoPy, last access: 9 September 2026) to enable a broader community to participate in the development. The Python-based version is envisaged to become operational in the near future, after implementing and testing all the features of the yet operational Matlab-based version.
References:
https://polly.tropos.de/
Baars, H., et al.: An overview of the first decade of PollyNET: an emerging network of automated Raman-polarization lidars for continuous aerosol profiling, Atmos. Chem. Phys., 16, 5111–5137, https://doi.org/10.5194/acp-16-5111-2016 , 2016.
Engelmann, R., et al.: The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: the neXT generation, Atmos. Meas. Tech., 9, 1767–1784, https://doi.org/10.5194/amt-9-1767-2016 , 2016.
Hofer, J., et al.: Long-term profiling of aerosol light extinction, particle mass, cloud condensation nuclei, and ice-nucleating particle concentration over Dushanbe, Tajikistan, in Central Asia, Atmos. Chem. Phys., 20, 4695–4711, https://doi.org/10.5194/acp-20-4695-2020 , 2020a.
Hofer, J., et al.: Optical properties of Central Asian aerosol relevant for spaceborne lidar applications and aerosol typing at 355 and 532 nm, Atmos. Chem. Phys., 20, 9265–9280, https://doi.org/10.5194/acp-20-9265-2020 , 2020b.
Hofer, J., et al.: Technical note: comparison of manually and automatically evaluated profiles of a PollyXT multiwavelength polarization Raman lidar, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2026-3928 , 2026.
Klamt, A., Yin, Z., Floutsi, A. A., Griesche, H., Haarig, M., Radenz, M., Jimenez, C., Gast, B., and Baars, H.: PollyNET: Pollynet Processing Chain, Zenodo (software), https://doi.org/10.5281/zenodo.13379737 , 2024.
