An operational processing chain for polarisation lidar ceilometers: from raw signals to aerosol properties, typing and layer detection

This record contains the technical note of an end-to-end processing chain for polarisation lidar ceilometers, developed and operated at ARPA Valle d'Aosta (Italy) on the Vaisala CL61 of the Aosta–Saint-Christophe station. The chain converts the raw signals of a single CL61 into quantitative, quality-controlled products for operational air-quality and environmental monitoring, using only the instrument files. Methodology (described in the technical note): (i) signal correction and Rayleigh calibration with quality controls; (ii) aerosol retrieval by an iterative forward Klett inversion with a vertically variable lidar ratio and functional relationships that depend on the particle backscatter and, optionally, on the depolarisation ratio, yielding particle backscatter, extinction, particle depolarisation ratio, volume and mass concentration and AOD; (iii) harmonisation with 1064-nm ceilometers through a depolarisation-dependent backscatter Ångström exponent; (iv) a six-class aerosol/cloud type mask (no signal, cloud, clean, fine, mixed, coarse) and the detection of the atmospheric boundary layer and of elevated aerosol layers by continuous wavelet transform combined with dynamic-programming (Viterbi) tracking, with the type and the mass budget of each layer. Every step is validated against independent observations (synthetic signals, a co-located CHM15k ceilometer, AERONET sun photometer, in situ PM). Examples of application: attribution of PM exceedances to wildfire smoke and desert dust, entrainment of residual-layer aerosol into the mixing layer, regional aerosol gradients along an Alpine valley. Content and licence: this version contains the technical note (PDF); the software described in the note is archived in version 1 of this record and is reserved for the group of developers who contributed to the chain. Both are released under the Creative Commons Attribution 4.0 International licence (CC BY 4.0): their use requires the citation of this version (DOI 10.5281/zenodo.23403517). Users are also asked to cite Goi et al. (in preparation) and Dionisi et al. (2018) for the functional relationships and Bellini et al. (2024, Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt-17-6119-2024) for the ALICENET procedures.