References

Scientific references

These papers define the physical assumptions and retrieval methods used by the migrated lidar processing chain.

Elastic backscatter retrieval

• Klett, J. D. (1981). Stable analytical inversion solution for processing lidar returns. Applied Optics, 20(2), 211-220. doi:10.1364/AO.20.000211.
• Klett, J. D. (1985). Lidar inversion with variable backscatter/extinction ratios. Applied Optics, 24(11), 1638-1643. doi:10.1364/AO.24.001638.
• Fernald, F. G. (1984). Analysis of atmospheric lidar observations: some comments. Applied Optics, 23(5), 652-653. doi:10.1364/AO.23.000652.
• Speidel, J., and Vogelmann, H. (2023). Correct(ed) Klett-Fernald algorithm for elastic aerosol backscatter retrievals: a sensitivity analysis. Applied Optics, 62(4), 861-868. doi:10.1364/AO.465944.

Raman retrieval

• Ansmann, A., Riebesell, M., and Weitkamp, C. (1990). Measurement of atmospheric aerosol extinction profiles with a Raman lidar. Optics Letters, 15(13), 746-748. doi:10.1364/OL.15.000746.
• Ansmann, A., Wandinger, U., Riebesell, M., Weitkamp, C., and Michaelis, W. (1992). Independent measurement of extinction and backscatter profiles in cirrus clouds by using a combined Raman elastic-backscatter lidar. Applied Optics, 31(33), 7113-7131. doi:10.1364/AO.31.007113.

Iterative retrieval and calibrated signals

• Di Girolamo, P., Ambrico, P. F., Amodeo, A., Boselli, A., Pappalardo, G., and Spinelli, N. (1999). Aerosol observations by lidar in the nocturnal boundary layer. Applied Optics, 38(21), 4585-4595. doi:10.1364/AO.38.004585.
• Baars, H., Seifert, P., Engelmann, R., and Wandinger, U. (2017). Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements. Atmospheric Measurement Techniques, 10, 3175-3201. doi:10.5194/amt-10-3175-2017.
• Li, D., Wu, Y., Gross, B., and Moshary, F. (2021). Capabilities of an automatic lidar ceilometer to retrieve aerosol characteristics within the planetary boundary layer. Remote Sensing, 13(18), 3626. doi:10.3390/rs13183626.

Molecular atmosphere and Rayleigh scattering

• Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R. (1999). On Rayleigh optical depth calculations. Journal of Atmospheric and Oceanic Technology, 16, 1854-1861. doi:10.1175/1520-0426(1999)016<1854:ORODC>2.0.CO;2.

Depolarization, overlap and preprocessing

• Freudenthaler, V. (2016). About the effects of polarising optics on lidar signals and the Delta90 calibration. Atmospheric Measurement Techniques, 9, 4181-4255. doi:10.5194/amt-9-4181-2016.
• Bravo-Aranda, J. A. et al. (2016). Assessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator. Atmospheric Measurement Techniques, 9, 4935-4953. doi:10.5194/amt-9-4935-2016.
• D'Amico, G., Amodeo, A., Mattis, I., Freudenthaler, V., and Pappalardo, G. (2016). EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data. Atmospheric Measurement Techniques, 9, 491-507. doi:10.5194/amt-9-491-2016.
• Hervo, M., Poltera, Y., and Haefele, A. (2016). An empirical method to correct for temperature-dependent variations in the overlap function of CHM15k ceilometers. Atmospheric Measurement Techniques, 9, 2947-2959. doi:10.5194/amt-9-2947-2016.
• Wandinger, U., and Ansmann, A. (2002). Experimental determination of the lidar overlap profile with Raman lidar. Applied Optics, 41(3), 511-514. doi:10.1364/AO.41.000511.
• Comeron, A. et al. (2023). An explicit formulation for the retrieval of the overlap function in an elastic and Raman aerosol lidar. Atmospheric Measurement Techniques, 16, 3015-3039. doi:10.5194/amt-16-3015-2023.

Implemented modules

This section maps the public package areas to operational use. For command sequences, CI behavior and release handling, see the operational guide.

Main processing modules

• lidarpy.nc_convert.measurement: binary measurement discovery, parsing and NetCDF writing.
• lidarpy.preprocessing.lidar_preprocessing: preprocessing workflow orchestration.
• lidarpy.plot.quicklook: lidar and synthetic quicklooks.

Synthetic signals

• lidarpy.retrieval.synthetic.generator.synthetic_signals
• lidarpy.retrieval.synthetic.generator.synthetic_signals_despo
• lidarpy.retrieval.synthetic.generator.synthetic_signals_2D
• lidarpy.retrieval.synthetic.generator.synthetic_raman_signals_2D

Retrieval

• lidarpy.retrieval.klett: Klett, quasi-beta and iterative elastic retrievals.
• lidarpy.retrieval.raman: Raman extinction and backscatter retrievals.
• lidarpy.retrieval.overlap: overlap helpers.
• lidarpy.retrieval.calibration: calibration-factor helpers.

Atmosphere and utilities

• lidarpy.atmo: standard atmosphere, molecular properties and transmittance.
• lidarpy.utils: lidar-specific filename, signal and type helpers.
• lidarpy.general_utils: generic IO, smoothing, plotting and optimization helpers.

SCC and depolarization

• lidarpy.scc: SCC conversion helpers, access client, configuration resources and plotting support.
• lidarpy.depolarization: calibration and retrieval helpers for depolarization workflows.

API HTML

The narrative site is static. Full API HTML can be generated locally with pdoc when documentation dependencies are installed:

.\.venv311\Scripts\python -m pdoc lidarpy -o site\api