Articles | Volume 14, issue 12
https://doi.org/10.5194/amt-14-7851-2021
https://doi.org/10.5194/amt-14-7851-2021
Research article
 | 
16 Dec 2021
Research article |  | 16 Dec 2021

Aeolus L2A aerosol optical properties product: standard correct algorithm and Mie correct algorithm

Thomas Flament, Dimitri Trapon, Adrien Lacour, Alain Dabas, Frithjof Ehlers, and Dorit Huber

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Cited articles

Ackermann, J.: The Extinction-to-Backscatter Ratio of Tropospheric Aerosol: A Numerical Study, J. Atmos. Ocean. Tech., 15, 1043– 1050, https://doi.org/10.1175/1520-0426(1998)015<1043:TETBRO>2.0.CO;2, 1998. a
Ansmann, A., Wandinger, U., Le Rille, O., Lajas, D., and Straume, A. G.: Particle backscatter and extinction profiling with the spaceborne high-spectral-resolution Doppler lidar ALADIN: methodology and simulations, Appl. Optics, 46, 6606, https://doi.org/10.1364/AO.46.006606, 2007. a
Baars, H., Radenz, M., Floutsi, A. A., Engelmann, R., Althausen, D., Heese, B., Ansmann, A., Flament, T., Dabas, A., Trapon, D., Reitebuch, O., Bley, S., and Wandinger, U.: Californian Wildfire Smoke Over Europe: A First Example of the Aerosol Observing Capabilities of Aeolus Compared to Ground‐Based Lidar, Geophys. Res. Lett., 48, e2020GL092194, https://doi.org/10.1029/2020GL092194, 2021. a
CALIPSO: CALIPSO, available at: https://www-calipso.larc.nasa.gov/products/lidar/browse_images/show_v4_detail.php?s=production&v=V4-10&browse_date=2020-06-19&orbit_time=04-07-30&page=1&granule_name=CAL_LID_L1-Standard-V4-10.2020-06-19T04-07-30ZN.hdf, last access: 1 March 2021. a
Collis, R. and Russell, P.: Lidar measurement of particles and gases by elastic backscattering and differential absorption, chap. Lidar measurement of particles and gases by elastic backscattering and differential absorption, Springer, Berlin, Heidelberg, 71–151, https://doi.org/10.1007/3-540-07743-X_18, 1976. a, b
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Short summary
This paper presents the main algorithms of the Aeolus Level 2 aerosol optical properties product. The processing chain was developed under contract with ESA. We show that the ALADIN instrument, although primarily designed to retrieve atmospheric winds, is also able to provide valuable information about aerosol and cloud optical properties. The algorithms are detailed, and validation on simulated and real examples is shown.