Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4335-2021
https://doi.org/10.5194/amt-14-4335-2021
Research article
 | 
11 Jun 2021
Research article |  | 11 Jun 2021

Deriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithms

Thomas Rieutord, Sylvain Aubert, and Tiago Machado

Related authors

Systematic evaluation of the predictability of different Mediterranean cyclone categories
Benjamin Doiteau, Florian Pantillon, Matthieu Plu, Laurent Descamps, and Thomas Rieutord
Weather Clim. Dynam., 5, 1409–1427, https://doi.org/10.5194/wcd-5-1409-2024,https://doi.org/10.5194/wcd-5-1409-2024, 2024
Short summary
A new downscaling method for sub-grid turbulence modeling
Lucie Rottner, Christophe Baehr, Fleur Couvreux, Guylaine Canut, and Thomas Rieutord
Atmos. Chem. Phys., 17, 6531–6546, https://doi.org/10.5194/acp-17-6531-2017,https://doi.org/10.5194/acp-17-6531-2017, 2017
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
ALICENET – an Italian network of automated lidar ceilometers for four-dimensional aerosol monitoring: infrastructure, data processing, and applications
Annachiara Bellini, Henri Diémoz, Luca Di Liberto, Gian Paolo Gobbi, Alessandro Bracci, Ferdinando Pasqualini, and Francesca Barnaba
Atmos. Meas. Tech., 17, 6119–6144, https://doi.org/10.5194/amt-17-6119-2024,https://doi.org/10.5194/amt-17-6119-2024, 2024
Short summary
Post-process correction improves the accuracy of satellite PM2.5 retrievals
Andrea Porcheddu, Ville Kolehmainen, Timo Lähivaara, and Antti Lipponen
Atmos. Meas. Tech., 17, 5747–5764, https://doi.org/10.5194/amt-17-5747-2024,https://doi.org/10.5194/amt-17-5747-2024, 2024
Short summary
Increasing aerosol optical depth spatial and temporal availability by merging datasets from geostationary and sun-synchronous satellites
Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, Zhaohui Zhang, Virginia Sawyer, Jennifer Wei, Sally Zhao, Min Oo, V. Praju Kiliyanpilakkil, and Xiaohua Pan
Atmos. Meas. Tech., 17, 5455–5476, https://doi.org/10.5194/amt-17-5455-2024,https://doi.org/10.5194/amt-17-5455-2024, 2024
Short summary
Multi-angle aerosol optical depth retrieval method based on improved surface reflectance
Lijuan Chen, Ren Wang, Ying Fei, Peng Fang, Yong Zha, and Haishan Chen
Atmos. Meas. Tech., 17, 4411–4424, https://doi.org/10.5194/amt-17-4411-2024,https://doi.org/10.5194/amt-17-4411-2024, 2024
Short summary
Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site
Anton Lopatin, Oleg Dubovik, Georgiy Stenchikov, Ellsworth J. Welton, Illia Shevchenko, David Fuertes, Marcos Herreras-Giralda, Tatsiana Lapyonok, and Alexander Smirnov
Atmos. Meas. Tech., 17, 4445–4470, https://doi.org/10.5194/amt-17-4445-2024,https://doi.org/10.5194/amt-17-4445-2024, 2024
Short summary

Cited articles

Arciszewska, C. and McClatchey, J.: The importance of meteorological data for modelling air pollution using ADMS-Urban, Meteorol. Appl., 8, 345–350, 2001. a
Arthur, D. and Vassilvitskii, S.: k-means++: The advantages of careful seeding, in: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Society for Industrial and Applied Mathematics, 1027–1035, 2007. a
Besse, P., Guillouet, B., and Laurent, B.: Wikistat 2.0: Educational Resources for Artificial Intelligence, arXiv: preprint, arXiv:1810.02688, 2018. a
Breiman, L., Friedman, J., Olshen, R., and Stone, C.: Classification and Regression Trees, Wadsworth, 1984. a, b
Brilouet, P.-E., Durand, P., and Canut, G.: The marine atmospheric boundary layer under strong wind conditions: Organized turbulence structure and flux estimates by airborne measurements, J. Geophys. Res.-Atmos., 122, 2115–2130, 2017. a
Download
Short summary
This article describes two methods to estimate the height of the very first layer of the atmosphere. It is measured with aerosol lidars, and the two new methods are based on machine learning. Both are open source and available under free licenses. A sensitivity analysis and a 2-year evaluation against meteorological balloons were carried out. One method has a good agreement with balloons but is limited by training, and the other has less good agreement with balloons but is more flexible.