Articles | Volume 11, issue 6
Atmos. Meas. Tech., 11, 3263–3280, 2018
https://doi.org/10.5194/amt-11-3263-2018
Atmos. Meas. Tech., 11, 3263–3280, 2018
https://doi.org/10.5194/amt-11-3263-2018

Research article 07 Jun 2018

Research article | 07 Jun 2018

A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

Swadhin Nanda et al.

Related authors

A first comparison of TROPOMI aerosol layer height (ALH) to CALIOP data
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Maarten Sneep, Mark ter Linden, Jiyunting Sun, and Pieternel F. Levelt
Atmos. Meas. Tech., 13, 3043–3059, https://doi.org/10.5194/amt-13-3043-2020,https://doi.org/10.5194/amt-13-3043-2020, 2020
Short summary
The 2018 fire season in North America as seen by TROPOMI: aerosol layer height intercomparisons and evaluation of model-derived plume heights
Debora Griffin, Christopher Sioris, Jack Chen, Nolan Dickson, Andrew Kovachik, Martin de Graaf, Swadhin Nanda, Pepijn Veefkind, Enrico Dammers, Chris A. McLinden, Paul Makar, and Ayodeji Akingunola
Atmos. Meas. Tech., 13, 1427–1445, https://doi.org/10.5194/amt-13-1427-2020,https://doi.org/10.5194/amt-13-1427-2020, 2020
Short summary
Defining aerosol layer height for UVAI interpretation using aerosol vertical distributions characterized by MERRA-2
Jiyunting Sun, J. Pepijn Veefkind, Peter van Velthoven, L. Gijsbert Tilstra, Julien Chimot, Swadhin Nanda, and Pieternel F. Levelt
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-39,https://doi.org/10.5194/acp-2020-39, 2020
Revised manuscript not accepted
Short summary
A neural network radiative transfer model approach applied to the Tropospheric Monitoring Instrument aerosol height algorithm
Swadhin Nanda, Martin de Graaf, J. Pepijn Veefkind, Mark ter Linden, Maarten Sneep, Johan de Haan, and Pieternel F. Levelt
Atmos. Meas. Tech., 12, 6619–6634, https://doi.org/10.5194/amt-12-6619-2019,https://doi.org/10.5194/amt-12-6619-2019, 2019
Short summary
The role of aerosol layer height in quantifying aerosol absorption from ultraviolet satellite observations
Jiyunting Sun, Pepijn Veefkind, Swadhin Nanda, Peter van Velthoven, and Pieternel Levelt
Atmos. Meas. Tech., 12, 6319–6340, https://doi.org/10.5194/amt-12-6319-2019,https://doi.org/10.5194/amt-12-6319-2019, 2019
Short summary

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Retrievals of dust-related particle mass and ice-nucleating particle concentration profiles with ground-based polarization lidar and sun photometer over a megacity in central China
Yun He, Yunfei Zhang, Fuchao Liu, Zhenping Yin, Yang Yi, Yifan Zhan, and Fan Yi
Atmos. Meas. Tech., 14, 5939–5954, https://doi.org/10.5194/amt-14-5939-2021,https://doi.org/10.5194/amt-14-5939-2021, 2021
Short summary
Introducing the MISR level 2 near real-time aerosol product
Marcin L. Witek, Michael J. Garay, David J. Diner, Michael A. Bull, Felix C. Seidel, Abigail M. Nastan, and Earl G. Hansen
Atmos. Meas. Tech., 14, 5577–5591, https://doi.org/10.5194/amt-14-5577-2021,https://doi.org/10.5194/amt-14-5577-2021, 2021
Short summary
Estimation of PM2.5 concentration in China using linear hybrid machine learning model
Zhihao Song, Bin Chen, Yue Huang, Li Dong, and Tingting Yang
Atmos. Meas. Tech., 14, 5333–5347, https://doi.org/10.5194/amt-14-5333-2021,https://doi.org/10.5194/amt-14-5333-2021, 2021
Short summary
Species correlation measurements in turbulent flare plumes: considerations for field measurements
Scott P. Seymour and Matthew R. Johnson
Atmos. Meas. Tech., 14, 5179–5197, https://doi.org/10.5194/amt-14-5179-2021,https://doi.org/10.5194/amt-14-5179-2021, 2021
Short summary
Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign
William G. K. McLean, Guangliang Fu, Sharon P. Burton, and Otto P. Hasekamp
Atmos. Meas. Tech., 14, 4755–4771, https://doi.org/10.5194/amt-14-4755-2021,https://doi.org/10.5194/amt-14-4755-2021, 2021
Short summary

Cited articles

Alexander, H., Maxime, H., Myles, T., Jean-Luc, L., Martial, H., Volker, L., team, E.-P., and TOPROF team: The E-PROFILE network for the operational measurement of wind and aerosol profiles over Europe, in: Instruments and Observing Methods, vol. 125, World Meteorological Organization, Madrid, Spain, available at: https://www.wmo.int/pages/prog/www/IMOP/publications/IOM-125_TECO_2016/Session_3/K3B_Haefele_et_al.pdf, 2016. a, b, c
CAMS: Saharan dust and smoke over France and UK, available at: https://atmosphere.copernicus.eu/news-and-media/news/saharan-dust-and-smoke-over-france-and-uk (last access: 5 June 2018), 2017. a
CNES, CNRS, University of Lille: ICARE data and services center, available at: http://www.icare.univ-lille1.fr/calipso/, last access: 6 June 2018. 
Corradini, S. and Cervino, M.: Aerosol extinction coefficient profile retrieval in the oxygen A-band considering multiple scattering atmosphere. Test case: SCIAMACHY nadir simulated measurements, J. Quant. Spectrosc. Ra., 97, 354–380, https://doi.org/10.1016/j.jqsrt.2005.05.061, available at: http://www.sciencedirect.com/science/article/pii/S0022407305002207, 2006. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Short summary
An approach to estimate the height of aerosol plumes over land from satellite measurements of the oxygen A band is proposed. The method, termed dynamic scaling, forces the retrieval to use spectral points that contain more height information. The method is tested in a synthetic environment as well as with GOME-2A and GOME-2B measurements of wildfire plumes over Europe, with very encouraging results. This method can be easily applied to other aerosol height algorithms using least squares.