Articles | Volume 10, issue 3
https://doi.org/10.5194/amt-10-783-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-10-783-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
08 Mar 2017
Research article |
| 08 Mar 2017
An exploratory study on the aerosol height retrieval from OMI measurements of the 477 nm O2 − O2 spectral band using a neural network approach
Department of Geoscience and Remote Sensing (GRS), Civil Engineering and Geosciences, TU Delft, the Netherlands
J. Pepijn Veefkind
Department of Geoscience and Remote Sensing (GRS), Civil Engineering and Geosciences, TU Delft, the Netherlands
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Tim Vlemmix
Department of Geoscience and Remote Sensing (GRS), Civil Engineering and Geosciences, TU Delft, the Netherlands
Johan F. de Haan
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Vassilis Amiridis
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens 15236, Greece
Emmanouil Proestakis
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens 15236, Greece
Laboratory of Atmospheric Physics, Department of Physics, University of
Patras, 26500, Greece
Eleni Marinou
Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens, Athens 15236, Greece
Department of Physics, Aristotle University of Thessaloniki, Thessaloniki,
54124, Greece
Pieternel F. Levelt
Department of Geoscience and Remote Sensing (GRS), Civil Engineering and Geosciences, TU Delft, the Netherlands
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
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- Aerosol Layer Height Retrieval Over Ocean From the Advanced Himawari Imager Using Spectral Reflectance Sensitivity H. Lim et al. 10.1109/LGRS.2023.3236299
- Minimizing aerosol effects on the OMI tropospheric NO2 retrieval – An improved use of the 477 nm O2 − O2 band and an estimation of the aerosol correction uncertainty J. Chimot et al. 10.5194/amt-12-491-2019
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- A First Approach to Aerosol Classification Using Space-Borne Measurement Data: Machine Learning-Based Algorithm and Evaluation W. Choi et al. 10.3390/rs13040609
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- Update of the HITRAN collision-induced absorption section T. Karman et al. 10.1016/j.icarus.2019.02.034
- Effects of spatiotemporal O4 column densities and temperature-dependent O4 absorption cross-section on an aerosol effective height retrieval algorithm using the O4 air mass factor from the ozone monitoring instrument W. Choi et al. 10.1016/j.rse.2019.05.001
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Latest update: 03 Nov 2024
Short summary
We have developed artificial neural network algorithms to retrieve aerosol layer height from satellite OMI observations of the 477 nm O2–O2 spectral band. Based on 3-year (2005–2007) cloud-free scenes over north-east Asia, the results show uncertainties of 260–800 m when aerosol optical thickness is larger than 1. These algorithms also enable aerosol optical thickness retrievals by exploring the OMI continuum reflectance. These results may be used for future trace gas retrievals from TROPOMI.
We have developed artificial neural network algorithms to retrieve aerosol layer height from...
