Articles | Volume 11, issue 12
Atmos. Meas. Tech., 11, 6589–6603, 2018
https://doi.org/10.5194/amt-11-6589-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 11, 6589–6603, 2018
https://doi.org/10.5194/amt-11-6589-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article 14 Dec 2018
Research article | 14 Dec 2018
Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 1: theoretical concept
Yves Govaerts and Marta Luffarelli
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Cited
9 citations as recorded by crossref.
- Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 2: application to geostationary and polar-orbiting satellite observations M. Luffarelli & Y. Govaerts 10.5194/amt-12-791-2019
- A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. 10.5194/amt-13-373-2020
- An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign W. Hou et al. 10.1016/j.jqsrt.2020.107161
- Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo X. Ceamanos et al. 10.3390/rs11242958
- Climate Data Records from Meteosat First Generation Part III: Recalibration and Uncertainty Tracing of the Visible Channel on Meteosat-2–7 Using Reconstructed, Spectrally Changing Response Functions F. Rüthrich et al. 10.3390/rs11101165
- Retrieval of Aerosol Optical Depth from the Himawari-8 Advanced Himawari Imager data: Application over Beijing in the summer of 2016 L. Wang et al. 10.1016/j.atmosenv.2020.117788
- On the retrieval of aerosol optical depth over cryosphere using passive remote sensing L. Mei et al. 10.1016/j.rse.2020.111731
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- Polarimetric remote sensing of atmospheric aerosols: Instruments, methodologies, results, and perspectives O. Dubovik et al. 10.1016/j.jqsrt.2018.11.024
8 citations as recorded by crossref.
- Joint retrieval of surface reflectance and aerosol properties with continuous variation of the state variables in the solution space – Part 2: application to geostationary and polar-orbiting satellite observations M. Luffarelli & Y. Govaerts 10.5194/amt-12-791-2019
- A review and framework for the evaluation of pixel-level uncertainty estimates in satellite aerosol remote sensing A. Sayer et al. 10.5194/amt-13-373-2020
- An algorithm for hyperspectral remote sensing of aerosols: 3. Application to the GEO-TASO data in KORUS-AQ field campaign W. Hou et al. 10.1016/j.jqsrt.2020.107161
- Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo X. Ceamanos et al. 10.3390/rs11242958
- Climate Data Records from Meteosat First Generation Part III: Recalibration and Uncertainty Tracing of the Visible Channel on Meteosat-2–7 Using Reconstructed, Spectrally Changing Response Functions F. Rüthrich et al. 10.3390/rs11101165
- Retrieval of Aerosol Optical Depth from the Himawari-8 Advanced Himawari Imager data: Application over Beijing in the summer of 2016 L. Wang et al. 10.1016/j.atmosenv.2020.117788
- On the retrieval of aerosol optical depth over cryosphere using passive remote sensing L. Mei et al. 10.1016/j.rse.2020.111731
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
Latest update: 28 Sep 2021
Short summary
This paper presents a new algorithm for the joint retrieval of surface reflectance and aerosol properties with continuous variations of the state variables in the solution space. This algorithm, named CISAR (Combined Inversion of Surface and AeRosol), relies on a simple atmospheric vertical structure composed of two layers and an underlying surface. Surface anisotropic reflectance effects are taken into account and radiatively coupled with atmospheric scattering.
This paper presents a new algorithm for the joint retrieval of surface reflectance and aerosol...
