Articles | Volume 11, issue 12
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.
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
CORRESPONDING AUTHOR
Rayference, 1030 Brussels, Belgium
Marta Luffarelli
Rayference, 1030 Brussels, Belgium
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16 citations as recorded by crossref.
- Aerosol optical depth retrieval from the EarthCARE Multi-Spectral Imager: the M-AOT product N. Docter et al. 10.5194/amt-16-3437-2023
- Quantitative assessment of the potential of optimal estimation for aerosol retrieval from geostationary weather satellites in the frame of the iAERUS‐GEO algorithm A. Georgeot et al. 10.1002/asl.1199
- 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
- Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data X. Ceamanos et al. 10.5194/amt-16-2575-2023
- 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
- Aerosol Optical Thickness Retrieval in Presence of Cloud: Application to S3A/SLSTR Observations M. Luffarelli et al. 10.3390/atmos13050691
- Himawari-8-Derived Aerosol Optical Depth Using an Improved Time Series Algorithm Over Eastern China D. Li et al. 10.3390/rs12060978
- Time series retrieval of Multi-wavelength Aerosol optical depth by adapting Transformer (TMAT) using Himawari-8 AHI data L. She et al. 10.1016/j.rse.2024.114115
- 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
- Carbonaceous aerosols remote sensing from geostationary satellite observation, Part I: Algorithm development using critical reflectance F. Bao et al. 10.1016/j.rse.2023.113459
- 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
- Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI F. Yin et al. 10.5194/gmd-15-7933-2022
- Neural Network AEROsol Retrieval for Geostationary Satellite (NNAeroG) Based on Temporal, Spatial and Spectral Measurements X. Chen et al. 10.3390/rs14040980
- On the retrieval of aerosol optical depth over cryosphere using passive remote sensing L. Mei et al. 10.1016/j.rse.2020.111731
Latest update: 20 Nov 2024
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...
