Articles | Volume 17, issue 5
https://doi.org/10.5194/amt-17-1497-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-1497-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Mar 2024
Research article |
| 12 Mar 2024
| 12 Mar 2024
Algorithm evaluation for polarimetric remote sensing of atmospheric aerosols
SRON Netherlands Institute for Space Research, Niels Bohrweg 4, 2333 CA Leiden, the Netherlands
Pavel Litvinov
GRASP SAS, Villeneuve-d’Ascq, 59650, France
Guangliang Fu
SRON Netherlands Institute for Space Research, Niels Bohrweg 4, 2333 CA Leiden, the Netherlands
Cheng Chen
GRASP SAS, Villeneuve-d’Ascq, 59650, France
Oleg Dubovik
Laboratoire d’Optique Atmosphérique, CNRS/Université de Lille, Villeneuve-d’Ascq, 59650, France
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30 citations as recorded by crossref.
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- An Algorithm for Aerosol Optical Properties Retrieval Over the Ocean Accelerated by a Neural Network From Single-View Multispectral Measurements of Intensity and Polarization Z. Ji et al. https://doi.org/10.1109/TGRS.2025.3630102
- Uncertainty in aerosol effective radiative forcing from anthropogenic and natural aerosol parameters in ECHAM6.3-HAM2.3 Y. Bhatti et al. https://doi.org/10.5194/acp-26-269-2026
- Aerosol Fine-Mode-Fraction Retrieval From GEO-KOMPSAT-2A/AMI Using a Deep Neural Network and Spectral Deconvolution Algorithm M. Kim et al. https://doi.org/10.1109/TGRS.2025.3591177
- Retrieval of aerosol composition from spectral aerosol optical depth and optical properties using a machine learning approach D. Ji et al. https://doi.org/10.5194/amt-19-421-2026
- Comparison of diurnal aerosol products retrieved from combinations of micro-pulse lidar and sun photometer observations over the KAUST observation site A. Lopatin et al. https://doi.org/10.5194/amt-17-4445-2024
- Phase matrix characterization of long-range-transported Saharan dust using multiwavelength-polarized polar imaging nephelometry E. Bazo et al. https://doi.org/10.5194/acp-25-6325-2025
- Polarized reflectance in China from DPC-2/GF-5(02) polarimetric satellite measurements: dataset and model inter-comparison Q. Liu et al. https://doi.org/10.1016/j.jqsrt.2026.109961
- Extended aerosol and surface characterization from S5P/TROPOMI with GRASP algorithm. Part I: Conditions, approaches, performance and new possibilities P. Litvinov et al. https://doi.org/10.1016/j.rse.2024.114355
- Tracking regional CH4 emissions through collocated air pollution measurement: a pilot application and robustness analysis in China Y. Li & B. Zheng https://doi.org/10.1038/s41612-025-01011-1
- Retrieval of global aerosol and surface properties from the Gaofen-5 Directional Polarimetric Camera measurements Z. Zhang et al. https://doi.org/10.5194/amt-19-2555-2026
- Satellite remote sensing of aerosol single scattering albedo: Instruments, algorithms, and challenges Y. Dong et al. https://doi.org/10.1016/j.jqsrt.2025.109802
- Development of Level 2 aerosol and surface products from cross-track scanning polarimeter POSP on board the GF-5(02) satellite C. Chen et al. https://doi.org/10.5194/essd-17-3497-2025
- Optimal choice of proxy for cloud condensation nuclei reduces uncertainty in aerosol-cloud-climate forcing H. Jia et al. https://doi.org/10.1126/sciadv.aea4828
- Aerosol single-scattering albedo derived by merging OMI/POLDER satellite products and AERONET ground observations Y. Dong et al. https://doi.org/10.5194/essd-17-3873-2025
- Where sky meets sea: Integrated aerosol and ocean color retrieval from PACE SPEXone multi-angle polarimetry M. Gao et al. https://doi.org/10.1016/j.rse.2026.115603
- Sensitivity of Airborne Methane Retrieval Algorithms (MF, ACRWL1MF, and DOAS) to Surface Albedo and Types: Hyperspectral Simulation Assessment J. Chen et al. https://doi.org/10.3390/atmos16111224
- Estimation of Cloud Condensation Nuclei (CCN) using a neural network retrieval algorithm—A synthetic study for SPEXone on the NASA PACE mission N. Hannadige et al. https://doi.org/10.1016/j.jqsrt.2026.109853
- A Capsule Network Model for Aerosol Retrieval from DPC/Gaofen-5(02) Satellite Multi-Angle Polarimetric Observation H. Gu et al. https://doi.org/10.34133/remotesensing.1008
- An Aerosol Retrieval Algorithm Over Land From Multispectral Single-Viewing Measurements of Intensity and Polarization Z. Ji et al. https://doi.org/10.1109/TGRS.2025.3562783
- Global Aerosol Retrieval Over Land Using the Chinese Satellite Polarimeter DPC-2/GF-5(02) Z. Zhang et al. https://doi.org/10.1109/TGRS.2025.3633391
- Synergetic retrieval from multi-mission spaceborne measurements for enhanced aerosol and surface characterization P. Litvinov et al. https://doi.org/10.5194/amt-18-7679-2025
- Remote sensing of aerosols over drylands: Challenges, uncertainties, and paths forward C. Chen et al. https://doi.org/10.1126/sciadv.aec4247
- Above Cloud Aerosol Detection and Retrieval from Multi-Angular Polarimetric Satellite Measurements in a Neural Network Ensemble Approach Z. Yuan et al. https://doi.org/10.5194/amt-18-5415-2025
- An efficient transformer-based aerosol retrieval algorithm for the polarization crossfire (PCF) satellite senor suite: development and validation> H. Gu et al. https://doi.org/10.1016/j.jqsrt.2025.109793
- Monitoring of aerosol optical-microphysical properties from DPC/GF-5(02): A case study of dust event in north China plain Y. Cao et al. https://doi.org/10.1016/j.atmosenv.2025.121193
- Cloud detection from multi-angular polarimetric satellite measurements using a neural network ensemble approach Z. Yuan et al. https://doi.org/10.5194/amt-17-2595-2024
- Capability of liquid cloud microphysical property retrieval from satellite-borne multi-angle hyperspectral polarimetric measurements Z. Yuan et al. https://doi.org/10.1016/j.jqsrt.2026.109940
- The SMART-P Algorithm for Aerosol and Ocean Properties Part 1: Algorithm Theoretical Basis and Expected Accuracy of PolCube Aerosol Products S. Lee et al. https://doi.org/10.3390/rs18040560
- Collaborative Neural Networks Significantly Improve Global Aerosol Retrievals From Multiangle Polarimeters G. Fu et al. https://doi.org/10.1109/TGRS.2026.3685881
Saved (final revised paper)
Latest update: 17 Aug 2026
Short summary
Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing sunlight (direct effect) and changing cloud properties (indirect effect). The scale of aerosol cooling is uncertain, hampering accurate climate predictions. We compare two algorithms for the retrieval of aerosol properties from multi-angle polarimetric measurements: Generalized Retrieval of Atmosphere and Surface Properties (GRASP) and Remote sensing of Trace gas and Aerosol Products (RemoTAP).
Aerosols are particles in the atmosphere that cool the climate by reflecting and absorbing...
