Articles | Volume 16, issue 7
https://doi.org/10.5194/amt-16-1803-2023
© Author(s) 2023. 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-16-1803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Apr 2023
Research article |
| 05 Apr 2023
| 05 Apr 2023
Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 1: Model description and Jacobian calculation
Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
Aviad Levis
Computer and Mathematical Sciences Department, California Institute of Technology, Pasadena, CA 91125, USA
Larry Di Girolamo
Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61801, USA
Vadim Holodovsky
Viterbi Faculty of Electrical and Computer Engineering, Technion –
Israel Institute of Technology, Haifa 3200003, Israel
Linda Forster
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Anthony B. Davis
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA 91109, USA
Yoav Y. Schechner
Viterbi Faculty of Electrical and Computer Engineering, Technion –
Israel Institute of Technology, Haifa 3200003, Israel
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Cited
14 citations as recorded by crossref.
- Spatial context importance in deep learning for global horizontal irradiance estimation from satellite imagery V. Becquet et al. https://doi.org/10.1016/j.solener.2026.114844
- DNN-Based 3-D Cloud Retrieval for Variable Solar Illumination and Multiview Spaceborne Imaging T. Klein et al. https://doi.org/10.1109/LGRS.2025.3550408
- Imagers for Spaceborne Cloud Tomography V. Holodovsky et al. https://doi.org/10.1109/TGRS.2025.3600736
- Errors in stereoscopic retrievals of cloud top height for single-layer clouds J. Loveridge & L. Di Girolamo https://doi.org/10.5194/amt-18-3009-2025
- Considering the Effects of Horizontal Heterogeneities in Satellite-Based Large-Scale Statistics of Cloud Optical Properties T. Várnai & A. Marshak https://doi.org/10.3390/rs16183388
- Cloud characterization by computed tomography methods using a satellite formation of 10 small satellites for improved climate prediction L. Elsner et al. https://doi.org/10.1016/j.actaastro.2025.06.053
- A Cloud’s Droplet Size—and Its Internal Structure—From Monochrome Multiangle Imaging A. Davis et al. https://doi.org/10.1109/TGRS.2026.3727841
- Tomographic reconstruction algorithms for retrieving two-dimensional ice cloud microphysical parameters using along-track (sub)millimeter-wave radiometer observations Y. Liu & I. Adams https://doi.org/10.5194/amt-18-1659-2025
- NeMF: Neural Microphysics Fields I. Kom-Betzer et al. https://doi.org/10.1109/TPAMI.2024.3467913
- Influence of cloud retrieval errors due to three-dimensional radiative effects on calculations of broadband shortwave cloud radiative effect A. Ademakinwa et al. https://doi.org/10.5194/acp-24-3093-2024
- Application of radon transform to multi-angle measurements made by the research scanning polarimeter: a new approach to cloud tomography. Part II: examples of retrievals from CAMP2Ex dataset M. Alexandrov et al. https://doi.org/10.3389/frsen.2025.1689824
- Cloud parameter retrieval based on satellite data: A review of methods, advances, and challenges Z. Li et al. https://doi.org/10.1016/j.atmosres.2026.109130
- Imaging of Atmospheric Dispersion Processes with Differential Absorption Lidar R. Lung & N. Polydorides https://doi.org/10.1137/23M1598404
- Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization J. Loveridge et al. https://doi.org/10.5194/amt-16-3931-2023
14 citations as recorded by crossref.
- Spatial context importance in deep learning for global horizontal irradiance estimation from satellite imagery V. Becquet et al. https://doi.org/10.1016/j.solener.2026.114844
- DNN-Based 3-D Cloud Retrieval for Variable Solar Illumination and Multiview Spaceborne Imaging T. Klein et al. https://doi.org/10.1109/LGRS.2025.3550408
- Imagers for Spaceborne Cloud Tomography V. Holodovsky et al. https://doi.org/10.1109/TGRS.2025.3600736
- Errors in stereoscopic retrievals of cloud top height for single-layer clouds J. Loveridge & L. Di Girolamo https://doi.org/10.5194/amt-18-3009-2025
- Considering the Effects of Horizontal Heterogeneities in Satellite-Based Large-Scale Statistics of Cloud Optical Properties T. Várnai & A. Marshak https://doi.org/10.3390/rs16183388
- Cloud characterization by computed tomography methods using a satellite formation of 10 small satellites for improved climate prediction L. Elsner et al. https://doi.org/10.1016/j.actaastro.2025.06.053
- A Cloud’s Droplet Size—and Its Internal Structure—From Monochrome Multiangle Imaging A. Davis et al. https://doi.org/10.1109/TGRS.2026.3727841
- Tomographic reconstruction algorithms for retrieving two-dimensional ice cloud microphysical parameters using along-track (sub)millimeter-wave radiometer observations Y. Liu & I. Adams https://doi.org/10.5194/amt-18-1659-2025
- NeMF: Neural Microphysics Fields I. Kom-Betzer et al. https://doi.org/10.1109/TPAMI.2024.3467913
- Influence of cloud retrieval errors due to three-dimensional radiative effects on calculations of broadband shortwave cloud radiative effect A. Ademakinwa et al. https://doi.org/10.5194/acp-24-3093-2024
- Application of radon transform to multi-angle measurements made by the research scanning polarimeter: a new approach to cloud tomography. Part II: examples of retrievals from CAMP2Ex dataset M. Alexandrov et al. https://doi.org/10.3389/frsen.2025.1689824
- Cloud parameter retrieval based on satellite data: A review of methods, advances, and challenges Z. Li et al. https://doi.org/10.1016/j.atmosres.2026.109130
- Imaging of Atmospheric Dispersion Processes with Differential Absorption Lidar R. Lung & N. Polydorides https://doi.org/10.1137/23M1598404
- Retrieving 3D distributions of atmospheric particles using Atmospheric Tomography with 3D Radiative Transfer – Part 2: Local optimization J. Loveridge et al. https://doi.org/10.5194/amt-16-3931-2023
Saved (final revised paper)
Latest update: 28 Sep 2026
Short summary
We describe a new method for measuring the 3D spatial variations in water within clouds using the reflected light of the Sun viewed at multiple different angles by satellites. This is a great improvement over older methods, which typically assume that clouds occur in a slab shape. Our study used computer modeling to show that our 3D method will work well in cumulus clouds, where older slab methods do not. Our method will inform us about these clouds and their role in our climate.
We describe a new method for measuring the 3D spatial variations in water within clouds using...
