Articles | Volume 9, issue 4
https://doi.org/10.5194/amt-9-1743-2016
© Author(s) 2016. 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-9-1743-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Apr 2016
Research article |
| 20 Apr 2016
Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC4RS using bi-spectral reflectance measurements within the 1.88 µm water vapor absorption band
Goddard Earth Sciences Technology and Research (GESTAR), Universities
Space Research Association, Columbia, Maryland, 21046, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USA
Steven Platnick
NASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USA
G. Thomas Arnold
Science Systems and Applications, Inc., Lanham, Maryland, 20706, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USA
Robert E. Holz
Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin, Madison, Wisconsin, 53706, USA
Paolo Veglio
Cooperative Institute for Meteorological Satellite Studies, University
of Wisconsin, Madison, Wisconsin, 53706, USA
John Yorks
NASA Goddard Space Flight Center, Greenbelt, Maryland, 20771, USA
Chenxi Wang
Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, 20740, USA
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Cited
10 citations as recorded by crossref.
- Sensitivity, Uncertainty, Information Content, and Channel Selection for Hyperspectral Reflective Solar Retrievals of Cirrus Cloud Properties J. Mast & P. Yang https://doi.org/10.1109/TGRS.2024.3413040
- An Assessment of the Impacts of Cloud Vertical Heterogeneity on Global Ice Cloud Data Records From Passive Satellite Retrievals C. Wang et al. https://doi.org/10.1029/2018JD029681
- Vicarious Calibration of eMAS, AirMSPI, and AVIRIS Sensors During FIREX-AQ C. Bruegge et al. https://doi.org/10.1109/TGRS.2021.3066997
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al. https://doi.org/10.5194/amt-13-2257-2020
- Achieving consistency between in-situ and remotely sensed optical and microphysical properties of Arctic cirrus: the impact of far-infrared radiances G. Di Natale et al. https://doi.org/10.5194/acp-26-1373-2026
- Improvements of 6S Look-Up-Table Based Surface Reflectance Employing Minimum Curvature Surface Method K. Lee et al. https://doi.org/10.1007/s13143-019-00164-3
- Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES K. Meyer et al. https://doi.org/10.5194/amt-18-981-2025
- The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products S. Platnick et al. https://doi.org/10.3390/rs13010002
- Remote sensing of multiple cloud layer heights using multi-angular measurements K. Sinclair et al. https://doi.org/10.5194/amt-10-2361-2017
- Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. https://doi.org/10.1029/2018JD028989
10 citations as recorded by crossref.
- Sensitivity, Uncertainty, Information Content, and Channel Selection for Hyperspectral Reflective Solar Retrievals of Cirrus Cloud Properties J. Mast & P. Yang https://doi.org/10.1109/TGRS.2024.3413040
- An Assessment of the Impacts of Cloud Vertical Heterogeneity on Global Ice Cloud Data Records From Passive Satellite Retrievals C. Wang et al. https://doi.org/10.1029/2018JD029681
- Vicarious Calibration of eMAS, AirMSPI, and AVIRIS Sensors During FIREX-AQ C. Bruegge et al. https://doi.org/10.1109/TGRS.2021.3066997
- A machine-learning-based cloud detection and thermodynamic-phase classification algorithm using passive spectral observations C. Wang et al. https://doi.org/10.5194/amt-13-2257-2020
- Achieving consistency between in-situ and remotely sensed optical and microphysical properties of Arctic cirrus: the impact of far-infrared radiances G. Di Natale et al. https://doi.org/10.5194/acp-26-1373-2026
- Improvements of 6S Look-Up-Table Based Surface Reflectance Employing Minimum Curvature Surface Method K. Lee et al. https://doi.org/10.1007/s13143-019-00164-3
- Evaluating spectral cloud effective radius retrievals from the Enhanced MODIS Airborne Simulator (eMAS) during ORACLES K. Meyer et al. https://doi.org/10.5194/amt-18-981-2025
- The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products S. Platnick et al. https://doi.org/10.3390/rs13010002
- Remote sensing of multiple cloud layer heights using multi-angular measurements K. Sinclair et al. https://doi.org/10.5194/amt-10-2361-2017
- Exploring Aerosols Near Clouds With High‐Spatial‐Resolution Aircraft Remote Sensing During SEAC4RS R. Spencer et al. https://doi.org/10.1029/2018JD028989
Saved (final revised paper)
Latest update: 28 May 2026
Short summary
Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar reflectance measurements at two narrow wavelength channels within the broader water vapor absorption band at 1.88 µm. Results from this technique compare well with other solar reflectance, IR, and lidar-based retrievals. This approach is complementary to traditional remote sensing techniques and can extend cloud retrieval capabilities for thin cirrus clouds.
Cirrus cloud optical and microphysical properties are retrieved from remote sensing solar...
