Articles | Volume 15, issue 3
https://doi.org/10.5194/acp-15-1265-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-1265-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
05 Feb 2015
Research article |
| 05 Feb 2015
Evaluation of CALIOP 532 nm aerosol optical depth over opaque water clouds
NASA Langley Research Center, Hampton, Virginia, USA
Science Systems and Applications, Inc., Hampton, Virginia, USA
D. Winker
NASA Langley Research Center, Hampton, Virginia, USA
A. Omar
NASA Langley Research Center, Hampton, Virginia, USA
M. Vaughan
NASA Langley Research Center, Hampton, Virginia, USA
NASA Langley Research Center, Hampton, Virginia, USA
Science Systems and Applications, Inc., Hampton, Virginia, USA
C. Trepte
NASA Langley Research Center, Hampton, Virginia, USA
NASA Langley Research Center, Hampton, Virginia, USA
G. Schuster
NASA Langley Research Center, Hampton, Virginia, USA
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- Quantifying the low bias of CALIPSO's column aerosol optical depth due to undetected aerosol layers M. Kim et al. 10.1002/2016JD025797
- Stratospheric Injection of Massive Smoke Plume From Canadian Boreal Fires in 2017 as Seen by DSCOVR‐EPIC, CALIOP, and OMPS‐LP Observations O. Torres et al. 10.1029/2020JD032579
- Aerosol Direct Radiative Effect Sensitivity Analysis T. Thorsen et al. 10.1175/JCLI-D-19-0669.1
- The Ascension Island Boundary Layer in the Remote Southeast Atlantic is Often Smoky P. Zuidema et al. 10.1002/2017GL076926
- EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product E. Proestakis et al. 10.5194/acp-19-11743-2019
- Modeling the smoky troposphere of the southeast Atlantic: a comparison to ORACLES airborne observations from September of 2016 Y. Shinozuka et al. 10.5194/acp-20-11491-2020
- The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm M. Kim et al. 10.5194/amt-11-6107-2018
- Progress and Challenges in Quantifying Wildfire Smoke Emissions, Their Properties, Transport, and Atmospheric Impacts I. Sokolik et al. 10.1029/2018JD029878
- Added Value of Aerosol Observations of a Future AOS High Spectral Resolution Lidar with Respect to Classic Backscatter Spaceborne Lidar Measurements F. Cornut et al. 10.3390/rs15020506
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- Assessment of smoke plume height products derived from multisource satellite observations using lidar-derived height metrics for wildfires in the western US J. Huang et al. 10.5194/acp-24-3673-2024
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- New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements W. Zhang et al. 10.3390/rs11202396
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- Identifying Absorbing Aerosols Above Clouds From the Spinning Enhanced Visible and Infrared Imager Coupled With NASA A-Train Multiple Sensors I. Chang & S. Christopher 10.1109/TGRS.2015.2513015
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- Global distribution of maritime low clouds with an emphasis on different aerosol types and meteorological parameters inferred from multi-satellite and reanalysis data during 2007–2016 B. Pan et al. 10.1016/j.atmosenv.2020.118082
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- Enhancements to the caliop aerosol subtyping and lidar ratio selection algorithms for level II version 4 A. Omar et al. 10.1051/epjconf/201817602006
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