Articles | Volume 15, issue 16
https://doi.org/10.5194/amt-15-4859-2022
© Author(s) 2022. 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-15-4859-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Aug 2022
Research article |
| 25 Aug 2022
| 25 Aug 2022
Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Science Systems and Applications, Inc., Greenbelt, MD 20706, USA
Kirk Knobelspiesse
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Bryan A. Franz
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Peng-Wang Zhai
JCET and Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Andrew M. Sayer
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Amir Ibrahim
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Brian Cairns
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
Otto Hasekamp
Netherlands Institute for Space Research (SRON, NWO-I), Utrecht, the Netherlands
Yongxiang Hu
MS 475, NASA Langley Research Center, Hampton, VA 23681-2199, USA
Vanderlei Martins
JCET and Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
P. Jeremy Werdell
NASA Goddard Space Flight Center, Code 616, Greenbelt, MD 20771, USA
Xiaoguang Xu
JCET and Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
Data sets
Aerosol Characterization from Polarimeter and Lidar Campaign ACEPOL Science Team https://doi.org/10.5067/SUBORBITAL/ACEPOL2017/DATA001
Short summary
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color derived from multi-angle polarimetric measurements. Standard error propagation methods are used to compute the uncertainties. A flexible framework is proposed to evaluate how representative these uncertainties are compared with real retrieval errors. Meanwhile, to assist operational data processing, we optimized the computational speed to evaluate the retrieval uncertainties based on neural networks.
In this work, we assessed the pixel-wise retrieval uncertainties on aerosol and ocean color...
