Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm

Miller, Daniel J.; Segal-Rozenhaimer, Michal; Knobelspiesse, Kirk; Redemann, Jens; Cairns, Brian; Alexandrov, Mikhail; van Diedenhoven, Bastiaan; Wasilewski, Andrzej

doi:https://doi.org/10.5194/amt-13-3447-2020

Articles | Volume 13, issue 6

https://doi.org/10.5194/amt-13-3447-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

New observations and related modelling studies of the aerosol–cloud–climate...

https://doi.org/10.5194/amt-13-3447-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 6

Research article

|

29 Jun 2020

Research article |

| 29 Jun 2020

Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm

Daniel J. Miller, Michal Segal-Rozenhaimer, Kirk Knobelspiesse, Jens Redemann, Brian Cairns, Mikhail Alexandrov, Bastiaan van Diedenhoven, and Andrzej Wasilewski

Data sets

Suite of Aerosol, Cloud, and Related Data Acquired Aboard ER2 During ORACLES 2016, Version 1, NASA Ames Earth Science Project Office ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/ER2/2016_V2

Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2017, Version 1, NASA Ames Earth Science Project Office ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V2, 2019

Suite of Aerosol, Cloud, and Related Data Acquired During ORACLES Campaign, Version 1, NASA Langley ASDC DAAC ORACLES Science Team https://doi.org/10.5067/ASDC_DAAC/ORACLES_AerosolCloud_AircraftRemoteSensing_Data_1

Suite of Aerosol, Cloud, and Related Data Acquired Aboard P3 During ORACLES 2018 ORACLES Science Team https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V2

Short summary

A neural network (NN) is developed and used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. The NN is applied to research scanning polarimeter (RSP) observations obtained during the ORACLES field campaign and compared to other co-located remote sensing retrievals of cloud effective radius and optical thickness. A NN approach can advance more complex iterative search retrieval algorithms by providing a quick initial guess.