Articles | Volume 15, issue 16
https://doi.org/10.5194/amt-15-4859-2022
https://doi.org/10.5194/amt-15-4859-2022
Research article
 | 
25 Aug 2022
Research article |  | 25 Aug 2022

Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean

Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu

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Cited articles

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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.