Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean, Part 1: performance evaluation and speed improvement
Abstract
Abstract. Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere-ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and nonlinearity of radiative transfer near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on several neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the technique to uncertainty evaluation in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, and guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.
Authors 12
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Goddard Space Flight Center · Science Systems and Applications (United States)
Affiliation as printed
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
Science Systems and Applications, Inc., Greenbelt, MD, USA
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Kirk David Knobelspiesse corresponding
Affiliation as printed
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
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Affiliation as printed
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
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University of Maryland, Baltimore County
Affiliation as printed
JCET/Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
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A. M. Sayer corresponding
Goddard Space Flight Center · University of Maryland, Baltimore County
Affiliation as printed
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
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Amir I. Ibrahim corresponding
Affiliation as printed
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
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Goddard Institute for Space Studies
Affiliation as printed
NASA Goddard Institute for Space Studies, New York, NY 10025, USA
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Space Research Organisation Netherlands
Affiliation as printed
Netherlands Institute for Space Research (SRON, NWO-I), Utrecht, The Netherlands
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Yongxiang Hu corresponding
Affiliation as printed
MS 475 NASA Langley Research Center, Hampton, VA 23681-2199, USA
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University of Maryland, Baltimore County
Affiliation as printed
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
JCET/Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
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Affiliation as printed
NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
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Xiaoguang Xu corresponding
University of Maryland, Baltimore County
Affiliation as printed
Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
JCET/Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
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