Preprints
https://doi.org/10.5194/egusphere-2022-1413
https://doi.org/10.5194/egusphere-2022-1413
 
08 Dec 2022
08 Dec 2022
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

The impact and estimation of uncertainty correlation for multi-angle polarimetric remote sensing of aerosols and ocean color

Meng Gao1,2, Kirk Knobelspiesse1, Bryan A. Franz1, Peng-Wang Zhai3, Brian Cairns4, Xiaoguang Xu3, and J. Vanderlei Martins3 Meng Gao et al.
  • 1NASA Goddard Space Flight Center, Code 616, Greenbelt, Maryland 20771, USA
  • 2Science Systems and Applications, Inc., Greenbelt, MD, USA
  • 3JCET/Physics Department, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
  • 4NASA Goddard Institute for Space Studies, New York, NY 10025, USA

Abstract. Multi-angle polarimetric (MAP) measurements contain rich information for characterization of aerosol microphysical and optical properties that can be used to improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere-ocean system, although uncertainty correlation among measurements is generally ignored due to lack of knowledge on its strength and characterization. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation from retrieval results and a method to estimate correlation strength from retrieval fitting residuals. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on neural network forward models, is used to conduct the retrievals and uncertainty quantification. In addition, we also discuss a flexible approach to include a correlated uncertainty model in the retrieval algorithm. The impact of angular correlation on retrieval uncertainties is discussed based on synthetic AirHARP and HARP2 measurements using a Monte Carlo uncertainty estimation method. Correlation properties are estimated using auto-correlation functions based on the fitting residuals from both synthetic AirHARP and HARP2 data and real AirHARP measurement, with the resulting angular correlation parameters found to be larger than 0.9 and 0.8 for reflectance and DoLP, respectively, which correspond to correlation angles of 10° and 5°. Although this study focuses on angular correlation from HARP instruments, the methodology to study and quantify uncertainty correlation is also applicable to other instruments with angular, spectral, or spatial correlations, and can help inform laboratory calibration and characterization of the instrument uncertainty structure.

Meng Gao et al.

Status: open (until 20 Feb 2023)

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Meng Gao et al.

Meng Gao et al.

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Short summary
Multi-angle polarimetric measurements have been shown to greatly improve the remote sensing capability of aerosols and help atmospheric correction for ocean color retrievals. However, the uncertainties in the measurements among different angles are often correlated, which have not been well characterized. In this work, we provide a practical framework to evaluate the impact of the angular uncertainty correlation and a method to directly estimate correlation strength from retrieval residuals.