Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Retrieval of the aerosol asymmetry factor from Sun–sky radiometer measurements: application to almucantar geometry and accuracy assessment

Not Accessible

Your library or personal account may give you access

Abstract

The Devaux–Vermeulen–Li (DVL) method is a simple method that directly retrieves aerosol optical parameters based on single-wavelength solar–sky radiation observations, without the assumption of aerosol microphysical properties. Inheriting the previous retrieval of single-scattering albedo (SSA) and scattering phase function, the DVL method is modified to derive the aerosol asymmetric factor (g) parameter. Interpolation methods were proposed to estimate the phase function over the extreme forward and backward scattering regions where instrumental observations are missing; thus, g could be derived from the phase function over the entire scattering angle region. To evaluate the g accuracy from the DVL algorithm, especially for non-spherical aerosols, synthetic retrieval with typical aerosol models (water-soluble, biomass burning, dust-sphericity, and dust-spheroid models) and retrievals from AERONET observations (Beijing site, from January 2011 to March 2015) were implemented at four wavelengths (440, 675, 870, and 1020 nm). The numerical experiments showed that DVL retrieves g with errors less than ±0.02 under “error-free” conditions. When measurement uncertainties were present, all g errors were within ±0.03, except for the angular pointing error for the coarse mode-dominated dust-sphericity/spheroid aerosols. Most importantly, g retrievals were not sensitive to the aerosol optical depth (AOD) and sky radiance errors, which are important influencing factors for SSA retrieval. Comparison of DVL retrievals with AERONET version 2 level 2.0 products [with AOD (440nm)>0.2] shows that the DVL g was well correlated with that of AERONET, especially for the 675, 870, and 1020 nm bands, with root mean square deviations (RMSDs) smaller than 0.02 and absolute values of mean bias deviation smaller than 0.01. Relatively larger deviations occurred at the 440 nm band, where g values were underestimated by approximately 0.03 compared to those of AERONET, with a higher RMSD of approximately 0.035. Both the synthetic retrieval and comparison with AERONET indicated that the algorithm performance for large, non-spherical particles is comparable to that of other spherical aerosol particles in retrieving g.

© 2017 Optical Society of America

Full Article  |  PDF Article
More Like This
Retrieval of the optical depth using an all-sky CCD camera

Francisco J. Olmo, Alberto Cazorla, Lucas Alados-Arboledas, Miguel A. López-Álvarez, Javier Hernández-Andrés, and Javier Romero
Appl. Opt. 47(34) H182-H189 (2008)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (8)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (2)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (10)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.