An online aerosol retrieval algorithm using OMI near-UV observations based on the optimal estimation method

U. Jeong, J. Kim, C. Ahn, O. Torres, X. Liu, P. K. Bhartia, R. J.D. Spurr, D. Haffner, K. Chance, B. N. Holben

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Abstract

An online version of the OMI (Ozone Monitoring Instrument) near-ultraviolet (UV) aerosol retrieval algorithm was developed to retrieve aerosol optical thickness (AOT) and single scattering albedo (SSA) based on the optimal estimation (OE) method. Instead of using the traditional look-up tables for radiative transfer calculations, it performs online radiative transfer calculations with the Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model to eliminate interpolation errors and improve stability. The OE-based algorithm has the merit of providing useful estimates of uncertainties simultaneously with the inversion products. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in Northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved AOT and SSA. The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The estimated retrieval noise and smoothing error perform well in representing the envelope curve of actual biases of AOT at 388 nm between the retrieved AOT and AERONET measurements. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface albedo at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for future studies.

Original languageEnglish
Pages (from-to)16615-16654
Number of pages40
JournalAtmospheric Chemistry and Physics Discussions
Volume15
Issue number12
DOIs
Publication statusPublished - 2015 Jun 18

All Science Journal Classification (ASJC) codes

  • Atmospheric Science
  • Space and Planetary Science

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    Jeong, U., Kim, J., Ahn, C., Torres, O., Liu, X., Bhartia, P. K., Spurr, R. J. D., Haffner, D., Chance, K., & Holben, B. N. (2015). An online aerosol retrieval algorithm using OMI near-UV observations based on the optimal estimation method. Atmospheric Chemistry and Physics Discussions, 15(12), 16615-16654. https://doi.org/10.5194/acpd-15-16615-2015