An optimization approach for aerosol retrievals using simulated MISR radiances

Date

2011-06-13

Department

Program

Citation of Original Publication

David J. Diner et al. "An optimization approach for aerosol retrievals using simulated MISR radiances". Atmospheric Research. 116 (15 October 2012) 1-14. https://doi.org/10.1016/j.atmosres.2011.05.020.

Rights

This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
Public Domain Mark 1.0

Subjects

Abstract

Currently, many satellite-based aerosol retrievals make use of lookup tables (LUTs) containing precomputed solutions to the radiative transfer (RT) equation. The benefit of this strategy is the avoidance of expensive runtime calculations, but its main drawback is that the LUTs discretize what is inherently a continuous, multivariate solution space. The operational retrieval algorithm for the Multi-angle Imaging SpectroRadiometer (MISR), for example, compares the observations to a set of 74 aerosol mixtures, each composed of particle models having prescribed optical properties and size distributions. In a recent “blind” study comparing the performance of several satellite retrieval algorithms on simulated data over a black surface, the MISR algorithm performed reasonably well in recovering the “true” spectral aerosol optical depths (AODs), but because the correct aerosol model was not contained within the MISR LUT, the retrieved AODs were biased low by ~ 14%. This motivated an investigation of whether an optimization approach, in which the aerosols are modeled by a set of continuously variable parameters recovered using nonlinear least-squares, could improve the results. In this paper, we demonstrate that such an approach using Levenberg–Marquardt optimization yields superior accuracy. Advances in computer speed, development of more efficient RT codes, and algorithm innovations will be necessary for this approach to satisfy the demands of a global, production-level satellite aerosol retrieval process, especially when used in conjunction with future instruments having enhanced sensitivity to diverse aerosol properties.