Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations

By Oleg Dubovik, Maurice Herman, A. Holdak, Tatyana Lapyonok, Didier Tanré, Jean-Luc Deuze, Fabrice Ducos, Alexander Sinyuk, Anton Lopatin. 2010

623 citations recorded by the source corpus.

Abstract. The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL micro-satellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation. The algorithm is designed to retrieve complete aerosol properties globally. Over land, the algorithm retrieves the parameters of underlying surface simultaneously with aerosol. In all situations, the approach is anticipated to achieve a robust retrieval of complete aerosol properties including information about aerosol particle sizes, shape, absorption and composition (refractive index). In order to achieve reliable retrieval from PARASOL observations even over very reflective desert surfaces, the algorithm was designed as simultaneous inversion of a large group of pixels within one or several images. Such multi-pixel retrieval regime takes advantage of known limitations on spatial and temporal variability in both aerosol and surface properties. Specifically the variations of the retrieved parameters horizontally from pixel-to-pixel and/or temporary from day-to-day are enforced to be smooth by additional a priori constraints. This concept is expected to provide satellite retrieval of higher consistency, because the retrieval over each single pixel will be benefiting from coincident aerosol information from neighboring pixels, as well, from the information about surface reflectance (over land) obtained in preceding and consequent observations over the same pixel. The paper provides in depth description of the proposed inversion concept, illustrates the algorithm performance by a series of numerical tests and presents the examples of preliminary retrieval results obtained from actual PARASOL observations. It should be noted that many aspects of the described algorithm design considerably benefited from experience accumulated in the preceding effort on developments of currently operating AERONET and PARASOL retrievals, as well as several core software components were inherited from those earlier algorithms.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/628f503da12fd3f385cff7ea64d6d6f97060cb4f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

In Global and Planetary Change

Citations in the corpus

Global observations of aerosol‐cloud‐precipitation‐climate interactions (2014, methodology): “To date, MISR provides a limited but near-global data set of aerosol type constraints for an extended period of time [Kahn et al., 2010]; complementary work using multiangle, multiwavelength, and polarization information from PARASOL is under way [Dubovik et al., 2011].”
Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm (2018, methodology): “The selected BRDF shape is a particular parameter set for the Rahman–Pinty– Verstraete (RPV) kernel (Rahman et al., 1993) that has been used as an initial guess for spectral multi-angle polarimetric aerosol remote sensing (Dubovik et al., 2011).”
Effects of internal mixing and aggregate morphology on optical properties of black carbon using a discrete dipole approximation model (2012, methodology): “…approach used in analyses of radiometric and polarimetric data requires a model of aerosol particle shape, and in the majority of studies the model of spherical or randomly oriented spheroids particles has been adopted (e.g., Deuze et al., 2001; Hasekamp et al., 2011; Dubovik et al., 2010).”
Directional Polarimetric Camera (DPC): Monitoring aerosol spectral optical properties over land from satellite observation (2018, background): “In recent years, with the progress of statistical optimization methods [39,40] and polarized surface models [41–44] , a new generation of multi-parameter POLDER inversion method has basi-”