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

Abstract

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 microsatellite 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.Correspondence to: O. Dubovik (dubovik@loa.univ-lille1.fr)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 o...

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

“…The V1 land AOD had negative biases of −0.1 for low SD and −0.05 for high SD and was persistently affected by surface reflectance issues and/or cloud contamination. Note that some recent aerosol retrieval algorithms have adopted a statistical spatial smoothness constraint for AOPs in the inversion procedure to improve accuracy (Dubovik et al, 2011;Xu et al, 2016).…”

Comparative assessment of GRASP algorithm for a dust event over Granada (Spain) during ChArMEx-ADRIMED 2013 campaign

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“…These approaches were the LIdar-Radiometer Inversion Code (LIRIC; Chaikovsky et al, 2008Chaikovsky et al, , 2012Chaikovsky et al, , 2016, which provides vertical distribution of volume concentrations, and the Generalized Aerosol Retrieval from Radiometer and Lidar Combined data (GARRLiC; Lopatin et al, 2013), which also allows the retrieval of SSA and RI. Currently, GARRLiC algorithm is included in the Generalized Retrieval of Atmosphere and Surface Properties inversion code (GRASP; Dubovik et al, 2011). However, very few studies have attempted to evaluate this recently developed inversion algorithm Bovchaliuk et al, 2016;Torres et al, 2017;Román et al, 2017), and therefore their evaluation under different atmospheric conditions is still necessary.…”

Exploration of a Polarized Surface Bidirectional Reflectance Model Using the Ground-Based Multiangle SpectroPolarimetric Imager

“…Measurements of aerosol abundances and microphysical properties are necessary for monitoring their distribution and for providing insight into the physical processes governing their environmental impacts. Theoretical sensitivity studies, e.g., [3,4] and observations from aircraft and spacecraft suggest that passive remote sensing of aerosol microphysics (using reflected sunlight as the illumination source) benefits from multispectral and multiangular observations, and is enhanced through incorporation of polarization, e.g., [5][6][7][8][9][10]. Radiative transfer calculations [3] imply that in order to meet the stringent requirements of aerosol climate impact assessments [11], inclusion of polarimetry with uncertainty in degree of linear polarization (DOLP) less than ±0.005 improves significantly upon the information content of multiangular spectral intensity measurements.…”