Remote sensing from satellite or airborne platforms of land or sea surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to Target (surface) to Sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non lambertian surface conditions, and new absorbing species (CH4, N2O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-theart approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling we are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.

Abstract. Spectral radiances measured at the top of the atmosphere in a wide spectral range (0.55-2.13/xm) are used to monitor the aerosol optical thickness and the aerosol size distribution (integrated on the vertical column) of the ambient (undisturbed) aerosol over the oceans. Even for the moderate resolution imaging spectrometer (MODIS) wide spectral range, only three parameters that describe the aerosol loading and size distribution can be retrieved. These three parameters are not always unique. For instance, the spectral radiance of an aerosol with a bilognormal size distribution can be simulated very well with a single lognormal aerosol with an appropriate mean radius and width of distribution. Preassumptions on the general structure of the size distribution are therefore required in the inversion of MODIS data. The retrieval of the aerosol properties is performed using lookup table computations. The volume size distribution in the lookup table is described with two lognormal modes: a single mode to describe the accumulation mode particles (radius <0.5/xm) and a single coarse mode to describe dust and/or salt particles (radius >1.0/xm). Note that two accumulation modes may be present, one dominated by gas phase processes and a second dominated by cloud phase processes. The coarse mode can also be split into several partially overlapping modes describing maritime salt particles and dust. The aerosol parameters we expect to retrieve are r/, the fractional contribution of the accumulation mode to scattering; z, the spectral optical thickness; and rm, the mean particle size of the dominant mode. Additional radiative quantities such as asymmetry parameter and effective radius are derived subsequently. The impact of the surface conditions, wind speed and chlorophyll content on the retrieval is estimated, the impact of potential sources of error like the calibration of the instrument is also tested. The algorithm has been applied successfully to actual data sets provided by the Thematic Mapper on Landsat 5 and by the MODIS airborne simulator on the ER-2 and tested against ground and airborne measurements. A first estimate of the general accuracy is Az = _+0.05 +_ 0.05z (at 550 nm), Ar m = 0.3rm, At/ = _+0.25.

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...

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