Ivan Kostadinov, L. Grassi, G. Ballista, Giorgio Giovanelli, Rodolfo Guzzi, Daniele Bortoli, W. Di Nicolantonio, C. Lecerf, Andrea Petritoli, Fabrizio Ravegnani, S. Scarpanti
The satellite remote sensing instruments for climatic studies are required to have: (1) fast time sampling, (2) high spectral resolution, (3) high space resolution, (4) wide field of view, (5) broad spectral range, (6) simultaneous measurements in different spectral intervals and/or type of measurements (7) lack of movable mechanical parts, etc. Here it is described the main idea of an input optic of remote sensing UV-VIS-IR instrument aimed for climatic studies form the space. It is attempted with the proposed optical system to satisfy requirements (2), (6), (5), (7) and, at least partially, the rest ones.
The new generation of instruments to measure the atmosphere gives a large amount of information whose content is not immediately obvious. For this reason the information content (in the Shannon sense) and the number of degrees of freedom for signal related to parameters to retrieve, are crucial to carry out, for instance, the selection of microwindows or subset of channels for retrieval. This seems to be even true for the miniaturized devices like those obtained by MEOMS technologies that have high flexibility because are highly integrated. In this paper we present the methodologies to obtain the information content related to wavelengths selection from satellite with limb and nadir view with the MEOMS technology in mind.
KEYWORDS: Aerosols, Scattering, Atmospheric modeling, Clouds, Atmospheric particles, Data processing, Reflectivity, Rayleigh scattering, Simulation of CCA and DLA aggregates, Atmospheric optics
The GOME instrument, on board the ERS-2 satellite, has been designed in order to collect radiation over the entire wavelength region from 240 to 790 nm, in which several atmospheric species and also aerosols and clouds can be observed. A prototypal processor for the aerosol optical thickness retrieval and aerosol classification starting from GOME data has been developed. This processor has been devised as a tool to be used for the development of an operational GOME data processing chain. The implemented retrieval algorithm is based on a spectral reflectance fitting procedure of the measured radiances by GOME instrument. The maximum likelihood principle has been used in order to define the objective function. The ranking is made choosing the minimum among the least squares residuals computed for different aerosol classes. For each pixel the output of processor gives the aerosol optical thickness, the aerosol classification, a relative retrieval residual and a flag that indicates if the pixel is cloudy. The results of some different GOME real data sets are shown.
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