ALGORITHM FOR RETRIEVAL OF INTEGRATED WATER VAPOR IN ATMOSPHERE OVER LAND FROM SATELLITE-BASED SPECTRORADIOMETER DATA

The fast algorithm is proposed for retrieving the atmospheric water vapor maps from multi-spectral images of the Earth captured by Ocean and Land Colour Instrument (OLCI) onboard European research satellite Sentinel-3. The algorithm is based on the multiple regressions between top of atmosphere spectral reflectance, geometrical parameters of satellite scene (solar and view angles) and total water vapor content in atmosphere. The regression equation is derived from the Monte-Carlo radiative transfer model taking into account experimental data on the variability of optical characteristics of the atmosphere and underlying surface. The equations includes top of atmosphere reflectance in near-IR water and oxygen absorption channels together with atmospheric transparent window channels of OLCI to exclude the impact of the surface spectral reflectance and the ground air pressure on the accuracy of atmospheric water vapor remote sensing. The algorithm has been tested on the data of OLCI prototype - Medium Resolution Imaging Spectrometer (MERIS). An ability of the developed algorithm to retrieve of the water vapor spatial distribution without the need for subsatellite data and digital elevation models is shown with an example of MERIS images for the territory of East Europe. A good correspondence is achieved between the MERIS and AERONET (Aerosol Robotic Network) data (standard deviation of integrated water vapor 1.24 kg/m²).

водяной пар, многоспектральные снимки Земли, спутниковая аппаратура Sentinel-3 OLCI, перенос излучения в атмосфере, спектральные коэффициенты яркости, уравнение множественной регрессии, оперативный алгоритм, water vapor, multi-spectral images of the Earth, satellite instrument Sentinel-3 OLCI, atmospheric radiative transfer, top of atmosphere reflectance, multiple regression equation, operational algorithm

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