Abstract
There are two different approaches to retrieve the air temperature and humidity fields from remote sensing data. One approach is a conventional one and it based on 1-D inverse problem solution. This approach assumes the two-stage procedure: vertical profile retrieval from radiance data and optimal interpolation of retrieval values. Another approach is based on the irradiance data direct assimilation within the objective analysis of these fields. The first approach is more widely used because of the international distribution of SATEM data through the meteorological data network. But, unfortunately, the retrieved temperature and atmospheric constituents profiles contain highly correlated noise components that prevents the increase of the satellite data information content along with sensor sensitivity improvement.
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© 2003 Springer Science+Business Media Dordrecht
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Pokrovsky, O.M. (2003). The Correlation Features of the Inverse Problem Solution in Atmospheric Remote Sensing. In: Swinbank, R., Shutyaev, V., Lahoz, W.A. (eds) Data Assimilation for the Earth System. NATO Science Series, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0029-1_18
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DOI: https://doi.org/10.1007/978-94-010-0029-1_18
Publisher Name: Springer, Dordrecht
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