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ABSTRACT

Aires et al. 2002

Aires, F., A. Chédin, N. Scott, and W.B. Rossow, 2002: A regularized neural network approach for retrieval of atmospheric and surface temperatures with the IASI instrument. J. Appl. Meteorol., 41, 144-159, doi:10.1175/1520-0450(2002)041<0144:ARNNAF>2.0.CO;2.

In this paper, a fast atmospheric and surface temperature retrieval algorithm is developed for the high resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. This algorithm is constructed on the basis of a neural network technique that has been regularized by introduction of a priori information. The performance of the resulting fast and accurate inverse radiative transfer model is presented for a large diversified dataset of radiosonde atmospheres including rare events. Two configurations are considered: a tropical-airmass specialized scheme and an all-air-masses scheme.

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