1NASA Langley Research Center, Hampton, VA 23681, USA
2Hampton University, VA 23668, USA and University of Wisconsin, Madison, WI 53706, USA
3EUMETSAT, Am Kavalleriesand 31, 64295 Darmstadt, Germany
4Met Office, Exeter, Devon, UK
5Science Systems and Applications, Inc., Hampton, VA 23666, USA
Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is an ultra-spectral satellite sensor with 8461 spectral channels. IASI spectra contain high information content on atmospheric, cloud, and surface properties. The instrument presents a challenge for using thousands of spectral channels in a physical retrieval system or in a Numerical Weather Prediction (NWP) data assimilation system. In this paper we describe a method of simultaneously retrieving atmospheric temperature, moisture, and cloud properties using all available IASI channels without sacrificing computational speed. The essence of the method is to convert the IASI channel radiance spectra into super-channels by an Empirical Orthogonal Function (EOF) transformation. Because the EOFs are orthogonal to each other, about 100 super-channels are adequate to capture the information content of the radiance spectra. A Principal Component-based Radiative Transfer Model (PCRTM) is used to calculate both the super-channel magnitudes and derivatives with respect to atmospheric profiles and other properties. A physical retrieval algorithm then performs an inversion of atmospheric, cloud, and surface properties in super channel domain directly therefore both reducing the computational need and preserving the information content of the IASI measurements.