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New infrared satellite sounders will give greatly increased spectral resolution. The expected improvements, such as increased vertical resolution of temperature and humidity profiles in numerical weather prediction (NWP) models, will rely on accurate cloud detection. Simulation of the expected radiances requires infrared spectra from clouds with known physical properties. ARIES, the Airborne Research Interferometer Evaluation System, is mounted on the U.K. Meteorological Office's research aircraft to gather data in preparation for the Infrared Atmospheric Sounding Interferometer (IASI). ARIES has a 1 cm-1 wavenumber maximum spectral resolution over the range 600 to 3000 cm-1 wavenumbers (wavelength, 16(DOT)7 to 3(DOT)3 micrometer). Infrared data over various cloud types have been measured along with in-situ temperature and humidity profiles -- often including microphysical measurements from within the cloud. With spectra from adjacent cloud free air, these provide data to model the cloud signature for NWP assimilation cloud detection. The data readily demonstrate the basic spectral signatures due to cloud:reduction of brightness temperature in the window regions, slope varying with cloud properties, solar reflection in the near-infrared and the opaque cloud top in the CO2 sounding regions. A cloud detection algorithm is being developed that is intended as the first step in NWP processing. The algorithm takes advantage of the likely method of data compression to be used for IASI spectral data, using Empirical Orthogonal Functions (EOF). The EOFS used here are for cloud-free spectra and the cloud detection algorithm uses the magnitude of a residual -- which will reflect the presence of cloud, amongst other spectral features not represented in the EOFS. If additional EOFS representing cloud where added the cloud detection algorithm could also use these additional values which would be contained in the predictor for the EOFS.
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