The Atmospheric Infrared Sounder (AIRS) (Aumann et al. 2003; Chahine et al. 2006) was launched in 2002 on AQUA, the second of the EOS polar-orbiting satellites. The AIRS was the first of a new generation of meteorological advanced sounders able to provide hyperspectral data for operational and research use. Initially, we briefly review the first assimilation trials to use full spatial resolution and higher spectral resolution hyperspectral radiance data, available in real time from the AIRS. The result from these assimilation trials was significant improvement in forecast skill in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS), compared to the global system without AIRS data over both the northern and southern hemispheres. A second trial was an experiment which showed the advantage of using all AIRS fields of view (fov) in the analysis as opposed to the use of sampled fields of view (typically one-in-eighteen) often used by numerical weather prediction (NWP) centres. Another trial showed the benefit of using hyperspectral data with expanded spectral coverage. We then describe recent experiments where radiances, derived from cloudy AIRS fovs and which represent the radiance emanating from the clear part of the cloudy fov, have been assimilated for global NWP. The beneficial impact of these data in the GDAS is recorded. The impact is an initial indication of the potential benefit of using cloudy hyperspectral radiances routinely in global NWP. Background

The year 2000 marks the 40th anniversary of the launch of the first weather satellite. The images of cloud systems from the early satellites enabled forecasters to locate and monitor the movements of storms. Today's satellites provide a wealth of quantitative information about the constantly changing state of the Earth's atmosphere, ocean, and land surface. Significant strides are being made by operational centers around the world to effectively use these remotely-sensed observations in forecast models. The satellite measurements are used to initialize, provide boundary conditions for, and verify predictions of models. As an example of the state of the art, this paper reviews how satellite observations are used in the numerical weather and climate prediction models of the U.S. National Weather Service. The National Weather Service, National Centers for Environmental Prediction (NCEP), Environmental Modeling Center (EMC) develops regional and global weather prediction models, coupled ocean-atmosphere models for seasonal to interannual climate predictions, and a coastal ocean forecast model. A three dimensional variational data assimilation system is used to specify the initial conditions for the forecast models. Data from the following satellite instruments are currently used in one or more of these models: High Resolution Infrared Sounder (HIRS), Microwave Sounding Unit (MSU), Advanced Microwave Sounding Unit-A (AMSU-A), Geostationary Operational Environmental Satellites (GOES) sounder, GOES, METEOSAT, and Geostationary Meteorology Satellite (GMS) imagers, Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave/Imager (SSM/I), ESA Remote-sensing Satellite-2 (ERS-2) scatterometer, Solar Backscatter Ultraviolet Spectrometer/2 (SBUV/2), and Oceanic Topography Experiment (TOPEX) and ERS-2 altimeters.

M. Masutani, J. S. Woollen, R. Errico, Y. Xie, T. Zhu, H. Sun, J. Terry, R. Yang, S. Greco, N. Prive, E. Andersson, T. W. Schlatter, A. Stoffelen, F. Weng, O. Reale, L. Riishojgaard, G. D. Emmitt, S. Lord, Z. Toth, G.J. Marseille, V. Anantharaj, K. Fielding, G. McConaughy, S.Worley, C.-F. Shih, M. Yamaguchi, J. C. Jusem, C. Hill, P. J. Fitzpatrick, D. Devenyi, S. Weygandt, S. A. Wood, Y. Song, E. Liu,D. Groff, M. Hart, G.Gayno, A. da Silva, M. J. McGill, D. Kleist, Y. Sato, S. Boukabara,

Michiko Masutani, Erik Andersson, Joe Terry, Oreste Reale, Juan Carlos Jusem, Lars Peter Riishojgaard, Tom Schlatter, Ad Stoffelen, Jack Woollen, Steve Lord, Zoltan Toth, Yucheng Song, Daryl Kleist, Yuanfu Xie, Nikki Prive, Emily Liu, Haibing Sun, Dave Emmitt, Steve Greco, Sid A. Wood, Gert-Jan Marseille, Ron Errico, Runhua Yang, Gail McConaughy, Dezso Devenyi, Steve Weygandt, Adrian Tompkins, Thomas Jung, Valentine Anantharaj, Chris Hill, Pat Fitzpatrick, Fuzhong Weng, Tong Zhu, Sid Boukabara NOAA/NWS/NCEP/EMC, Camp Springs, MD NASA/GSFC, Greenbelt, MD NOAA/NESDIS/ORA, Camp Springs, MD European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK NOAA/Earth System Research Laboratory, Boulder, CO Simpson Weather Associates (SWA), Charlottesville, VA Royal Dutch Meteorological Institute (KNMI), DeBilt, Netherlands 8Mississippi State University/GRI, MS RS Information Systems (RSIS), VA Science Applications International Corporation (SAIC) $Goddard Earth Science and Technology Center, University of Maryland, Baltimore, MD QSS Group, Inc. *I. M. Systems Group, Inc. (IMSG) &Science Systems and Applications Inc (SSAI). MD @Cooperative Institute for Research in the Atmosphere (CIRA)/CSU