Use of the MODIS imager to help deal with AIRS cloudy radiances

The assimilation of the Atmospheric InfraRed Sounder (AIRS) data is expected to improve the quality of NWP products. Currently, operational use of such data is limited to the cloud-free pixels or to the channels far above the clouds for cloudy pixels. This paper focuses on the validation of various cloud-detection schemes applied to AIRS data. The clouds are detected and characterized, in cloud-top and cover, by using the NESDIS, ECMWF, CO2-slicing and MLEV schemes. These four different AIRS cloud descriptions are evaluated by independent information retrieved with the Meteo-France cloud mask applied to MODIS data and taken as our reference. The validation for a ten-day period over the North-east Atlantic is presented. The use of satellite cloudy radiances is a great challenge for numerical weather prediction. Work is in progress to assimilate such data by using enhanced observation operators dealing with clouds. In this work, we try to contribute to this effort by investigating the linearity assumption of an observation operator, with a simple diagnostic cloud scheme, for different cloud types. Copyright © 2005 Royal Meteorological Society

[1]  Richard A. Frey,et al.  On Cloud Altitude Determinations from High Resolution Interferometer Sounder (HIS) Observations , 1990 .

[2]  William L. Smith,et al.  Improved Cloud Motion Wind Vector and Altitude Assignment Using VAS. , 1983 .

[3]  William L. Smith,et al.  AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems , 2003, IEEE Trans. Geosci. Remote. Sens..

[4]  Hung-Lung Huang,et al.  Application of Principal Component Analysis to High-Resolution Infrared Measurement Compression and Retrieval , 2001 .

[5]  Graeme Kelly,et al.  A satellite radiance‐bias correction scheme for data assimilation , 2001 .

[6]  Moustafa T. Chahine,et al.  Remote Sounding of Cloudy Atmospheres. I. The Single Cloud Layer , 1974 .

[7]  A. Simmons,et al.  The ECMWF operational implementation of four‐dimensional variational assimilation. I: Experimental results with simplified physics , 2007 .

[8]  A. Mcnally,et al.  A cloud detection algorithm for high‐spectral‐resolution infrared sounders , 2003 .

[9]  A. P. McNally,et al.  A note on the occurrence of cloud in meteorologically sensitive areas and the implications for advanced infrared sounders , 2002 .

[10]  W. Paul Menzel,et al.  The MODIS cloud products: algorithms and examples from Terra , 2003, IEEE Trans. Geosci. Remote. Sens..

[11]  Lihang Zhou,et al.  AIRS near-real-time products and algorithms in support of operational numerical weather prediction , 2003, IEEE Trans. Geosci. Remote. Sens..

[12]  Philippe Lopez,et al.  The capability of 4D‐Var systems to assimilate cloud‐affected satellite infrared radiances , 2004 .

[13]  D. Randall,et al.  A Semiempirical Cloudiness Parameterization for Use in Climate Models , 1996 .

[14]  Jun Li,et al.  Minimum Local Emissivity Variance Retrieval of Cloud Altitude and Effective Spectral Emissivity—Simulation and Initial Verification , 2004 .

[15]  Moustafa T. Chahine,et al.  Sea surface temperature measurements with AIRS: RTG.SST comparison , 2003, SPIE Optics + Photonics.

[16]  Florence Rabier,et al.  Cloud characteristics and channel selection for IASI radiances in meteorologically sensitive areas , 2004 .