Susskind and Atlas (2004) show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes.
Further improvements in AIRS sounding methodology have been made since the results shown in Atlas and Susskind (2004). A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, will be delivered to the Goddard DAAC for production of AIRS derived products, including clear column radiances. Results will be shown of the accuracy and spatial distribution of temperature-moisture profiles and clear columm radiances derived from AIRS/AMSU-A as a function of fractional cover using the Version 4.0 algorithm.
References
Susskind, J., C.D. Barnet, and J.M. Blaisdell, "Retrieval of Atmospheric and Surface Parameters from AIRS/AMSU/HSB Data in the Presence of Clouds," IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 2, 2003.
Susskind, J., R. Atlas, "Atmospheric Soundings from AIRS/AMSU/HSB," SPIE Defense and Security Symposium, Orlando, Florida, April 12-16, 2004.
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