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The accuracy of temperature and moisture vertical profiles retrieved from infrared spectral measurements is dependent on accurate definition of all contributions from the observed “surface–atmosphere” system to the outgoing radiances. The associated inverse problem is ill posed. Instrument noise is a major contributor to errors in modeling spectral measurements. This paper considers an approach for noise reduction in the Geostationary Operational Environmental Satellite (GOES) spectral channels using spatial averaging that is based upon spectral characteristics of the measurements, spatial properties of atmospheric fields of temperature and moisture, and properties of the inverse problem. Spatial averaging over different fields of regard is studied for the GOES-8 sounder spectral bands. Results of the statistical analysis are presented.

journal of applied meteorology

Mathematical Aspects in Meteorological Processing of Infrared Spectral Measurements from the GOES Sounder. Part I: Constructing the Measurement Estimate Using Spatial Smoothing