An improved algorithm for generating global window brightness temperaturesfrom multiple satellite infrared imagery

An improved algorithm for the generation of gridded window brightness tempe ratures is presented. The primary data source is the International Satellit e Cloud Climatology Project, level B3 data, covering the period from July 1 983 to the present. The algorithm rakes window brightness, temperatures fro m multiple satellites, both geostationary and polar orbiting, which have al ready been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latit ude-longitude grid. The gridding uses a hierarchical scheme based on spheri cal kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to down weight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data a re interpolated from adjacent processed images using a form of motion compe nsated interpolation based on the estimation of motion vectors using an hie rarchical block matching scheme. Examples are shown of the various stages i n the process. Also shown are examples of the usefulness of this type of da ta in GCM validation.