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Ken Tanaka, Karen Woodberry, Harry Hendon, and Murry Salby


Synoptic images of the global cloud field have been created from measurements of infrared radiation taken aboard four geostationary and two polar-orbiting platforms simultaneously observing the earth's cloud field. A series of spatial and temporal interpolations, together with data reliability criteria, are used to map synoptic measurements from the geostationary satellites and asynoptic measurements from the polar-orbiting satellites. The synoptic global cloud imagery (GCI) that results has a horizontal resolution of 0.7° in longitude by 0.35° in latitude and a temporal resolution of 3 h, providing an unprecedented view of the global cloud pattern. Each composite image represents a nearly instantaneous snapshot of the entire earth's cloud field. Collectively, the composite imagery resolve, on a global basis, most of the variability inherent to organized convection, including several harmonics of the diurnal cycle. Because of its homogeneous properties, the GCI lends itself easily to a variety of space-time analyses useful for studying global cloud behavior.

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Karen Woodberry, Ken Tanaka, Harry Hendon, and Murry Salby


Synoptic images of the global cloud pattern composited from six contemporaneous satellites provide an unprecedented view of the global cloud field. Having horizontal resolution of about 0.5° and temporal resolution of 3 h, the global cloud imagery (GCI) resolves most of the variability of organized convection, including several harmonies of the diurnal cycle. Although the GCI has these attractive features, the dense and three-dimensional nature of that data make it a formidable volume of information to treat in a practical and efficient manner.

An interactive image analysis system (IAS) has been developed to investigate the space-time variability of global cloud behavior. In the IAS, data, hardware, and software are integrated into a single system providing a variety of space-time covariance analyses in menu-driven format. Owing to its customized architecture and certain homogeneous properties of the GCI, the IAS calculates such quantities with exceptional performance. Many covariance statistics are derived from three-dimensional data with interactive speed, allowing the user to interrogate the archive iteratively in a single session. The three-dimensional nature of those analyses and the speed with which they are performed distinguish the IAS from conventional image processing of two-dimensional data and suggest the IAS as a prototype for dealing with large volumes of multidimensional data as will be produced by NASA's Earth Observing System.

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