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Detailed Analysis of Composited Digital Radar and Satellite Data

David W. ReynoldsDepartment of Atmospheric Science, Colorado State University, Ft. Collins, Colo. 80523

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Eric A. SmithDepartment of Atmospheric Science, Colorado State University, Ft. Collins, Colo. 80523

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A technique is developed to digitally composite satellite and radar imagery in a common coordinate reference frame. Results obtained from using Geosynchronous Operational Environmental Satellite (GOES) visible and infrared data, 5 cm radar data, and recording raingage data are presented. The composite displays are created on Colorado State University's All Digital Video Imaging System for Atmospheric Research (ADVISAR), an interactive image processing system that uses modern high fidelity digital video display technology. An efficient methodology based on analytic transforms for remapping dissimilar digital image formats into common map projections is discussed. Applications of multi-sensor composite images are demonstrated with the use of two case studies. The technique is shown to enhance our understanding of a) convective development, b) organization of mesoscale features as they relate to the synoptic scale, c) severe storm development, and d) precipitation mechanisms. Our final comments concern the compositing technique's potential for on-line interactive forecast systems, particularly in terms of an embedding approach.

A technique is developed to digitally composite satellite and radar imagery in a common coordinate reference frame. Results obtained from using Geosynchronous Operational Environmental Satellite (GOES) visible and infrared data, 5 cm radar data, and recording raingage data are presented. The composite displays are created on Colorado State University's All Digital Video Imaging System for Atmospheric Research (ADVISAR), an interactive image processing system that uses modern high fidelity digital video display technology. An efficient methodology based on analytic transforms for remapping dissimilar digital image formats into common map projections is discussed. Applications of multi-sensor composite images are demonstrated with the use of two case studies. The technique is shown to enhance our understanding of a) convective development, b) organization of mesoscale features as they relate to the synoptic scale, c) severe storm development, and d) precipitation mechanisms. Our final comments concern the compositing technique's potential for on-line interactive forecast systems, particularly in terms of an embedding approach.

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