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CASA and LEAD: Adaptive Cyberinfrastructure for Real-Time Multiscale Weather Forecasting
November 2006 (vol. 39 no. 11)
pp. 56-64
Beth Plale, Indiana University Bloomington
Dennis Gannon, Indiana University Bloomington
Jerry Brotzge, University of Oklahoma, Norman
Kelvin Droegemeier, University of Oklahoma, Norman
Jim Kurose, University of Massachusetts Amherst
David McLaughlin, University of Massachusetts Amherst
Robert Wilhelmson, University of Illinois at Urbana-Champaign
Sara Graves, University of Alabama in Huntsville
Mohan Ramamurthy, University Corporation for Atmospheric Research
Richard D. Clark, Millersville University
Sepi Yalda, Millersville University
Daniel A. Reed, University of North Carolina at Chapel Hill
Everette Joseph, Howard University
V. Chandrasekar, Colorado State University
Two closely linked projects aim to dramatically improve storm forecasting speed and accuracy. CASA is creating a distributed, collaborative, adaptive sensor network of low-power, high-resolution radars that respond to user needs. LEAD offers dynamic workflow orchestration and data management in a Web services framework designed to support on-demand, real-time, dynamically adaptive systems.
Index Terms:
Grid computing, System-evel science, CASA, LEAD, Web services, Weather Forecasting, Multiscale modeling
Citation:
Beth Plale, Dennis Gannon, Jerry Brotzge, Kelvin Droegemeier, Jim Kurose, David McLaughlin, Robert Wilhelmson, Sara Graves, Mohan Ramamurthy, Richard D. Clark, Sepi Yalda, Daniel A. Reed, Everette Joseph, V. Chandrasekar, "CASA and LEAD: Adaptive Cyberinfrastructure for Real-Time Multiscale Weather Forecasting," Computer, vol. 39, no. 11, pp. 56-64, Nov. 2006, doi:10.1109/MC.2006.375
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