CASA and LEAD: Adaptive Cyberinfrastructure for Real-Time Multiscale Weather Forecasting

  • Authors:
  • 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

  • Affiliations:
  • Indiana University Bloomington;Indiana University Bloomington;University of Oklahoma, Norman;University of Oklahoma, Norman;University of Massachusetts Amherst;University of Massachusetts Amherst;University of Illinois at Urbana-Champaign;University of Alabama in Huntsville;University Corporation for Atmospheric Research;Millersville University;Millersville University;University of North Carolina at Chapel Hill;Howard University;Colorado State University

  • Venue:
  • Computer
  • Year:
  • 2006

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Abstract

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.