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Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD

  • Beth Plale
  • Dennis Gannon
  • Dan Reed
  • Sara Graves
  • Kelvin Droegemeier
  • Bob Wilhelmson
  • Mohan Ramamurthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3515)

Abstract

LEAD is a large-scale effort to build a service-oriented infrastructure that allows atmospheric science researchers to dynamically and adaptively respond to weather patterns to produce better-than-real time predictions of tornadoes and other “mesoscale” weather events. In this paper we discuss an architectural framework that is forming our thinking about adaptability and give early solutions in workflow and monitoring.

Keywords

Doppler Radar Business Processing Execution Language Mesoscale Weather Current Weather Condition Hardware Performance Counter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Beth Plale
    • 1
  • Dennis Gannon
    • 1
  • Dan Reed
    • 2
  • Sara Graves
    • 3
  • Kelvin Droegemeier
    • 4
  • Bob Wilhelmson
    • 5
  • Mohan Ramamurthy
    • 6
  1. 1.Indiana University 
  2. 2.University of North CarolinaChapel Hill
  3. 3.University of Alabama Huntsville 
  4. 4.Oklahoma University 
  5. 5.University of Illinois Urbana Champaign 
  6. 6.UCAR, Unidata 

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