Each year across the United States, floods, tornadoes, hail, strong winds, lightning and winter storms—what scientists call mesoscale weather events—cause hundreds of deaths, routinely disrupt transportation and commerce, and result in annual economic losses greater than $13 billion. Unfortunately, the information technology framework that exist today cannot provide scientists with the ability to use real-time, on-demand mesoscale weather models that adapt to changing conditions. The Linked Environments for Atmospheric Discovery (LEAD) project aims to change that. The goal of LEAD is to create a series of interconnected, heterogeneous virtual IT grid environments that will serve as a complete framework for mesoscale weather research.

The RENCI Contribution

RENCI focuses on two areas for LEAD: performance monitoring and adaptation; and fault-tolerance, performability and recovery for the distributed LEAD environment. For the first, RENCI is developing site-level performance monitoring, focusing on monitoring and measuring the distributed data streams needed for data assimilation and distributed execution. The second focus area emphasizes fault monitoring and rescheduling to ensure continued execution of distributed applications. Our approach will enable the LEAD infrastructure to react to crucial changes in weather conditions or to changing resource availability allowing the system to proactively assess and detect anomalies.


National Science Foundation, Grant No. ATM-0331578.

Project Leader

  • Kelvin Droegemeier, University of Oklahoma

Co-Principal Investigators

  • Keith Brewster, Dan Weber, Min Xue, University of Oklahoma
  • V. Chandraseka, Colorado State University
  • Richard Clark, Sepi Yalda, Millersville University
  • Ben Domenico, Don Murray, Mohan Ramamurthy, Anne Wilson, University Corporation for Atmospheric Research (UCAR) Unidata Program
  • Dennis Gannon, Beth Plale, Indiana University
  • Sara Graves, Rahul Ramachandran, John Rushing, University of Alabama in Huntsville
  • Everette Josesph, Legand Burge, Jiang Li Howard University
  • Robert Wilhelmson, University of Illinois at Urbana-Champaign

Project Team

  • Brad Viviano
  • Gopi Kandaswamy


Daniel A. Reed, Lavanya Ramakrishnan et al. “Service-oriented Environments in Research and Education for Dynamically Interacting with Mesoscale Weather,” IEEE Computing in Science and Engineering, Nov-Dec 2005

Beth Plale, Dennis Gannon, Sara Graves, Daniel A. Reed, Kelvin Droegemeier, Robert Wilhelmson, Mohan Ramamurthy. “Towards Dynamically Adaptive Weather Analysis and Forecasting in LEAD,” Preprints, International Conference on Computer Science, May, 2005.

Daniel A. Reed, et al. “Linked Environments for Atmospheric Discovery (LEAD): A Cyberinfrastructure for Mesoscale Meteorology Research and Education,” Preprints , 20th Conference on Interactive Information Processing Systems for Meteorology, Oceanography and Hydrology, Seattle, WA, American Meteorology Society, 2004.

Lavanya Ramakrishnan and Daniel A. Reed. “Monitoring and orchestrating a mesoscale meteorological cyberinfrastructure” Preprints , 23rd Conference on Interactive Information Processing Systems for Meteorology, Oceanography and Hydrology, San Antonio, TX, American Meteorology Society, 2007.