Award Abstract #0331480
Information Technology Research (ITR): Linked Environments for Atmospheric Discovery (LEAD)

NSF Org:	AGS Division of Atmospheric and Geospace Sciences
Initial Amendment Date:	September 16, 2003
Latest Amendment Date:	April 14, 2009
Award Number:	0331480
Award Instrument:	Cooperative Agreement
Program Manager:	Stephan P. Nelson AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences
Start Date:	October 1, 2003
Expires:	September 30, 2009 (Estimated)
Awarded Amount to Date:	$2234101
Investigator(s):	Beth Plale plale@cs.indiana.edu (Principal Investigator) Dennis Gannon (Former Principal Investigator) Suresh Marru (Co-Principal Investigator) Beth Plale (Former Co-Principal Investigator)
Sponsor:	Indiana University P O Box 1847 Bloomington, IN 47402 812/855-0516
NSF Program(s):	CYBERINFRASTRUCTURE, ITR LARGE GRANTS, PHYSICAL & DYNAMIC METEOROLOGY
Field Application(s):	0000099 Other Applications NEC, 0104000 Information Systems
Program Reference Code(s):	SMET, OTHR, HPCC, 9251, 9216, 9178, 7231, 4444, 1688, 1661, 1652, 0000
Program Element Code(s):	7231, 1688, 1525

ABSTRACT

Each year across the United States, floods, tornadoes, hail, strong winds, lightning, and winter storms cause hundreds of deaths and result in annual economic losses of more than $13B. Their mitigation is stifled by rigid information technology frameworks that cannot accommodate the unique real time, on-demand, and dynamically-adaptive needs of weather research.

Linked Environments for Atmospheric Discovery (LEAD), the foundation of which is a series of interconnected virtual "Grid environments," allows scientists and students to access, prepare, predict, manage, analyze, and visualize a broad array of meteorological information independent of format and physical location. A transforming element of LEAD is the ability for analysis tools, forecast models, and data repositories to function as dynamically adaptive, on-demand systems that can change configuration rapidly and automatically in response to the evolving weather; respond immediately to user decisions based upon the weather problem at hand; and steer remote observing systems to optimize data collection and forecast/warning quality.

LEAD will allow researchers, educators, and students to run atmospheric models and other tools in much more realistic, real time settings than is now possible, hasten the transition of research results to operations, and bring the pedagogical benefits of sophisticated atmospheric science tools into high school classrooms for the first time. Its capabilities will be integrated into dozens of universities and operational research centers that collectively reach 21,000 university students, 1800 faculty, and hundreds of operational practitioners.

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