Each year across the United States, mesoscale weather events cause hundreds of deaths, routinely disrupt transportation and commerce, and result in annual economic losses greater than $13B. The ability to understand, forecast, and mitigate the impacts of such events is stifled by rigid information technology frameworks that cannot accommodate the real time, on-demand, and dynamically-adaptive needs of mesoscale weather research; its disparate, high volume data sets and streams; and its tremendous computational demands.

In response to this pressing need for a comprehensive national cyberinfrastructure in mesoscale meteorology, particularly one that can interoperate with those being developed in other cognate disciplines, a new National Science Foundation project – known as Linked Environments for Atmospheric Discovery (LEAD) – has been funded to facilitate the identification, access, preparation, assimilation, prediction, management, analysis, mining, and visualization of a broad array of meteorological data and model output, independent of format and physical location. A transforming element of LEAD is dynamic workflow orchestration and data management, which will allow use of analysis tools, forecast models, and data repositories as dynamically adaptive, on-demand systems that can a) change configuration rapidly and automatically in response to weather; b) continually be steered by new data; c) respond to decision-driven inputs from users; d) initiate other processes automatically; and e) steer remote observing technologies to optimize data collection for the problem at hand.

We describe in this paper the concepts, implementation plans, and expected impacts of LEAD, the underpinning of which will be a series of interconnected, heterogeneous virtual IT “Grid environments” designed to provide a complete framework for mesoscale meteorology research and education. A set of Integrated Grid and Web Services Testbeds will maintain a rolling archive of several months of recent data, provide tools for operating on them, and serve as an infrastructure (i.e., a mini Grid) for developing distributed Web services capabilities. Education Testbeds will integrate education and outreach throughout the entire LEAD program, and will help shape LEAD research into applications that are congruent with pedagogic requirements, national standards, and evaluation metrics. Ultimately, the LEAD environments will enable researchers, educators, and students to run atmospheric models and other tools in much more realistic, real time settings than is now possible, with emphasis on the use of locally or otherwise uniquely available data.