The project entitled Linked Environments for Atmospheric Discovery (LEAD) is a nine-institution effort funded by the National Science Foundation Information Technology Research Division to improve data access and prediction of mesoscale, high-impact weather. Over the past three years, scientists and engineers have worked together with students and faculty of the Millersville's Meteorology and BSE programs to democratize the implementation of high-resolution modeling and its subsequent visualization for literally anyone who yearns to interactively explore mesoscale phenomena. At the seam between expert scientists/developers and inexperienced end-users are twelve undergraduates at Millersville University (MU) who are currently serving as the core team for testing and providing feedback for numerous tools and Web services that have been developed by the LEAD team and ensuring that these prototypes (Integrated Test Beds) are congruent with the needs of educators and researchers. In addition, the MU team is leading the development of educational components that incorporate LEAD technology in a Web-based environment that invites guided inquiry.

Key activities described in this poster are: 1) Testing the LEAD portal; 2) Orchestrating the LEAD workflow engine; 3) Steering a high-resolution atmospheric numerical modeling system (WRF); 4) Visualizing model output using IDV; 5) Developing LEAD-to-Learn educational modules; 6) Building a LEAD ontology vocabulary for use in a data-mining (inquiry/discovery) service. The LEAD effort is poised to revolutionize the way end-users access data and model output; specify (steer) a model domain; assimilate data for model initialization; start a workflow made up of services that run across the TeraGrid; launch a high-resolution numerical prediction system, in this case, the Weather Research and Forecasting System (WRF); and visualize the output using Unidata's IDV. The MU team has been submitting jobs via the LEAD portal, testing the complete system, and reporting problems to the developers. The team has also created sophisticated Web-based educational wrappers to guide a user through the process while focusing on the investigation of important meteorological phenomena, such as jet streams, lake effect snowfalls, fronts, land/sea breeze circulations, skewT-logp diagrams, genesis and maintenance of squall lines and associated bow echoes, and the Q-G omega and height tendency equations. In addition, the learning modules include an IDV beginner's tutorial and a user-friendly online Portal for organizing LEAD products and for configuring, launching, and monitoring workflows (specialized, automated model runs).