On 1 October 2003, the National Science Foundation funded a Large Information Technology Research (ITR) grant known as Linked Environments for Atmospheric Discovery (LEAD). A multi-disciplinary effort involving 9 institutions and more than 100 scientists, students and technical staff, LEAD is creating an integrated, scalable framework in which meteorological analysis tools, forecast models, and data repositories can operate as dynamically adaptive, on-demand, grid-enabled systems that a) change configuration rapidly and automatically in response to weather; b) respond to decision-driven inputs from users; c) initiate other processes automatically; and d) steer remote observing technologies to optimize data collection for the problem at hand.

LEAD has adopted a grid and web service-oriented architecture with two principal objectives:

· To lower the entry barrier for using, and increase the sophistication of problems that can be addressed by, complex end-to-end weather analysis and forecasting/simulation tools.

· To improve our understanding of and ability to detect, analyze and predict mesoscale atmospheric phenomena by interacting with weather in a dynamically adaptive manner. To address these severe limitations, LEAD is

LEAD comprises a complex array of services, applications, interfaces, and local and remote computing, networking and storage resources – so-called environments – that can be used in a stand-alone fashion or linked together in workflows to study mesoscale weather; thus the name “Linked Environments for Atmospheric Discovery.” This framework provides users with an almost endless set of capabilities ranging from simply accessing data and perhaps visualizing it to running highly complex and linked data ingest, assimilation and forecast processes in real time and in a manner that adjusts dynamically to inputs as well as outputs.

Now almost three years into its five-year life as an NSF ITR grant, LEAD unveiled its first integrative test bed in July, 2006 as part of the tri-annual Unidata Users Workshop. We describe in this paper the paradigm shift being ushered in by LEAD through the use of a grid and web service-oriented architecture that empowers users to complete in a few minutes the sorts of experiments that typically require weeks or months to configure (e.g., launching a WRF forecast on demand with a grid spacing, domain location, duration, observational data and other options specified by the user, followed by visualization and analysis of the output). We propose to conduct a live demonstration of the LEAD system at the beginning of the presentation by configuring and launching a WRF forecast on the TeraGrid and then reviewing the results at the conclusion of the session. User feedback from the Unidata Workshop will be described as well as future plans including the application of LEAD technologies in the National Collegiate Forecast Contest, the WRF Developmental Test Bed Center, and the annual NSSL/SPC Spring Forecast Experiment.