85th AMS Annual Meeting

Wednesday, 12 January 2005: 9:00 AM
Cyberinfrastructure to support real-time, end-to-end regional forecasting
Tom Baltzer, UCAR, Boulder, CO; and D. Lindholm, M. Ramamurthy, and B. Domenico
Poster PDF (152.2 kB)
For nearly a decade, the academic community has been running regionalized mesoscale models in near-realtime to support local needs in education, research, and outreach. The use of mesoscale modeling systems (e.g., MM5, WRF, RAMS, ARPS and Workstation Eta) in quasi-operational settings is continuing to grow and has resulted in over 30 such efforts at just U. S. universities. The success of real-time modeling programs like those at the University of Oklahoma/CAPS and University of Washington is well known, but many new efforts (e.g., University of Northern Iowa’s STORM Project) in the Unidata community are continually emerging.

Over the years, Unidata has developed several tools that have either directly or indirectly facilitated these modeling activities. For example, the community is using Unidata technologies such as the Internet Data Distribution (IDD) system, Local Data Manger (LDM), decoders, netCDF libraries, Thematic Realtime Environmental Distributed Data Services (THREDDS), GEMPAK, and the Integrated Data Viewer (IDV) in their real-time prediction efforts. In essence, these technologies for data reception and processing, local and remote access, cataloging, and analysis and visualization coupled with technologies from others in the community are becoming the foundation of a cyberinfrastructure to support an end-to-end regional forecasting system. To build on these capabilities, the Unidata Program Center is pleased to be a significant contributor to the Linked Environments for Atmospheric Discovery (LEAD) project, a NSF-funded multi-institutional large Information Technology Research effort. The goal of LEAD is to create an integrated and scalable framework for identifying, accessing, preparing, assimilating, predicting, managing, analyzing, mining, and visualizing a broad array of meteorological data and model output, independent of format and physical location. To that end, LEAD will create a series of interconnected, heterogeneous Grid environments to provide a complete framework for mesoscale research, including a set of integrated Grid and Web Services.

This talk will focus on the transition from today’s end-to-end systems into the types of systems that the LEAD project envisions.

Supplementary URL: