The WRF system will be the initial focus of the DTC, but the vision is ultimately to accommodate other developing modeling systems, such as a unified (mesoscale to global) capability. Consistent with the WRF goals, the DTC goals include facilitating the transition of new NWP and data assimilation research capabilities into an efficient and effective weather forecasting process. A key objective of the DTC is to offer to the research community a functionally equivalent operational environment to test and evaluate new NWP methods, without interfering with day-to-day operational forecasting. The DTC will be a key component in the WRF process of testing new model code and numerical forecasting techniques such that promising enhancements can be considered for implementation at the operational forecast centers. The DTC will allow researchers to run post-analyses of poor weather forecasts with complete operational NWP initialization data sets, and to perform extended periods of "retrospective" and real-time numerical weather forecasts with new NWP configurations in a fully cycled manner- neither of which is practical for the research community to do currently. The DTC will also facilitate the development of advanced tools for data access, quality control, verification, and high-performance computing supportive of the WRF program, as well as sophisticated user support services in the application of these tools.
The proposed DTC facility will be located in Boulder, Colorado at the National Center for Atmospheric Research (NCAR), but operated jointly by NCAR and NOAA where it will take advantage of existing modeling, data assimilation, high-performance computing, and data management expertise and facilities within the Boulder area. At the same time, the DTC will reach out to the broader research community for additional expertise, participation, and computational resources. During the WRF development and evaluation process, researchers will be invited, through a peer-review proposal process, to work directly with DTC scientific and technical personnel, including on-site representation by members of the operational NWP community. A systematic, rigorous testing process will lead to demonstrated improvements in forecast accuracy of new NWP modeling and data assimilation systems prior to consideration for final testing and implementation at the operational centers.