P58  Transitioning Promising New Mesoscale Innovations from    Research to Operations: Defining a Process to Bridge the     ÒValley of DeathÓ

Wolff, Jamie K., Louisa B. Nance,  Barbara G. Brown and Ying-Hwa Kuo, National Center for Atmospheric Research, Brad S. Ferrier, National Centers for Environmental Prediction, and Clifford F. Mass, University of Washington

To facilitate the transition of new science innovations from research to operations (R2O), the Developmental Testbed Center (DTC) encourages the user community to contribute new innovations back to the code base.  Through this process, a crucial aspect of the DTC mission can be exercised: extensive testing and evaluation of promising codes emerging from the research community can be performed in a common framework to demonstrate the potential of new science and technologies for use in operations.  For codes to progress from the research to operational realm, several stages of testing must occur.  In an effort to streamline the R2O process, the DTC has laid out a testing protocol to engage the research community in the steps necessary for preparing and nominating mesoscale modeling code deemed ready for extensive DTC testing and evaluation in an operationally similar environment.  Briefly, the first stage of testing will be conducted by the researchers on high-impact or field program case studies.  In an effort to provide a common framework for researchers to demonstrate the merits of new developments, the DTC is establishing the Mesoscale Model Evaluation Testbed (MMET), which will provide initialization and observation data sets that can be used by the entire user community for testing and evaluation at this initial stage.  The DTC will utilize the same data sets from the MMET to provide baseline results to the research community for specific operational configurations.  If improved forecast accuracy is shown during the first stage of testing using reasonable compute resources, the innovation may be recommended to continue on to the second stage of testing.  The second stage of testing will be conducted by the DTC and would be more extensive in nature and potentially include data assimilation cycling depending on the target application.  Along with sharing the extensive test results with the user community, information will be shared with interested operational entities.  The ultimate decision to proceed to the pre-implementation testing phase would be based on a variety of factors, including forecast performance and computational resource requirements.  Through this process, the goal is to accelerate the rate at which new technology is infused into operational weather forecasting.