P77 Demonstrating the utility of the Mesoscale Model Evaluation Testbed (MMET) in a research environment

Wolff, Jamie K., National Center for Atmospheric Research (NCAR), Pedro A. Jimenez, CIEMAT, Spain, Jimy Dudhia, NCAR, Gary Lackmann, North Carolina State University, Kelly Mahoney, Cooperative Institute for Research in the Environmental Sciences and National Oceanic and Atmospheric Administration, and Michelle Harrold, NCAR

A wide range of NWP science innovations are under development in the research community that have the potential to positively impact operational numerical weather prediction (NWP) models. The Developmental Testbed Center (DTC) helps facilitate the transition of these new innovations from research to operations (R2O); however, with the extensive number of new techniques available in the research community, it is critical to clearly define a testing protocol in order to streamline the R2O process. The DTC has defined such a process that relies on shared responsibilities of the researchers, the DTC and operational centers to test promising new mesoscale modeling code. As part of this process, the DTC instituted the Mesoscale Model Evaluation Testbed (MMET) which established a common testing framework to assist the research community with demonstrating the merits of new developments. MMET provides initialization and observation data sets for several case studies and week-long extended periods that can be used by the entire NWP community for testing and evaluation. The DTC has also utilized the MMET data sets to provide baseline results to the NWP community for select operational configurations. These results can be used to compare against updated versions of the WRF model or for testing sensitivities to different physical and dynamical configurations in order to progressively improve the forecast performance.

The NWP community is encouraged to engage in the use of MMET. This presentation will describe the components of this collaborative process through the use of three user-contributed examples. The first compared the performance of the WRF model as a result of introducing a better representation of the effects that topography exerts over the surface winds. The other two utilized different microphysics schemes to investigate the forecast performance for two different high impact events.