To support the goals above, the NOAA’s Next-Generation Global Prediction System program is funding the Global Model Test Bed (GMTB) for creating a software infrastructure and governance process for facilitating transition of research to operations specifically in the area of atmospheric physical parameterizations. To that end, GMTB has begun development of the Common Community Physics Package (CCPP), a collection of physical parameterizations with a well-described interface that lowers the bar for community scientists to contribute innovations to be considered for operational implementation. Community involvement is further enhanced by the flexibility of using the CCPP in non-NCEP models, including the GMTB single column model (SCM).
In order to evaluate innovations proposed for inclusion in the supported CCPP and for advancement toward operational consideration, GMTB has put in place a hierarchical test “harness” that can be used both by its own staff and by community scientists with access to NOAA computational platforms. This harness contains a variety of tools of multiple levels of complexity, ranging the GMTB SCM, case studies for diagnostics, and an automated workflow for running, postprocessing, and evaluating physics for global models. This harness was used to assess an advanced cumulus parameterization option for the NCEP Global Forecast System, the Grell-Freitas scale-aware scheme, in both cold start and cycled data assimilation modes, and is now available for conducting experiments with the developmental version of the GFS that employs the Finite-Volume in the Cubed-Sphere dynamical core. A highlight of this workflow is the ability to conduct a variety of assessments, ranging from traditional verification results (bias and error of meteorological variables such as temperature, moisture, and winds for surface and upper-air, stratified by regions of the globe including the tropical belt) to complementary information that provides additional insight into the model performance, including tropical cyclone and tropical cyclogenesis verification, surface radiation budget, and bias assessment against increments provided by the data assimilation system. Finally, to summarize the results and provide feedback to decision-makers, the score-card used by the U.S. National Weather Service for evaluating innovations prior to operational implementation is also available.
In this presentation, we will provide information on how the community can access the tools provided by GMTB and collaborate with its staff through the Developmental Testbed Center Visitor Program, which supports projects of interest for operational numerical weather prediction.