Open AccessMesoscale Model Evaluation Testbed (MMET): A Resource for Transitioning NWP Innovations from Research to Operations (R2O)
Author(s) -
Jamie K. Wolff,
Michelle Harrold,
Tracy Hertneky,
Eric Aligo,
Jacob R. Carley,
Brad S. Ferrier,
Geoff DiMego,
Louisa Nance,
YingHwa Kuo
Publication year - 2016
Publication title -
bulletin of the american meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.367
H-Index - 197
eISSN - 1520-0477
pISSN - 0003-0007
DOI - 10.1175/bams-d-15-00001.1
Subject(s) - testbed , computer science , initialization , process (computing) , systems engineering , protocol (science) , mesoscale meteorology , resource (disambiguation) , numerical weather prediction , operations research , meteorology , environmental science , engineering , physics , programming language , medicine , computer network , alternative medicine , pathology , operating system
A wide range of numerical weather prediction (NWP) innovations are under development in the research community that have the potential to positively impact operational models. The Developmental Testbed Center (DTC) helps facilitate the transition of these innovations from research to operations (R2O). With the large number of innovations available in the research community, it is critical to clearly define a testing protocol 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 NWP advancements. As part of the first stage of this process, the DTC instituted the mesoscale model evaluation testbed (MMET), which established a common testing framework to assist the research community in demonstrating the merits of developments. The ability to compare performance across innovations for critical cases provides a mechanism for selecting the most promising capabilities for further testing. If the researcher demonstrates improved results using MMET, then the innovation may be considered for the second stage of comprehensive testing and evaluation (T&E) prior to entering the final stage of preimplementation T&E. MMET provides initialization and observation datasets for several case studies and multiday periods. In addition, the DTC provides baseline results for select operational configurations that use the Advanced Research version of Weather Research and Forecasting Model (ARW) or the National Oceanic and Atmospheric Administration (NOAA) Environmental Modeling System Nonhydrostatic Multiscale Model on the B grid (NEMS-NMMB). These baselines can be used for testing sensitivities to different model versions or configurations in order to improve forecast performance.