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Jamie K. Wolff, Michelle Harrold, Tracy Hertneky, Eric Aligo, Jacob R. Carley, Brad Ferrier, Geoff DiMego, Louisa Nance, and Ying-Hwa Kuo

Abstract

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.

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Jeffrey Beck, John Brown, Jimy Dudhia, David Gill, Tracy Hertneky, Joseph Klemp, Wei Wang, Christopher Williams, Ming Hu, Eric James, Jaymes Kenyon, Tanya Smirnova, and Jung-Hoon Kim

Abstract

A new hybrid, sigma-pressure vertical coordinate was recently added to the Weather Research and Forecasting (WRF) Model in an effort to reduce numerical noise in the model equations near complex terrain. Testing of this hybrid, terrain-following coordinate was undertaken in the WRF-based Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) models to assess impacts on retrospective and real-time simulations. Initial cold-start simulations indicated that the majority of differences between the hybrid and traditional sigma coordinate were confined to regions downstream of mountainous terrain and focused in the upper levels. Week-long retrospective simulations generally resulted in small improvements for the RAP, and a neutral impact in the HRRR when the hybrid coordinate was used. However, one possibility is that the inclusion of data assimilation in the experiments may have minimized differences between the vertical coordinates. Finally, analysis of turbulence forecasts with the new hybrid coordinate indicate a significant reduction in spurious vertical motion over the full length of the Rocky Mountains. Overall, the results indicate a potential to improve forecast metrics through implementation of the hybrid coordinate, particularly at upper levels, and downstream of complex terrain.

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Tammy M. Weckwerth, Lindsay J. Bennett, L. Jay Miller, Joël Van Baelen, Paolo Di Girolamo, Alan M. Blyth, and Tracy J. Hertneky

Abstract

A case study of orographic convection initiation (CI) that occurred along the eastern slopes of the Vosges Mountains in France on 6 August 2007 during the Convective and Orographically-Induced Precipitation Study (COPS) is presented. Global positioning system (GPS) receivers and two Doppler on Wheels (DOW) mobile radars sampled the preconvective and storm environments and were respectively used to retrieve three-dimensional tomographic water vapor and wind fields. These retrieved data were supplemented with temperature, moisture, and winds from radiosondes from a site in the eastern Rhine Valley. High-resolution numerical simulations with the Weather Research and Forecasting (WRF) Model were used to further investigate the physical processes leading to convective precipitation.

This unique, time-varying combination of derived water vapor and winds from observations illustrated an increase in low-level moisture and convergence between upslope easterlies and downslope westerlies along the eastern slope of the Vosges Mountains. Uplift associated with these shallow, colliding boundary layer flows eventually led to the initiation of moist convection. WRF reproduced many features of the observed complicated flow, such as cyclonic (anticyclonic) flow around the southern (northern) end of the Vosges Mountains and the east-side convergent flow below the ridgeline. The WRF simulations also illustrated spatial and temporal variability in buoyancy and the removal of the lids prior to convective development. The timing and location of CI from the WRF simulations was surprisingly close to that observed.

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Barbara Brown, Tara Jensen, John Halley Gotway, Randy Bullock, Eric Gilleland, Tressa Fowler, Kathryn Newman, Dan Adriaansen, Lindsay Blank, Tatiana Burek, Michelle Harrold, Tracy Hertneky, Christina Kalb, Paul Kucera, Louisa Nance, John Opatz, Jonathan Vigh, and Jamie Wolff

Capsule summary

MET is a community-based package of state-of-the-art tools to evaluate predictions of weather, climate, and other phenomena, with capabilities to display and analyze verification results via the METplus system.

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