13A.4 The Community Leveraged Unified Ensemble in the 2017 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

Thursday, 11 January 2018: 2:15 PM
Room 17A (ACC) (Austin, Texas)
Adam J. Clark, NSSL, Norman, OK; and I. L. Jirak, S. R. Dembek, S. J. Lin, L. M. Harris, M. J. Morin, R. M. Hepper, G. J. Creager, M. Xue, F. Kong, K. W. Thomas, K. Brewster, T. A. Supinie, Y. Jung, K. R. Fossell, J. Carley, G. Romine, B. T. Gallo, B. Roberts, A. R. Dean, D. A. Imy, C. R. Alexander, G. Manikin, J. S. Kain, S. J. Weiss, and R. A. Sobash

The 2017 Spring Forecasting Experiment (SFE2017) was conducted 1 May – 2 June with participation from more than 80 forecasters, researchers, and model developers from around the world. The primary goals of the HWT are to accelerate the transfer of promising new tools from research to operations, to inspire new initiatives for operationally relevant research, and to identify and document sensitivities and the performance of state-of-the art convection-allowing experimental modeling systems (CAMs). As in previous experiments, a very large suite of experimental CAM guidance contributed by our collaborators was central to the generation of experimental severe weather outlooks and model evaluation activities. Furthermore, for the second year, these contributions have been coordinated into a single ensemble framework called the Community Leveraged Unified Ensemble (CLUE). The 2017 CLUE was constructed by having all groups agree on a set of model specifications (e.g., grid-spacing, vertical levels, domain size, etc) so that the simulations contributed by each group could be used in carefully designed controlled experiments. This design once again allowed us to conduct several experiments geared toward identifying optimal configuration strategies for CAM-based ensembles, and is especially well timed to help inform the design of near future operational systems, which are rapidly being developed. The 2017 CLUE included 81 members using 3-km grid-spacing that allowed a set of 6 unique experiments. The experiments included comparisons of different data assimilation methods, as well as evaluations of the Finite Volume Cubed Sphere Model (FV3) at convection-allowing scales. This talk will provide an overview of the 2017 CLUE and highlight noteworthy results from SFE2017.
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