Thursday, 10 January 2013: 8:30 AM
Room 18B (Austin Convention Center)
, University of North Carolina at Chapel Hill, Morehead City, NC; and R. Beardsley, C. Chen, Q. Xu, H. Wang, Y. C. Teng
, D. Forrest, R. H. Weisberg, L. Zheng, Y. Huang, J. Westerink, P. C. Kerr, A. Donahue, A. T. Haase, J. Feyen, J. Rhome
, G. Crane
, E. Smith
, and B. Baltes
We have created the Coastal Ocean Modeling Testbed (COMT), a modeling community testbed to help accelerate progress in both research and the transition to operational use of coastal models. This testbed facilitates sharing of model grids, forcings and results, the archival of observational data and the information required to replicate model runs, and the development of cyber-infrastructure to efficiently access, visualize, skill assess, and evaluate model results. To date, COMT activities have focused on predicting hypoxia in the Chesapeake Bay, predicting hypoxia in the Northern Gulf of Mexico and predicting coupled waves, surge and inundation due to nor'easters in the Gulf of Maine and hurricanes in the Gulf of Mexico.
This presentation summarizes results from the coupled waves, surge and inundation component of the testbed. Models included in the analyses are ADCIRC, FVCOM, SELFE, SLOSH, SWAN, SWAVE and WWMII. Model skill assessments are performed using an extensive set of water level and wave time series from historical storms. Inter-model comparisons provide insight into the different model responses using the same forcing and similar model configurations. Evaluations include predicted water levels, inundation extents and execution speed. The impact of grid resolution on predicted inundation extents is evaluated by comparing model results from the base grid with those from a highly refined gird. Overall results quantify model performance expectations and resource requirements, thereby helping to clarifying their relative value and demands of different models and model implementations for operational use.
The testbed is led by the Southeastern Universities Research Association (SURA) with funding from the NOAA Integrated Ocean Observing System (IOOS) program. Computing resources have been provided by the National Science Foundation XSEDE program.
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