Wednesday, 31 January 2024: 4:30 PM-6:00 PM
343 (The Baltimore Convention Center)
Submitters:
Tracy Fanara, CIRES @ NOAA/NWS/WPC/HMT, NWS/Space Weather Prediction Center, College Park, MD;
Ayumi Fujisaki-Manome, University of Michigan, School for Environment and Sustainability (SEAS), Ann Arbor, MI;
Greg Seroka;
John G. W. Kelley and
Shachak Pe'eri, NOAA, NOS/OCS/CSDL, Silver Spring, MD
Chair:
Tracy Fanara, CIRES @ NOAA/NWS/WPC/HMT, NWS/Space Weather Prediction Center, College Park, MD
The NOAA Unified Forecast System (UFS) is a proposed community-based, coupled comprehensive Earth modeling system that is designed to incorporate coastal hydrodynamic, hydrologic, and oceanographic forecast model core(s) into a simplified NOAA modeling suite. The UFS Coastal Applications Team (CAT) - Water Quantity set up three sub-application teams–marine navigation, risk reduction, and total water level–to set the foundation for the selection of an oceanographic model(s) to be part of the UFS that supports the marine navigation, coastal resilience, and disaster and risk mitigation communities. The three sub-application teams have developed consensus user requirements, developed criteria for selecting oceanographic models, selected a list of models for further evaluation, and recommended skill assessment guidelines for subsequent evaluation of the models.
The marine navigation sub-application team is now evaluating the coastal model cores, with NOAA partnering with academic collaborators to generate the model mesh; set up the models; run simulations for tides alone and then coupled to atmosphere, wave, sea ice, and hydrologic models; and then evaluate the model performance and accuracy based on selected criteria. A purpose is to build the coastal modeling communities around these models, and train the next generation of modelers and scientists, to support the UFS and other operational coastal oceanographic models and their applications.
We encourage oral and poster presentations on:
- Coastal modeling, including coupled earth-system models in the coastal zone, in support of the UFS CAT effort, including from academic, government, and industry testers, and from model developers
- Coastal ocean models and products supporting precision marine navigation, the Blue Economy, and other critical needs (e.g. water levels, ocean currents, surface waves)
- Coastal ocean studies for public safety, disaster and risk mitigation, and resilience for coastal economies and communities
- Coastal studies for ecological health, water quality, pollutant transport, invasive species, and impacts on industries (e.g. tourism and fisheries)
4:30 PM
12.1
Advanced Sea Ice Modeling for Integration into a Storm-Surge, Wave, and Ice Forecasting System for Alaska’s Coast
Ayumi Fujisaki-Manome, Univ. of Michigan, Ann Arbor, MI; and H. Hu, J. Wang, J. Westerink, D. Wirasaet, G. Ling, M. Choi, S. Moghimi, E. Myers, A. Abdolali, A. J. van der Westhuysen, K. Steffan, C. Dawson, C. Janzen, R. Bochenek, J. Lopez, and A. Abdolali
5:00 PM
12.3
Development and Code Infrastructure of The Coastal Modeling Framework Based on Unified Forecast System (UFS-Coastal)
Ufuk Turuncoglu, NCAR, Boulder, CO; NCAR, Boulder, CO; and P. Velissariou, S. Moghimi, Y. Sun, D. Wirasaet, J. Westerink, Y. J. Zhang, C. Lemmen, J. Qi, S. Li, C. Chen, H. Arango, and E. Myers
5:15 PM
12.4
Storm Surge Total Water Predictions Using the UFS-Coastal Modeling Framework: A Case Study for Hurricane Florence (2018)
Panagiotis Velissariou, NOAA/UCAR, Baton Rouge, LA; and U. Turuncoglu, S. Moghimi, Y. Sun, D. Wirasaet, J. Westerink, Y. J. Zhang, C. Lemmen, and E. Myers
5:30 PM
12.5
Total Water Level Twelve Year Hindcast Validation of STOFS-2D-Global, NOAA’s Fast Integrated Global Multi-Scale Multi-Process Operational Water Level Model
Joannes J. Westerink, University of Notre Dame, Notre Dame, IN; and C. Blakely, M. T. Contreras, G. Ling, D. Wirasaet, A. R. Cerrone, D. Wood, A. Tejaswi, W. J. Pringle, Z. Cobell, S. Bunya, R. Luettich, E. Myers, S. Moghimi, G. Seroka, Y. Funakoshi, L. Tang, L. Shi, K. M. Dresback, C. M. Szpilka, R. L. Kolar, M. B. Owensby, and C. Massey
5:45 PM
12.6
Advances in the ADCIRC Prediction System
Brian O. Blanton, Renaissance Computing Institute, Chapel Hill, NC; University of North Carolina at Chapel Hill, Chapel Hill, NC; and R. Luettich, S. Bunya, and Z. Cobell

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