Session 9 Coastal Modeling and Evaluation for the Unified Forecast System (UFS) and Other Applications II

Wednesday, 15 January 2025: 8:30 AM-10:00 AM
218 (New Orleans Ernest N. Morial Convention Center)
Host: 23rd Symposium on the Coastal Environment
Submitters:
Gregory Dusek, NWS, Silver Spring, MD and Gregory Seroka, NOAA, NOS/OCS/CSDL/CMMB, Silver Spring, MD
Cochairs:
Tracy Fanara, CIRES @ NOAA/NWS/WPC/HMT, NWS/Space Weather Prediction Center, College Park, MD; Saeed Moghimi, NOAA, NOS/OCS/CSDL/CMMB, Silver Spring, MD and Ayumi Fujisaki-Manome, University of Michigan, School for Environment and Sustainability (SEAS), Ann Arbor, MI

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 (e.g. total water level), 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 has been evaluating the coastal model cores for the past 1.5 years+, 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. Goals of this effort are to build the coastal modeling communities around these models; train the next generation of modelers and scientists, exposing them to operational model requirements and constraints; and 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)

Papers:
8:30 AM
9.1
Enhancing Great Lakes Ice Forecasting: Integration of CICE6 and the Unified Forecast System
Ayumi Fujisaki-Manome, NOAA/GLERL, Ann Arbor, MI; and O. doty, J. Kessler, and D. Titze

8:45 AM
9.2
Improving Representation of the Coastal Transition Zone for the Next-Generation Great Lakes Operational Forecast System
Dan Titze, GLERL, Ann Arbor, MI; and D. Cannon, M. Mattwig, B. C. Odstrchel, J. C. Feyen, and Y. Hong

9:00 AM
9.3
Enhancing Winter Wave Dynamics Understanding in Large Lakes: Integration of Buoy and SWOT Observations
Kate Pereira, Colorado School of Mines, Golden, CO; and E. J. Anderson and H. Henderson

9:15 AM
9.4
Development of a New Coupled Inland-Coastal 3D Operational Forecast System for Southeastern US Coast (SECOFS)
Yinglong Joseph Zhang, Virginia Institute of Marine Science, Williamsburg, VA; and J. Yoo, L. bloemendaa, S. Moghimi, A. Zhang, X. Chen, and T. Fanara

9:30 AM
9.5
Development of the East Florida Coastal Ocean Model (EFCOM)
Orion Witmer-Scharton, University of South Florida, St. Petersburg, FL; and Y. Liu, H. Xu, and S. John

9:45 AM
9.6
APSViz: Creating, managing, and visualizing data products from the ADCIRC Prediction System
Brian O. Blanton, Renaissance Computing Institute, Chapel Hill, NC; and R. Luettich, L. Stillwell, P. Owen, M. Watson, J. McManus, and J. L. Tilson

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner