22 July 2013 U.S. IOOS Coastal Ocean Modeling Testbed IOOS COASTAL OCEAN MODELING TESTBED (COMT) Rick Luettich, University of North Carolina at Chapel Hill Don Wright, Liz Smith, Southeast Univ. Research Association (SURA) Becky Baltes, NOAA Integrated Ocean Observing System Office Rich Signell, US Geological Survey
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22 July 2013 U.S. IOOS Coastal Ocean Modeling Testbed IOOS COASTAL OCEAN MODELING TESTBED (COMT) Rick Luettich, University of North Carolina at Chapel.
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22 July 2013
U.S. IOOS Coastal Ocean Modeling Testbed
IOOS COASTAL OCEAN MODELING TESTBED (COMT)
Rick Luettich, University of North Carolina at Chapel Hill
Don Wright, Liz Smith, Southeast Univ. Research Association (SURA)Becky Baltes, NOAA Integrated Ocean Observing System Office
Rich Signell, US Geological Survey
COMT BeginningCOMT Beginning
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“Certain ocean prediction system development and evaluation activities involve federal, academic and private sector participants,…….Examples include: …..; design and operation of model testbeds (“model evaluation environments”);…”
Ocean.US. 2008. The Integrated Ocean Observing System (IOOS) Modeling and Analysis Workshop Report, Ocean.US Publication No. 18, 21 pp.
COMT MissionCOMT Mission
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Targeted R&D to accelerate the transfer of scientific and technical advancements to improved operational products and services
COMT MissionCOMT Mission
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Targeted R&D to accelerate the transfer of scientific and technical advancements to improved operational products and services
•Research to Operations
COMT MissionCOMT Mission
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Targeted R&D to accelerate the transfer of scientific and technical advancements to improved operational products and services
•Research to Operations•Operations to Research
COMT CharacteristicsCOMT Characteristics
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• Operational broadly interpreted = predictive?• Quantitative data on the behavior and implementation
requirements of models• Organized archive of observations, model inputs and model
results• Tools that leverage or define community standards - efficient
access, visualization, skill assessment and other evaluation of models
• Research environment where researchers and operational agencies can work together
COMT V1.0COMT V1.0
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Led by Southeast Universities Research Association (SURA)
Estuarine Hypoxia – Chesapeake BayEstuarine Hypoxia – Chesapeake BayProject Lead: Carl Friedrichs -> Marjy Friedrichs, VIMSEvaluate coupled hydrodynamic and water quality models in use or in consideration for use for operations (incl. regulation)
• 5 Hydrodynamic models• 5 Biogeochemical / DO models• Improvements in model skill for
predicting time & location of hypoxia• Ensemble mean better skill
predicting “dead zone”• Transition of simple DO
model to NOAA CSDL CBOFS model
Shelf Hypoxia – Northern Gulf of MexicoShelf Hypoxia – Northern Gulf of Mexico
Project Lead: John Harding, NGI -> Katja Fennel, DalhousieEvaluate and advance a coupled hydrodynamic and biogeochemical model for nowcast / forecasts of shelf physical and ecosystem processes.
• Improved skill in hydrologic conditions, not in dissolved oxygen
• Hypoxia sensitive to stratification and biogeochemical submodel
• Considerable sensitivity to uncertainty in physical model forcings
TAMU ROMS NOAA NGOM
NRL IASNFS NCOM NRL/FSU HYCOM
• Initiation / evolution of hypoxic events on synoptic timescales
Storm Surge / InundationStorm Surge / InundationProject Lead: Rick Luettich, UNCEvaluate the behavior and implementation requirements of coastal models of tides, surge, waves, inundation
• Models FVCOM/SWAVE SELFE/WWM ADCIRC/SWAN WWIII
• Wave-current interaction major impact on coastal circulation
Nested
• Gulf of Maine – extratropical storms in 2005, 2007, 2010• Nested unstructured grids
• Significance of “Surge Forerunner” - Hurricane Ike
• Unstructured models comparable results, ADCIRC fastest & most features
• SLOSH overall fastest, least accurate
• Gulf of Mexico – hurricanes Rita (2005), Ike (2008)
Cyber-InfrastructureCyber-InfrastructureProject Lead: Eoin Howlett, ASA & Sarah Graves, UAHDevelop data standards, particularly for unstructured gridsDevelop a testbed data archive and tools
• access to observed data, forcing, model input• deliver results for model
analysis, comparison, visualization, and evaluation – NCTOOLBOX, IMEDS
• capabilities to manipulate model output on unstructured grids