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)

5 teams, 64 scientists/analysts

Multi-sector engagement (federal agency, academia, industry)

started 6/1/2010

21 manuscripts submitted for JGR Special Issue 2/2013

10 accepted 7/2013

http://testbed.sura.org

Coastal Inundation

Rick Luettich, UNC-CH

Gulf & Atlantic Coast

Shelf Hypoxia

John Harding, USMKatja Fennel, UD

Gulf of Mexico

Cyber Infrastructure Eoin Howlett, ASASara Graves, UAH

Testbed Advisory

Rich Signell, USGS

Evaluation Group

Estuarine HypoxiaChesapeake Bay

Carl Friedrichs, VIMSMarjy Friedrichs, VIMS

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

1.67 km

• 2D is fine, horizontal resolution is critical

Storm Surge / InundationStorm Surge / Inundation

• Models (2D & 3D) FVCOM/SWAVE SELFE/WWM ADCIRC/SWAN SLOSH/SWAN

• 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

• project web portal & front end for data archive

COMT 2.0 – StatusCOMT 2.0 – StatusSpring / Summer 2012

• COMT Terms of Reference – NOAA IOOS• Identification of Priorities – NOAA IOOS

December 2012• FFO by NOAA IOOS – with priorities• SURA solicited Letters of Interest, ~30 received

January 2013• SURA encouraged 16 project proposals• 14 proposals received, independently reviewed by SRAC

February 2013• 5 - 2yr projects selected for SURA’s proposal ($3.7M / 2 yrs)

May 2013• SURA responded to comments from NOAA IOOS review

June 2013• COMT approved for 2 years, probable start date 9/1/2013,

funding unspecified.

COMT 2.0 – Proposed ProjectsCOMT 2.0 – Proposed Projects

Chesapeake Bay Ecological Forecasting PI - Marjy Friedrichs (VIMS/W&M)

Integration of US West Coast Operational Coastal and Ocean Models PI - Alex Kuropov (Oregon State University).

Puerto Rico/U.S. Virgin Islands Surge and Wave Inundation Predictions PI - Andre Van der Westhuysen (NOAA/NCEP)

Northern Gulf of Mexico Ecological Forecasting PI - Katja Fennel (Dalhousie University).

“Cyberinfrastructure” PI - Eoin Howlette (ASA).