Super-Regional Testbed for Improving Forecasts of Environmental Processes for the U.S. Atlantic and Gulf of Mexico Coasts The Role of the SURA Testbed in the Improvement of U.S. Coastal and Estuarine Prediction John Harding, Northern Gulf Institute Carl Friedrichs, Virginia Institute of Marine Science Rick Luettich, University of North Carolina, Chapel Hill Rich Signell, United States Geological Survey Coastal Zone July2011 U.S.

1.Build a common infrastructure for access, analysis and visualization of all ocean model data produced by the Federal Backbone and the IOOS Regions. 2.Develop skill metrics and assess models in three different regions and dynamical regimes 3.Transition models, tools, toolkits and other capabilities to federal operational facilities 4.Build stronger relationships between academia and operational centers through collaboration Super-Regional Testbed Goals U.S.

Testbed Management Testbed Advisory Evaluation Group Shelf Hypoxia Gulf of Mexico Estuarine Hypoxia Chesapeake Bay Cyber Infrastructure Coastal Inundation Gulf and East Coast IOOS Testbed Team Structure Rick Luettich, UNC-CHJohn Harding, NGI Carl Friedrichs, VIMS Rich Signell, USGS Eoin Howlett, ASA Don Wright, SURA Doug Levin, NOAA/IOOS Liz Smith, SURA 25 members 21 members 20 members 17 members 8 members U.S.

Inundation Extra-tropical – Gulf of Maine Tropical – Gulf of Mexico - 4 models: 3 unstructured grid +1 structured grid - Coupled wave-storm surge-inundation (TWL) - Consistent forcing, validation and skill assessment using existing IMEDS tool -Extensive observational data sets for historical storms Ike and Rita in standard formats -SURA has secured NSF TeraGrid supercomputer resources Inundation Extra-tropical – Gulf of Maine Tropical – Gulf of Mexico - 4 models: 3 unstructured grid +1 structured grid - Coupled wave-storm surge-inundation (TWL) - Consistent forcing, validation and skill assessment using existing IMEDS tool -Extensive observational data sets for historical storms Ike and Rita in standard formats -SURA has secured NSF TeraGrid supercomputer resources Extratropical Grid Tropical Grids for Galveston Bay

Domains Gulf of Maine with high resolution nesting in Scituate, MA Nested 5620 nodes 10 m – 1 km horiz resolution CI Challenge (unstructured grids & multi-plots)

IMEDS – Interactive Model Evaluation and Diagnostics System Stand-alone desktop model validation toolkit Based on NOAA standards Robust error metrics: Erms, bias, Scatter Index, Skill Score Explore model errors as a function of time, space, event Statistical Analyses Temporal correlation Quantile-Quantile (distributions) Peak event (peak over threshold) Parameters Added To-Date Error Metrics RMS Error Bias, Angular bias Scatter Index Circular correlation Performance (Skill) Scores WindsSpeed, Direction Waves (Windsea and swell)Height, Period, Direction Storm SurgeWater level, High water marks CI Challenge (tools)

April 2007 “Patriot’s Day Storm” Interesting Science & CI Challenge (multi-plots) Currents w/o wavesCurrents w waves April 18, 04 AM (GMT)

Estuarine Hypoxia Chesapeake Bay 1. Estuary: – 5 Hydrodynamic models (so far) – 6 Hydro-DO model pairs (so far) – 2004 data from up to 40 CBP stations – Comparing T, S, max (dS/dz), DO via target diagrams 2. Shelf: OBCs 5 hydrodynamic models Estuarine Hypoxia Chesapeake Bay 1. Estuary: – 5 Hydrodynamic models (so far) – 6 Hydro-DO model pairs (so far) – 2004 data from up to 40 CBP stations – Comparing T, S, max (dS/dz), DO via target diagrams 2. Shelf: OBCs 5 hydrodynamic models Models doing better on oxygen than stratification! Stratification (dS/Dz) Dissolved Oxygen Std dev of observations

Map of Late July 2004 Observed Dissolved Oxygen [mg/L] ~ 40 EPA Chesapeake Bay stations Each sampled ~ 20 times in 2004 Temperature, Salinity, Dissolved Oxygen Data set for model skill assessment: ( Observations: S and DO from Up to 40 CBP station locations CI Challenge (data storage and formats)

Skill Metrics: Target diagram (modified from M. Friedrichs) Dimensionless version of plot normalizes by standard deviation of observations CI Challenge (tools)

(by M. Scully) Dissolved Oxygen: Top-to-Bottom  S and Bottom DO in Central Chesapeake Bay ChesROMS-1term model - All models reproduce DO better than they reproduce stratification. - If stratification is not controlling DO, what is? Interesting Science & CI Challenge (tools & multi-plots)

Shelf Hypoxia Gulf of Mexico Compare Hydrodynamic & biogeochemical hindcast comparisons of hypoxia model (stand alone) coupled to 3 different Gulf of Mexico hydrodynamic models Evaluate two shelf hypoxia formulations (NOAA & EPA) Assist transition of Navy AMSEAS Gulf Forecasts and NOAA OceanNOMADS data server Shelf Hypoxia Gulf of Mexico Compare Hydrodynamic & biogeochemical hindcast comparisons of hypoxia model (stand alone) coupled to 3 different Gulf of Mexico hydrodynamic models Evaluate two shelf hypoxia formulations (NOAA & EPA) Assist transition of Navy AMSEAS Gulf Forecasts and NOAA OceanNOMADS data server

Preliminary analyses indicate no systematic differences among simulations Compare simulated surface chlorophyll and SeaWiFS climatology (June example). Clim b.c. SeaWiFS HYCOM b.c. IASFNFS b.c. IASNFS b.c. Corr = 0.84 HYCOM b.c. Corr = 0.71 Corr = 0.72 Clim b.c. Log(chl) model Interesting Science & CI Challenge (tools & multi-plots) Courtesy Katja Fennel

Where Does Hypoxic Bottom Water Come From? Interesting Science & CI Challenge (Lagrangian tools) Oxygen (mg/l) 17 Courtesy Bruce Lipphardt, U. Delaware

Model Evaluations – AMSEAS-GOM – Forecast Days 1 – JUNE 2010 Sonic Layer Depth (SLD) with Temperature and Salinity at Surface & 100m Courtesy Frank Bub, NAVOCEANO CI Challenge (tools & multi-plots)

NCEP OPC for Near-Term Ocean Prediction Access EDAC for Long-Term Archive & NCEP Backup NGI & NCDDC EDAC/ OceanNOMADS Improve Access to Gulf Data & Predictions FY11 NODC OceanNOMADS Transition Milestone & CI Challenge (distributed data) Surface Currents

1.Build a common infrastructure for access, analysis and visualization of all ocean model data produced by the Federal Backbone and the IOOS Regions. 2.Develop skill metrics and assess models in three different regions and dynamical regimes 3.Transition models, tools, toolkits and other capabilities to federal operational facilities 4.Build stronger relationships between academia and operational centers through collaboration Super-Regional Testbed Goals U.S.