The Role of the SURA Testbed in the Improvement of U.S. Coastal and Estuarine Prediction
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Transcript of The Role of the SURA Testbed in the Improvement of U.S. Coastal and Estuarine Prediction
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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
PredictionJohn Harding, Northern Gulf Institute
Carl Friedrichs, Virginia Institute of Marine ScienceRick Luettich, University of North Carolina, Chapel Hill
Rich Signell, United States Geological Survey
Coastal Zone 201119 July2011
U.S.
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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.
http://testbed.sura.org/
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IOOS Testbed Team Structure
Rick Luettich, UNC-CHJohn Harding, NGICarl 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.
http://testbed.sura.org/
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Inundation Extra-tropical – Gulf of MaineTropical – 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
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Domains
Gulf of Maine with high resolution nesting in Scituate, MA
Nested
5620 nodes10 m – 1 km horiz resolution
CI Challenge (unstructured grids & multi-plots)
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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 AnalysesTemporal correlationQuantile-Quantile (distributions)Peak event (peak over threshold)
Parameters Added To-Date
Error MetricsRMS ErrorBias, Angular biasScatter IndexCircular correlationPerformance (Skill) Scores
Winds Speed, DirectionWaves (Windsea and swell) Height, Period, DirectionStorm Surge Water level, High water marks
CI Challenge (tools)
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April 2007 “Patriot’s Day Storm”Interesting Science & CI Challenge (multi-plots)
Currents w/o waves Currents w waves
April 18, 04 AM (GMT)
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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 diagrams2. Shelf: OBCs 5 hydrodynamic models
Models doing better on oxygen than stratification!
Stratification (dS/Dz) Dissolved Oxygen
Std dev of observations
Std dev of observations
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Map of Late July 2004
Observed Dissolved Oxygen [mg/L]
~ 40 EPA Chesapeake Bay stationsEach sampled ~ 20 times in 2004
Temperature, Salinity, Dissolved Oxygen
Data set for model skill assessment:
(http://earthobservatory.nasa.gov/Features/ChesapeakeBay)
Observations: S and DO from Up to 40 CBP station locationsCI Challenge (data storage and formats)
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Skill Metrics: Target diagram
(modified from M. Friedrichs)
Dimensionless version of plot normalizes by standard deviation of observations
CI Challenge (tools)
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(by M. Scully)
Dissolved Oxygen: Top-to-Bottom DS 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)
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Shelf Hypoxia Gulf of MexicoCompare Hydrodynamic & biogeochemical hindcast comparisons of hypoxia model (stand alone) coupled to 3 different Gulf of Mexico hydrodynamic modelsEvaluate two shelf hypoxia formulations (NOAA & EPA)Assist transition of Navy AMSEAS Gulf Forecasts and NOAA OceanNOMADS data server
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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 = 0.71Corr = 0.72
Clim b.c.
Log(chl) model
Log(
chl)S
eaW
iFS
Interesting Science & CI Challenge (tools & multi-plots)
Courtesy Katja Fennel
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Where Does Hypoxic Bottom Water Come From? Interesting Science & CI Challenge (Lagrangian tools)
Oxygen (mg/l)1 7
Courtesy Bruce Lipphardt, U. Delaware
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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)
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http://www.northerngulfinstitute.org/edac/ocean_nomads.php
NCEP OPC for Near-Term Ocean Prediction Access
EDAC for Long-Term Archive & NCEP Backup
NGI & NCDDC EDAC/ OceanNOMADSImprove Access to Gulf Data & Predictions
FY11 NODC OceanNOMADS Transition Milestone & CI Challenge (distributed data)
Surface Currents
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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.
http://testbed.sura.org/node/429