A Super-Regional Modeling Testbed for Improving Forecasts of Environmental Processes for the U.S. Atlantic and Gulf of Mexico Coasts Don Wright, SURA Principal Investigator Rich Signell, USGS Technical Advisory and Evaluation Group Chair

Testbed Origin - FY10 IOOS Budget “$4,000,000 is for a competitive extramural regional test bed… to understand, predict, and mitigate the consequences of both extreme events and chronic conditions in the U.S. Atlantic and Gulf regions. Such a test bed should include no less than 20 academic partners and research institutions to guarantee… community-modeling”

Improving Forecasts of Coastal Environmental Processes Factors: Open boundary conditions, met and river forcing conditions, physics vs. parameterizations, data assimilation approach, amount of data assimilated, numerics, vertical and horizontal resolution, model coupling. “Which model is better?” is often not the right question. What factors in the simulation resulted in a better solution? How much better? At what cost? Improving cyberinfrastructure leads to greater access by more people, and leads to faster improvements

Defining Improvement To measure improvement for environmental processes, we need to define skill metrics for specific environmental processes and often for specific region Inundation, search and rescue, deep oil spills, navigation, hypoxia, harmful algal blooms, diver operations, ocean energy siting, beach erosion, regional impact of climate change, all require different skill metrics Operational centers need community help in this process – too broad for the National Backbone!

The ocean community needs a common cyberinfrastructure to access, analyze and display data from the different models: each model currently has their own standards and toolsets A Common Cyberinfrastructure for Model Data Structured Grids Unstructured Grid 5x5 6x3 10 nodes Variety of Stretched Vertical Coordinates

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

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, MSU 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

Cyberinfrastructure (CI) All Regions – All Teams  Extending CI from OGC, Unidata and others (NOAA DMIT, USGS CDI) to support unstructured grids, and add functionality  Web Access via OpenDAP w/CF  Unidata Common Data Model/NetCDF Java Library API  Distributed search capability  Browser based map viewer (WMS)  Toolbox for scientific desktop analysis  All components standards-based! Search services Mapping services and browse application Analyze in scientific desktop application

Glider/Model Comparison Script

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, Rita and Gustav in standard formats -SURA has provided 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, Rita and Gustav in standard formats -SURA has provided supercomputer resources Extratropical Grid Tropical Grids for Galveston Bay

Inundation Successes High quality grids, forcing, and extensive observational data for specific storms publically available for community testing Direct comparisons between operational inundation models (e.g., SLOSH) with academic community models Community building within research community by modeling groups working together Improved academic - government relationship through partnership

Inundation Team Federal Partners Jesse Feyen (NOAA) – NOAA Storm Surge Road Map Amy Hasse (NOAA NWS) - Met Development Lab Jeff Hanson (USACE) – Model skill assessment Jamie Rhome (NOAA Natl Hurricane Center) – Storm surge unit lead Hendrik Tolman (NOAA NCEP) – Transition to operations Non-Federal Partners Rick Luettich (UNC) – Lead Bob Beardsley (WHOI) – FVCOM extra-tropical, skill assessment Changsheng Chen (UMASS-Dartmouth) – FVCOM Chunyan Li (LSU) – FVCOM tropical Aaron Donahue (Notre Dame) – ADCIRC tropical, skill assessment Dave Forrest (VIMS) – ELCIRC SELFE Will Perrie (Bedford Institute of Oceanography) – Wave modeling Don Slinn (UF) – SLOSH Harry Wang (VIMS) – ELCIRC SELFE Joannes Westerink (Notre Dame) - ADCIRC Bob Weisberg (USF) – FVCOM Lianyuan Zheng (USF) - FVCOM

Shelf Hypoxia Gulf of Mexico Hydrodynamic & biogeochemical hindcast comparisons of hypoxia model (stand alone) coupled to 3 different Gulf of Mexico hydrodynamics models Evaluation of two shelf hypoxia formulations (NOAA & EPA) Shelf Hypoxia Gulf of Mexico Hydrodynamic & biogeochemical hindcast comparisons of hypoxia model (stand alone) coupled to 3 different Gulf of Mexico hydrodynamics models Evaluation of two shelf hypoxia formulations (NOAA & EPA)

Shelf Hypoxia Successes Hypoxia code: Fennel ROMS => NOAA FVCOM (NOAA contact: Rich Patchen, CSDL) Consolidated multi-year hypoxia data set available for NOAA Hypoxia Watch Data Portal (NOAA contact: Scott Cross, NCDDC) Accelerated development of NOAA NCDDC OceanNOMADS capability as Navy “White Front Door” for archived operational ocean nowcast/forecast products (NOAA:Scott Cross) Supporting transition of U.S. Navy operational Gulf of Mexico regional ocean nowcast/forecast capability (NAVY: Frank Bub, NAVO)

Shelf Hypoxia Team Federal Partners Frank Bub (NAVOCEANO) – Advisor, Transition to operations Scott Cross (NESDIS/NODC/NCDDC) – East Coast Regional Science Officer Richard Greene (EPA) – Ecosystem Dynamics John Lehrter (EPA) – Ecologist Alan Lewitus (NOAA) – Advisor Rich Patchen (NOAA/OCS/CSDL) – Modeling, transition to operations CSDL Dong Ko (NRL-EPA) – Modeling Eugene Wei (NOAA/OCS/CSDL/MMAP) – Modeling Jiangtao Xu (NOAA/OCS/CSDL) – Hypoxia modeling Non-Federal Partners John Harding (MSU) – Team Leader Katja Fennel (Dalhousie Uni) – Biogeochemical modeling Pat Fitzpatrick (MSU) – Modeling of hurricanes, weather forecasting Courtney Harris (VIMS) – Numerical modeling, sediment transport Rob Hetland (TAMU) – Hydrodynamic modeling Bruce Lipphardt (Udel) – Model skill assessment using observations Steve Morey (FSU) – Navy Coastal Ocean Model (NCOM) Jerry Wiggert (USM) – Coupled physical-biogeochemical modeling

Estuarine Hypoxia Chesapeake Bay 1. Estuary: – 5 Hydrodynamic models – 3 Biological (DO) models – 2004 data from 28 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 – 3 Biological (DO) models – 2004 data from 28 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

Science Interlude: Understanding DO in CBay

Hypoxia in Chesapeake Bay Variations in river inflow have little effect DO has no correlation with stratification Simple 1 term model for DO works as well as watershed nutrient loading, 11 component, fully 3D water quality model Extent of hypoxia zone is strongly related to wind direction!

CONOPS for R2O

Skill metrics and identification of key performance factors and cost for three important dynamical regimes and environmental issues Foundation of a cyberinfrastructure framework for search, access and display of all Federal Backbone & RA model data, via browser and scientific desktop application CONOPS for transition from research to operations Improved communication between research and operations Testbed Year 1 Products

Web Site:

Expand to more regions and more coastal issues Examine more factors (e.g. data assimilation approaches, model coupling) Build out the cyberinfrastructure (more functionality, toolboxes for other languages, web services, outreach, training) Find a way to sustain testbed activities Future Work for the Testbed

Additional Slides

Data Interoperability Model

Curvilinear Horz., Stretched Vertical Grid Stretched surface and terrain following vertical coordinates Curvilinear orthogonal horizontal coordinates

Stovepiped Model Data Access The GoMOOS Nowcast/Forecast Circulation Model (University of Maine)

Comparing Models with Data in Matlab Model 1: UMASS- ECOM Model 2: UMAINE- POM Data: SST 2008-Sep-08 07:32

14 Different Ocean Forecast Models Spanning CONUS Waters in IDV