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Estuarine Hypoxia Modeling Breakout

Estuarine Hypoxia Modeling Breakout. Carl Friedrichs (VIMS) and the Estuarine Hypoxia Team. Outcomes from breakout session: 1) What are the tangible deliverables from the testbed ? Include: -- Summaries of results of head-to-head model comparisons. [check]

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Estuarine Hypoxia Modeling Breakout

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  1. Estuarine Hypoxia Modeling Breakout Carl Friedrichs(VIMS) and the Estuarine Hypoxia Team Outcomes from breakout session: 1) What are the tangible deliverables from the testbed? Include: -- Summaries of results of head-to-head model comparisons. [check] -- Model validation with observations. [check] -- Legacy data sets. [in progress] -- Skill assessment tools. [in progress] Presented at U.S.IOOS/SURA Modeling Testbed All-Hands Annual Meeting Washington, DC, June 23, 2011

  2. Estuarine Hypoxia Modeling Breakout 2) Specify elements of testbed work that could be brought to operational readiness or significantly inform current operations: Possible pathway to operational use of 1-term hypoxia model: -- 1-term hypoxia model has been added to CSDL CBOFS research model. [check] -- Estuarine Hypoxia Team vets the hypoxia formulation. [in progress] -- EHT convinces CSDL that the operational formulation for hypoxia has value. [in progress] -- CSDL makes a request to CO-OPS to update the operational CBOFS with 1-term hypoxia. -- CO-OPS agrees and CO-OPS makes a request to NCEP to update to operational CBOFS. -- NCEP agrees and updates operational CBOFS with 1-term hypoxia. -- NCEP releases operational hypoxia forecasts with their present CBOFS output. -- CO-OPS posts operational output of hypoxia released by NCEP. Example: http://tidesandcurrents.noaa.gov/ofs/cbofs/cbofs.html

  3. Estuarine Hypoxia Modeling Breakout 3) Lessons learned: -- Chesapeake Bay hydrodynamic models behave remarkably similarly, including their errors. -- All the hydrodynamic models under-predict salinity stratification. -- Hypoxia is predicted with more skill than salinity stratification for all models. -- Strongest control of seasonal hypoxia appears to be wind speed & direction. -- Over-mixing is likely due in part to incorrect setting of minimum background TKE. -- Multiple models predict hypoxia with more skill than individual models.

  4. Estuarine Hypoxia Modeling Breakout 4) Priorities for next 6 months -- Complete our proposed first year work: -- Complete 2005 simulations. -- Complete hydrodynamic-hypoxia model combinations. -- Provide written recommendations for possible transition paths to agencies. -- Inventory/recommend standard skill assessment metrics. 5) Publications and presentations: -- CZ11, Gordon Conference, CERF, ECM12,AMS, Ocean Sciences. -- Hydrodynamic comparison (C. Friedrichs et al.); Hypoxia comparison (M. Friedrichs et al.); Wind sensitivity paper (Scully et al.); Background TKE paper (Scully et al.); Improving interpretation of monitoring (A. Bever et al.).

  5. Estuarine Hypoxia Modeling Breakout 6) Priorities for next 2 years: -- Continue to work closely with NOAA-CSDL and NOAA-NCEP to transition our findings for use in short-term (≤ ~15 day) hypoxia forecast tools at NOAA. -- Continue to work closely with the EPA Chesapeake Bay Program to incorporate our findings into the future evolution of CBP scenario hypoxia forecast models. --Further explore the model properties that lead to the inability of hydrodynamic models to capture the observed intensity of density stratification. -- More fully include unstructured grid models in the Year 2 estuarine hydrodynamics and hypoxia intercomparison. -- Expand the parameter space of model runs to include additional degrees of biological model complexity as well as coordinated, idealized sensitivity runs across multiple models.

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