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Estuarine Hypoxia Component of Testbed 2

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Presentation on theme: "Estuarine Hypoxia Component of Testbed 2"— Presentation transcript:

1 Estuarine Hypoxia Component of Testbed 2
Marjorie Friedrichs, VIMS, lead Carl Friedrichs, VIMS, co-lead Wen Long and Raleigh Hood, UMCES Malcolm Scully, ODU FY12 Testbed 2 Kick-off Telecon

2 Objectives Compare relative skill of various hydrodynamic and dissolved oxygen models in reproducing observations on seasonal time scales in Chesapeake Bay, by examining: bottom/surface temperature bottom/surface salinity bottom/surface dissolved oxygen maximum stratification depth of maximum stratification hypoxic volume Provide information to managers such that results of these analyses could be transitioned to operational/scenario models Hydrodynamic and DO models characterized by varying level of complexity

3 Five Hydrodynamic Models Configured for the Bay
EFDC Shen VIMS CH3D Cerco & Wang USACE UMCES-ROMS Li & Li UMCES CBOFS (ROMS) Lanerolle & Xu NOAA ChesROMS Long & Hood UMCES

4 Five biological models
ICM: CBP model; complex biology BGC: NPZD-type biogeochemical model 1eqn: Simple one equation respiration (includes SOD) 1term-DD: depth-dependent respiration (not a function of x, y, temperature, nutrients…) 1term: Constant net respiration Point out study region, model domain, MAB and SAB.

5 Data from 40 CBP stations = ~40 CBP stations used in
this model-data comparison mostly 2004 some 2005 results bottom T, bottom S, stratification = max dS/dz, depth of max dS/dz bottom DO, hypoxic volume Point out study region, model domain, MAB and SAB.

6 Stratification (max dS/dz; 2004)
bias [psu/m] unbiased RMSD [psu/m] Stratification is a challenge; CH3D, EFDC reproduce seasonal/spatial variability best

7 Sensitivity Experiments
Maximum Stratification CH3D, EFDC ROMS Stratification is insensitive to grid resolution and changes in atmospheric forcing

8 Stratification (max dS/dz; 2004)
bias [psu/m] unbiased RMSD [psu/m] ROMS with new TKE parameter Adjusting the minimum TKE parameter reduces the bias in ChesROMS

9 Hypoxic Volume bias [km3] unbiased RMSD [km3] Even without nutrients! Several simple DO models reproduce seasonal variability of hypoxic volume about as well as ICM

10 Hypoxic Volume 5-model average does better than any single model
bias [km3] unbiased RMSD [km3] Even without nutrients! 5-model average does better than any single model

11 Overall Progress from Testbed 1
Compared 5 different hydrodynamic models with 5 different DO models (examined 12 different combinations of hydrodynamics+DO for 2004, subset of these for 2005) Density stratification at pycnocline is a challenge Simplest DO models reproduce seasonal variability as well as most complex models Multi-model average for hypoxic volume does better than any single model Models do much better in our wet year (2005) than our dry year (2004) 2. Began to examine sensitivity experiments with individual models Strong sensitivities to wind, min TKE, advection scheme Weak sensitivities to river discharge, coastal BC, grid resolution Hydrodynamic and DO models characterized by varying level of complexity

12 Overall Progress from Testbed 1 (cont.)
3. Transitioning information to federal agencies Simple DO model incorporated into the research version of NOAA CSDL’s Chesapeake Bay Operational Forecast System Participated in Eco-Forecasting workshop at NOAA/ NCEP to further hammer out transition steps for moving to fully operational version of the DO model Provided advice to the CBP on future estuarine and hypoxia modeling strategies, in support of federally mandated environmental restoration, via a STAC workshop report Hydrodynamic and DO models characterized by varying level of complexity

13 Update on Testbed 1 Deliverables
We are on track to provide all deliverables as promised by Dec. 31, 2011 Hydrodynamic and DO models characterized by varying level of complexity

14 Plans for Testbed 2 Year 1 Improve modeled density stratification
Examine choice of turbulence closure scheme and advection scheme 2. Idealized sensitivity experiments with all models Concentrating on wind, may also include river discharge 3. Additional skill metric Averaged Discrete Frechet Distance 4. Presentations/publications Five publications are in preparation Multiple presentations to managers and scientific community Hydrodynamic and DO models characterized by varying level of complexity

15 “Wish List” for Testbed 2
Unstructured Grids SELFE FVCOM 2. Potential for < 10 day operational forecasts Need to examine skill of models in reproducing high frequency data sets 3. Interannual/Interdecadal skill We have simulations from from multiple models, but we do not yet have the resources to make these comparisons These are all things that the current set of Pis could accomplish within the time frame of this project if more funding becomes available

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