us ioos modeling testbed leadership teleconference may 3, 2011

US IOOS Modeling TestbedLeadership Teleconference

May 3, 2011

Estuarine Hypoxia Team

Carl Friedrichs, VIMS

[email protected]

804-684-7303

Outcomes and Scientific Insights Gained

5 Hydrodynamic Models Run for 2004:

~ 54,000 wet grid cells

(1) CH3D(C. Cerco/L. Linker, USACE/EPA/CBP)

~ 18,000 wet grid cells

(2) EFDC(J. Shen/B. Hong,

VIMS)

Outcomes and Scientific Insights Gained (cont.)

5 Hydrodynamic Models Run for 2004 (cont.):

(3) ChesROMS (R. Hood/W. Long, UMCES)

~5000 wet cells

(4) UMCES ROMS (M. Li/J. Li, UMCES)

~20,000 wet cells

(5) CBOFS2 ROMS (L. Lanerolle, NOAA-CSDL)

~20,000 wet cells


Six DO-Hydrodynamic combinations compared so far for 2004:

(1) ICM: Complex biology w/CH3D (C. Cerco/L. Linker – USACE/EPA/CBP)

(2) ChesROMS-bgc: NPZD biogeochemical model (W. Long/R. Hood – UMCES)

(3) EFDC-1eqn: Simple DO model with SOD (J. Shen/B. Hong – VIMS)

(4) CBOFS-1term: Constant net respiration (L. Lanerolle – NOAA-CSDL)

(5) ChesROMS-1term: Constant net respiration (M. Scully – ODU)

(6) ChesROMS-1DD: Depth-dependent net respiration (M. Scully – ODU)


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)


Metric for model skill assessment: Target diagram analysis

(modified from M. Friedrichs)


Five hydrodynamic models, today’s example parameters:

-- bottom temperature

-- bottom salinity

-- maximum stratification (dS/dz)

Six dissolved oxygen models, today’s example parameters:

-- bottom DO, including model performance at individual stations

-- hypoxic volume, including model performance in time


(M. Friedrichs, A. Bever)

Results: Bottom Temperature (2004)

Models all successfully reproduce seasonal/spatial variability of bottom temperature (ROMS models do best)

outer circle: mean of data

inner circle: CH3D

(CBP model)


Models all reasonably reproduce seasonal/spatial variability of bottom salinity (CH3D, EFDC do best)

Results: Bottom Salinity (2004)


mean of data

CH3D


Stratification is a challenge; CH3D, EFDC reproduce seasonal/spatial variability best

Results: Stratification (max dS/dz)


mean of data


Simple models reproduce seasonal/temporal variability in bottom DO about as well as ICM

Results: Bottom Dissolved Oxygen



inner circle: ICM

(complex CBP model)

[Note: This does not evaluate ability to model year-to-year

changes associated with yearly differences in nutrient input.]


1-term DO model underestimates high DO and overestimates low DO: high not high enough, low not low enough (M. Friedrichs, A. Bever)

Results: Bottom Dissolved Oxygen – data from individual monitoring stations (normalized by individual station observed standard deviations)

ICM (complex CBP model)ChesROMS with

simple 1-term DO

[mg/L]

circle: mean of data


Several simple DO models reproduce seasonal variability of hypoxic volume about as well as ICM

Results: Hypoxic Volume



inner circle: ICM(complex CBP model)


changes associated with yearly differences in nutrient input.]


Several simple DO models reproduce seasonal variability of hypoxic volume about as well as ICM

Results: Hypoxic Volume Time Series

(A. Bever)


changes associated with yearly differences in nutrient input!]

(spatially interpolated observations)


Analyses: Uncertainties in hypoxic volume observations and models

(A. Bever)

In July 2004, ICM underestimates observed hypoxia at CBP stations, but difference between interpolated model results and integration of complete model results is ~ 5 km3

Hypoxic Volume from CBP interpolated observations and ICM (complex) model


Analyses: Uncertainties in hypoxic volume observations and models

1) Summer 2004 hypoxic volume from interpolation of observations: ~ 7.5 km3

2) Summer 2004 hypoxic volume from ICM: ~ 11 km3

3) Summer 2004 hypoxic volume from ChesROMS-1DD: ~ 8 km3

Spatial/temporal uncertainties in HV interpolations: ~ 5 km3

It’s not clear which of these three summer 2004 estimates is closest to the true value.

Hypoxic Volume from CBP interpolated observations and ICM (complex) model and ChesROMS-1DD (simple 1 term model)


Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Date in 2004

Hyp

oxic

Vol

ume

in k

m3

Base Case

Analyses: Effects of physical forcing on hypoxia – ChesROMS-1term

(by M. Scully)



Date in 2004

Hyp

oxic

Vol

ume

in k

m3

Base Case


Seasonal changes in hypoxia are not a function of seasonal changes in freshwater

Freshwater river inputconstant in time

(by M. Scully)



Date in 2004

Hyp

oxic

Vol

ume

in k

m3

Base CaseJuly wind year-round


Seasonal changes in hypoxia may largely be due to seasonal changes in wind

(by M. Scully)



Date in 2004

Hyp

oxic

Vol

ume

in k

m3

Base Case

January wind year-round


Seasonal changes in hypoxia may largely be due to seasonal changes in wind

(by M. Scully)

Summarize Testbed Products Completed by June

Broad-view Highlights of Key Products Completed by June

• Intercomparison of skill for 5 CB Hydrodynamic models for all of 2004

• Sensitivity tests on these models (e.g., freshwater, ocean forcing, wind, horizontal and vertical grid resolution, vertical diffusivity)

• Intercomparison of skill for 6 CB Hypoxia models for all of 2004

• Sensitivity tests on these models (e.g., freshwater, wind, vertical diffusivity)

• Error bounds on hydrodynamic and DO models

• Grids, forcings and output posted in NetCDF by Cyberinfrastructure Team

• Workshop-based recommendations for EPA-CBP transition to new (multiple) hydrodynamic models (including draft of white paper for CBP)

• “Alpha” transition of 1-term DO model for operational forecast use by NOAA-CSDL

Anticipated Progress During NCE (Jun-Dec)

Broad-view Highlights of Example Progress Anticipated for NCE

• Include all of 2005 in hydrodynamic and hypoxia modeling intercomparison• Include results from unstructured grid SELFE model in intercomparison• Assess effect of multi-model ensemble modeling on skill/error bounds• Finish configuration of multiple CB ROMS grids and forcings on single cluster at

CSDMS for optimally controlled intercomparison/sensitivity tests• Collaborate with Cyberinfrastructure Team to preserve model output legacy• Relate results of MAB modeling to Chesapeake Bay conditions.• Complete white paper report for Chesapeake Bay Program on recommended

transition to new/multiple hydrodynamic models• Present results at national science meetings• Submit papers, e.g.,

– C. Friedrichs et al. – Hydrodynamic model comparison to be published in ECM 2011 volume. – M. Friedrichs et al. – Hypoxia model comparison to be published in Biogeosciences (perhaps)– M. Scully et al. – Physical modulation of seasonal hypoxia in Chesapeake Bay – A. Bever et al. – Use of models to interpret errors in observations of Chesapeake Bay hypoxia– Estuarine & Shelf Hypoxia Teams – Comparison of hypoxia controls in CB vs. GoM

Challenges to Progress and Lessons Learned

1) Getting subs to do timely invoicing is a pain!

Challenges to Progress and Lessons Learned

2) Uncertainty about budget (asked to spend, spend, spend), then 6 month NCE.

3) Some trouble engaging the Middle Atlantic Bight modeling group.

4) It was good to have the team lead and those in charge of intercomparison not have a model “in the running”.

5) The openness of all participants, including Feds, was even better than we ever had expected.

6) Engagement of NOAA-CSDL and EPA/NOAA CBP was outstanding.

How Can TAEG Help You?How can SURA Mgmt Help You?

-- TAEG/SURA continue to search for/push for options of follow up testbed projects/funding.

-- Could SURA be the academic arm of the proposed NOAA-NCEP estuarine forecasting effort?

-- SURA could lead the publication of cross-team overview articles, organize special sessions at national meetings, and special issues of journals.

-- TAEG/SURA could help us plan how legacy tools/data will be preserved and made available to the community after the project is over.

Presentations at Scientific and Agency Meetings

Presentations focused specifically on activities and results of

Estuarine Hypoxia Team Testbed Model Intercomparison(i.e., as opposed to individual scientists’ own tangentially-related research projects)

• Past Presentations:– 07/13/10 by C. Friedrichs at EPA/NOAA-CBP STAC Quarterly Meeting, Annapolis, MD.

– 10/14/10 by C. Friedrichs at NSF CSDMS 2010 Meeting, San Antonio, TX.

– 01/12/11 by C. Friedrichs at EPA/NOAA-CBP STAC Quarterly Meeting, Annapolis, MD.

– 02/22/11 by A. Bever at EPA/NOAA-CBP DO Data Meeting, Annapolis, MD.

– 03/23/11 by M. Friedrichs at EPA/NOAA-CBP STAC Quarterly Meeting, Annapolis, MD.

– 04/05/11 by R. Hood at EPA/NOAA-CBP Modeling Subcommittee Meeting, Annapolis, MD.

• Future Planned (so far)– Jun ‘11 by M. Friedrichs at CCMP Hydrodynamic Modeling Workshop, Edgewater, MD.

– Jun ‘11 by A. Bever at GRC Coastal Ocean Modeling Conference, South Hadley, MA.

– Nov ‘11 by C. Friedrichs at Estuarine & Coastal Modeling 2011, St. Augusting, FL.

– Nov ‘11 by A. Bever at Coastal & Estuarine Research Federation, Daytona Beach, FL.

– Feb ‘12 by M. Friedrichs at 2012 Ocean Sciences Meeting, Salt Lake City, UT.

us ioos modeling testbed leadership teleconference may 3, 2011

Documents

simple models

temperature roms models

model performance

model skill assessment

model underestimates

salinity ch3d

dissolved oxygen data

npzd biogeochemical