Results of the US IOOS Testbed for Comparison of Hydrodynamic and Hypoxia Models of Chesapeake Bay

Results of the US IOOS Testbed for Comparison of Hydrodynamic and Hypoxia Models of Chesapeake Bay

Carl Friedrichs (VIMS) and the Estuarine Hypoxia Team

Federal partners• David Green (NOAA-NWS) – Transition to operations at NWS• Lyon Lanerole, Rich Patchen, Frank Aikman (NOAA-CSDL) – Transition to operations at CSDL; CBOFS2• Lewis Linker (EPA), Carl Cerco (USACE) – Transition to operations at EPA; CH3D, CE-ICM• Doug Wilson (NOAA-NCBO) – Integration w/observing systems at NCBO/IOOS

Non-federal partners• Marjorie Friedrichs, Aaron Bever (VIMS) – Metric development and model skill assessment• Ming Li, Yun Li (UMCES) – UMCES-ROMS hydrodynamic model• Wen Long, Raleigh Hood (UMCES) – ChesROMS with NPZD water quality model • Scott Peckham (UC-Boulder) – Running multiple ROMS models on a single HPC cluster• Malcolm Scully (ODU) – ChesROMS with 1 term oxygen respiration model• Kevin Sellner (CRC) – Academic-agency liason; facilitator for model comparison• Jian Shen (VIMS) – SELFE, FVCOM, EFDC models• John Wilkin, Julia Levin (Rutgers) – ROMS-Espresso + 7 other MAB hydrodynamic models

Presented at MABPOMHorn Point, MD, October 12, 2011

Results of the US IOOS Testbed for Comparison of Hydrodynamic and Hypoxia Models of Chesapeake Bay

Carl Friedrichs (VIMS) and the Estuarine Hypoxia Team

Federal partners• David Green (NOAA-NWS) – Transition to operations at NWS• Lyon Lanerole, Rich Patchen, Frank Aikman (NOAA-CSDL) – Transition to operations at CSDL; CBOFS2• Lewis Linker (EPA), Carl Cerco (USACE) – Transition to operations at EPA; CH3D, CE-ICM• Doug Wilson (NOAA-NCBO) – Integration w/observing systems at NCBO/IOOS

Non-federal partners• Marjorie Friedrichs, Aaron Bever (VIMS) – Metric development and model skill assessment• Ming Li, Yun Li (UMCES) – UMCES-ROMS hydrodynamic model• Wen Long, Raleigh Hood (UMCES) – ChesROMS with NPZD water quality model • Scott Peckham (UC-Boulder) – Running multiple ROMS models on a single HPC cluster• Malcolm Scully (ODU) – ChesROMS with 1 term oxygen respiration model• Kevin Sellner (CRC) – Academic-agency liason; facilitator for model comparison• Jian Shen (VIMS) – SELFE, FVCOM, EFDC models• John Wilkin, Julia Levin (Rutgers) – ROMS-Espresso + 7 other MAB hydrodynamic models

Presented at MABPOMHorn Point, MD, October 12, 2011

Here today

• Methods: (i) Models, (ii) observations, (iii) skill metrics

• Results (i): What is the relative hydrodynamic skill of these CB models?

• Results (ii): What is the relative dissolved oxygen skill ofthese CB models?

• Summary and Conclusions

Results of the US IOOS Testbed for Comparison of Hydrodynamic (and Hypoxia) Models of Chesapeake Bay

OUTLINE

Presented at MABPOMHorn Point, MD, October 12, 2011

Methods (i) Models: 5 Hydrodynamic Models (so far)

(& J. Wiggert/J. Xu, USM/NOAA-CSDL)

o ICM: CBP model; complex biologyo bgc: NPZD-type biogeochemical modelo 1eqn: Simple one equation respiration (includes SOD)o 1term-DD: depth-dependent net respiration

(not a function of x, y, temperature, nutrients…)o 1term: Constant net respiration

Methods (i) Models (cont.): 5 Dissolved Oxygen Models (so far)

o ICM: CBP model; complex biologyo bgc: NPZD-type biogeochemical modelo 1eqn: Simple one equation respiration (includes SOD)o 1term-DD: depth-dependent net respiration

(not a function of x, y, temperature, nutrients…)o 1term: Constant net respiration

Methods (i) Models (cont.): 5 Dissolved Oxygen Models (so far)

o CH3D + ICMo EFDC + 1eqn, 1termo CBOFS2 + 1term, 1term+DD o ChesROMS + 1term, 1term+DD, bgc

Methods (i) Models (cont.): 8 Multiple combinations (so far)

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)

Methods (ii) observations: S and DO from Up to 40 CBP station locations

Methods (iii) Skill Metrics: Target diagram

(modified from M. Friedrichs)

Dimensionless version of plot normalizes by standard deviation of observations

• Methods: (i) Models, (ii) observations, (iii) skill metrics

• Results (i): What is the relative hydrodynamic skill of these CB models?

• Results (ii): What is the relative dissolved oxygen skill ofthese CB models?

• Summary and Conclusions

Results of the US IOOS Testbed for Comparison of Hydrodynamic (and Hypoxia) Models of Chesapeake Bay

OUTLINE

Presented at MABPOMHorn Point, MD, October 12, 2011

unbiasedRMSD

[°C]

bias [°C]

unbiasedRMSD[psu]

bias [psu]

unbiasedRMSD

[psu/m]

bias [psu/m]

unbiasedRMSD

[m]

bias [m]

(a) Bottom Temperature (b) Bottom

Salinity

(c) Stratificationat pycnocline (d) Depth of

pycnocline

Outer circle in each case = error from simply using mean of all data

Inner circle in (a) & (b) = errorfrom CH3D model

Results (i): Hydrodynamic Model Comparison

- All models do very well hind-casting temperature.

- All do well hind-casting bottom salinity with CH3D and EFDC doing best.

- Stratification is a challenge for all the models.

- All underestimate strength and variability of stratification with CH3D and EFDC doing slightly better.

- CH3D and ChesROMS do slightly better than others for pycnocline depth, with CH3D too deep, and the others too shallow.

- All underestimate variability of pycnocline depth.

(from A. Bever, M. Friedrichs)

ChesROMS

EFDC

UMCES-ROMS

CH3D

CBOFS2

Results (i) Hydrodynamics: Temporal variability of stratification at 40 stations

Mean salinity of individualstations

[psu]

- Model behavior for stratification is similar in terms of temporal variation of error at individual stations

(from A. Bever, M. Friedrichs)

Used 4 models to test sensitivity of hydrodynamic skill to:

o Vertical grid resolution (CBOFS2)o Freshwater inflow (CBOFS2; EFDC)o Vertical advection scheme (CBOFS2)o Choice of wind models (ChesROMS; EFDC)o Horizontal grid resolution (UMCES-ROMS)o Coastal boundary condition (UMCES-ROMS)o 2004 vs. 2005 (UMCES-ROMS)

Results (i) Hydrodynamics (cont.): Sensitivity to model refinement

-0.2-0.4-0.6-0.8

0.2

-0.2

-0.2

CBOFS2

CBOFS2 model pycnocline depth is insensitive to: vertical grid resolution, vertical advection scheme and freshwater river input

Results (i) Hydrodynamics (cont.): Sensitivity of pycnocline depth

(from A. Bever, M. Friedrichs)

Stratification at pycnocline is not sensitive to horizontal grid resolution or changes in atmospheric forcing. (Stratification is still always underestimated)

CH3D, EFDC

ROMS 2004

Stratification

Results (i) Hydrodynamics (cont.): Sensitivity of stratification at pycnocline

(from A. Bever, M. Friedrichs)

ROMS 2005

Bottom salinity IS sensitive to horizontal grid resolution

High horiz res

Low horiz res

Bottom Salinity

Results (i) Hydrodynamics (cont.): Sensitivity of bottom salinity

(from A. Bever, M. Friedrichs)

• Methods: (i) Models, (ii) observations, (iii) skill metrics

• Results (i): What is the relative hydrodynamic skill of these CB models?

• Results (ii): What is the relative dissolved oxygen skill ofthese CB models?

• Summary and Conclusions

Results of the US IOOS Testbed for Comparison of Hydrodynamic and Hypoxia Models of Chesapeake Bay

OUTLINE

Presented at MABPOMHorn Point, MD, October 12, 2011

Results (ii): Dissolved Oxygen Model Comparison

- Simple models reproduce dissolved oxygen (DO) and hypoxic volume about as well as more complex models.- All models reproduce DO better than they reproduce stratification.- A five-model average does better than any one model alone.

(from A. Bever, M. Friedrichs)

(by M. Scully)

Results (ii) 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.- So if stratification is not controlling DO, what is?

(by M. Scully)

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

Date in 2004

Hyp

oxic

Vol

ume

in k

m3

20

10

0

Base Case

(by M. Scully)

ChesROMS-1term model

Results (ii) (cont.): Effect of Physical Forcing on Dissolved Oxygen

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

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

Date in 2004

Hyp

oxic

Vol

ume

in k

m3

20

10

0

Base Case

Freshwater river input constant

(by M. Scully)(by M. Scully)

ChesROMS-1term model

Results (ii) (cont.): Effect of Physical Forcing on Dissolved Oxygen

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

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

Date in 2004

Hyp

oxic

Vol

ume

in k

m3

20

10

0

Base CaseJuly wind year-round

(by M. Scully)(by M. Scully)

ChesROMS-1term model

Results (ii) (cont.): Effect of Physical Forcing on Dissolved Oxygen

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

Date in 2004

Hyp

oxic

Vol

ume

in k

m3

20

10

0

Base Case

January wind year-round

(by M. Scully)(by M. Scully)

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

ChesROMS-1term model

Results (ii) (cont.): Effect of Physical Forcing on Dissolved Oxygen

• Available models generally have similar skill in terms of hydrodynamic quantities

• All the models underestimate strength and variability of salinity stratification.

• No significant improvement in hydrodynamic model skill due to refinements in: – Horizontal/vertical resolution, atmospheric forcing, freshwater input, ocean forcing.

• In terms of DO/hypoxia, simple constant net respiration rate models reproduce seasonal cycle about as well as complex models.

• Models reproduce the seasonal DO/hypoxia better than seasonal stratification.

• Seasonal cycle in DO/hypoxia is due more to wind speed and direction than to seasonal cycle in freshwater input, stratification, nutrient input or respiration.– Note: This does not mean than inter-annual variation in nutrient input/respiration is unimportant.

• Averaging output from multiple models provides better hypoxia hindcast than relying on any individual model alone.

SUMMARY & CONCLUSIONS