jerry d. wiggert (usm) wen long (umces) jiangtao xu (noaa/nos/csdl) raleigh r. hood (umces) erin b....

Jerry D. Wiggert (USM)

Wen Long (UMCES)

Jiangtao Xu (NOAA/NOS/CSDL)

Raleigh R. Hood (UMCES)

Erin B. Jones (USM)

Lyon W. J. Lanerolle (NOAA)

Christopher W. Brown (CICS-ESSIC NOAA)

This research funded by NOAA-MERHAB & IOOS-SURA

Application of a Coupled Physical-Biogeochemical Application of a Coupled Physical-Biogeochemical Model to Simulate and Forecast the Ecological Model to Simulate and Forecast the Ecological

Variability of Chesapeake BayVariability of Chesapeake Bay

Aquatic Sciences, 20 February 2013

OutlineOutline

- ChesROMS Community Model

- Biogeochemical Model Implementation & Waypoints

- Assessment of Ecosystem Model Solutions

- Concluding Remarks

MODIS Image from Kemp et al. 2005


ChesROMS Community ModelChesROMS Community Model✦ ROMS 3.0

✦ Curvilinear Horizontally

✦ σ-coordinate Vertically

✦ Includes major tributaries

✦ Coarse mesh for model development (100*150*20)

✦ Forcing: Tides, Winds, Heat Fluxes and Rivers

✦ Validated Physical Model w/ 15-Year Hindcast (Xu et al., accepted)

✦ Currently expanding the biogeochemical model

✦ Goal: Improved Simulation of BGC processes & Water Quality Fields

✦ Use Output to inform Ecological Models (HABs, pathogens, etc.)

✦ Open Source Available at:

http://sourceforge.net/projects/chesroms/ ChesROMS Team:Chris Brown, Tom Gross, Brooke Denton, Raleigh Hood, Mohan Karyampudi, Lyon Lanerolle, Wen Long, Raghu Murtugudde, Dave Potsiadlo, M. Bala Krishna Prasad, Jerry Wiggert, Jiangtao Xu


CBP Sampling SitesCBP Sampling Sites

CB4.1C (upper bay)

CB5.3 (middle bay)

CB6.3 (lower bay)

Map Courtesy of Chesapeake Bay Program

Chesapeake Bay Program (http://chesapeakebay.net/)

Data Used For:Initial ConditionsRiver Boundary Conditions

Solution Validation Sites (following Xu & Hood, 2006)

CB3.3C (Upper Bay)CB5.3 (Mid-bay)C6.3 (Lower Bay)

• Chlorophyll• Dissolved Oxygen• DON, PON• Freshwater Flux• NO3/NO2/NH4

• TSS


Chesapeake Bay Ecological Prediction Chesapeake Bay Ecological Prediction System (CBEPS)System (CBEPS)

1) Ocean Quality Control System (OQCS)

• Automatic retrieval of historical and real-time data for validation and model forcing

2) Ocean Hydrodynamic Modeling System (OHMS)

•ChesROMS and Empirical Habitat Models

3) Ocean Model Assessment System (OMAS)

•Skill assessment of model predictions against data acquired by OQCS

4) Ocean Model Dissemination System (OMDS)

•Data archive and forecast dissemination

1)Utilizes data interoperability techniques to facilitate efficient provision of model results to end users

Brown, et al., J. Mar. Sys., 2013.


BGC Modeling Targets & Implementation GoalsBGC Modeling Targets & Implementation Goals

•Phytoplankton Bloom Dynamics• Capture Spatio-temporal Physical-Biogeochemical

Interactions Associated with Estuarine Circulation

•Particulate and Dissolved Constituents • N-cycling Linkage of Water Column & Benthos

•Dissolved Oxygen Evolution• Denitrification Onset - Offers Insight into N Balances &

Budget

Hindcast Year Chosen for Model Implementation is 1999

(“Typical” Conditions; Model Physics Validated)Xu, et al., Est. and Coasts., 2011.

Improved ChesROMS BGC Realism ->

More Robust Ecological Forecast System (CBEPS)


ChesROMS Biogeochemical Flows

1) Benthic NH4 Efflux & NO3 Uptake ramp up as overlying DO decreases

2) Reduce POM sinking in bottom layer

i) Promote O2 Demand in Water Column

ii) Promote BGC link to Estuarine Circulation

1) Reduce DL Sinking Velocity

2) Particle Aggregation (Stickiness)

i) Regulates Bloom Dynamics, POM Loads & Sinking/Export of Organic Matter

ii) Tends to Degrade O2 Evolution (WC DO Increases)

Sensitivity Explorations

Aspects of Implementation

Overcome “Tension” in BGC Mechanisms Bloom Dynamics <-> Hypoxia Realism <-> DIN Concentrations <-> Bloom Dynamics

Overall Goals

DO is Indicated by the Light Blue Background


Summary of Sensitivity StudiesSummary of Sensitivity Studies

Test 64 -> 85: ⬇ DL Sink Velocity (0.5 x); ⬆ Max Nitrification Rate (4x)Test 64 -> 91: Constant Phytoplankton Growth RateTest 91 -> 96: ⬇ Non-Dim Zooplankton Growth Rate (0.8x)Test 96 -> 100: ⬆ Coagulation Param (1.5x) Test 91 -> 104: Zooplankton Grazing ≠ f(Temperature)Test 100 -> 105: ⬇ DL Sink Velocity (0.5 x)

1 CB2.2

2 CB3.1

3 CB3.2

4 CB3.3C

5 CB4.1C

6 CB4.1W

7 CB4.2W

8 CB4.3C

9 CB4.3W

10 CB4.4

11 CB5.1

12 CB5.2

13 CB5.3

14 CB5.4W

15 CB5.5

16 CB6.1

17 CB6.3

18 CB6.4

19 CB7.1

20 CB7.1N

21 CB7.1S

22 CB7.2

23 CB7.2E

24 CB7.3

Index Station

Chlorophyll Ammonium

Nitrate DO


Hypoxic Volume (kmHypoxic Volume (km33) Comparisons) Comparisons

Initial Baseline Solution (Test 64)

Test 64 -> 85: ⬇ DL Sink Velocity (0.5 x); ⬆ Max Nitrification Rate (4x)

Test 91 -> 96: ⬇ Non-Dim Zooplankton Growth Rate (0.8x)

New Baseline Solution (Test 105)

• Extension of Hypoxic Volume Envelope for Model

• Overall, the 4 mg/ml threshold is a closer fit to the CBP-based Hypoxic Volume

• Seasonal variability consisting of onset and dissipation timing are reasonable


Baseline SolutionBaseline SolutionChlorophyll

Dissolved Oxygen

Upper Bay (4.1C)

Upper Bay

Mid-Bay (5.3)

Mid-Bay

Lower Bay (6.3)

Lower Bay


Extending the ModelExtending the Model

Ideally, Phys-BGC Model Will Naturally Capture Interannual Variabilityor

Model Provides Additional Insights into the Chesapeake System


SummarySummary1) Retain Organic Matter in Water Column

• Promotes Water Column Oxygen Demand (to a point)

• BUT! Oxic N-cycling Promotes O2 Production

2) Model Suggests a “Pulsing” of low DO conditions in bottom waters through the summer

• Linkage to variability in modeled phytoplankton biomass

Refining Hypoxic Fidelity in the Model

3)How to Amplify Denitrification in the Water Column and Anoxia Establishment?

• Adjust the Nitrification - Denitrification Transition

QuickTime™ and aMotion JPEG OpenDML decompressor

are needed to see this picture.

Bottom Dissolved Oxygen

Chesapeake Bay System and Availability of CBP Data Provide an Ideal Proving Ground for Development of the Biogeochemical Module


Thank You!Thank You!

jerry d. wiggert (usm) wen long (umces) jiangtao xu (noaa/nos/csdl) raleigh r. hood (umces) erin b....

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