Working Group 4 Coastal Biogeochemistry Forum, June 23- 25, 2004 K. Lindsay, G. McKinley, C. Nevison, K. Plattner, R. Seifert Can coastal ecosystems be represented in global models? a. How many different types of coastal zones need representation (temperature / topography / phytoplankton types)? b. What processes do we need to capture / understand how well? c. Can these processes be parameterized / resolved in models?
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Working Group 4 Coastal Biogeochemistry Forum, June 23-25, 2004
Working Group 4 Coastal Biogeochemistry Forum, June 23-25, 2004. K. Lindsay, G. McKinley, C. Nevison, K. Plattner, R. Seifert Can coastal ecosystems be represented in global models? - PowerPoint PPT Presentation
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Working Group 4
Coastal Biogeochemistry Forum, June 23-25, 2004
K. Lindsay, G. McKinley, C. Nevison, K. Plattner, R. Seifert
Can coastal ecosystems be represented in global models?
a. How many different types of coastal zones need representation (temperature / topography / phytoplankton types)?
b. What processes do we need to capture / understand how well?c. Can these processes be parameterized / resolved in models?
MOM4 0.6o-3o x 3o SST, U
0.3 m/s
MOM4 3.75o x 4.5o
Global Ocean Models
Regional Oceanic Modeling System (ROMS)
• 3-dimensional circulation model
• U.S. West Coast configuration (28oN - 48oN; 1000 km offshore)
• Several models with varying horizontal resolution (20km, 15km and 5km)
• Partially to fully eddy-resolving
• 20 vertical layers (sigma-coordinates)
• Climatological forcing (Levitus T,S; COADS)
• Coupled to an NPDZ ecosystem model including a formulation of the carbon cycle
15km
5km
- Level 0 (15 km)- Level 1 (5 km)
UCLA ROMS: US West Coast Configuration
ROMS NPDZ model: N and C cycles
San FranciscoSan Francisco
Pt. Arena Pt. Arena
MontereyBay
MontereyBay
ROMS 15 km ROMS 5 km
Chl-a (mg m-3)
Surface Chl-a: ROMS 15km vs. 5 kmAnnual Mean
ROMS 15 km ROMS 5 km
Chl-a (mg m-3)
Surface Chl-a: ROMS 15 km vs. 5 km
Snapshot May 21
Can ROMS be Applied to Non-Upwelling Coastal Ecosystems?
What Changes are Needed to NPDZ Model?
Alternatives to Prognostic Numerical Models?
In some cases, simpler diagnostic or correlative models may also be useful
a) Bakun Upwelling Index
b) Coastal N2O Emissions
c) Coastal CO Production
Bakun Upwelling Index schematic from www.pfeg.noaa.gov
Upwelling Estimated from QSCAT Wind Data
Nevison et al., 2004
Upwelling Along Global Eastern Boundaries Estimated from Satellite Winds
annual average upwelling rate (m/s)
Nevison et al., 2004
N2O and O2 are Strongly Anticorrelated in Ocean Depth Profiles
Data from Butler et al., 1988
Sharp Increase Observed in Surface N2O near Coast
Nevison et al., 2004
Coastal N2O Sources estimated from Satellite Winds and subsurface Oxygen Climatology
values are N2O (nM)
Nevison et al., 2004
Carbon Monoxide Produced by Photodissociation of Colored Dissolved Organic Matter (CDOM)
(SeaWiFS 1997-1999)
Spectrally Resolved Calculation:
CO Production = ∫F *AQY * (1-e-A) dZafiriou et al., 2003
The End
BGC-Ecosystem Model in ROMS
• NPDZ-type ecosystem model incl. C and O2 cycles
• Tuned to upwelling conditions applying literature values
Initial and boundary conditions:• T, S: Levitus (monthly)
• NO3: World Ocean Atlas (seasonal)
• NH4, Phyto, Zoo, Det (Large/Small), CaCO3: const. (arbitr.)
• DIC: - Surface: based on pCO2 climatology (Takahashi et al., 2002) - Layers with seasonal variations of T: Interpolation of DIC based on seasonal T variations - Deep ocean: NOAA/GLODAP climatology (annual)
• ALK: - Surface: NTA/T relationship (Millero et al., 1998) - Layers with seasonal variations of T: Interpolation of NTA based on seasonal T variations - Deep ocean: NOAA/GLODAP climatology (annual) - All layers: Computation of Alk from NTA and S
Eddy Kinetic Energy increases largely withfiner model resolution