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Modeling Pacific Physical and Biological Processes

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Presentation on theme: "Modeling Pacific Physical and Biological Processes"— Presentation transcript:

1 Modeling Pacific Physical and Biological Processes
Fei CHAI University of Maine U.S.A. 1

2 Regional Ocean Model System (ROMS):
12-km Resolution Sea Surface Temperature (SST) Sea Surface Height (SSH) 3 day averaged model output 1993 to 2006 1993 2006 4-km 1-km 12-km

3 First Mode of EOF Analysis of SSH
Model Satellite

4 How to Link? Fishing Suspension- feeding Nano- Benthivorous Fish
Pelagic Invertebrate Predators Phytoplankton Seabirds Deposit-feeding Benthos Suspension- feeding DOC Ammonia Fishing Detritus Micro- Zooplankton Meso- Nitrate+Nitrite Nano- Planktivorous Piscivorous Pre-recruits Marine Mammals spawning recruitment Bacteria How to Link?

5 3D Circulation-Ecosystem Modeling
Modular Ocean Model (MOM) Basin scale, coarse resolution (0.5o to 2o), Regional Ocean Model System (ROMS) Basin scale, finer resolution (1/2o), Basin scale, finer resolution (12.5km), West Coast of the North America (NCOM) 9 Km with physical data assimilation, present Gulf of Maine (POM) 3 Km resolution with SST assimilation, present

6 Chai et al., 2003 Winter surface NO3 difference (1979-90) - (1964-75)
PDO Index and Modeled Primary Production Anomaly Ekman Pumping Anomaly and Modeled Chlorophyll Front (0.2 mg/m3) Anomaly Chai et al., 2003

7 ROMS-Biology (50-km) Simulated Surface Chlorophyll (mg/m3)
Gulf of Alaska, averaged 15 May - 15 June ( ) 1998 1999 2000 1997 Jan. April Aug. Dec.

8 Coupled Bio-Physical Modeling
NRL West Coast NCOM with SeaWIFS Chlorophyll NRL West Coast NCOM with Model Chlorophyll Monthly Sequence: June – August 2001

9 Pacific Basin ROMS-CoSINE (12-km) Simulation Annual Mean Sea Surface Temperature (SST)
Modeled SST (oC) Satellite SST (oC) 9

10 Surfare Chlorophyll Comparison in situ, the modeled, and SeaWiFS
10 Historical Data SeaWiFS

11 Seasonal SST Comparison
Observed QuikScat NCEP COADS Dec Jan

12 An Individual Based Model (IBM) for Peruvian Anchovy
Model the entire anchovy life history: spawning events, egg hatching, larva development, growth of juvenile and adults Based on conservation of energy (bioenergetics): growth=consumption-respiration-egestion-excretion Input: temperature and four plankton groups from ROMS-CoSiNE; Output: anchovy growth (length and weight) 3D circulation, offline simulation, output: location, length and weight

13 Anchovy Recruitment in Response to ENSO
Strong El Nino Moderate El Nino Temperature diatom mesozooplankton Recruitment mesozooplankton Recruitment diatom There is a clear seasonal and interannual variability characterized by anchovy recruitment to 5cm.

14 Sea Surface Temperature Anomaly
El Nino and Peruvian Anchovy Fishery Sea Surface Temperature Anomaly 10 x 106 MT Annual Anchovy Catch

15 GoMOOS - http://www.gomoos.org
Goal To provide data and data products that serve public and private sector needs for: solving practical problems predicting events, and further understanding natural systems in the Gulf of Maine

16 Xue et al., CRS, 2006

17 Modeled Surface Chlorophyll, April 2002 SeaWiFS April 2002

18 Comparing with Buoy B, E, I
Black: buoy (night time values) Red: model Green: SeaWiFS

19 Challenges and Recommendations
Physical, nutrients, plankton, and higher levels Improving physical models, data assimilation Spatial and temporal scales, Basin-regional-local; seasonal, interannual, and decadal Surface forcing (wind, heat, fresh water), boundaries Cannot proceed by simply including more variables Simplify the problem with focusing on target species Incorporating structured population and IBM Considering uncertainties, probabilistic simulations Better communication


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