33--Dimensional coupled physicalDimensional coupled physical--biological modelling biological modelling the North Atlantic: the North Atlantic:

impact of biogeochemical parameters impact of biogeochemical parameters spatial variabilityspatial variability

Svetlana Losa, Oceanography Department, Dalhousie University

Alain F. Vezina, Bedford Institute of Oceanography Dan Wright, Bedford Institute of Oceanography Youyu Lu, Bedford Institute of Oceanography Keith Thompson, Oceanography Department,

Dalhousie University

Svetlana Svetlana LosaLosa, Oceanography Department, , Oceanography Department, Dalhousie UniversityDalhousie University

Alain F. Alain F. VezinaVezina, Bedford Institute of Oceanography , Bedford Institute of Oceanography Dan Wright, Bedford Institute of Oceanography Dan Wright, Bedford Institute of Oceanography YouyuYouyu Lu, Bedford Institute of Oceanography Lu, Bedford Institute of Oceanography Keith Thompson, Oceanography Department, Keith Thompson, Oceanography Department,

Dalhousie UniversityDalhousie University

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What is it all about ?What is it all about ?

The coupled model description Physical pool Strategy for coupling Biogeochemical modelModel validation Impact of biological model parameters spatial variabilityParameter estimation problem Conclusions

The coupled model description The coupled model description Physical pool Physical pool Strategy for coupling Strategy for coupling Biogeochemical modelBiogeochemical modelModel validation Model validation Impact of biological model parameters Impact of biological model parameters spatial variabilityspatial variabilityParameter estimation problem Parameter estimation problem Conclusions Conclusions

The Physical ModelThe Physical Model

A North Atlantic circulation model, based on the Los Alamos Parallel Ocean Program (POP) (Smith et al. 1992) with an implicit treatment of the Coriolis term and vertical diffusion.The K-profile parameterization (Large et al., 1994) is used for vertical mixing.1 horizontal resolution (10S-80N, 99W-20E). 23 vertical levels (10, 20, 35, 55, 75, 100, 135, 185, 260, 360, 510, 710, 985,1335, 1750, 2200, 2700, 3200, 3700, 4200, 4700, 5200, 5700).

A North Atlantic circulation model, based on A North Atlantic circulation model, based on the Los Alamos Parallel Ocean Program (POP) the Los Alamos Parallel Ocean Program (POP) (Smith et al. 1992) with an implicit treatment (Smith et al. 1992) with an implicit treatment of the of the CoriolisCoriolis term and vertical diffusion.term and vertical diffusion.The KThe K--profile parameterization (Large et al., profile parameterization (Large et al., 1994) is used for vertical mixing.1994) is used for vertical mixing.1 horizontal resolution (10S1 horizontal resolution (10S--80N, 99W80N, 99W--20E). 20E). 23 vertical levels (10, 20, 35, 55, 75, 100, 23 vertical levels (10, 20, 35, 55, 75, 100, 135, 185, 260, 360, 510, 710, 985,1335, 135, 185, 260, 360, 510, 710, 985,1335, 1750, 2200, 2700, 3200, 3700, 4200, 4700, 1750, 2200, 2700, 3200, 3700, 4200, 4700, 5200, 5700). 5200, 5700).

ForcingForcingForcing

Climatological monthly mean wind stress (da Silva et al., 1994).

Climatological monthly mean temperature and salinity (I. Yashayaev, Bedford Institute of Oceanography).Northern and Southern boundaries are closed with sponge layers at which the water temperature and salinity are relaxed to climatological values.

ClimatologicalClimatological monthly mean wind stress monthly mean wind stress ((dada Silva et al., 1994).Silva et al., 1994).

ClimatologicalClimatological monthly mean temperature monthly mean temperature and salinity (I. and salinity (I. YashayaevYashayaev, Bedford Institute , Bedford Institute of Oceanography).of Oceanography).Northern and Southern boundaries are closed Northern and Southern boundaries are closed with sponge layers at which the water with sponge layers at which the water temperature and salinity are relaxed to temperature and salinity are relaxed to climatologicalclimatological values.values.

Initial and Boundary conditionsInitial and Boundary conditions

The Ecosystem ModelThe Ecosystem Model

P

N

Z

D

PP DP

εDZ

(1- β)GP

βGD

GP

DDwD

I

Biological boundary and initial condition

Biological boundary and Biological boundary and initial conditioninitial condition

Climatological seasonal mean nitrate estimates (World Ocean Database, 1998)Climatological monthly mean chlorophyll estimates obtained by averaging SeaWiFSdata over the period 1997-2003. Zinit = 0.02 and decreases exponentially with the depth.Dinit = 0.1

ClimatologicalClimatological seasonal mean nitrate seasonal mean nitrate estimates (World Ocean Database, 1998)estimates (World Ocean Database, 1998)ClimatologicalClimatological monthly mean chlorophyll monthly mean chlorophyll estimates obtained by averaging estimates obtained by averaging SeaWiFSSeaWiFSdata over the period 1997data over the period 1997--2003. 2003. ZZinitinit = 0.02 and decreases exponentially with = 0.02 and decreases exponentially with the depth.the depth.DDinitinit = 0.1= 0.1

The model has captured essential features of

the ocean phytoplankton dynamics:

The model has captured essential features of The model has captured essential features of

the ocean phytoplankton dynamics:the ocean phytoplankton dynamics:

a strong seasonal cycle in biological productivity in the mid- to high latitudes in the N. Atlantic;phytoplankton biomass remains low and relatively invariant year-round in the subtropical to equatorial parts of the basin (except for regions of elevated biomass along west Africa and the equator);

subsurface chlorophyll maximum.

The coupled model had difficulty simulating the nitrate seasonal cycle.

a strong seasonal cycle in biological productivity in a strong seasonal cycle in biological productivity in the midthe mid-- to high latitudes in the N. Atlantic;to high latitudes in the N. Atlantic;phytoplankton biomass remains low and relatively phytoplankton biomass remains low and relatively invariant yearinvariant year--round in the subtropical to equatorial round in the subtropical to equatorial parts of the basin (except for regions of elevated parts of the basin (except for regions of elevated biomass along west Africa and the equator);biomass along west Africa and the equator);

subsurface chlorophyll maximum.subsurface chlorophyll maximum.

The coupled model had difficulty simulating the The coupled model had difficulty simulating the nitrate seasonal cycle.nitrate seasonal cycle.

Horizontal distribution of optimized model parametersHorizontal distribution of optimized model parameters((LosaLosa, , KivmanKivman and and RyabchenkoRyabchenko/Journal of Marine System, 2004)/Journal of Marine System, 2004)

α, mg C m2 /(mg Chl W h)

Vp* , mg C /(mgChl h)

Kyewalyanga et al., 1998I II III IV V

spring 0.073 +- 0.048 0.100 +- 0.045 0.075 +- 0.028 0.078 +-0.025 0.069 +-0.032autumn 0.019 +- 0.007 0.040 +- 0.020 0.037 +- 0.006 0.049 +- 0.037 0.023 +-0.008

Kyewalyanga et al., 1998I II III IV V

spring 3.30 +- 2.63 6.01 +- 2.35 6.88 +- 3.30 8.23 +-2.62 6.64 +-3.37autumn 2.24 +- 1.56 4.51 +- 2.09 4.58 +- 2.32 4.43 +-2.68 4.88 +-1.28

Horizontal distribution of optimized model parametersHorizontal distribution of optimized model parameters

((LosaLosa, , KivmanKivman and and RyabchenkoRyabchenko/Journal of Marine System, 2004)/Journal of Marine System, 2004)

Horizontal distribution of optimized model parametersHorizontal distribution of optimized model parameters((LosaLosa, , KivmanKivman and and RyabchenkoRyabchenko/Journal of Marine System, 2004)/Journal of Marine System, 2004)

The spatial distribution of the parameters is, obviously, a result of a combined effect of several factors such as solar irradiance, temperature, etc., which may affect lati-tudinal changes of chemical conditions and plankton species composition. However, it is rather difficult to distinguish which of the physical and biological factors, and in which region, contributes more to the spatial vary-ability of the physiological model parameters.

The spatial distribution of the parameters is, The spatial distribution of the parameters is, obviously, a result of a combined effect of obviously, a result of a combined effect of several factors such as solar several factors such as solar irradianceirradiance, , temperature, etc., which may affect temperature, etc., which may affect latilati--tudinaltudinal changes of chemical conditions and changes of chemical conditions and plankton species composition. However, it is plankton species composition. However, it is rather difficult to distinguish which of the rather difficult to distinguish which of the physical and biological factors, and in which physical and biological factors, and in which region, contributes more to the spatial varyregion, contributes more to the spatial vary--ability of the physiological model parameters.ability of the physiological model parameters.

August horizontal distribution of the surface chlorophyll “a” concentration (mgChl m-3) in the North Atlantic

a) the model solution obtained with constant biological parameters; b) the model solution obtained with spatially variable biological parameters and c) SeaWiFS (http://seawifs.gsfc.nasa.gov/SEAWIFS.html) data averaged over 1997-2003.

Chlorophyll vertical profilesChlorophyll vertical profiles

ConclusionsConclusionsUsing some of the biological parameters, Using some of the biological parameters, -- previously previously considered as constants, considered as constants, -- spatially variable allows to spatially variable allows to

get a significant improvements in the modelget a significant improvements in the model--data data agreement agreement

Relationships between physical and biological Relationships between physical and biological patterns appears to be different in physically patterns appears to be different in physically distinct regions. distinct regions. Parameterization of the different biological Parameterization of the different biological respond to the variability in physics, under respond to the variability in physics, under different environmental conditions, still remains different environmental conditions, still remains of a real challenge.of a real challenge.Correct formulation of data assimilation problem Correct formulation of data assimilation problem for biology is a powerful tool for investigating for biology is a powerful tool for investigating mentioned above problem, as well as for mentioned above problem, as well as for forecasting purposes. forecasting purposes.