Impact of altimetric data assimilated in a eddy-permitting, coupled physical-biogeochemical model of the North Atlantic ocean

Florent GARNIER (CNRS/UJF/LGGE, MEOM team, France)

CoAuthors

Guillem CANDILLE (CNRS/UJF/LGGE, MEOM team, France); Pierre BRASSEUR (CNRS/UJF/LGGE, MEOM team, France); Jean-Michel BRANKART (CNRS/UJF/LGGE, MEOM team, France); Jacques VERRON (CNRS/UJF/LGGE, MEOM team, France)

Event: 2014 Ocean Surface Topography Science Team Meeting

Session: Science Results from Satellite Altimetry: Finer scale ocean processes (mesoscale and coastal)

Presentation type: Type Poster

In recent years, the assimilation of data into coupled physical-biogeochemical models of the ocean has been addressed primarily by investigating the potential of ocean colour observations to constrain the primary production and associated biogeochemical fluxes. Within this framework a sequential assimilation system was developed during the SeaWIFS period in a North Atlantic NEMO configuration at 1/4° (NATL025) coupled to Bio-GeoChemical (BGC) models of various complexity levels (Fontana et al., 2013; Garnier et al., 2014).
It is now well established that the physical field uncertainties in an eddy-permiting model configuration strongly impact the biological response (Béal et al, 2010; Levy et al, 2013), leading to important misfits between the model solutions and the ocean colour satellite data. In order to include the effets of unresolved scales on the dynamics, the NATL025 circulation model coupled to the PISCES BGC model has been adapted by introducing stochastic perturbations to the equation of state and produce ensemble simulations, as described in (Brankart, 2013). The description of these dynamical prior uncertainties allows to perform along-track altimetric data assimilation using the Jason-2, Envisat and Saral/Altika satellite data. In a companion presentation (poster presented by Candille et al.), it is demonstrated that the assimilation is able to significantly improve the dynamical representation of frontal circulations, for instance in the Gulf Stream region and its north-eastwards extension where the Atlantic spring bloom occurs.
In this presentation, we will use this assimilative system to investigate two additional questions:
1) what is the dispersion of the chlorophyll state variable induced by an ensemble simulation that takes into account the uncertainties coming from unresolved scales of the dynamics, and how does it impact ocean colour data assimilation ?
2) what are the direct effects of satellite altimetric data assimilation onto the chlorophyll representation, and therefore subsequently what are the impacts of the physics at smaller scale on the biogeochemistry ?
On the basis of this impact experiments, we will further discuss the complementarity between altimetric and ocean colour data to improve the estimation of the BGC state of the North Atlantic, and suggest a number of possible approaches to combine these two data sets in a consistent assimilation framework.

References:
Béal, D., Brasseur, P., Brankart, J-M AND, O. Y., Verron, J., 2010. Characterization of mixing errors in a coupled physical biogeochemical model of the north atlantic: implications for nonlinear estimation using gaussian anamorphosis. Ocean Science vol.6, 247-262.
Brankart, J.-M., 2013. Impact of uncertainties in the horizontal density gradient upon low resolution global ocean modelling. Ocean Modelling vol.66, 64-76, doi:10.1016/j.ocemod.2013.02.004.
Doron, M., Brasseur, P., Brankart, J.-M., Losa, S. N., Melet, A., 2013.
Stochastic estimation of biogeochemical parameters from globcolour ocean colour satellite data in a north atlantic 3d ocean coupled physical-biogeochemical model. Journal of Marine Systems vol.117-118, 81-85, doi:10.1016/j.jmarsys.2013.02.007.
Garnier et al., 2014: Towards data assimilation in a state-of-the-art PISCES coupled physical
biogeochemical model of the North Atlantic. In submission
Fontana, C., Brasseur, P., Brankart, J.-M., 2013. Toward a multivariate reanalysis of the north atlantic biogeochemistry during 1998-2006 based on the assimilation of seawifs chlorophyll data. Ocean Science vol.9, 37-56, doi:10.5194/os-9-1-2013.
 
Florent GARNIER
CNRS/UJF/LGGE, MEOM team
France
Florent.Garnier@legi.grenoble-inp.fr