Improving the physics of a coupled physical-biogeochemical model of the North Atlantic through data assimilation: impact on the ecosystem.
Résumé
Several studies on coupled physical–biogeochemical models have shown that major deficiencies in the biogeochemical fields
arise from the deficiencies in the physical flow fields. This paper examines the improvement of the physics through data
assimilation, and the subsequent impact on the ecosystem response in a coupled model of the North Atlantic. Sea surface
temperature and sea surface height data are assimilated with a sequential method based on the SEEK filter adapted to the coupling
needs. The model domain covers the Atlantic from 20°S to 70°N at eddy-permitting resolution. The biogeochemical model is a
NPZD-DOM model based on the P3ZD formulation. The results of an annual assimilated simulation are compared with an annual
free simulation.
With assimilation, the representation of the mixed layer depth is significantly improved in mid latitudes, even though the mixed
layer depth is generally overestimated compared to the observations. The representation of the mean and variance of the currents is
also significantly improved.
The nutrient input in the euphotic zone is used to assess the data assimilation impact on the ecosystem. Data assimilation results
in a 50% reduction of the input due to vertical mixing in mid-latitudes, and in a four- to six-fold increase of the advective fluxes in
mid-latitudes and subtropics. Averaged zonally, the net impact is a threefold increase for the subtropical gyre, and a moderate (20–
30%) decrease at mid and high latitudes.
Surface chlorophyll concentration increases along the subtropical gyre borders, but little changes are detected at mid and high
latitudes. An increase of the primary production appears along the Gulf Stream path, but it represents only 12% on average for mid
and high latitudes. In the subtropical gyre centre, primary production is augmented but stays underestimated (20% of observations).
These experiments show the benefits of physical data assimilation in coupled physical–biogeochemical applications.
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