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A general ecosystem model for applications to primary productivity and carbon cycle studies in the global oceans
Institution:1. Joint Center for Satellite Data Assimilation, NOAA Center for Weather and Climate Prediction, 5830 University Research Ct, 20740 College Park, MD, USA;2. Department of Atmospheric Sciences, Texas A&M University, 3150 TAMU, 77840 College Station, TX, USA;3. Department of Earth System Science and Policy, University of North Dakota, 58202 Grand Forks, ND, USA;1. IAP RAS, 46 Ulyanov Str., 603950 Nizhny Novgorod, Russia;2. Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Abstract:We have developed a general 1-D multi-component ecosystem model that incorporates a skillful upper ocean mixed layer model based on second moment closure of turbulence. The model is intended for eventual incorporation into coupled 3-D physical–biogeochemical ocean models with potential applications to modeling and studying primary productivity and carbon cycling in the global oceans as well as to promote the use of chlorophyll concentrations, in concert with satellite-sensed ocean color, as a diagnostic tool to delineate circulation features in numerical circulation models. The model is nitrogen-based and the design is deliberately general enough and modular to enable many of the existing ecosystem model formulations to be simulated and hence model-to-model comparisons rendered feasible. In its more general form (GEM10), the model solves for nitrate, ammonium, dissolved nitrogen, bacteria and two size categories of phytoplankton, zooplankton and detritus, in addition to solving for dissolved inorganic carbon and total alkalinity to enable estimation of the carbon dioxide flux at the air–sea interface. Dissolved oxygen is another prognostic variable enabling air–sea exchange of oxygen to be calculated. For potential applications to HNLC regions where productivity is constrained by the availability of a trace constituent such as iron, the model carries the trace constituent as an additional prognostic variable. Here we present 1-D model simulations for the Black Sea, Station PAPA and the BATS site. The Black Sea simulations assimilate seasonal monthly SST, SSS and surface chlorophyll, and the seasonal modulations compare favorably with earlier work. Station PAPA simulations for 1975–1977 with GEM5 assimilating observed SST and a plausible seasonal modulation of surface chlorophyll concentration also compare favorably with earlier work and with the limited observations on nitrate and pCO2 available. Finally, GEM5 simulations at BATS for 1985–1997 are consistent with the available time series. The simulations suggest that while it is generally desirable to employ a comprehensive ecosystem model with a large number of components when accurate depiction of the entire ecosystem is desirable, as is the prevailing practice, a simpler formulation such as GEM5 (N2PZD model) combined with assimilation of remotely sensed SST and chlorophyll concentrations may suffice for incorporation into 3-D prediction models of primary productivity, upper ocean optical clarity and carbon cycling.
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