scholarly journals Including an ocean carbon cycle model into <i>i</i>LOVECLIM (v1.0)

2015 ◽  
Vol 8 (5) ◽  
pp. 1563-1576 ◽  
Author(s):  
N. Bouttes ◽  
D. M. Roche ◽  
V. Mariotti ◽  
L. Bopp
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Dissolved Inorganic Carbon ◽  
Carbon Dioxide Concentration ◽  
Deep Ocean ◽  
Cycle Model ◽  
Carbon Cycle Model ◽  
Radiative Balance ◽  
Ocean Carbon

Abstract. The atmospheric carbon dioxide concentration plays a crucial role in the radiative balance and as such has a strong influence on the evolution of climate. Because of the numerous interactions between climate and the carbon cycle, it is necessary to include a model of the carbon cycle within a climate model to understand and simulate past and future changes of the carbon cycle. In particular, natural variations of atmospheric CO2 have happened in the past, while anthropogenic carbon emissions are likely to continue in the future. To study changes of the carbon cycle and climate on timescales of a few hundred to a few thousand years, we have included a simple carbon cycle model into the iLOVECLIM Earth System Model. In this study, we describe the ocean and terrestrial biosphere carbon cycle models and their performance relative to observational data. We focus on the main carbon cycle variables including the carbon isotope ratios δ13C and the Δ14C. We show that the model results are in good agreement with modern observations both at the surface and in the deep ocean for the main variables, in particular phosphates, dissolved inorganic carbon and the carbon isotopes.

scholarly journals Including a full carbon cycle into the <i>i</i>LOVECLIM model (v1.0)

2014 ◽  
Vol 7 (3) ◽  
pp. 3937-3984 ◽  
Author(s):  
N. Bouttes ◽  
D. M. Roche ◽  
V. Mariotti-Epelbaum ◽  
L. Bopp
Keyword(s):  
Carbon Cycle ◽  
Atmospheric Carbon Dioxide ◽  
Climate Model ◽  
Carbon Dioxide Concentration ◽  
Deep Ocean ◽  
Carbon Cycle Model ◽  
Radiative Balance ◽  
Natural Variations ◽  
Good Agreement

Abstract. The atmospheric carbon dioxide concentration plays a crucial role in the radiative balance and as such has a strong influence on the evolution of climate. Because of the numerous interactions between climate and the carbon cycle, it is necessary to include a model of the carbon cycle within a climate model to understand and simulate past and future changes of the carbon cycle. In particular, natural variations of atmospheric CO2 have happened in the past, while anthropogenic carbon emissions are predicted to continue in the future. To study changes of the carbon cycle and climate on timescales of a few hundred to a few thousand years, we have included a simple carbon cycle model into the iLOVECLIM Earth System Model. In this study, we describe the ocean and terrestrial biosphere carbon cycle models and their performance relative to observational data. We focus on the main carbon cycle variables including the carbon isotope ratios δ13C and the Δ14C. We show that the model results are in good agreement with modern observations both at the surface and in the deep ocean for the main variables, in particular phosphates, DIC and the carbon isotopes. The model can thus be used for long-term past and future climate–carbon studies.

scholarly journals Improved routines to model the ocean carbonate system: mocsy 1.0

2014 ◽  
Vol 7 (3) ◽  
pp. 2877-2902 ◽  
Author(s):  
J. C. Orr ◽  
J.-M. Epitalon
Keyword(s):  
Best Practices ◽  
Dissolved Inorganic Carbon ◽  
Equilibrium Constants ◽  
Potential Temperature ◽  
Deep Ocean ◽  
Total Alkalinity ◽  
Carbonate System ◽  
Carbon Cycle Model ◽  
The North ◽  
Ocean Carbon

Abstract. Software used by modelers to compute ocean carbonate chemistry is often based on code from the Ocean Carbon Cycle Model Intercomparison Project (OCMIP), last revised in 2005. As an update, we offer here new publicly available Fortran 95 routines to model the ocean carbonate system (mocsy). Both codes take as input dissolved inorganic carbon CT and total alkalinity AT, the only two tracers of the ocean carbonate system that are unaffected by changes in temperature and salinity and conservative with respect to mixing, properties that make them ideally suited for ocean carbon models. With the same basic thermodynamic equilibria, both codes compute surface-ocean pCO2 in order to simulate air–sea CO2 fluxes. The mocsy package goes beyond the OCMIP code by computing all other carbonate system variables (e.g., pH, CO32−, and CaCO3 saturation states) and by doing so throughout the water column. Moreover, it avoids three common model approximations: that density is constant, that modeled potential temperature is equivalent to in situ temperature, and that depth is equivalent to pressure. These approximations work well at the surface, but total errors in computed variables grow with depth, e.g., reaching −8 μatm in pCO2, +0.010 in pH, and +0.01 in ΩA at 5000 m. Besides the equilibrium constants recommended for best practices, mocsy also offers users three new options: (1) a recent formulation for total boron that increases its ocean content by 4%, (2) an older formulation for KF common to all other such software, and (3) recent formulations for K1 and K2 designed to also include low-salinity waters. More total boron increases borate alkalinity and reduces carbonate alkalinity, which is calculated as a difference from total alkalinity. As a result, the computed surface pCO2 increases by 4 to 6 μatm, while the computed aragonite saturation horizon (ASH) shallows by 60 m in the North Atlantic and by up to 90 m in the Southern Ocean. Changes due to the new formulation for K1 and K2 enhance pCO2 by up to 8 μatm in the deep ocean and in high-latitude surface waters. These changes are comparable in magnitude to errors in the same regions associated with neglecting nutrient contributions to total alkalinity, a common practice in ocean biogeochemical modeling. The mocsy code with the standard options for best practices and none of the 3 approximations agrees with results from the CO2SYS package generally within 0.005%.

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