scholarly journals Design and Validation of an Offline Oceanic Tracer Transport Model for a Carbon Cycle Study

2008 ◽  
Vol 21 (12) ◽  
pp. 2752-2769 ◽  
Author(s):  
Vinu Valsala ◽  
Shamil Maksyutov ◽  
Ikeda Motoyoshi
Keyword(s):  
Carbon Cycle ◽  
Transport Model ◽  
Vertical Mixing ◽  
Cost Effective ◽  
Ocean Currents ◽  
Passive Tracer ◽  
Tracer Transport ◽  
Carbon Cycle Model ◽  
Transport Calculation ◽  
Ocean Carbon

Abstract An offline passive tracer transport model with self-operating diagnostic-mode vertical mixing and horizontal diffusion parameterizations is used with assimilated ocean currents to find the chlorofluorocarbon (CFC-11) cycle in oceans. This model was developed at the National Institute for Environmental Studies (NIES) under the carbon cycle research project inside the Greenhouse Gas Observing Satellite (GOSAT) modeling group. The model borrows offline fields from precalculated monthly archives of assimilated ocean currents, temperature, and salinity, and it evolves a prognostic passive tracer with prescribed surface forcing. The model’s performance is validated by simulating the CFC-11 cycle in the ocean starting from the preindustrial period (1938) with observed anthropogenic perturbations of atmospheric CFC-11 to comply with the Ocean Carbon-Cycle Model Intercomparison Project Phase-2 (OCMIP-2) flux protocol. The model results are compared with ship observations as well as the results of candidate models of OCMIP-2 and a performance is assessed. The model simulates the deep-ventilation processes in the Atlantic Ocean appreciably well and yields a good agreement in the column inventory of the CFC-11 amplitude and phase compared to the observation. The statistical skill test shows that this model outperforms other candidate models of OCMIP-2 because of its higher resolution and assimilated offline input feeding, and it shows a potential role in improving transport calculation in the ocean with cost-effective computation.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to sub-annual variations in fossil fuel CO<sub>2</sub> emissions

2016 ◽  
Vol 16 (4) ◽  
pp. 1907-1918 ◽  
Author(s):  
Xia Zhang ◽  
Kevin R. Gurney ◽  
Peter Rayner ◽  
David Baker ◽  
Yu-ping Liu
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Tracer Transport ◽  
Annual Variations ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

scholarly journals On ocean carbon-cycle model comparison

Tellus B ◽  
1999 ◽  
Vol 51 (2) ◽  
pp. 509-510 ◽  
Author(s):  
James C. Orr
Keyword(s):  
Carbon Cycle ◽  
Model Comparison ◽  
Cycle Model ◽  
Ocean Carbon Cycle ◽  
Carbon Cycle Model ◽  
Ocean Carbon

Simulation of the Natural Distribution of Carbon and Nutrients in the Ocean Based on the Global Ocean Carbon Cycle Model MOM4_L40

2015 ◽  
Vol 58 (1) ◽  
pp. 1-19 ◽  
Author(s):  
LI Qing-Quan ◽  
TAN Juan ◽  
WANG Lan-Ning ◽  
WEI Min ◽  
ZHAO Qi-Geng
Keyword(s):  
Carbon Cycle ◽  
Global Ocean ◽  
Cycle Model ◽  
Ocean Carbon Cycle ◽  
Natural Distribution ◽  
Carbon Cycle Model ◽  
Ocean Carbon

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 Optimization of Biological Production for Indian Ocean upwelling zones: Part – I: Improving Biological Parameterization via a variable Compensation Depth

2017 ◽  
Author(s):  
Mohanan Geethalekshmi Sreeush ◽  
Vinu Valsala ◽  
Sreenivas Pentakota ◽  
Koneru Venkata Siva Rama Prasad ◽  
Raghu Murtugudde
Keyword(s):  
Indian Ocean ◽  
Carbon Cycle ◽  
Global Ocean ◽  
New Production ◽  
Monsoon Period ◽  
Carbon Cycle Model ◽  
Chl A ◽  
Compensation Depth ◽  
The Indian Ocean ◽  
Ocean Carbon

Abstract. Biological modeling approach adopted by the Ocean Carbon Cycle Model Inter-comparison Project (OCMIP-II) provided amazingly simple but surprisingly accurate rendition of the annual mean carbon cycle for the global ocean. Nonetheless, OCMIP models are known to have seasonal biases which are typically attributed to their bulk parameterization of compensation depth. Utilizing the principle of minimum solar radiation for the production and its attenuation by the surface Chl-a, we have proposed a new parameterization for a spatially and temporally varying compensation depth which captures the seasonality in the production zone reasonably well. This new parameterization is shown to improve the seasonality of CO2 fluxes, surface ocean pCO2, biological export and new production in the major upwelling zones of the Indian Ocean. The seasonally varying compensation depth enriches the nutrient concentration in the upper ocean yielding more faithful biological exports which in turn leads to an accurate seasonality in carbon cycle. The export production strengthens by ~ 70 % over western Arabian sea during monsoon period and achieved a good balance between export and new production in the model. This underscores the importance of having a seasonal balance in model export and new production for a better representation of the seasonality of carbon cycle over upwelling regions The study also implies that both the biological and solubility pumps play an important role in the Indian Ocean upwelling zones.

Inverse Multiparameter Modeling of Paleoclimate Carbon Cycle Indices

1993 ◽  
Vol 40 (3) ◽  
pp. 281-296 ◽  
Author(s):  
C. Heinze ◽  
K. Hasselmann
Keyword(s):  
Carbon Cycle ◽  
Ocean Circulation ◽  
Functional Relationship ◽  
Three Dimensional ◽  
Oceanic Circulation ◽  
Carbon Cycle Model ◽  
Last Glaciation ◽  
Ocean Carbon ◽  
Cycle Parameter ◽  
Cycle Indices

AbstractA simple linear response model describing the functional relationship between ocean carbon cycle parameters and paleoclimate tracers (atmospheric pCO2, δ13C, CaCO3 saturation) was derived from a set of sensitivity experiments performed previously using a three-dimensional carbon cycle model. The linear model is optimally fitted to ice and marine sediment core records for the last 120,000 yr to estimate the carbon cycle parameter changes that could have caused the observed reduction of atmospheric CO2 partial pressure during the last glaciation. The analysis indicates that the glacial pCO2 reduction was primarily caused by a strengthening of the biological POC pump and a retardation of the oceanic circulation. An increase in deep-sea alkalinity and a change in the advective pattern of the ocean circulation have a smaller impact on atmospheric CO2 but are necessary to explain the full set of paleoclimate tracers.

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