CO2 air–sea disequilibrium and preformed alkalinity in the Pacific and Indian oceans calculated from subsurface layer data

This work estimates new regionalized empirical parameterizations for preformed alkalinity (AT o) and the CO2 air-sea disequilibrium ( not equal to dis). Both are key terms for the computation of anthropogenic CO2 in the back-calculation methods. Data from the subsurface layer (75-180m depth range) c...

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Veröffentlicht in:Journal of marine systems 2011-02, Vol.84 (3-4), p.67-77
Hauptverfasser: Pardo, Paula C., Vázquez-Rodríguez, Marcos, Pérez, Fiz F., Rios, Aida F.
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Sprache:eng
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Zusammenfassung:This work estimates new regionalized empirical parameterizations for preformed alkalinity (AT o) and the CO2 air-sea disequilibrium ( not equal to dis). Both are key terms for the computation of anthropogenic CO2 in the back-calculation methods. Data from the subsurface layer (75-180m depth range) covering an area from North to South and from 19 degree E to 67.5 degree W (Pacific and Indian oceans) were taken from GLODAP (The Global Ocean Data Analysis Project) database. The subsurface layer is proved as a reliable reference for representing the main characteristics of the different water masses of the oceans. Besides, handing data from the two ocean basins altogether makes the new parameterizations of AT o and not equal to dis to be more globally consistent. Nevertheless, each ocean basin, at least in some regions, has different oceanographic characteristics based on its proper dynamical processes and water masses formation. In order to maintain each ocean basin 'identity' the whole domain was divided in six different regions (two of them sharing waters from Pacific and Indian oceans) and parameterizations in each region for both terms were obtained. Previously, data were transformed into a grid of 4 degree lat-5 degree lon. and the results obtained from the parameterizations were visualized and compare with pCO2 climatologies. From the comparisons with previous a not equal to dis estimations good results are obtained showing the reliability and robustness of the new regionalized empiric parameterizations.
ISSN:0924-7963
DOI:10.1016/j.jmarsys.2010.08.006