Prediction of surface ocean pCO2 from observations of salinity, temperature and nitrate: The empirical model perspective |
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| Authors: | Hyun -Woo Lee Kitack Lee Bang -Yong Lee |
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| Institution: | (1) School of Environmental Science and Engineering, Pohang University of Science and Technology, 790-784 Pohang, Korea;(2) Korea Polar Research Institute, KORDI, Songdo Techno Park, 406-840 Incheon, Korea |
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| Abstract: | This paper evaluates whether a thermodynamic ocean-carbon model can be used to predict the monthly mean global fields of the
surface-water partial pressure of CO2 (pCO2SEA) from sea surface salinity (SSS), temperature (SST), and/or nitrate (NO3) concentration using previously published regional total inorganic carbon (CT) and total alkalinity (AT) algorithms. The obtained pCO2SEA values and their amplitudes of seasonal variability are in good agreement with multi-year observations undertaken at the
sites of the Bermuda Atlantic Timeseries Study (BATS) (31°50’N, 60°10’W) and the Hawaiian Ocean Time-series (HOT) (22°45’N,
158°00’W). By contrast, the empirical models predicted CT less accurately at the Kyodo western North Pacific Ocean Time-series (KNOT) site (44°N, 155°E) than at the BATS and HOT sites,
resulting in greater uncertainties in pCO2SEA predictions. Our analysis indicates that the previously published empirical CT and AT models provide reasonable predictions of seasonal variations in surface-water pCO2SEA within the (sub) tropical oceans based on changes in SSS and SST; however, in high-latitude oceans where ocean biology affects
CT to a significant degree, improved CT algorithms are required to capture the full biological effect on CT with greater accuracy and in turn improve the accuracy of predictions of pCO2SEA. |
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| Keywords: | global carbon cycle pCO2 total inorganic carbon total alkalinity remote sensing |
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