Prediction of Surface Ocean pCO2 from Observations of Salinity, Temperature and Nitrate: the Empirical Model Perspective
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- Prediction of Surface Ocean pCO2 from Observations of Salinity, Temperature and Nitrate: the Empirical Model Perspective
- Other Titles
- 염분도, 온도, 질산염의 측정을 통한 표층해양 CO2분압예측
- Hyun-Woo Lee
Lee, Bang Yong
- global carbon cycle; pCO2; remote sensing; total alkalinity; total inorganic carbon
- Issue Date
- Hyun-Woo Lee, Lee, Bang Yong, Kitack Lee. 2008. "Prediction of Surface Ocean pCO2 from Observations of Salinity, Temperature and Nitrate: the Empirical Model Perspective". Ocean Science Journal, 43(4): 195-208.
- 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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