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| Carter, B. R.; Feely, R. A.; Williams, N. L.; Dickson, A. G.; Fong, M. B.; Takeshita, Y.. |
| We have taken advantage of the release of version 2 of the Global Data Analysis Project data product (Olsen et al. ) to refine the locally interpolated alkalinity regression (LIAR) code for global estimation of total titration alkalinity of seawater (A(T)), and to extend the method to also produce estimates of nitrate (N) and in situ pH (total scale). The updated MATLAB software and methods are distributed as Supporting Information for this article and referred to as LIAR version 2 (LIARv2), locally interpolated nitrate regression (LINR), and locally interpolated pH regression (LIPHR). Collectively they are referred to as locally interpolated regressions (LIRs). Relative to LIARv1, LIARv2 has an 18% lower average A(T) estimate root mean squared error... |
| Tipo: Text |
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| Ano: 2018 |
URL: https://archimer.ifremer.fr/doc/00662/77386/79020.pdf |
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