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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Seawater total alkalinity (TA) is one important determinant used to monitor the ocean carbon cycle, whose spatial distributions have previously been characterized along the United States East Coast via discrete bottle samples. Using these data, several regional models for TA retrievals based on practical salinity (S) have been developed. Broad-scale seasonal or interannual variations, however, are not well resolved in these models and existing data are highly seasonally biased. This study reports findings from the first long duration deployment of a new, commercially available TA titrator aboard a research vessel and the continuous underway surface TA measurements produced. The instrument, operated on seven East Coast USA cruises during six months in 2017 and for two months in 2018 on the summertime East Coast Ocean Acidification survey (ECOA-2), collected a total of nearly 11,000 surface TA measurements. Data from these efforts, along with a newly synthesized set of more than 11,000 regional surface TA observations, are analyzed to re-examine distributions of TA and S along the United States East Coast. Overall, regional distributions of S and TA generally agreed with prior findings, but linear TA:S regressions varied markedly over time and deviated from previously developed models. This variability is likely due to a combination of biological, seasonal, and episodic influences and indicates that substantial errors of ±10–20 μmol kg−1 in TA estimation from S can be expected due to these factors. This finding has likely implications for numerical ecosystem modeling and inorganic carbon system calculations. New results presented in this paper provide refined surface TA:S relationships, present more data in space and time, and improve TA modeling uncertainty.

Department

Ocean Process Analysis Laboratory

Publication Date

5-20-2021

Journal Title

Marine Chemistry

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.marchem.2021.103960

Document Type

Article

Included in

Oceanography Commons

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