Articles | Volume 19, issue 1
https://doi.org/10.5194/bg-19-241-2022
https://doi.org/10.5194/bg-19-241-2022
Research article
 | 
17 Jan 2022
Research article |  | 17 Jan 2022

An empirical MLR for estimating surface layer DIC and a comparative assessment to other gap-filling techniques for ocean carbon time series

Jesse M. Vance, Kim Currie, John Zeldis, Peter W. Dillingham, and Cliff S. Law

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Latest update: 13 Dec 2024
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Short summary
Long-term monitoring is needed to detect changes in our environment. Time series of ocean carbon have aided our understanding of seasonal cycles and provided evidence for ocean acidification. Data gaps are inevitable, yet no standard method for filling gaps exists. We present a regression approach here and compare it to seven other common methods to understand the impact of different approaches when assessing seasonal to climatic variability in ocean carbon.
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