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

Viewed

Total article views: 2,673 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,898 725 50 2,673 99 33 46
  • HTML: 1,898
  • PDF: 725
  • XML: 50
  • Total: 2,673
  • Supplement: 99
  • BibTeX: 33
  • EndNote: 46
Views and downloads (calculated since 01 Apr 2021)
Cumulative views and downloads (calculated since 01 Apr 2021)

Viewed (geographical distribution)

Total article views: 2,673 (including HTML, PDF, and XML) Thereof 2,447 with geography defined and 226 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
Download
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.
Altmetrics
Final-revised paper
Preprint