A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

Steve D. Jones, Corinne Le Quere, Christian Rodenbeck, Andrew Manning, Are Olsen

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
8 Downloads (Pure)

Abstract

We have developed a statistical gap-filling method adapted to the specific coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a ‘‘radius of influence’’ to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage.
Original languageEnglish
Pages (from-to)1554-1575
Number of pages22
JournalJournal of Advances in Modeling Earth Systems
Volume7
Issue number4
Early online date24 Oct 2015
DOIs
Publication statusPublished - Dec 2015

Cite this