A statistical gap‐filling method to interpolate global monthly surface ocean carbon dioxide data. (24th October 2015)

• Record Type: Journal Article
• Authors: Jones, Steve D.; Le Quéré, Corinne; Rödenbeck, Christian; Manning, Andrew C.; Olsen, Are
• Is Part Of: Journal of advances in modeling earth systems. Volume 7:Number 4(2015:Dec.)
• Page Start: 1554
• Page End: 1575
• Publication Date: 2015-10-24
• Subjects: ocean -- CO2 -- interpolation; Geological modeling -- Periodicals; Climatology -- Periodicals; Geochemical modeling -- Periodicals; 551.5011
• DOI: 10.1002/2014MS000416
• Languages: English
• ISSNs: 1942-2466

Abstract

Abstract: We have developed a statistical gap‐filling method adapted to the specific coverage and properties of observed fugacity of surface ocean CO2 (fCO2 ). We have used this method to interpolate the Surface Ocean CO2 Atlas (SOCAT) v2 database on a 2.5°×2.5° global grid (south of 70°N) for 1985–2011 at monthly resolution. The method combines a spatial interpolation based on a "radius of influence" to determine nearby similar fCO2 values 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 from the fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on the spatial and temporal range of the interpolation. Tests of the method using model data show that it performs as well as or better than previous regional interpolation methods, but in addition it provides a near‐global and interannual coverage. Key Points: We developed a statistical method to interpolate surface ocean CO2 data Multiple tests show that the method performs well compared to other methods The method provides a near‐global data set of fCO2 suitable for many purposes