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

摘要

AbstractWe 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.