Description: This data set provides climatological distributions of d13C of dissolved inorganic carbon for the global oceans. This includes present and reconstructed preindustrial d13C, and the decline over the industrialized period; the full oceanic 13C Suess effect. These distributions were constructed as described in: Eide, Marie; Olsen, Are; Ninnemann, Ulysses S; Eldevik, Tor (in press): A global estimate of the full oceanic 13C Suess Effect since the Preindustrial. Global Biogeochemical Cycles, 31(3), 492-514, doi:10.1002/2016GB005472 and Eide, Marie; Olsen, Are; Ninnemann, Ulysses S; Johannessen, Truls (in press): A global ocean climatology of preindustrial and modern ocean d13C. Global Biogeochemical Cycles, 31(3), 515-534, doi:10.1002/2016GB005473 These articles should be cited whenever the data are used. The data are provided as two files; one for the global oceans for 200 m and deeper levels, this includes present and preindustrial d13C and the 13C Suess effect; and one that cover the entire water column but only includes the 13C Suess effect estimates as d13C distributions have not been constructed for the upper 200 m. See Eide et al. (2017a) and Eide et al. (2017b) for details. The Suess effect estimates from 200 m and downwards are the same in the two data files. The climatology is based on data that were mostly collected during the 1990s, and the present d13C and 13C Suess effect distributions should be considered to represent that time period. The preindustrial distribution is based on the modern observations, corrected for the full 13C Suess effect since the industrial revolution. The data are provided on a 1 degree x 1 degree grid at the following depth levels: For the present and preindustrial d13C and the 13C Suess effect: 10 to 33 (200 m to 5500 m) For the 13C Suess effect including the upper 200 m: 1 to 33 (0 to 5500 m)

Description: 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.

Description: 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 for 1985-2017 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.