Breitkreuz, Charlotte; Paul, André; Kurahashi-Nakamura, Takasumi; Losch, Martin; Schulz, Michael (2018): A dynamically consistent gridded data set of the global, monthly-mean oxygen isotope ratio of seawater, link to NetCDF files. PANGAEA, https://doi.org/10.1594/PANGAEA.889922, Supplement to: Breitkreuz, C et al. (2018): A dynamical reconstruction of the global monthly-mean oxygen isotopic composition of seawater. Journal of Geophysical Research: Oceans, 123(10), 7206-7219, https://doi.org/10.1029/2018JC014300
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We present a dynamically consistent gridded data set of the global, monthly-mean oxygen isotope ratio of seawater (δ¹⁸Osw). The data set is created from an optimized simulation of an ocean general circulation model constrained by global monthly δ¹⁸Osw data collected from 1950 until 2011 and climatological salinity and temperature data collected from 1951 to 1980. The optimization was obtained using the adjoint method for variational data assimilation, which yields a simulation that is consistent with the observational data and the physical laws incorporated in the model. Our data set performs equally well as a previous data set in terms of model-data misfit and brings an improvement in terms of physical consistency and a seasonal cycle. The data assimilation method shows high potential for interpolating sparse data sets in a physical meaningful way. Comparatively big errors, however, are found in our data set in the surface levels in the Arctic Ocean mainly because there is no influence of isotopically highly depleted precipitation on the ocean in areas with sea-ice, and because of the low model resolution.
The data set is the 100-year monthly-mean of the optimized 400-year equilibrium model simulation. It includes simulated δ¹⁸Osw, potential temperature, and salinity on the model grid. The model uses a cubed-sphere grid with a horizontal resolution of 2.8° and 15 vertical levels. We additionally provide the data interpolated onto a 1° lat-lon grid. Values at the edge of the ocean, which could not be interpolated, are set to the respective values in the raw data set on the model grid.
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