The study makes use of a neural network-based extrapolation of the largest collection of surface ocean CO2 observations collected within the surface ocean CO2 Atlas (SOCAT). Based on their results, the authors find that at basin-scale the dominant frequencies at which pCO2 anomalies occur match those from the major climate modes, i.e. El Niño Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation and Southern Annular Mode. For most of the global ocean changes in circulation/biology dominate the anomaly frequency spectrum, whereas in the North Atlantic temperature effects are largely responsible for the observation-based anomalies. For most of the ocean, oscillation periods of >10 years dominate the anomaly frequency spectrum, hence the authors put into question whether a 34-year time series Is long enough to capture the full spectrum of climate-induced variability in the air-sea CO2 transfer, arguing for the extension of the ongoing measurement efforts.
More information:
Eos: https://eos.org/editor-highlights/sea-surface-carbon-patterns-linked-to-large-scale-climate-modes
SOCAT: https://www.socat.info/
Original publication:
Landschützer, P., Ilyina, T., and Lovenduski, N. S. (2019) Detecting regional modes of variability in observation‐based surface ocean pCO2. Geophysical Research Letters, 46. doi: 10.1029/2018GL081756
Contact:
Dr Peter Landschützer
Max Planck Institute for Meteorology
Phone: +49 (0)40 41173 145
Email: peter.landschuetzer@mpimet.mpg.de
Dr Tatiana Ilyina
Max Planck Institute for Meteorology
Phone: +49 (0)40 41173 164
Email: tatiana.ilyina@mpimet.mpg.de