Estimating carbonate parameters from hydrographic data for the intermediate and deep waters of the Southern Hemisphere oceans

• Published in: Biogeosciences
• Main Authors: Bostock, H. C., Mikaloff Fletcher, S. E., Williams, M. J. M.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2013
• Subjects: article; Verlagsveröffentlichung; Indian; Pacific; Southern Ocean
• Online Access: https://doi.org/10.5194/bg-10-6199-2013; https://noa.gwlb.de/receive/cop_mods_00021616; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00021571/bg-10-6199-2013.pdf; https://bg.copernicus.org/articles/10/6199/2013/bg-10-6199-2013.pdf

Using ocean carbon data from global datasets, we have developed several multiple linear regression (MLR) algorithms to estimate alkalinity and dissolved inorganic carbon (DIC) in the intermediate and deep waters of the Southern Hemisphere (south of 25° S) from only hydrographic data (temperature, salinity and dissolved oxygen). A Monte Carlo experiment was used to identify a potential density (σθ) of 27.5 as an optimal break point between the two regimes with different MLR algorithms. The algorithms provide a good estimate of DIC (R2=0.98) and alkalinity (R2=0.91), and excellent agreement for aragonite and calcite saturation states (R2=0.99). Combining the algorithms with the CSIRO Atlas of Regional Seas (CARS), we have mapped the calcite saturation horizon (CSH) and aragonite saturation horizon (ASH) for the Southern Ocean at a spatial resolution of 0.5°. These maps are more detailed and more consistent with the oceanography than the previously gridded GLODAP data. The high-resolution ASH map reveals a dramatic circumpolar shoaling at the polar front. North of 40° S the CSH is deepest in the Atlantic (~ 4000 m) and shallower in the Pacific Ocean (~ 2750 m), while the CSH sits between 3200 and 3400 m in the Indian Ocean. The uptake of anthropogenic carbon by the ocean will alter the relationships between DIC and hydrographic data in the intermediate and deep waters over time. Thus continued sampling will be required, and the MLR algorithms will need to be adjusted in the future to account for these changes.