FN Archimer Export Format PT J TI Optimum satellite remote sensing of the marine carbonate system using empirical algorithms in the global ocean, the Greater Caribbean, the Amazon Plume and the Bay of Bengal BT AF Land, Peter E. Findlay, Helen S. Shutler, Jamie D. Ashton, Ian Holding, Thomas Grouazel, Antoine GIRARD-ARDHUIN, Fanny Reul, Nicolas Piolle, Jean-Francois Chapron, Bertrand Quilfen, Yves Bellerby, Richard G.J. Bhadury, Punyasloke Salisbury, Joseph Vandemark, Douglas Sabia, Roberto AS 1:1;2:1;3:2;4:2;5:2;6:3;7:3;8:3;9:3;10:3;11:3;12:4,5;13:6;14:7;15:7;16:8; FF 1:;2:;3:;4:;5:;6:PDG-ODE-LOPS-SIAM;7:PDG-ODE-LOPS-SIAM;8:PDG-ODE-LOPS-SIAM;9:PDG-ODE-LOPS-SIAM;10:PDG-ODE-LOPS-SIAM;11:PDG-ODE-LOPS-SIAM;12:;13:;14:;15:;16:; C1 Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1 3DH, UK University of Exeter, Penryn, Cornwall, TR10 9FE, UK Ifremer, University Brest, CNRS, IRD, Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, F-29280, Brest, France SKLEC-NIVA Centre for Marine and Coastal Research, State Key Laboratory for Estuarine and Coastal Research, East China Normal University Zhongshan N. Road, 3663, Shanghai, 200062, China Norwegian Institute for Water Research, Thormølensgate 53D, N-5006, Bergen, Norway Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur, 741 246, West Bengal, India Ocean Processes Analysis Laboratory, University of New Hampshire, Durham, NH, 3824, United States Telespazio-Vega U.K. for European Space Agency (ESA), ESRIN, Frascati, Italy C2 PML, UK UNIV EXETER, UK IFREMER, FRANCE UNIV E CHINA NORMAL, CHINA NIVA, NORWAY IISER, INDIA UNIV NEW HAMPSHIRE, USA ESA, ITALY SI BREST TOULON SE PDG-ODE-LOPS-SIAM UM LOPS IN WOS Ifremer UMR copubli-europe copubli-int-hors-europe copubli-sud IF 9.085 TC 17 UR https://archimer.ifremer.fr/doc/00591/70267/68368.pdf LA English DT Article DE ;Carbonate chemistry;Earth observation;Ocean acidification;Total alkalinity;Dissolved inorganic carbon;SMOS;Aquarius;CORA;HadGEM2-ES AB Improving our ability to monitor ocean carbonate chemistry has become a priority as the ocean continues to absorb carbon dioxide from the atmosphere. This long-term uptake is reducing the ocean pH; a process commonly known as ocean acidification. The use of satellite Earth Observation has not yet been thoroughly explored as an option for routinely observing surface ocean carbonate chemistry, although its potential has been highlighted. We demonstrate the suitability of using empirical algorithms to calculate total alkalinity (AT) and total dissolved inorganic carbon (CT), assessing the relative performance of satellite, interpolated in situ, and climatology datasets in reproducing the wider spatial patterns of these two variables. Both AT and CT in situ data are reproducible, both regionally and globally, using salinity and temperature datasets, with satellite observed salinity from Aquarius and SMOS providing performance comparable to other datasets for the majority of case studies. Global root mean squared difference (RMSD) between in situ validation data and satellite estimates is 17 μmol kg−1 with bias  < 5 μmol kg−1 for AT and 30 μmol kg−1 with bias  < 10 μmol kg−1 for CT. This analysis demonstrates that satellite sensors provide a credible solution for monitoring surface synoptic scale AT and CT. It also enables the first demonstration of observation-based synoptic scale AT and CT temporal mixing in the Amazon plume for 2010–2016, complete with a robust estimation of their uncertainty. PY 2019 PD DEC SO Remote Sensing Of Environment SN 0034-4257 PU Elsevier BV VL 235 UT 000501937600022 DI 10.1016/j.rse.2019.111469 ID 70267 ER EF