FN Archimer Export Format PT J TI The CISE-LOCEAN seawater isotopic database (1998–2021) BT AF Reverdin, Gilles Waelbroeck, Claire Pierre, Catherine Akhoudas, Camille Aloisi, Giovanni Benetti, Marion Bourlès, Bernard Danielsen, Magnus Demange, Jérôme Diverrès, Denis Gascard, Jean-Claude Houssais, Marie-Noëlle Le Goff, Hervé Lherminier, Pascale Lo Monaco, Claire Mercier, Herle Metzl, Nicolas Morisset, Simon Naamar, Aïcha Reynaud, Thierry Sallée, Jean-Baptiste Thierry, Virginie Hartman, Susan E. Mawji, Edward M. Olafsdottir, Solveig Kanzow, Torsten VELO, Anton Voelker, Antje Yashayaev, Igor Haumann, Alexander Leng, Melanie J. Arrowsmith, Carol Meredith, Michael AS 1:1;2:1;3:1;4:1;5:2;6:1;7:3;8:4;9:1;10:3;11:1;12:1;13:1;14:5;15:1;16:16;17:1;18:6;19:1;20:5;21:1;22:5;23:7;24:7;25:4;26:8;27:9;28:10,11;29:12;30:13;31:14;32:14;33:15; FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:PDG-ODE-LOPS-OH;15:;16:;17:;18:;19:;20:PDG-ODE-LOPS-OH;21:;22:PDG-ODE-LOPS-OH;23:;24:;25:;26:;27:;28:;29:;30:;31:;32:;33:; C1 Sorbonne University, LOCEAN - IPSL, CNRS–IRD–MNHN, Paris, France Université de Paris, Institut de Physique du Globe de Paris, CNRS, 75005 Paris, France UMS IMAGO, IRD, Plouzané, France Marine and Fresh Water Institute, Iceland University of Brest, LOPS, IUEM, UBO–CNRS–IRD–Ifremer, Plouzané, France Amundsen Science, Québec, Canada National Oceanogaphy Center, Southampton, UK MARUM/Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany Intituto de Investigaciones Marinas de Vigo, CSIC, Vigo, Spain Istituto Português do Mar e da Atmosfera, Lisbon, Portugal Centro de Ciencias do Mar, Faro, Portugal Bedford Institute of Oceanogaphy, Dartmouth, Nova Scotia Canada Atmospheric and Oceanic Sciences Program, Princeton University, Princeton, USA British Geological Survey, Nottingham, UK British Geological Survey, Nottingham, UK 15British Antarctic Survey, Cambridge, UK University of Brest, LOPS, IUEM, UBO–CNRS–IRD–Ifremer, Plouzané, France C2 UNIV SORBONNE, FRANCE IPGP, FRANCE IRD, FRANCE MFRI, ICELAND IFREMER, FRANCE AMUNDSEN SCIENCE, CANADA NOC, UK INST A WEGENER, GERMANY INST INVEST MARINAS CSIC, SPAIN IPMA, PORTUGAL CCMAR, PORTUGAL BEDFORD INST OCEANOG, CANADA UNIV PRINCETON, USA BRITISH GEOL SURVEY, UK BRITISH ANTARCTIC SURVEY, UK CNRS, FRANCE SI BREST SE PDG-ODE-LOPS-OH UM LOPS IN WOS Ifremer UMR WOS Cotutelle UMR DOAJ copubli-france copubli-p187 copubli-europe copubli-univ-france copubli-int-hors-europe IF 11.4 TC 6 UR https://archimer.ifremer.fr/doc/00750/86197/91470.pdf https://archimer.ifremer.fr/doc/00750/86197/94534.pdf LA English DT Article CR EGEE EUREC4A_OA MD 205 / OISO-26 OISO - OCÉAN INDIEN SERVICE D'OBSERVATION OVIDE OVIDE 2018 PIRATA RREX 2017 SURATLANT VT 120 / OISO-21 VT 127 / OISO-22 VT 136 / OISO-23 VT 147 / OISO-25 BO L'Atalante Marion Dufresne Thalassa AB The characteristics of the CISE-LOCEAN sea water isotope data set (δ18O, δ2H, later designed as δD) are presented. This data set covers the time period from 1998 to 2021 and currently includes close to 8000 data entries, all with δ18O, three quarters of them also with δD, associated with a time and space stamp and usually a salinity measurement. Until 2010, samples were analysed by isotopic ratio mass spectrometry, and since then mostly by cavity ring-down spectroscopy (CRDS). Instrumental uncertainty on individual data in this dataset is usually with a standard deviation as low as 0.03 / 0.15 ‰ for δ18O and δD. An additional uncertainty is related to uncertain isotopic composition of the in-house standards that are used to convert daily data into the VSMOW scale. Different comparisons suggest that since 2010 the latter have remained within at most 0.03 / 0.20 ‰ for δ18O and δD. Therefore, combining the two suggests a standard deviation of at most 0.05 / 0.25 ‰ for δ18O / δD. Finally, for some samples, we find that there has been evaporation during collection and storage, requiring adjustment of the isotopic data produced by CRDS, based on d-excess. This adds an uncertainty on the adjusted data of roughly 0.05 / 0.10 ‰ on δ18O and δD. This issue of conservation of samples is certainly a strong source of quality loss for parts of the database, and ‘small’ effects may have remained undetected. The internal consistency of the database can be tested for subsets of the dataset, when time series can be obtained (such as in the southern Indian Ocean or North Atlantic subpolar gyre). These comparisons suggest that the overall uncertainty of the spatially (for a cruise) or temporally (over a year) averaged data is on the order of or less than 0.03 / 0.15 ‰ for δ18O / δD. On the other hand, 17 comparisons with duplicate sea water data analysed in other laboratories or with other data sets in deep regions suggest a larger scatter. When averaging the 17 comparisons done for δ18O, we find a difference close to the adjustment applied at LOCEAN to convert salty water data from the activity to the concentration scale. Such a difference is expected, but the scatter found suggests that care is needed when merging datasets from different laboratories. Examples of time series in the surface North Atlantic subpolar gyre illustrate the temporal changes in water isotope composition that can be detected with a carefully validated dataset. PY 2022 PD JUL SO Earth System Science Data SN 1866-3508 PU Copernicus GmbH VL 14 IS 6 UT 000808540000001 BP 2721 EP 2735 DI 10.5194/essd-14-2721-2022 ID 86197 ER EF