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  • 1
    Publication Date: 2022-10-10
    Description: The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulphur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured onboard the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using CRM measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 μmol kg-1 in dissolved inorganic carbon, 4 μmol kg-1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments.
    Type: Article , NonPeerReviewed
    Format: text
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  • 2
  • 3
    Publication Date: 2022-04-27
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 4
    Publication Date: 2022-01-24
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 5
    Publication Date: 2022-10-26
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jiang, L.-Q., Pierrot, D., Wanninkhof, R., Feely, R. A., Tilbrook, B., Alin, S., Barbero, L., Byrne, R. H., Carter, B. R., Dickson, A. G., Gattuso, J.-P., Greeley, D., Hoppema, M., Humphreys, M. P., Karstensen, J., Lange, N., Lauvset, S. K., Lewis, E. R., Olsen, A., Pérez, F. F., Sabine, C., Sharp, J. D., Tanhua, T., Trull, T. W., Velo, A., Allegra, A. J., Barker, P., Burger, E., Cai, W-J., Chen, C-T. A., Cross, J., Garcia, H., Hernandez-Ayon J. M., Hu, X., Kozyr, A., Langdon, C., Lee., K, Salisbury, J., Wang, Z. A., & Xue, L. Best practice data standards for discrete chemical oceanographic observations. Frontiers in Marine Science, 8, (2022): 705638, https://doi.org/10.3389/fmars.2021.705638.
    Description: Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above.
    Description: Funding for L-QJ and AK was from NOAA Ocean Acidification Program (OAP, Project ID: 21047) and NOAA National Centers for Environmental Information (NCEI) through NOAA grant NA19NES4320002 [Cooperative Institute for Satellite Earth System Studies (CISESS)] at the University of Maryland/ESSIC. BT was in part supported by the Australia’s Integrated Marine Observing System (IMOS), enabled through the National Collaborative Research Infrastructure Strategy (NCRIS). AD was supported in part by the United States National Science Foundation. AV and FP were supported by BOCATS2 Project (PID2019-104279GB-C21/AEI/10.13039/501100011033) funded by the Spanish Research Agency and contributing to WATER:iOS CSIC interdisciplinary thematic platform. MH was partly funded by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement N°821001 (SO-CHIC).
    Keywords: Data standard for chemical oceanography ; Discrete chemical oceanographic observations ; Column header abbreviations ; WOCE WHP exchange formats ; Quality control flags ; Content vs. concentration ; CO2SYS ; TEOS-10
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
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    Earth System Science Data
    In:  EPIC3GLODAPv2.2022: the latest version of the global interior ocean biogeochemical data product, Earth System Science Data Discuss. [preprint], Earth System Science Data, ISSN: 1866-3508
    Publication Date: 2022-09-28
    Description: The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface-to-bottom ocean biogeochemical bottle data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of seawater samples. GLODAPv2.2022 is an update of the previous version, GLODAPv2.2021 (Lauvset et al., 2021). The major changes are as follows: data from 96 new cruises were added, data coverage was extended until 2021, and for the first time we performed secondary quality control on all sulphur hexafluoride (SF6) data. In addition, a number of changes were made to data included in GLODAPv2.2021. These changes affect specifically the SF6 data, which are now subjected to secondary quality control, and carbon data measured onboard the RV Knorr in the Indian Ocean in 1994–1995 which are now adjusted using CRM measurements made at the time. GLODAPv2.2022 includes measurements from almost 1.4 million water samples from the global oceans collected on 1085 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on systematic evaluation of bias. The data are available in two formats: (i) as submitted by the data originator but converted to World Ocean Circulation Experiment (WOCE) exchange format and (ii) as a merged data product with adjustments applied to minimize bias. For the present annual update, adjustments for the 96 new cruises were derived by comparing those data with the data from the 989 quality controlled cruises in the GLODAPv2.2021 data product using crossover analysis. SF6 data from all cruises were evaluated by comparison with CFC-12 data measured on the same cruises. For nutrients and ocean carbon dioxide (CO2) chemistry comparisons to estimates based on empirical algorithms provided additional context for adjustment decisions. The adjustments that we applied are intended to remove potential biases from errors related to measurement, calibration, and data handling practices without removing known or likely time trends or variations in the variables evaluated. The compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 μmol kg-1 in dissolved inorganic carbon, 4 μmol kg-1 in total alkalinity, 0.01–0.02 in pH (depending on region), and 5 % in the halogenated transient tracers. The other variables included in the compilation, such as isotopic tracers and discrete CO2 fugacity (fCO2), were not subjected to bias comparison or adjustments.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , notRev
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  • 7
    Publication Date: 2022-06-09
    Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(8), (2021): S143–S198, https://doi.org/10.1175/BAMS-D-21-0083.1.
    Description: This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Global ocean conditions in 2020 reflected a transition from an El Niño in 2018–19 to a La Niña in late 2020. Pacific trade winds strengthened in 2020 relative to 2019, driving anomalously westward Pacific equatorial surface currents. Sea surface temperatures (SSTs), upper ocean heat content, and sea surface height all fell in the eastern tropical Pacific and rose in the western tropical Pacific. Efflux of carbon dioxide from ocean to atmosphere was larger than average across much of the equatorial Pacific, and both chlorophyll-a and phytoplankton carbon concentrations were elevated across the tropical Pacific. Less rain fell and more water evaporated in the western equatorial Pacific, consonant with increased sea surface salinity (SSS) there. SSS may also have increased as a result of anomalously westward surface currents advecting salty water from the east. El Niño–Southern Oscillation conditions have global ramifications that reverberate throughout the report.
    Description: Argo data used in the chapter were collected and made freely available by the International Argo Program and the national programs that contribute to it. (https://argo.ucsd.edu, https://www.ocean-ops. org). The Argo Program is part of the Global Ocean Observing System. Many authors of the chapter are supported by NOAA Research, the NOAA Global Ocean Monitoring and Observing Program, or the NOAA Ocean Acidification Program. • L. Cheng is supported by National Natural Science Foundation of China (42076202) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDB42040402. • R. E. Killick is supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. PMEL contribution numbers 5214, 5215, 5216, 5217, and 5247.
    Repository Name: Woods Hole Open Access Server
    Type: Book chapter
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