Supplementary material to "GLODAPv2.2020 – the second update of GLODAPv2"
Bibliographic record
Abstract
The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing regular compilations of surface to bottom ocean biogeochemical data, with an emphasis on seawater inorganic carbon chemistry and related variables determined through chemical analysis of water samples.GLODAPv2.2020 is an update of the previous version, GLODAPv2.2019.The major changes are: data from 106 more cruises added, extension of time coverage until 2019, and 105 the inclusion of available discrete fugacity of CO 2 (fCO 2 ) values in the merged product files.GLODAPv2.2020includes measurements from more than 1.2 million water samples from the global oceans collected on 946 cruises.The data for the 12 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl 4 ) have undergone extensive quality control, especially systematic evaluation of bias.The data are available in two formats: (i) as submitted by the data originator but updated to WOCE exchange format 110 and (ii) as a merged data product with adjustments applied to minimize bias.These adjustments were derived by comparing the data from the 106 new cruises with the data from the 840 quality-controlled cruises of the GLODAPv2.2019data product.They correct for errors related to measurement, calibration, and data handling practices, while taking into account any 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 115 silicate, 2 % in phosphate, 4 µmol kg -1 in dissolved inorganic carbon, 4 µmol kg -1 in total alkalinity, 0.01-0.02,depending on region, in pH, and 5 % in the halogenated transient tracers.The other variables included in the compilation, such as isotopic tracers and discrete fCO 2 were not subjected to bias comparison or adjustments.The original data, their documentation and doi codes are available at the Ocean Carbon Data System of NOAA NCEI (https://www.nodc.noaa.gov/ocads/oceans/GLODAPv2_2020/,last access: 20 June 2020).This site also provides access 120 to the merged data product, which is provided as a single global file and as four regional ones -the Arctic, Atlantic, Indian, and Pacific oceans -under https://doi.org/10.25921/2c8h-sa89(Olsen et al., 2020).The bias corrected product files also include significant ancillary and approximated data.These were obtained by interpolation of, or calculation from, measured data.This living data update documents the GLODAPv2.2020methods and provides a broad overview of the secondary quality control procedures and results.125 IntroductionThe oceans mitigate climate change by absorbing atmospheric CO 2 corresponding to a significant fraction of anthropogenic CO 2 emissions (Friedlingstein et al., 2019; Gruber et al., 2019) and most of the excess heat in the Earth System caused by the enhanced greenhouse effect (Cheng et al., 2020; Cheng et al., 2017).The objective of GLODAP (Global Ocean Data Analysis Project, www.glodap.info,last access: 25 May 2020) is to ensure provision of high quality 130 and bias-corrected water column bottle data from the ocean surface to bottom that document the state and the evolving changes in physical and chemical ocean properties, e.g., the inventory of the excess CO 2 in the ocean, natural oceanic carbon, ocean acidification, ventilation rates, oxygen levels, and vertical nutrient transports.The GLODAP core variables, which are quality controlled and bias corrected, are salinity, dissolved oxygen, inorganic macronutrients (nitrate, silicate, and phosphate), seawater CO 2 chemistry variables (dissolved inorganic carbon -TCO 2 , total alkalinity -135 TAlk, and pH on the total H + scale), and the halogenated transient tracers CFC-11, CFC-12, CFC-113, and CCl 4 .Other chemical tracers are usually also measured on the cruises included in GLODAP.A subset of these data is distributed as part of the product but has not been extensively quality controlled or checked for measurement biases in this effort.For some of these variables, better sources of data may exist, for example the product by Jenkins et al. (2019) Are Olsen 31/7/2020 11
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.465 | 0.323 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".