Supplementary material to "GLODAPv2.2020 – the second update of GLODAPv2"
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,465 | 0,323 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».