The Global Ocean Data Analysis Project version 3 (GLODAPv3) &ndash; an internally consistent biogeochemical data product for the world ocean

Lange, Nico; Lauvset, Siv K.; Carter, Brendan R.; Humphreys, Matthew P.; Woosley, Ryan J.; Olsen, Are; Bittig, Henry C.; Kozyr, Alex; Álvarez, Marta; Azetsu-Scott, Kumiko; Becker, Susan; Brown, Peter J.; Cotrim da Cunha, Leticia; Dias, Larissa; Hoppema, Mario; Ishii, Masao; Jeansson, Emil; Murata, Akihiko; Müller, Jens Daniel; Pérez, Fiz F.; Schirnick, Carsten; Steinfeldt, Reiner; Ulfsbo, Adam; Velo, Anton; Tanhua, Toste

doi:10.5194/essd-2026-496

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https://doi.org/10.5194/essd-2026-496

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31 Jul 2026

| 31 Jul 2026

Status: this preprint is currently under review for the journal ESSD.

The Global Ocean Data Analysis Project version 3 (GLODAPv3) – an internally consistent biogeochemical data product for the world ocean

Nico Lange, Siv K. Lauvset, Brendan R. Carter, Matthew P. Humphreys, Ryan J. Woosley, Are Olsen, Henry C. Bittig, Alex Kozyr, Marta Álvarez, Kumiko Azetsu-Scott, Susan Becker, Peter J. Brown, Leticia Cotrim da Cunha, Larissa Dias, Mario Hoppema, Masao Ishii, Emil Jeansson, Akihiko Murata, Jens Daniel Müller, Fiz F. Pérez, Carsten Schirnick, Reiner Steinfeldt, Adam Ulfsbo, Anton Velo, and Toste Tanhua

Abstract. The Global Ocean Data Analysis Project (GLODAP) is a synthesis effort providing surface-to-bottom ocean biogeochemical observations determined through chemical analysis of discrete bottle samples, with an emphasis on seawater inorganic carbon chemistry and related variables. Version 3 of GLODAP comprises data from 1181 cruises, spanning more than 50 years of observations (1972–2023). It includes all data from the previous GLODAPv2.2023 (Lauvset et al., 2024) together with newly added data from 57 cruises. For all cruises, 13 core variables (temperature, salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, CFC-11, CFC-12, CFC-113, CCl₄, and SF₆) have undergone extensive quality control with particular focus on the identification and removal of systematic differences between cruises. The data are available in two formats: (i) as submitted by the data originators, converted to World Ocean Circulation Experiment (WOCE) exchange format, and (ii) as a merged data product in which adjustments have been applied. These adjustments were determined using crossover analyses in combination with a newly developed global inversion method, the furthest-first routine. The applied adjustments are intended to remove systematic differences arising from differences in measurement methods, calibration, and/or data-handling practices, while preserving known or likely temporal trends and natural variability. The consistency of the adjusted data product is estimated to be 0.0013 for salinity, 0.7 % for oxygen, 0.4 % for nitrate, 0.5 % for silicate, 0.5 % for phosphate, 1.2 µmol kg⁻¹ for dissolved inorganic carbon, and 1.4 µmol kg⁻¹ for total alkalinity. Consistency estimates could not be derived for transient tracers, but they are believed to be consistent to better than 5 % (10 % for SF₆). The enhanced consistency enables different datasets to be used together with greater confidence. Newly introduced cruise-specific uncertainty estimates for all core variables provide more granular quantifications of remaining cruise-to-cruise inconsistencies. Additional variables, including pH, discrete CO₂ fugacity (fCO₂), isotopic tracers, and others, were not subjected to secondary quality control but are included in the data product.

The original data, their documentation (metadata), and DOIs are available through the Ocean Carbon and Acidification Data System (OCADS) of NOAA’s National Centers for Environmental Information (NCEI), which also hosts the merged data product. All secondary quality control decisions and supporting information can be found in the online adjustment table (https://glodapv3.geomar.de, last accesses 26.06.2026). The product is distributed as a single global file and as four regional subsets (Arctic, Atlantic, Indian, and Pacific Oceans) under https://doi.org/10.25921/m6tp-mj50 (Lange et al., 2026). These adjusted files also include ancillary and approximated data obtained through interpolation or calculation from measured data.

How to cite. Lange, N., Lauvset, S. K., Carter, B. R., Humphreys, M. P., Woosley, R. J., Olsen, A., Bittig, H. C., Kozyr, A., Álvarez, M., Azetsu-Scott, K., Becker, S., Brown, P. J., Cotrim da Cunha, L., Dias, L., Hoppema, M., Ishii, M., Jeansson, E., Murata, A., Müller, J. D., Pérez, F. F., Schirnick, C., Steinfeldt, R., Ulfsbo, A., Velo, A., and Tanhua, T.: The Global Ocean Data Analysis Project version 3 (GLODAPv3) – an internally consistent biogeochemical data product for the world ocean, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2026-496, in review, 2026.

Received: 01 Jul 2026 – Discussion started: 31 Jul 2026

Competing interests: At least one of the (co-)authors is a member of the editorial board of Earth System Science Data.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

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RC1:
'Comment on essd-2026-496', Anonymous Referee #1, 26 Aug 2026 reply
General
GLODAPv3 is the third full re-evaluation of the synthesis, with this time 1181 cruise files, about 1.50 million samples, 1972–2023. Relative to v2.2023 it replaces the WLSQ inversion with the furthest-first (FF) algorithm, lets the regional clusters emerge from the crossover network rather than prescribing them, reduce the minimum adjustment limits (DIC and Talk) by a factor 2, adds per-cruise uncertainties, and adds an explicit trend-preservation step. All these advances are clear. In particular the FF inversion is a striking improvement. Section 4.2 is very insightful, no previous GLODAP release has stated that clearly that the network contains no direct Atlantic-Pacific connection, or that the Indo-Pacific link rests on one cruise. My comments are mostly about the text, not the analysis. The one place where I think the paper could be clearer and more thorough in its explanation is the carbonate system: the choice of input pair, the choice of constants, at a moment when the literature on constants has moved considerably, how users should treat pH data. Nothing below requires new data. Overall, congratulations and thank you on behalf of the community to the authors for putting this together.
Main comments
The consistency numbers in the abstract are not the quantity that the earlier versions reported. The abstract values (1.2 µmol kg-1 DIC, 1.4 TAlk …) are the adjusted CWMO wRMSE of Table 9. In the v2 family the quoted consistency was the minimum adjustment limit. Lauvset et al. (2024) say that those numbers are "not uncertainties but rather a priori estimates of global inter-cruise consistency". So going from 4 to 1.2 µmol kg-1 can be read as a threefold improvement in data quality by the reader, but that is not the case. This should somehow be made clearer. It also sits awkwardly with Eq. 2. With A_min = 2 µmol kg-1 and σ about 0.8, the product ships u_cruise ≈ 2.15 µmol kg⁻¹ for DIC while the abstract advertises 1.2. I guess my confusion here could be fixed with a few sentences, reporting ucruise so that the number is comparable with v2 and with the product files, or keeping the wRMSE and better explain what it is and what the v2 equivalent was. The abstract should also make clear that these values describe consistency within regional clusters and that inter-basin consistency is not constrained by the present network.

The numbers in section 3.2 and in Table 8 disagree for most core variables. Table 8 is internally perfect, every column sums to 1224, and unadjusted + adjusted + (-888) + (-777) reproduces "with data" exactly, but numbers in the text don’t agree (e.g. the text says there are 998 entries with TAlk data, table says 851). Alkalinity needs a separate look because the paragraph does not add up on its own terms (998 - 30 - 282 = 686, not 544), and the gap to Table 8 is larger than for other variables.

The pH data are left in an ambiguous state for users. The reasoning in section 4.1 is careful and I agree with the decision. But looking at it from an outside user perspective. GLODAPv2.2023 shipped adjusted pH with a stated consistency of 0.01 to 0.02. GLODAPv3 ships unadjusted pH, no consistency estimate, and nine cruises that earlier versions had excluded are back in. The message for user is confusing, can we still trust and use pH data the same way it was possible to do in the earlier versions. Please develop the text around this, explain how to pH estimates, what uncertainty to assume, whether measured pH or pH calculated from adjusted TCO2-TAlk is preferable and under what conditions, whether v2-adjusted and v3-unadjusted pH can be combined in a time series.

The carbonate-system choices could be more justified. Section 2.2.7 states that "for calculations of TAlk or TCO2, only pHT data were used, and fCO₂ data were not considered", with no reason given. Section 4.1 says that there are inconsistencies beyond uncertainty propagation when fCO₂ is combined with TCO2 or TAlk (García-Ibáñez et al., 2022) but that concerns calculated pH, not the use of fCO₂ as an input for TAlk or TCO2 (and the reference is missing from the list). "Currently no consensus exists on which set of constants should be used (Carter et al., 2024b)" is weaker than the literature cited in the preceding sentence. Fong and Dickson (2019), Woosley (2021), Woosley and Moon (2023), Schockman and Byrne (2021), Sulpis et al. (2020) all point out to disagreement in the Lueker et al. constants and provide updated sets of constants. Lueker may remain the best compromise for a global legacy product, but that case should be made rather than deferred to an absent consensus. I wonder given the temperature and salinity range over which the chosen set of constants is validated, what fraction of GLODAPv3 falls outside.

Minor
Lines 227. Did you mean PyCO2SYS, rather than CO2SYSv2?
Table 5 footnote a still lists pH among adjusted variables.
Table 9 labels salinity in ppm, I am confused if that is a typo or if I am not following something

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Citation: https://doi.org/10.5194/essd-2026-496-RC1
RC2:
'Comment on essd-2026-496', Enhui Liao, 12 Sep 2026 reply
This manuscript presents GLODAPv3, a valuable contribution to the oceanographic and broader Earth science communities. The authors have gone beyond data collection by developing and applying methods to evaluate consistency among cruises, identify systematic offsets, preserve temporal trends, and provide additional uncertainty information. These methodological developments strengthen the scientific utility of the product and support the combined use of observations from different periods, regions, and measurement programs. Overall, I consider this an important dataset and a worthwhile contribution to ESSD. My comments primarily concern discrepancies in the reported numbers, consistency between the text and figures or tables, and clarification of several methodological descriptions. Addressing these points would improve the clarity, reproducibility, and usability of the manuscript.
Lines 600–601 (p. 25) state that salinity data from 152 entries required adjustment, whereas Table 8 (p. 23) reports 158 adjusted entries. The other salinity counts agree, including the 861 entries remaining after exclusions. Please reconcile the adjustment count and ensure that the associated figures use the same final selection. Similar discrepancies occur in the counts reported for other variables; please check all numerical summaries against the final dataset.

The seven action categories in Table 4 (p. 10) sum to 1225 for both salinity and oxygen. However, lines 126–127 report 1181 cruise files, and lines 549–551 report 1224 QC entries. Table 4 describes its units as “cruises,” although “entries” may be intended. Please clarify the statistical unit, and use “cruises” and “entries” consistently throughout the manuscript.

Lines 48–50 and 126–127 state that GLODAPv3 contains all GLODAPv2.2023 data plus 57 newly added cruises, yielding 1181 cruises. The cited GLODAPv2.2023 publication reports 1108 cruises; 1108 + 57 = 1165, leaving a difference of 16 cruises. Please reconcile these totals by specifying any additions, reinstatements, removals, or changes in cruise definitions.

Lines 625–644 (p. 25) distinguish pre-2010, 2010–2018, and post-2018 Japanese silicate data. Lines 895–896 (p. 32), however, refer to preadjustments to pre-2010 and post-2019 Japanese data. These descriptions treat 2019 differently. Please specify the intended year intervals and use them consistently.

Equation (1) (p. 17) is printed as a sum of Wr/W. This does not express the weighted mean described in lines 385–398 because the denominator lacks the sum of the weights. Please write the numerator as Σ_j(W_ijr_ij) and the denominator as Σ_jW_ij, and define the summation set. Consider using a symbol such as r̄_i for CWMO, rather than x̄, since x already denotes the adjustment vector in lines 344–346.

Lines 349–350 state that shorter time separations receive higher weights. Lines 353–355 state that the additional factors are normalized so that low values indicate high confidence, multiplied together, rescaled to 1–2, and then multiplied by the inverse variance. If the final rescaling preserves the ordering, less confident crossovers would receive larger weights. Please provide the complete scaling equations, including the normalization bounds and whether the final mapping reverses the ordering.

Lines 347–348 define the base weight as the squared inverse of the offset standard deviation. The Figure 5 caption (lines 359–361) instead describes the inverse standard deviation as the weight. Please reconcile the caption and methods with the implemented calculation.

Lines 381–382 state that a trend is retained if α exceeds 1.96 times its standard error. Please clarify whether the intended criterion is |α| > 1.96 SE(α), so that significant negative trends are also retained.

In Figure 10 (p. 23), the legend defines the light-blue, orange, and red categories as <2 × limit, 2–4 × limit, and >4 × limit. The caption (lines 575–577) instead defines them as below the minimum, between one and two times the limit, and above twice the limit. These definitions differ by a factor of two. Please reconcile the legend and caption. Please also specify the year range represented by “2010s”.

The Figure 6 caption (p. 16) states that the figure shows three main processes, whereas the figure labels steps 1–4 and the text also describes four steps. Please make it consistent.

The Table 7 caption (lines 438–440) states that qualifying cruises are adjusted in the third step. Lines 406–415 define step 3 as selection of the “Cruises-to-Adjust” list, while lines 417–419 place the final adjustment inversion in step 4. Please reconcile these descriptions.

Table 10 (p. 33) labels the phosphate row “PO₂,” whereas the manuscript otherwise uses PO₄. Please correct the variable label.

Table 5 and its footnote (p. 12) include pH among the variables receiving additive adjustments. Lines 222–225 and 739–740 explicitly state that secondary QC was not applied to pH in GLODAPv3. Please remove pH from the applicable adjustment list.

Table 9 labels salinity as ppm and reports 1.9 → 1.3, whereas lines 604–605 report 0.0019 → 0.0013 for the same wRMSE. Please check the unit.

The reference to Müller and Gruber, “Progression of ocean interior acidification over the industrial era,” is dated 2034 at lines 1287–1288. The paper was published in 2024. Please correct the year.

Line 227 cites “CO2SYSv2 (Humphreys et al., 2022),” but the corresponding reference at lines 1204–1205 is “PyCO2SYS v1.8: marine carbonate system calculations in Python.” Please verify the software implementation and version intended here and correct the citation accordingly.

Gruber et al. (2019), cited at line 106, has no matching entry in the reference list. Other citations also appear to be missing. Please cross-check all in-text citations against the reference list and add missing entries or correct the author–year citations as appropriate.

A challenge is that crossover differences contain both measurement biases and real ocean variability. One possible option would be to sample existing multiyear or multidecadal ocean biogeochemical model output at the actual cruise locations, dates, and depths. A case without imposed measurement biases could test whether the method introduces unnecessary corrections to real ocean changes. Cases with imposed cruise biases and calibration shifts could test its ability to recover known errors. Such experiments could quantify false adjustments, residual errors, regional trend distortion, and performance in weakly connected parts of the crossover network. Where appropriate, they could also test whether corrections inferred from deep water remain suitable for the upper water column. This suggestion does not need to be implemented in the current revision, but it could be discussed in the manuscript or considered for future work.

Line 70 (p. 2): replace “last accesses” with “last accessed.”

Line 256 (p. 11): insert a space in “andTAlk” to give “and TAlk.”

Table 6 caption (p. 17): replace “natural variably” with “natural variability.”

Line 552 (p. 22): replace “A summary … are presented” with “A summary … is presented.”

Lines 604, 670, 677, and 685 (pp. 25–27): correct the repeated abbreviation “wRSME” to “wRMSE.”

Figure 15 caption (p. 31): replace “the NNATL region and the Arctic is excluded” with “the NNATL region and the Arctic are excluded.”

Figure 19 caption (p. 35): replace “Figure 19.:” with “Figure 19:”.

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Citation: https://doi.org/10.5194/essd-2026-496-RC2

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The Global Ocean Data Analysis Project version 3 (GLODAPv3) – an internally consistent biogeochemical data product for the World Ocean Nico Lange et al. https://doi.org/10.25921/m6tp-mj50

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GLODAP is a data product for ocean inorganic carbon and related biogeochemical variables measured by the chemical analysis of water bottle samples from scientific cruises. GLODAPv3 is the third version release of GLODAP. The data that are included have been subjected to extensive quality control, including systematic evaluation of systematic cruise differences. This version contains data from 1181 hydrographic cruises covering the world's oceans from 1972 to 2023.


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