the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Jul 2026
Coastal Ocean Data Analysis Product in North America (Version 2026)
Abstract. The coastal Ocean Data Analysis Product in North America (CODAP-NA, Version 2026) represents a major expansion of coastal ocean carbonate chemistry synthesis for North American continental margins. Compared to CODAP-NA Version 2021, the updated product integrates newly available cruise observations spanning more than four decades, substantially increasing both the spatial and temporal coverage of coastal biogeochemical measurements across North American continental shelves. Observations from multiple research programs have been harmonized into a unified, internally consistent format through standardized quality control procedures, enabling large-scale analyses of ocean carbon cycling and ocean acidification along the North American margins. This version comprises 446 cruises, 31,864 hydrographic profiles, and 195,489 discrete data records covering continental shelf environments from Alaska to Mexico in the west and from Canada to the Caribbean in the east from 1981 to 2024. Fourteen variables (including temperature, salinity, dissolved oxygen, dissolved inorganic carbon, total alkalinity, pH on the Total Scale, carbonate ion, fugacity of carbon dioxide, silicate, phosphate, nitrate, nitrite, nitrate plus nitrite, and ammonium) were subjected to extensive quality control. CODAP-NA Version 2026 is available as a merged data product in CSV, MATLAB, and NetCDF formats (https://doi.org/10.25921/h2ff-9d66) through the NOAA Ocean Carbon and Acidification Data System (OCADS: https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0315529.html). The original cruise data were archived and are accessible via a summary table at the NCEI Ocean Acidification Data Stewardship repository (https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/synthesis/CODAP-NAv2.html).
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Status: open (until 08 Sep 2026)
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RC1: 'Comment on essd-2026-516', Anonymous Referee #1, 17 Aug 2026
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AC1: 'Reply on RC1', Li-Qing Jiang, 01 Sep 2026
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We thank the Reviewer for the constructive comments that helped improve the manuscript!
We have carefully reviewed all the comments and revised the manuscript. Please find below a point-by-point response to the reviewer comments. Additionally, we attached a pdf file with pictures.
1. The manuscript would benefit from further development of the content across all sections, especially one describing the data synthesis and variables contained, and the quality control methods. Each section should provide additional details, clearer explanations, and sufficient supporting information to strengthen the overall presentation and ensure that the main points are fully addressed. Expanding the content where appropriate would improve the manuscript’s clarity, depth, and overall scientific contribution.
Answer: We thank the reviewer for this constructive feedback. We agree that additional methodological detail and clearer explanations enhance the manuscript’s transparency and utility. Accordingly, we have substantially expanded Sections 2–4 (Study Site, Data Sources, and Quality-Control Methods) to provide comprehensive descriptions of the data and workflow, as well as explicit criteria for assigning quality flags.
2. The figures currently focus primarily on the updated temporal and spatial distribution resulting from the data synthesis. While these representations are useful, the manuscript would benefit from including additional analyses that provide further evidence of the quality and internal consistency of the CODAP dataset. For example, the authors could consider presenting information on the detection and treatment of outliers using ESPER, as well as the use of WOA23 for an independent assessment of CTD temperature data.
Answer: Thank you for this constructive suggestion. We have expanded our Data Quality Control section to explicitly detail our outlier detection, flagging, and independent validation procedures.
ESPER Outlier Analysis: ESPER-derived values are not used as the single source of truth for flagging outliers. However, when a variable is determined using multiple approaches—for example, pH measured directly with spectrophotometers and calculated from dissolved inorganic carbon (DIC) and total alkalinity (TA)—ESPER estimates provide an independent reference to help identify which value may be problematic. By calculating residual differences between measured values and ESPER-predicted values (e.g., ΔTALK = TALKmeasured - TALKESPER), along with evaluating multi-panel property-property plots (TA vs. Depth, TA vs. Salinity, TA vs. DIC, TA vs. Silicate), we holistically identify anomalous data points. Points exhibiting significant deviations across multiple property relationships are assigned standard QC flags (e.g., QC Flag 4 = bad data) and excluded from primary analysis. Also, our quality control procedure was evaluated by cross-referencing individual profiles, examining consistency among profiles within a single cruise, and performing cruise-to-cruise comparisons.
WOA23 Climatological Assessment: CTD temperature and salinity profiles were independently cross-referenced against historical climatological envelopes from the World Ocean Atlas 2023 (WOA23) to check for sensor drift or depth-calibration errors prior to running ESPER routines.
For example, the measure CTD temperature was recorded at 17.22°C, whereas the corresponding WOA23 climatological baseline at that depth is ~4°C. This yields an anomalous temperature residual of 13.2°C, which is far outside any realistic hydrographic variance for intermediate deep waters in this region. This point was flagged as an outlier (QC flag 4).
3. Providing additional details and supporting analyses of this nature would help substantiate the statement in the abstract that CODAP is internally consistent. Such information would also strengthen the methodological transparency of the study and give readers greater confidence in the reliability and quality of the resulting data synthesis. For example, was CO2 internal consistency analysis used to help improve the data consistency?
Answer: Thank you for this constructive comment. We agree that detailing our internal consistency analysis strengthens the methodological transparency of CODAP and provides greater confidence in data quality. Thermodynamic internal consistency checks were explicitly performed for cruises with overdetermined carbonate system parameters (i.e., simultaneous measurements of three or more parameters among DIC, TA, pH, and pCO2/fCO2). Using CO2SYS, we calculated pair-wise discrepancies between measured values and those calculated from parameter pairs (e.g., comparing measured pH against pH calculated from TA and DIC). These residuals allowed us to identify systematic offsets, evaluate the constant consistency, and apply bias corrections or adjust quality flags prior to finalizing the synthesis product. We have added a dedicated subsection (Section 4.4: Carbonate System Thermodynamic Internal Consistency).
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AC1: 'Reply on RC1', Li-Qing Jiang, 01 Sep 2026
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Data sets
Coastal Ocean Data Analysis Product in North America (CODAP-NA, Version 2026) from 1981-08-23 to 2024-11-23 (NCEI Accession 0315529) Hyelim Yoo et al. https://doi.org/10.25921/h2ff-9d66
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Dear authors,
the manuscript submitted to ESSD entitled "Coastal Ocean Data Analysis Product in North America (CODAP-NA, Version 2026)" is a very relevant contribution to ocean data managing paving the way for a better, easier and more robust and through assessment on ocean acidification research in coastal areas of North America. The synthesis data product presented will be of major relevance and use for the oceanographic, both observers, modellers and ecologist, dealing the OA research. This manuscript is sort of continuation or update of a previous manuscript explaining an earlier version of the data synthesis product CODAP (https://essd.copernicus.org/articles/13/2777/2021/ ).
Despite the relevance and already release of the data product, I have a major comment about the manuscript:
The manuscript would benefit from further development of the content across all sections, especially one describing the data synthesis and variables contained, and the quality control methods. In particular, each section should provide additional details, clearer explanations, and sufficient supporting information to strengthen the overall presentation and ensure that the main points are fully addressed. Expanding the content where appropriate would improve the manuscript’s clarity, depth, and overall scientific contribution.
The figures currently focus primarily on the updated temporal and spatial distribution resulting from the data synthesis. While these representations are useful, the manuscript would benefit from including additional analyses that provide further evidence of the quality and internal consistency of the CODAP dataset. For example, the authors could consider presenting information on the detection and treatment of outliers using ESPER, as well as the use of WOA23 for an independent assessment of CTD temperature data.
Providing additional details and supporting analyses of this nature would help substantiate the statement in the abstract that CODAP is internally consistent. Such information would also strengthen the methodological transparency of the study and give readers greater confidence in the reliability and quality of the resulting data synthesis. For example, was CO2 internal consistency analysis used to help improve the data consistency?
I have provided some annotations in the pdf attached with minor issues.
Best regards