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1. A compilation of global bio-optical in situ data for ocean colour satellite applications – version three

   https://doi.org/10.5194/essd-14-5737-2022  

   Valente, André; Sathyendranath, Shubha; Brotas, Vanda; Groom, Steve; Grant, Michael; Jackson, Thomas; Chuprin, Andrei; Taberner, Malcolm; Airs, Ruth; Antoine, David; et al (January 2022, Earth System Science Data)

   Abstract. A global in situ data set for validation of ocean colour productsfrom the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented.This version of the compilation, starting in 1997, now extends to 2021,which is important for the validation of the most recent satellite opticalsensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprisesin situ observations of the following variables: spectral remote-sensingreflectance, concentration of chlorophyll-a, spectral inherent opticalproperties, spectral diffuse attenuation coefficient, and total suspendedmatter. Data were obtained from multi-project archives acquired via openinternet services or from individual projects acquired directly from dataproviders. Methodologies were implemented for homogenization, qualitycontrol, and merging of all data. Minimal changes were made on the originaldata, other than conversion to a standard format, elimination of some points,after quality control and averaging of observations that were close in timeand space. The result is a merged table available in text format. Overall,the size of the data set grew with 148 432 rows, with each row representing aunique station in space and time (cf. 136 250 rows in previous version;Valente et al., 2019). Observations of remote-sensing reflectance increasedto 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There wasalso a near tenfold increase in chlorophyll data since 2016. Metadata ofeach in situ measurement (original source, cruise or experiment, principalinvestigator) are included in the final table. By making the metadataavailable, provenance is better documented and it is also possible toanalyse each set of data separately. The compiled data are available athttps://doi.org/10.1594/PANGAEA.941318 (Valente et al., 2022). 

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2. An Ocean-Colour Time Series for Use in Climate Studies: The Experience of the Ocean-Colour Climate Change Initiative (OC-CCI)

   https://doi.org/10.3390/s19194285  

   Sathyendranath, Shubha; Brewin, Robert; Brockmann, Carsten; Brotas, Vanda; Calton, Ben; Chuprin, Andrei; Cipollini, Paolo; Couto, André; Dingle, James; Doerffer, Roland; et al (October 2019, Sensors)

   Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean-colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea-viewing Wide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel. 

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3. Surface Ocean CO2 Atlas Database Version 2022 (SOCATv2022) (NCEI Accession 0253659)

   https://doi.org/10.25921/1h9f-nb73  

   Bakker, Dorothee C.; Alin, Simone R.; Becker, Meike; Bittig, Henry C.; Castaño-Primo, Rocío; Feely, Richard A.; Gkritzalis, Thanos; Kadono, Koji; Kozyr, Alex; Lauvset, Siv K.; et al (January 2022, NOAA National Centers for Environmental Information)

   This dataset consists of the Surface Ocean CO2 Atlas Version 2022 (SOCATv2022) data product files. The ocean absorbs one quarter of the global CO2 emissions from human activity. The community-led Surface Ocean CO2 Atlas (www.socat.info) is key for the quantification of ocean CO2 uptake and its variation, now and in the future. SOCAT version 2022 has quality-controlled in situ surface ocean fCO2 (fugacity of CO2) measurements on ships, moorings, autonomous and drifting surface platforms for the global oceans and coastal seas from 1957 to 2021. The main synthesis and gridded products contain 33.7 million fCO2 values with an estimated accuracy of better than 5 μatm. A further 6.4 million fCO2 sensor data with an estimated accuracy of 5 to 10 μatm are separately available. During quality control, marine scientists assign a flag to each data set, as well as WOCE flags of 2 (good), 3 (questionable) or 4 (bad) to individual fCO2 values. Data sets are assigned flags of A and B for an estimated accuracy of better than 2 μatm, flags of C and D for an accuracy of better than 5 μatm and a flag of E for an accuracy of better than 10 μatm. Bakker et al. (2016) describe the quality control criteria used in SOCAT versions 3 to 2022. Quality control comments for individual data sets can be accessed via the SOCAT Data Set Viewer (www.socat.info). All data sets, where data quality has been deemed acceptable, have been made public. The main SOCAT synthesis files and the gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Access to data sets with an estimated accuracy of 5 to 10 (flag of E) and fCO2 values with flags of 3 and 4 is via additional data products and the Data Set Viewer (Table 8 in Bakker et al., 2016). SOCAT publishes a global gridded product with a 1° longitude by 1° latitude resolution. A second product with a higher resolution of 0.25° longitude by 0.25° latitude is available for the coastal seas. The gridded products contain all data sets with an estimated accuracy of better than 5 µatm (data set flags of A to D) and fCO2 values with a WOCE flag of 2. Gridded products are available monthly, per year and per decade. Two powerful, interactive, online viewers, the Data Set Viewer and the Gridded Data Viewer (www.socat.info), enable investigation of the SOCAT synthesis and gridded data products. SOCAT data products can be downloaded. Matlab code is available for reading these files. Ocean Data View also provides access to the SOCAT data products (www.socat.info). SOCAT data products are discoverable, accessible and citable. The SOCAT Data Use Statement (www.socat.info) asks users to generously acknowledge the contribution of SOCAT scientists by invitation to co-authorship, especially for data providers in regional studies, and/or reference to relevant scientific articles. The SOCAT website (www.socat.info) provides a single access point for online viewers, downloadable data sets, the Data Use Statement, a list of contributors and an overview of scientific publications on and using SOCAT. Automation of data upload and initial data checks allows annual releases of SOCAT from version 4 onwards. SOCAT is used for quantification of ocean CO2 uptake and ocean acidification and for evaluation of climate models and sensor data. SOCAT products inform the annual Global Carbon Budget since 2013. The annual SOCAT releases by the SOCAT scientific community are a Voluntary Commitment for United Nations Sustainable Development Goal 14.3 (Reduce Ocean Acidification) (#OceanAction20464). More broadly the SOCAT releases contribute to UN SDG 13 (Climate Action) and SDG 14 (Life Below Water), and to the UN Decade of Ocean Science for Sustainable Development. Hundreds of peer-reviewed scientific publications and high-impact reports cite SOCAT. The SOCAT community-led synthesis product is a key step in the value chain based on in situ inorganic carbon measurements of the oceans, which provides policy makers with critical information on ocean CO2 uptake in climate negotiations. The need for accurate knowledge of global ocean CO2 uptake and its (future) variation makes sustained funding of in situ surface ocean CO2 observations imperative. 

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4. The annual update GLODAPv2.2023: the global interior ocean biogeochemical data product

   https://doi.org/10.5194/essd-16-2047-2024  

   Lauvset, Siv K; Lange, Nico; Tanhua, Toste; Bittig, Henry C; Olsen, Are; Kozyr, Alex; Álvarez, Marta; Azetsu-Scott, Kumiko; Brown, Peter J; Carter, Brendan R; et al (January 2024, Earth System Science Data)

   Abstract. 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. GLODAPv2.2023 is an update of the previous version, GLODAPv2.2022 (Lauvset et al., 2022). The major changes are as follows: data from 23 new cruises were added. In addition, a number of changes were made to the data included in GLODAPv2.2022. GLODAPv2.2023 includes measurements from more than 1.4 million water samples from the global oceans collected on 1108 cruises. The data for the now 13 GLODAP core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, chlorofluorocarbon-11 (CFC-11), CFC-12, CFC-113, CCl4, and SF6) have undergone extensive quality control with a focus on the 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 23 new cruises were derived by comparing those data with the data from the 1085 quality-controlled cruises in the GLODAPv2.2022 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. The original data, their documentation, and DOI codes are available at the Ocean Carbon and Acidification Data System of NOAA National Centers for Environmental Information (NCEI), which also provides access to the merged data product. This 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/zyrq-ht66 (Lauvset et al., 2023). These bias-adjusted product files also include significant ancillary and approximated data, which were obtained by interpolation of, or calculation from, measured data. This living data update documents the GLODAPv2.2023 methods and provides a broad overview of the secondary quality control procedures and results. 

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5. Coastal Ocean Data Analysis Product in North America (CODAP-NA) – an internally consistent data product for discrete inorganic carbon, oxygen, and nutrients on the North American ocean margins

   https://doi.org/10.5194/essd-13-2777-2021  

   Jiang, Li-Qing; Feely, Richard A.; Wanninkhof, Rik; Greeley, Dana; Barbero, Leticia; Alin, Simone; Carter, Brendan R.; Pierrot, Denis; Featherstone, Charles; Hooper, James; et al (January 2021, Earth System Science Data)

   null (Ed.)

   Abstract. Internally consistent, quality-controlled (QC) data products play animportant role in promoting regional-to-global research efforts tounderstand societal vulnerabilities to ocean acidification (OA). However,there are currently no such data products for the coastal ocean, where mostof the OA-susceptible commercial and recreational fisheries and aquacultureindustries are located. In this collaborative effort, we compiled, quality-controlled, and synthesized 2 decades of discrete measurements ofinorganic carbon system parameters, oxygen, and nutrient chemistry data fromthe North American continental shelves to generate a data product calledthe Coastal Ocean Data Analysis Product in North America (CODAP-NA). Thereare few deep-water (> 1500 m) sampling locations in the currentdata product. As a result, crossover analyses, which rely on comparisonsbetween measurements on different cruises in the stable deep ocean, couldnot form the basis for cruise-to-cruise adjustments. For this reason, carewas taken in the selection of data sets to include in this initial releaseof CODAP-NA, and only data sets from laboratories with known qualityassurance practices were included. New consistency checks and outlierdetections were used to QC the data. Future releases of this CODAP-NAproduct will use this core data product as the basis for cruise-to-cruisecomparisons. We worked closely with the investigators who collected andmeasured these data during the QC process. This version (v2021) of theCODAP-NA is comprised of 3391 oceanographic profiles from 61 researchcruises covering all continental shelves of North America, from Alaska toMexico in the west and from Canada to the Caribbean in the east. Data for 14variables (temperature; salinity; dissolved oxygen content; dissolvedinorganic carbon content; total alkalinity; pH on total scale; carbonateion content; fugacity of carbon dioxide; and substance contents of silicate,phosphate, nitrate, nitrite, nitrate plus nitrite, and ammonium) have beensubjected to extensive QC. CODAP-NA is available as a merged data product(Excel, CSV, MATLAB, and NetCDF; https://doi.org/10.25921/531n-c230,https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0219960.html, last access: 15 May 2021)(Jiang et al., 2021a). The original cruise data have also been updated withdata providers' consent and summarized in a table with links to NOAA'sNational Centers for Environmental Information (NCEI) archives(https://www.ncei.noaa.gov/access/ocean-acidification-data-stewardship-oads/synthesis/NAcruises.html). 

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