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Global surface ocean pH, acidity, and Revelle Factor on a 1x1 degree global grid from 1770 to 2100 (NCEI Accession 0206289)
This dataset contains spatial distribution of surface ocean pH (total hydrogen scale), acidity (or hydrogen ion activity, unit: nmol/kg, or 10^-9 mol/kg) and Revelle Factor (a measure of the ocean's buffer capacity, unitless) on a 1x1 degree global grid (Longitude: [20.5:1:379.5], Latitude: [-89.5:1:89.5]) in all 12 months of the years from 1770 to 2100 (1770, 1780, 1790, ..., 2100). This data product is produced by combining a recent observational seawater carbon dioxide (CO2) data product, i.e., the 6th version of the Surface Ocean CO2 Atlas (1991-2018, ~23 million observations), with temporal trends at individual locations of the global ocean from a robust Earth System Model (ESM2M), to provide a high-resolution regionally varying view of global surface ocean pH, acidity, and the Revelle Factor. The climatology extends from the pre-Industrial era (1770 C.E.) to the end of this century under historical atmospheric CO2 concentrations (pre-2005) and the Representative Concentrations Pathways (RCP2.6, RCP4.5, RCP6.0 and RCP8.5, post-2005) of the Intergovernmental Panel on Climate Change (IPCC)’s 5th Assessment Report (AR5). By linking the modeled pH trends to the observed modern pH distribution, the climatology benefits from recent improvements in both model design and observational data coverage, and is likely to provide improved regional OA trajectories than the model output could alone, therefore, will help guide the regional OA adaptation strategies. Revelle Factor is defined as the ratio between the fractional change in pCO2 to the fractional change in dissolved inorganic carbon (DIC). This dataset is available in netCDF format. Some plots and animation files are also available for your presentation purposes. For details of the calculation and gridding method, please refer to Jiang, L.-Q., B. R. Carter, R. A. Feely, S. Lauvset, and A. Olsen (2019), Surface ocean pH and buffer capacity: past, present and future, Nature Scientific Reports, 9:18624, https://doi.org/10.1038/s41598-019-55039-4.
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RFR-LME Ocean Acidification Indicators from 1998 to 2024 (NCEI Accession 0287551)
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Dataset Description: Gridded monthly data products of surface ocean acidification indicators from 1998 to 2024 and on a 0.25° by 0.25° spatial grid have been developed for eleven U.S. Large Marine Ecosystems (LMEs) using a machine learning algorithm called random forest regression (RFR). The data products are called RFR-LMEs, and were constructed using observations from the Surface Ocean CO2 Atlas — co-located with surface ocean properties from various satellite, reanalysis, and observational products — with an approach that utilized two types of machine learning algorithms: (1) Gaussian mixture models to cluster the data into subregions with similar environmental variability and (2) RFRs that were trained and applied separately in each cluster to interpolate the observational data in space and time. RFR-LMEs also rely on previously published seawater property estimation routines to obtain the full suite of ocean acidification indicators. The products show a domain-wide carbo n dioxide partial pressure increase of 1.6 ± 0.4 μatm yr−1 and pH decrease of 0.0015 ± 0.0004 yr−1. More information on the creation and validation of RFR-LMEs is available in the following publication: Sharp, J.D., Jiang, L., Carter, B.R., Lavin, P.D., Yoo, H., Cross, S.L., 2024. A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States. Scientific Data, 11, 715, 10.1038/s41597-024- 03530-7.
Global subsurface ocean acidification indicators at depth levels of 50, 100, and 200 meters from 1750-01-01 to 2100-12-31 (NCEI Accession 0287573)
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This data package contains 10 global subsurface ocean acidification (OA) indicators at standardized depth levels of 50, 100, and 200 meters. The indicators include fugacity of carbon dioxide, pH on the total scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content. They are presented on a global ocean grid of 1° × 1°, as decadal averages spanning from preindustrial conditions (1750) through historical conditions (1850–2010) and projected into five future scenarios defined by Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from 2020 to 2100. These OA indicators were generated by following the same approach as described by Jiang et al. (2023) (https://doi.org/10.1029/2022MS003563), and utilized data from 14 Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), as well as a gridded data product provided by Lauvset et al. (2016) (https://doi.org/10.5194/essd-8-325-2016).
Indian ocean acidification and its driving mechanisms over the last four decades from 1980-01-01 to 2019-12-31 (NCEI Accession 0307663)
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The dataset contains sea-surface temperature, salinity, dissolved inorganic carbon, total alkalinity, pH, and partial pressure of CO2 for the Indian Ocean region (Longitude: 30°E-120°E, Latitude: 30°S-30°N). The data is available from 1980 to 2019 on a monthly time scale. Each of these data variables has a spatial resolution of 1/12°.
Global surface ocean acidification indicators from 1750 to 2100 (NCEI Accession 0259391)
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This data package contains a hybrid surface OA data product that is produced based on three recent observational data products: (a) the Surface Ocean CO2 Atlas (SOCAT, version 2022), (b) the Global Ocean Data Analysis Product version 2 (GLODAPv2, version 2022), and (c) the Coastal Ocean Data Analysis Product in North America (CODAP-NA, version 2021), and 14 Earth System Models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The trajectories of ten OA indicators, including fugacity of carbon dioxide, pH on Total Scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, Revelle Factor, total dissolved inorganic carbon content, and total alkalinity content are provided under preindustrial conditions, historical conditions, and future Shared Socioeconomic Pathways: SSP1-19, SSP1-26, SSP2-45, SSP3-70, and SSP5-85 from 1750 to 2100 on a global surface ocean grid. These OA trajectories are improved relative to previous OA data products with respect to data quantity, spatial and temporal coverage, diversity of the underlying data and model simulations, and the provided SSPs over the 21st century.
Climatological distribution of ocean acidification indicators from surface to 500 meters water depth on the North American ocean margins from 2003-12-06 to 2018-11-22 (NCEI Accession 0270962)
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This data package contains 1x1 degree coastal climatologies (mean fields of oceanographic variables on a regular geographic grid at specific depths) of pH on the Total Scale, total hydrogen ion content, free hydrogen ion content, carbonate ion content, aragonite saturation state, calcite saturation state, total dissolved inorganic carbon content, and total alkalinity content from surface to 500 meters water depth on North American ocean margins. These climatologies were developed with the World Ocean Atlas (WOA) gridding technologies of the NOAA National Centers for Environmental Information (NCEI), based on the recently released Coastal Ocean Data Analysis Product in North America (CODAP-NA, https://doi.org/10.5194/essd-13-2777-2021), along with the Global Ocean Data Analysis Product version 2 (GLODAPv2, version 2021, https://doi.org/10.5194/essd-13-5565-2021). The relevant variables were adjusted to the year of 2010 based on the algorithms as developed by Carter et al. (2021, https://doi.org/10.1002/lom3.10461) before the gridding. This data package contains a total of 8 NetCDF files, one for each of the variable. It is recommended to use the objectively analyzed mean fields (with "_an" postfix) for each variable.