This dataset includes surface underway measurements of pH, salinity and water temperature obtained during R/V Xue Long CHINARE2018 Expedition (EXPOCODE 76XL20180723) Japan Sea, Sea of Okhotsk, North Pacific Ocean, Bering Sea, Chukchi Sea and Arctic Ocean from 2018-07-23 to 2018-09-22. The instrument used to measure pH data is an advanced spectrophotometric loop flow analyzer for high-precision seawater pH (LFA-pH). The pH data are calibrated with respect to discrete measurements of spectrophotometic pH during the cruise. The descriptions of data quality-control are given in a recently submitted manuscript to Geophysical Research Letters.

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.

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.

This dataset includes surface underway data collected from R/V Nathaniel B. Palmer in the South Pacific Ocean and Southern Oceans from 2016-12-24 to 2017-12-06. These data include barometric pressure, partial pressure (or fugacity) of carbon dioxide - water, salinity and sea surface temperature. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement. These data were collected by Stewart C. Sutherland and Taro Takahashi of Lamont-Doherty Earth Observatory (LDEO) and Colm Sweeney of NOAA Earth System Research Laboratory (ESRL) as part of the SOOP R/V Nathaniel B. Palmer 2017 dataset.

This dataset includes high-frequency (hourly to sub-hourly) coastal acidification time-series data collected during nine deployments in the aforementioned seven estuaries along the US East Coast, US West Coast and Gulf of Mexico from 2015-04-23 to 2020-07-29. These data include water temperature, salinity, partial pressure of carbon dioxide (pCO2) in water, dissolved oxygen (DO) in water, and pH on the total scale. The instruments used to collected these data include Sunburst SAMI-CO2, Pro-Oceanus CO2-Pro CV and a LiCOr LI-820 CO2 gas analyzers for autonomous pCO2 measurements, Sea-Bird SeapHOx and SeaFET instruments for pH measurements, Sea-Bird SeapHOx and Aanderaa Oxygen Optode instruments for DO measurements, and YSI water sensing instrument packages for measurements of conductivity (salinity), temperature and depth. Beginning in 2015, the U.S. Environmental Protection Agency’s (EPA) National Estuary Program (NEP) started a collaboration with partners in seven estuaries along the East Coast (Barnegat Bay; Casco Bay), West Coast (Santa Monica Bay; San Francisco Bay; Tillamook Bay), and the Gulf of Mexico (GOM) Coast (Tampa Bay; Mission-Aransas Estuary) of the United States to expand the use of autonomous monitoring partial pressure of carbon dioxide (pCO2) and pH sensors to evaluate carbonate chemistry in the estuarine environment.

This dataset includes surface underway data collected from R/V Sikuliaq in the North Pacific Ocean, Gulf of Alaska, Bering Sea, Chukchi Sea and Arctic Ocean from 2016-12-31 to 2017-11-07. These data include barometric pressure, partial pressure (or fugacity) of carbon dioxide - water, salinity and sea surface temperature. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement. These data were collected by Stewart C. Sutherland and Taro Takahashi of Lamont-Doherty Earth Observatory (LDEO) and Colm Sweeney of NOAA Earth System Research Laboratory (ESRL) as part of the SOOP_R/V_Sikuliaq_2017 dataset.

This dataset contains water temperature, salinity, phytoplankton, zooplankton, and suspended particulate matter taken by CTD, nets, and other instrumentation in the Bering and Chukchi Seas from the research vessel icebreaker Xue Long during the 5-th Chinese National Arctic Scientific Research Expedition (CHINARE5). The objectives of the CHINARE5 were to improve understanding of basic environmental information of marine hydrology in summer 2012 in areas of the Bering Sea, Chukchi Sea, Chukchi Sea Rise, and to provide basic information for global climate change research. The main work was undertaken through sectional observations of the aforementioned sea areas. Data are in CNV, XLSX formats. This dataset is U.S. State Department MSR U2012-020 as part of the World Data Services for Geophysics and Oceanography.