The Ocean Data Inventory database is an inventory of all of the oceanographic time series data held by the Ocean Science Division at the Bedford Institute of Oceanography. The data archive includes about 5800 current meter and acoustic doppler time series, 4500 coastal temperature time series from thermographs, as well as a small number (200) of tide gauges. Many of the current meters also have temperature and salinity sensors. The area for which there are data is roughly defined as the North Atlantic and Arctic from 30° - 82° N, although there are some minor amounts of data from other parts of the world. The time period is from 1960 to present. The database is updated on a regular basis.

Monthly and annual means of various heat budget terms were derived for the tropical Pacific Ocean for a period of 20 years between 1957 and 1976, inclusive, from about five ... million marine weather reports. This dataset contains monthly and annual means, as well as a long-term 20-year mean.

The world's oceans are becoming increasingly acidic, with the average ocean pH falling from 8.11 in 1985 to 8.05 in 2022. This seemingly small change represents a significant increase in acidity, damaging the fine chemical balance of the oceans and posing a risk to marine ecosystems. The more emissions, the more acidic As global CO2 emissions continue to rise, the oceans absorb more CO2 per year, playing a crucial role in regulating atmospheric CO2 levels. The increased dissolution of CO2 in seawater causes the oceans’ pH to decrease. The acidification of the oceans creates conditions that dissolve minerals such as carbonates, which are the backbone of reefs and marine life’s shells and skeletons. In addition, certain species of harmful algae proliferate in acidified waters, putting fish, marine mammals, and the full food chain in danger. Warmer oceans on top of acidification Acidification is not the only climate change-related issue the oceans must adapt to. In 2023, the average ocean surface temperature worldwide was almost one degree Celsius higher than the 20th century average. Such departures from average conditions are called anomalies, and although they fluctuate, the global ocean surface temperature anomaly has shown a marked upward trend over the past decades. A warming ocean brings a series of cascading effects, including the melting of sea ice, sea level rise, and marine heatwaves. On top of that, less carbon sinks to the deep ocean in warmer waters, making them a less efficient carbon pool and therefore aggravating climate change.

An ocean current is a continuous, directed movement of seawater generated by forces acting upon this mean flow, such as breaking waves, wind, the Coriolis effect, cabbeling, and temperature and salinity differences, while tides are caused by the gravitational pull of the Sun and Moon. Depth contours, shoreline configurations, and interactions with other currents influence a current's direction and strength. Ocean currents flow for great distances, and together, create the global conveyor belt which plays a dominant role in determining the climate of many of the Earths regions. More specifically, ocean currents influence the temperature of the regions through which they travel. General near surface ocean current data was provided by Petroleum Affairs Division. Data was created as part of the Irish Offshore Strategic Environmental Assessment (IOSEA).

Domestic marine pollution incident statistics: The number of reported incidents is divided by county and city.

The GLobal Ocean Data Analysis Project (GLODAP) is a cooperative effort to coordinate global synthesis projects funded through NOAA/DOE and NSF as part of the Joint Global Ocean Flux Study - Synthesis and Modeling Project (JGOFS-SMP). Cruises conducted as part of the World Ocean Circulation Experiment (WOCE), Joint Global Ocean Flux Study (JGOFS) and NOAA Ocean-Atmosphere Exchange Study (OACES) over the decade of the 1990s have created an oceanographic database of unparalleled quality and quantity. These data provide an important asset to the scientific community investigating carbon cycling in the oceans.

World Ocean Atlas 2018 (WOA18) is a set of objectively analyzed (one degree grid and quarter degree grid) climatological fields of in situ temperature, salinity, dissolved oxygen, Apparent Oxygen Utilization (AOU), percent oxygen saturation, phosphate, silicate, and nitrate at standard depth levels for annual, seasonal, and monthly compositing periods for the World Ocean. Quarter degree fields are for temperature and salinity only. It also includes associated statistical fields of observed oceanographic profile data interpolated to standard depth levels on quarter degree, one degree, and five degree grids. Temperature and salinity fields are available for six decades (1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2004, and 2005-2017) an average of all decades representing the period 1955-2017, as well as a thirty year "climate normal" period 1981-2010. Oxygen fields (as well as AOU and percent oxygen saturation) are available using all quality controlled data 1960-2017, nutrient fields using all quality controlled data from the entire sampling period 1878-2017. This accession is a product generated by the National Centers for Environmental Information's (NCEI) Ocean Climate Laboratory Team. The analyses are derived from the NCEI World Ocean Database 2018.

This National Centers for Environmental Information (NCEI) archival information package (AIP) contains a product generated by NCEI-- the Global Ocean Currents Database (GOCD). It is derived from NCEI AIPs that hold in situ ocean current data from a diverse range of instruments, collection protocols, processing methods, and data storage formats. For acceptance into the GOCD, the data must have sufficient quality control and thorough documentation. The GODC merges the variety of original formats into the NCEI standard network common data form (NetCDF) format. From the shipboard acoustic Doppler current profiler sets, the GOCD creates files that hold single vertical ocean currents profiles. The GOCD spans 1962 to 2013.

Salinity data collected on the Australian shelf between 1995 to 2014 have been assembled into a single data collection. Profiles, trajectories and timeseries datasets within the 500m depth contour and collected by different organisations have been included. A full list of datasets used to produce this collection is provided below:

• The Integrated Marine Observing System (IMOS):

• Seals CTD profiles

• Argo profiles

• Glider deployments

• CTD Casts performed at National Reference Station

• Moorings

• AUV deployments

• Sensor networks in the Great Barrier Reef

• Ship underway

• Royal Australian Navy (RAN):

• Sea Surface Temperature measurements on NSW coast

• The Australian Institute of Marine Science (AIMS):

• CTD casts

• Defence Science and Technology Organisation:

• Glider deployments

• Charles Darwin University – Xavier Hoenner:

• Hawksbill Turtles

• CSIRO Ocean and Atmosphere:

• Moorings

• Trajectory

• Underway

• World Ocean Database 2013 (WOD) – standard depth data products:

• XBT profiles (XBT)

• CTD casts (CTD)

• Surface only data (SUR)

• Undulating Oceano Recorder (UOR)

Salinity measurements from the different sources have been assembled into a common data structure in a relational database. Quality Control flags have been mapped to a common scheme and associated to each measurements.

Around 25 Million measurements are available in this dataset collection.

Datasets like gliders, moorings or ship underway are sampled at high resolution (e.g.: data every seconds). A sub-sampling approach has been applied to some of these datasets in order to reduce the number of measurements. For example, ship underway data have been averaged over a period of 1 minute and sub-sampled every 5 minutes. Hourly average have been performed on most of the moorings timeseries.

Various quality control checks have been performed on the dataset. A full list of quality control checks is available in the Lineage section of the metadata records.

A national shelf and coastal data atlas has been created using all the salinity measurements. The observations have been binned on an horizontal grid of ¼ degree with standard vertical levels (every 10 meters from the surface to -500m). Moreover, a monthly time range have been used over the period January 1995 to December 2014. The number of observations in each grid square has been determined and additional statistics have been calculated like the mean, the standard deviation, the minimum and maximum values for each grid square.

Two WFS services have been created to publish the individual observations, and the statistics, used to produce the data atlas.

Economics: National Ocean Watch (ENOW) contains annual time-series data for about 400 coastal counties, 30 coastal states, and the nation, derived from the Bureau of Labor Statistics and the Bureau of Economic Analysis. It describes 23 industries in six economic sectors that depend on the oceans and Great Lakes and measures four economic indicators: Establishments, Employment, Wages, and Gross...

MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (originally known as EOS AM-1) and Aqua (originally known as EOS PM-1) satellites. Terra's orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths (see MODIS Technical Specifications). These data will improve our understanding of global dynamics and processes occurring on the land, in the oceans, and in the lower atmosphere. MODIS is playing a vital role in the development of validated, global, interactive Earth system models able to predict global change accurately enough to assist policy makers in making sound decisions concerning the protection of our environment.

Terra NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group; (2014): MODIS-Terra Ocean Color Data; NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. http://dx.doi.org/10.5067/TERRA/MODIS_OC.2014.0 Accessed on 07/28/2015.

Aqua NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group; (2014): MODIS-Aqua Ocean Color Data; NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. http://dx.doi.org/10.5067/AQUA/MODIS_OC.2014.0 Accessed on 07/28/2015.

In 2023, the Seto Inland Sea area showed, with 73 confirmed cases, the highest number of marine pollution cases, followed by Coast of Hokkaido with 69 confirmed cases. In total, 397 cases of marine pollution were confirmed in Japanese sea areas during the period.

It provides annual statistics on vessel arrivals by flag and ocean/river.

This dataset contains level 1 in situ measurements of temperature and salinity from several autonomous, profiling APEX floats. These floats change their buoyancy by inflating an external bladder with oil, allowing them to dive and surface regularly. Conductivity, Temperature and Depth sensors (CTDs) allow them to collect vertical profiles of temperature and salinity. This provided measurements of the ocean's physical characteristics around Greenland. The floats wer deployed as part of the Oceans Melting Greenland (OMG) project. The goal of the project is to find out what contributions the ocean has on Greenland's melting glaciers.

This dataset contains the version 1.0 CYGNSS level 3 ocean microplastic concentration data record, which provides 18 netCDF files, each containing one month of daily gridded maps of microplastic number density (#/km^2). Microplastic concentration number density is indirectly estimated by an empirical relationship between ocean surface roughness and wind speed (Evans and Ruf, 2021). User caution is advised in regions containing independent, non-correlative factors affecting ocean surface roughness, such as anomalous atmospheric conditions within the Intertropical Convergence Zone, biogenic surfactants (such as algal blooms), oil spills, etc. This product reports microplastic concentration on a daily temporal and 0.25-degree latitude/longitude spatial grid with 30-day, 1 degree latitude/longitude feature resolution, as constrained by the binning and spatiotemporal averaging of the Mean Square Slope (MSS) anomaly (i.e., difference between measured and predicted ocean surface roughness for a given wind speed).

The cross-disciplinary themes will result in a diverse data catalogue. The ship collected data will be in the form of sea surface meteorology (2-D wind speed and direction, total irradiance, Photosynthetically Active Radiation/PAR, air temperature, atmospheric pressure, humidity); atmospheric carbon dioxide (pCO2); biological, chemical and physical properties and processes in the marine photic zone (carbonate chemistry - pCO2, total alkalinity, pH, DIC; dissolved gases - oxygen; nutrient concentrations, ammonium regeneration, nitrification, nitrogen fixation, zooplankon ecology, chlorophyll concentration, photosynthetic pigment composition, bacterial production, phytoplankton and bacterial speciation, concentrations of biogenic trace compounds such as dimethyl sulphide/DMS and dimthylsulphoniopropionate/DMSP, salinity, temperature, zooplankon ecology) and bioassays of these same parameters under different future IPCC CO2 and temperature scenarios. The long-term (18 month) laboratory based mesocosm experiments will include data on individual organism response (growth, immune response, reproductive fitness) under different future IPCC CO2 and temperature scenarios in rocky intertidal, soft sediment and calcareous biogenic habitats, as well as the effects on commercially important species of fish and shellfish. The analysis of sediment cores will provide greater resolution of the paleo record during the Paleocene-Eocene Thermal Maximum (PETM). Data will be used to aid the parameterisation of coastal and continental shelf seas (Northern Europe and the Arctic) model runs as well as larger scale global models. The shipboard fieldwork will take place around the UK, in the Arctic Ocean and the Southern Ocean. The mesocosms will look at temperate marine species common to UK shelf seas. Sediment cores have been collected from Tanzania. The models will look from the coastal seas of Northern Europe to the whole globe. Data to be generated will include data collected at sea, short-term (2-3 day) ship-board bioassays, from long-term (18 month) laboratory based mesocosm experiments and reconstructed paleo records from sediment cores. The 5 year UK Ocean Acidification Research Programme is the UK’s response to growing concerns over ocean acidification. Aims: 1 - to reduce uncertainties in predictions of carbonate chemistry changes and their effects on marine biogeochemistry, ecosystems and other components of the Earth System; 2 - to understand the responses to ocean acidification, and other climate change related stressors, by marine organisms, biodiversity and ecosystems and to improve understanding of their resistance or susceptibility to acidification; 3 - to provide data and effective advice to policy makers and managers of marine bioresources on the potential size and timescale of risks, to allow for development of appropriate mitigation and adaptation strategies. The study unites over 100 marine scientists from 27 institutions across the UK. It is jointly funded by Department for Environment, Food and Rural Affairs (Defra), the Natural Environment Research Council (NERC) and Department of Energy and Climate Change (DECC).

The World Ocean Database (WOD) is the world's largest publicly available uniform format quality controlled ocean profile dataset. Ocean profile data are sets of measurements of an ocean variable vs. depth at a single geographic location within a short (minutes to hours) temporal period in some portion of the water column from the surface to the bottom. To be considered a profile for the WOD, there must be more than a single depth/variable pair. Multiple profiles at the same location from the same set of instruments is an oceanographic cast. Ocean variables in the WOD include temperature, salinity, oxygen, nutrients, tracers, and biological variables such as plankton and chlorophyll. Quality control procedures are documented and performed on each cast and the results are included as flags on each measurement. The WOD contains the data on the originally measured depth levels (observed) and also interpolated to standard depth levels to present a more uniform set of iso-surfaces for oceanographic and climate work. The source of the WOD is more than 20,000 separate archived datasets contributed by institutions, project, government agencies, and individual investigators from the United States and around the world. Each dataset is available in its original form in the National Centers for Environmental Information data archives. All datasets are converted to the same standard format, checked for duplication within the WOD, and assigned quality flags based on objective tests. Additional subjective flags are set upon calculation of ocean climatological mean fields which make up the World Ocean Atlas (WOA) series. The WOD consists of periodic major releases and quarterly updates to those releases. Each major release is associated with a concurrent release of a WOA release, and contains final quality control flags used in the WOA, which includes manual as well as automated steps. Each quarterly update release includes additional historical and recent data and preliminary quality control. The latest major release was WOD 2018 (WOD18), which includes nearly 16 million oceanographic casts, from the second voyage of Captain Cook (1772) to the modern Argo floats (end of 2017). The WOD presents data in netCDF ragged array format following the Climate and Forecast (CF) conventions for ease of use mindful of space limitations.

This dataset provides a World Ocean Atlas of Argo inferred statistics. The primary data are exclusively Argo profiles. The statistics are done using the whole time range covered by the Argo data, starting in July 1997. The atlas is provided with a 0.25° resolution in the horizontal and 63 depths from 0 m to 2,000 m in the vertical. The statistics include means of Conservative Temperature (CT), Absolute Salinity, compensated density, compressiblity factor and vertical isopycnal displacement (VID); standard deviations of CT, VID and the squared Brunt Vaisala frequency; skewness and kurtosis of VID; and Eddy Available Potential Energy (EAPE). The compensated density is the product of the in-situ density times the compressibility factor. It generalizes the virtual density used in Roullet et al. (2014). The compressibility factor is defined so as to remove the dependency with pressure of the in-situ density. The compensated density is used in the computation of the VID and the EAPE.

This entry covers global ocean data aggregated to a monthly time resolution. The catalogue entry includes temperature and salinity characteristics of the upper oceans and complements the other seasonal forecast catalogue entries for the land and atmospheric variables. Seasonal forecasts provide a long-range outlook of changes in the Earth system over periods of a few weeks or months, as a result of predictable changes in some of the slow-varying components of the system. For example, ocean temperatures typically vary slowly, on timescales of weeks or months; as the ocean has an impact on the overlaying atmosphere, the variability of its properties (e.g. temperature) can modify both local and remote atmospheric conditions. Such modifications of the 'usual' atmospheric conditions are the essence of all long-range (e.g. seasonal) forecasts. This is different from a weather forecast, which gives a lot more precise detail - both in time and space - of the evolution of the state of the atmosphere over a few days into the future. Beyond a few days, the chaotic nature of the atmosphere limits the possibility to predict precise changes at local scales. This is one of the reasons long-range forecasts of atmospheric conditions have large uncertainties. To quantify such uncertainties, long-range forecasts use ensembles, and meaningful forecast products reflect distributions of outcomes. Given the complex, non-linear interactions between the individual components of the Earth system, the best tools for long-range forecasting are climate models which include as many of the key components of the system and possible; typically, such models include representations of the atmosphere, ocean and land surface. These models are initialised with data describing the state of the system at the starting point of the forecast and used to predict the evolution of this state in time. While uncertainties coming from imperfect knowledge of the initial conditions of the components of the Earth system can be described with the use of ensembles, uncertainty arising from approximations made in the models are very much dependent on the choice of model. A convenient way to quantify the effect of these approximations is to combine outputs from several models, independently developed, initialised and operated. To this effect, the C3S provides a multi-system seasonal forecast service, where data produced by state-of-the-art seasonal forecast systems developed, implemented and operated at forecast centres in several European countries is collected, processed and combined to enable user-relevant applications. The composition of the C3S seasonal multi-system and the full content of the database underpinning the service are described in the documentation. The seasonal forecast data is grouped in several catalogue entries (CDS datasets), currently defined by the model component and type of variable: outputs from the ocean component or the atmospheric one (single-level or multi-level, on pressure surfaces) and the level of post-processing applied (data at original time resolution, processing on temporal aggregation and post-processing related to bias adjustment). The data includes forecasts created in real-time each month starting from the publication of this entry and retrospective forecasts (hindcasts) initialised over periods in the past specified in the documentation for each origin and system.

This dataset summarizes 2015 Ocean Economy employment statistics for the U.S. coastal states by breaking down each ocean economic indicator per each ocean sector. The dataset also provides percent employment and percent GDP by sector. This percentage is a percent of the ocean sector compared to the total Ocean Economy for each state. This information was harvested from the Economics: National Ocean Watch (ENOW) time-series data on the ocean and Great Lakes economy, derived from the Bureau of Labor Statistics and the Bureau of Economic Analysis. ENOW data measures four economic indicators: Establishments, Employment, Wages, and Gross Domestic Product (GDP) for six economic sectors that are dependent on the oceans and Great Lakes, including: Marine Construction, Living Resources, Offshore Mineral Extraction, Ship and Boat Building, Tourism and Recreation, and Marine Transportation.