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.

The basic version of this North Atlantic dataset was created by Andrew Bunker of Woods Hole Oceanographic Institution. He analyzed observations from the ship reports of the Voluntary Observing Fleet ... into irregularly-spaced areas over the ocean. The atlas presented here contains a revision of the early data interpolated to a regularly-spaced 1-degree grid over the Atlantic.

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.

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.

Satellite-derived Ocean Color Data sets from historical and currently operational NASA and International Satellite missions including the NASA Coastal Zone Color Scanner (CZCS) (1978 - 1986), NASDA's Ocean Color Temperature Scanner (OCTS) (1996 - 1997), NASA/GeoEYE Sea-viewing Wide Field-of-view Sensor (SeaWiFS) (1997 - 2010), NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua spacecraft (2000 - present) and ESA's medium-spectral resolution, imaging spectrometer (MERIS) (2002 - present). Level-1A Data Products Level-1A products contain the raw radiance counts from all bands as well as spacecraft and instrument telemetry. Calibration and navigation data, and instrument and selected spacecraft telemetry are also included. Level-1A data are used as input for geolocation, calibration, and processing. Ocean Level-2 Data Products Each Level-2 product is generated from a corresponding Level-1A product.The main data contents of the product are the geophysical values for each pixel,derived from the Level-1A raw radiance counts by applying the sensor calibration, atmospheric corrections, and bio-optical algorithms. Each Level-2 product corresponds exactly in geographical coverage (scan-line and pixel extent) to that of its parent Level-1A product and is stored in one physical HDFfile. Ocean Level-3 Binned Data Products Level-3 binned data products consist of the accumulated data for all Level-2 data corresponding to a period of one day, 8 days, a calendar month, or a calendar year. Each Level-3 binned data product is stored in one or more HDF files. Each multi-file product includes a main file containing all product-level metadata and data for each bin that are common to all the binned geophysical parameters, and multiple subordinate files, each of which contains data of one binned geophysical parameter for all bins. Subordinate files must be read in conjunction with the associated main file. Ocean Level-3 Standard Mapped Image Products The Level-3 standard mapped image (SMI) products are image representations of binned data products generated from SeaWiFS, MODIS, OCTS or CZCS data. The data in each SMI product represents an image of the parameter specified by the global attribute Parameter. This object is a two-dimensional array of an Equidistant Cylindrical (also known as Platte Carre) projection of the globe. The values can be stored as bytes, 2-byte integers, or 4- byte floats. The first two are scaled real values and may be converted projected to geophysical values using the global attributes Scaling, Scaling Equation, Base, Slope, and Intercept. The standard SMI products are generated from binned data products, one for each of the following geophysical parameters: chlorophyll a concentration, angstrom coefficient, normalized water-leaving radiance at each visible wavelength, aerosol optical thickness, epsilon, and diffuse attenuation coefficient at 490 nm. For MODIS, products are generated for sea surface temperature (SST), 4 micron SST (SST4) and nighttime SST (NSST). Thus, each SMI product represents data binned over the period covered by the parent product. The arithmetic mean is used in each case to obtain the values for the SMI grid points from the binned data products. Each SMI product contains one image of a geophysical parameter and is stored in one physical HDF file.

The World Ocean Database (WOD) is the largest uniformly formatted, quality-controlled, publicly available historical subsurface ocean profile database. From Captain Cook's second voyage in 1772 to today's automated Argo floats, global aggregation of ocean variable information including temperature, salinity, oxygen, nutrients, and others vs. depth allow for study and understanding of the changing physical, chemical, and to some extent biological state of the World's Oceans. Browse the bucket via the AWS S3 explorer: https://noaa-wod-pds.s3.amazonaws.com/index.html

World Ocean Database 2009 (WOD09) is a collection of scientifically quality-controlled ocean profile and plankton data that includes measurements of temperature, salinity, oxygen, phosphate, nitrate, silicate, chlorophyll, alkalinity, pH, pCO2, TCO2, Tritium, delta-13Carbon, delta-14Carbon, delta-18Oxygen, Freons, Helium, delta-3Helium, Neon, and plankton. A discussion of data sources is provided. Data are both historical and modern with the most recent data from 2008.

World Ocean Database 2009 is an update of World Ocean Database 2005. It expands on the older version by including new variables, data types, and additional historical, as well as modern, observations. It contains all data from earliest observation through our collection as of Dec. 31, 2009. The 2009 database, updated from the 2005 edition, is significantly larger providing approximately 9.1 million temperature profiles and 3.5 million salinity reports. The 2009 database also captures 29 categories of scientific information from the oceans, including oxygen levels and chemical tracers, plus information on gases and isotopes that can be used to trace the movement of ocean currents. An online version of the World Ocean Database is updated quarterly.

DVD-ROM Disc 1 contains:

OSD, Ocean Station Data
Low & High-resolution CTD/XCTD, Conductivity-Temperature-Depth data
Plankton data

DVD-ROM Disc 2 contains:

MBT, Mechanical / Digital / Micro Bathythermograph data
XBT, Expendable Bathythermograph data
SUR, Surface-only data
APB, Autonomous Pinniped data
MRB, Moored buoy data
PFL, Profiling float data
DRB, Drifting buoy data
UOR, Undulating Oceanographic Recorder data
GLD, Glider data

This DVD contains six directories named:

CODES (contains codes associated with the secondary header, biological header, and taxa data);
DATA (contains yearly sorted data, dating from 1773 though 2009);
DOC (contains the documentation);
ODV (contains the Ocean Data View software for viewing the WOD09 data, developed by Dr. Reiner Schiltzer, AWI. This software will decompress selected files and offers users several options for viewing the WOD09 data. ODV works on PCs only);
PROGRAMS (contains source code and executables for programs which are examples of how to read the data and can be used to reformat the data into comma-delimited or space-delimited forms);
UTILS (contains the gzip utility for uncompressing WOD09 data files).

The World Ocean Database DVDs are currently available via the NCEI Online Store at https://www.ncdc.noaa.gov/nespls/olstore.prodspecific?prodnum=5035

This dataset contains daily-averaged ocean potential temperature and salinity interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.

Atlantic Ocean core data, about 400K years, SPECMAP. This archive gives Paleoclimate data for a selection of Atlantic cores. It has oxygen-18 data for about 16 cores covering about 400,000 ... years. Age models for the cores are given. Derived sea surface temperature estimates for 15 cores are given. Delta 13-C data is available for selected cores. Planktic foraminifera counts and factor loadings are given for the cores. Another file includes solar orbital data. This is SPECMAP archive No. 1, 28 Mar 1989.

This collection contains an operational Satellite Ocean Heat Content Suite (SOHCS) product generated by NOAA National Environmental Satellite, Data, and Information Service (NESDIS). The operational algorithm implemented was developed at the University of Miami/Rosenstiel School of Marine and Atmospheric Science (RSMAS). The SOHCS product measures the integrated vertical temperature from the sea surface to the depth of the 26°C isotherm. The Algorithm uses a reduced gravity model to estimate the 20 degree isotherm depth based on objectively analyzed blended sea surface height anomaly fields from operational altimeters (Satellite with ARgos and ALtiKa (SARAL), Jason-1, Jason-2 and Cryosat-2) and Geo-Polar blended SST analyses. The data consists of seven parameters including sea surface height anomaly and its mapping error, depth of the 20° and 26° Celsius isotherm, mixed layer depth, ocean heat content and sea surface temperature. The grid spacing of the data in both latitude and longitude is 0.25°.

The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data products produced as part of NASA's MEaSUREs Program. Remote Sensing Systems generates SSM/I and SSMIS binary data products using a unified, physically based algorithm to simultaneously retrieve ocean wind speed, water vapor, cloud water, and rain rate. The SSMIS data have been carefully intercalibrated to the brightness temperature level of the previous SSM/I and therefore extend this important time series of ocean winds, vapor, cloud and rain values. This algorithm is a product of 20 years of refinements, improvements, and verifications. The Global Hydrology Resource Center has reformatted the binary data into a netCDF data product for each temporal group for each satellite. The netCDF SSMI/SSMIS collection will be available for F14 for a weekly average.

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 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.

This dataset is a collection of marine environmental data layers suitable for use in Southern Ocean species distribution modelling. All environmental layers have been generated at a spatial resolution of 0.1 degrees, covering the Southern Ocean extent (80 degrees S - 45 degrees S, -180 - 180 degrees). The layers include information relating to bathymetry, sea ice, ocean currents, primary production, particulate organic carbon, and other oceanographic data.

An example of reading and using these data layers in R can be found at https://australianantarcticdivision.github.io/blueant/articles/SO_SDM_data.html.

The following layers are provided:

1. Layer name: depth Description: Bathymetry. Downloaded from GEBCO 2014 (0.0083 degrees = 30sec arcmin resolution) and set at resolution 0.1 degrees. Then completed with the bathymetry layer manually corrected and provided in Fabri-Ruiz et al. (2017) Value range: -8038.722 - 0 Units: m

Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Fabri-Ruiz S, Saucede T, Danis B and David B (2017). Southern Ocean Echinoids database_An updated version of Antarctic, Sub-Antarctic and cold temperate echinoid database. ZooKeys, (697), 1.

1. Layer name: geomorphology Description: Last update on biodiversity.aq portal. Derived from O'Brien et al. (2009) seafloor geomorphic feature dataset. Mapping based on GEBCO contours, ETOPO2, seismic lines). 27 categories Value range: 27 categories Units: categorical Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10

2. Layer name: sediments Description: Sediment features Value range: 14 categories Units: categorical Source: Griffiths 2014 (unpublished) URL: http://share.biodiversity.aq/GIS/antarctic/

3. Layer name: slope Description: Seafloor slope derived from bathymetry with the terrain function of raster R package. Computation according to Horn (1981), ie option neighbor=8. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Unit set at degrees. Value range: 0.000252378 - 16.94809 Units: degrees Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Horn, B.K.P., 1981. Hill shading and the reflectance map. Proceedings of the IEEE 69:14-47

4. Layer name: roughness Description: Seafloor roughness derived from bathymetry with the terrain function of raster R package. Roughness is the difference between the maximum and the minimum value of a cell and its 8 surrounding cells. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Value range: 0 - 5171.278 Units: unitless Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/

5. Layer name: mixed layer depth Description: Summer mixed layer depth climatology from ARGOS data. Regridded from 2-degree grid using nearest neighbour interpolation Value range: 13.79615 - 461.5424 Units: m Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

6. Layer name: seasurface_current_speed Description: Current speed near the surface (2.5m depth), derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS model) Value range: 1.50E-04 - 1.7 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data

7. Layer name: seafloor_current_speed Description: Current speed near the sea floor, derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS) Value range: 3.40E-04 - 0.53 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data

8. Layer name: distance_antarctica Description: Distance to the nearest part of the Antarctic continent Value range: 0 - 3445 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

9. Layer name: distance_canyon Description: Distance to the axis of the nearest canyon Value range: 0 - 3117 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

10. Layer name: distance_max_ice_edge Description: Distance to the mean maximum winter sea ice extent (derived from daily estimates of sea ice concentration) Value range: -2614.008 - 2314.433 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

11. Layer name: distance_shelf Description: Distance to nearest area of seafloor of depth 500m or shallower Value range: -1296 - 1750 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

12. Layer name: ice_cover_max Description: Ice concentration fraction, maximum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

13. Layer name: ice_cover_mean Description: Ice concentration fraction, mean on [1957-2017] time period Value range: 0 - 0.9708595 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

14. Layer name: ice_cover_min Description: Ice concentration fraction, minimum on [1957-2017] time period Value range: 0 - 0.8536261 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

15. Layer name: ice_cover_range Description: Ice concentration fraction, difference maximum-minimum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

16. Layer name: ice_thickness_max Description: Ice thickness, maximum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

17. Layer name: ice_thickness_mean Description: Ice thickness, mean on [1957-2017] time period Value range: 0 - 1.614133 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

18. Layer name: ice_thickness_min Description: Ice thickness, minimum on [1957-2017] time period Value range: 0 - 0.7602701 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

19. Layer name: ice_thickness_range Description: Ice thickness, difference maximum-minimum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

20. Layer name:

This collection contains the Global Ocean Currents Database (GOCD). The GOCD is an NCEI Standard Product, and is derived from datasets archived at NCEI that contain 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 meet quality control requirements and have thorough documentation. The GOCD merges the variety of original formats into an 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 includes data collected from 1962-09-30 to 2013-12-23.

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.

The SDC_GLO_CLIM_TS_V1 product contains two different monthly climatologies for temperature and salinity, SDC_GLO_CLIM_TS_V1_1 and SDC_GLO_CLIM_TS_V1_2 from the World Ocean Data (WOD) database. Only the basic quality control flags from the WOD are used. The climatology, V1_1, considers temperature and salinity profiles from Conductivity Depth Temperature (CTD) profilers, Ocean station data (OSD) and Moored buoy data (MRB) along with Profiling Floats (PFL) from 1900 to 2017. The climatology, V1_2, utilizes only PFL data from 2003 to 2017. V1_1 considers depth layers from surface to 6000 m while V1_2 only from 0 to 2000 m. The gridded fields are computed using DIVAnd (Data Interpolating Variational Analysis) version 2.3.1.

This level 3 product includes ocean color and satellite ocean biology data produced or collected under EOSDIS. This dataset may be used for studying the biology and hydrology of coastal zones, changes in the diversity and geographical distribution of coastal marine habitats, biogeochemical fluxes and their influence in Earth's oceans …

Derived from pilot charts from the US Naval Oceanographic Office. Based on data from 1901-1978.

Long Island Sound observation data from Project Oceanology. These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats. cdm_data_type=Point Conventions=COARDS, CF-1.6, Unidata Dataset Discovery v1.0 featureType=Point geospatial_lat_units=degrees_north geospatial_lon_units=degrees_east id=Project Oceanology Navigation info_url=http://lisicos.uconn.edu/ infoUrl=http://lisicos.uconn.edu/ institution=University of Connecticut keywords_vocabulary=GCMD Science Keywords naming_authority=edu.connecticut sourceUrl=(source database) standard_name_vocabulary=CF-1.6 station=Project Oceanology Data station_site_desc=Project_Oceanology Navigation Data testOutOfDate=now-1day