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68 results for “oceanography”

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dryad32/100

Data from: Matching genetics with oceanography: directional gene flow in a Mediterranean fish species

Open the record for dataset details and reuse information.

publicSep 2011View details →
dryad32/100

Data from: Matching oceanography and genetics at the basin scale. Seascape connectivity of the Mediterranean shore crab in the Adriatic Sea

Open the record for dataset details and reuse information.

publicOct 2014View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign Rutgers Slocum Gliders

This dataset provides the Conductivity, Temperature, and Depth measurements carried by a Slocum glider. The measurements were collected during the 2019-2020 SWOT prelaunch field campaign conducted near the SWOT crossover location in the California Currents, 300km west of Monterey, California, USA. It has 883 CTD profiles with glider diving depths varying between 500 m and 1000 m. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign WHOI/NOAA Moored Fixed-Depth CTDs

This dataset provides the conductivity, temperature and depth (CTD) measurements from the fixed-depth CTD sensors mounted on a full-depth mooring deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. These fixed-depth CTDs cover the full depth from the ocean surface to the bottom. The surface buoy is equipped with a Global Positioning System (GPS) https://doi.org/10.5067/SWTPR-GPS01. There is also an adjacent bottom pressure recorder https://doi.org/10.5067/SWTPR-BPR01. The campaign also deployed another two CTD moorings, a slocum glider, one bottom pressure recorder and one Pressure Inverted Echo Sounder. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign NOAA Prawlers

This dataset provides the conductivity, temperature and depth (CTD) profiles from a Prawler profiler mooring deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. The campaign also deployed another two CTD moorings, a slocum glider, one bottom pressure recorder and one Pressure Inverted Echo Sounder. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign SIO Pressure-sensing Inverted Echo Sounder (PIES)

This dataset provides the in-situ measurements from a Pressure-sensing Inverted Echo Sounder (PIES) deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. The campaign also deployed three CTD moorings, a slocum glider, and another bottom pressure recorder. The PIES measurements include bottom pressure and the round-trip travel time from the IES, which can be used to derive equivalent steric height through regression. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign JPL Global Positioning Systems (GPS)

This dataset provides the 1Hz time series of the sea surface height measured by a surface buoy equipped with a Global Position System (GPS). The GPS-mooring was deployed by the SWOT prelaunch field campaign conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. The GPS measurements represent the total sea surface height including the Inverted barometer component. The same mooring also carries fixed-depth CTD sensors https://doi.org/10.5067/SWTPR-CTD11. They were used together with atmospheric pressure and bottom pressure measurements to close the sea surface equation (Wang et al., 2022). The campaign also deployed another two CTD moorings, a slocum glider, and a Pressure Inverted Echo Sounder (PIES). Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign NOAA Bottom Pressure Recorders (BPR)

This dataset provides the bottom pressure measurements collected during the 2019-2020 SWOT prelaunch field campaign conducted around the SWOT crossover location in the California Currents, 300km west of Monterey, California, USA. The Paroscientific Digiquartz pressure sensor was used. The data are recorded on a 15-second interval.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign SIO Mooring WireWalker (WW)

This dataset provides the conductivity, temperature and depth (CTD) measurements from the CTD sensors on a WireWalker profiler on a full-depth mooring deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. The WW samples the upper 500 m of the water column, while the deep ocean below 500 m are measured by fixed-depth CTDs https://doi.org/10.5067/SWTPR-CTD01. The campaign also deployed another two CTD moorings, a slocum glider, one bottom pressure recorder and one Pressure Inverted Echo Sounder. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
nasa32/100

SWOT 2019-2020 Prelaunch Oceanography Field Campaign SIO Moored Fixed-Depth CTDs

This dataset provides the conductivity, temperature and depth (CTD) measurements from the fixed-depth CTD sensors mounted on a full-depth mooring deployed by the SWOT prelaunch field campaign. The campaign was designed to test the performance of several instruments/platforms in meeting the SWOT Calibration/Validation (CalVal) requirement. It was conducted near the SWOT CalVal crossover location, about 300 kilometers west of Monterey, California between September, 2019 and January, 2020. These fixed-depth CTDs are below 500 m while the upper part of the mooring has a WireWalker (WW) profiler. The CTD data from WW is available here https://doi.org/10.5067/SWTPR-WW001. The campaign also deployed another two CTD moorings, a slocum glider, one bottom pressure recorder and one Pressure Inverted Echo Sounder. Details can be found in the user guide and the journal reference given in the documentation section.

restrictednotspecifiedApr 2025View details →
zenodo28/100

Real-time oceanography captured by autonomous sailbuoy in Lofoten/Vesterålen 2018

<p>Real-time oceanography from sailbuoy <a href="http://sailbuoy.no/13-news/74-introducing-the-sb-echo">Echo</a>&#39;s long-endurance data acquisition campaign for the&nbsp;<a href="https://prosjektbanken.forskningsradet.no/en/project/FORISS/269188">Glider project</a>.</p> <p>The study area ranged from 66&ndash;71N and 8&ndash;19E, focusing on the coastal shelf area surrounding the Lofoten and Vester&aring;len islands,&nbsp;Norway, from March to August 2018.</p> <p>The dataset contains 4684 oceanography data points, and ~10000 auxiliary data points, spread over a period of 154 days.</p> <p><strong>Oceanography variables</strong></p> <p>GPS</p> <ul> <li><code>Time</code> UTC</li> <li><code>Lat</code> latitude WGS84</li> <li><code>Long</code> longitude WGS84</li> </ul> <p>Conductivity and temperature, from <a href="https://nbosi.com">NBOSI</a> CT sensors</p> <ul> <li><code>CTTemp</code> Sea surface temperature <code>&deg;C</code></li> <li><code>CTCond</code> Sea water conductivity <code>mS/cm</code></li> </ul> <p>From <a href="https://www.aanderaa.com/">Aanderaa</a> Oxygen Optode 4831</p> <ul> <li><code>O2Con</code> Oxygen O₂ concentration <code>&micro;M</code></li> <li><code>O2Air</code> Oxygen O₂ air saturation <code>%</code></li> <li><code>O2Temp</code> Oxygen O₂ water temperature <code>&deg;C</code></li> </ul> <p>The data is published as 2 TSV files from iridium real-time messages that were received, parsed, and exported from <a href="https://iridium2.azurewebsites.net/">Offshore Sensing&#39;s portal</a>.</p> <p>For more information on the <a href="https://www.akvaplan.niva.no/">Akvaplan-niva</a>-led Glider project, including its partners, technology, and results, see Camus et al.:<br> <a href="https://doi.org/10.3390/s21206752">Autonomous Surface and Underwater Vehicles as Effective Ecosystem Monitoring and Research Platforms in the Arctic&mdash;The Glider Project</a>. Sensors 2021, 21, 6752. <a href="https://doi.org/10.3390/s21206752">https://doi.org/10.3390/s21206752</a></p> <p>In 2022, Akvaplan-niva starts&nbsp;publishing the complete set of data from Glider (phase I) on their research archive on&nbsp;<a href="https://zenodo.org/communities/akvaplan-niva">Zenodo</a>.</p>

opencc-by-4.0Jun 2022View details →
zenodo28/100

data for manuscript submmited to Journal of Physical Oceanography

<p>The .xtf files are echosounder images used in the paper.</p> <p>timeseries_dBdz2_hes_Lo.mat and&nbsp;hes_Lo_scatter_plot_data.mat are DNS results.</p> <p>Other .mat data are observed data.</p>

opencc-by-4.0Oct 2021View details →
zenodo28/100

Physical oceanography during RV DONG FANG HONG 3 cruise NORC2022

<p>In August 2022, a bottom lander was deployed for 20 days on the continental slope of the northern SCS to investigate the propagation of NLIWs and their impact on the variability of nepheloid layers. The deployment site of the lander was situated in the Dongsha Slope, which is located within the NLIW shoaling zone and has a water depth of 723 m. The displacement of the bottom lander was assessed using a separated pressure sensor that sampled at a frequency of 1 Hz. This lander was deployed on August 16 and successfully recovered on September 6.</p>

opencc-by-4.0Sep 2023View details →
nasa28/100

SWOT Postlaunch Oceanography Field Campaign Shipboard CTD and Water Sample Data

The SWOT Postlaunch Oceanography Field Campaign Shipboard CTD and Water Sample Data collection provides the conductivity, temperature and depth (CTD) measurements and water sample measurements from shipboard instruments deployed by the Surface Water and Ocean Topography (SWOT) postlaunch field campaign. The SWOT satellite mission launched in late 2022 and underwent a calibration and validation (cal/val) phase in 2023. As part of cal/val, an array of oceanographic instruments was deployed at a site 300 km offshore of California. Shipboard data come from four research cruises on the Bold Horizon and the Sally Ride, with different time spans ranging from February 23, 2023 to November 2, 2024. These measurements were used to adjust the calibrations of mooring CTD sensors (deployed in the same field campaign) to a common and well-calibrated reference, to enable the calculation of steric height for SWOT cal/val analyses. <br><br>Most, but not all of the CTD casts were collected at the actual mooring sites. For some casts, mooring instruments were attached temporarily to the ship CTD system for cross-calibration, and these may have been done anywhere en route to/from the mooring sites. Due to the varying depth ratings of the mooring instruments thus attached, not all CTD casts covered the full water column. The resulting CTD data collection is an irregular pattern of sampling locations and depths, which includes a number of full-depth casts in the vicinity of the moorings.

restrictednotspecifiedJul 2025View details →
zenodo24/100

(Copernicus - WEkEO Hackathon 22 – 23 JUNE 2023 ) Digital Cartography Simulation of Essential ocean variables (EOV) (educational support resource in space oceanography)

<p>Description of idea : The multidimensional view of the Earth and its immediate environment that is provided by space borne sensors, operating at many wavelengths and directed at many different phenomena, has revolutionized man&#39;s understanding of his planet and the surrounding space environment.<strong>(John H. McElroy.,1985),</strong></p> <p>Earth observation satellites measuring in the visible and infrared spectral domain provide a global perspective for many&nbsp; required to determine the role of the ocean in the global climate system, as well as the effects on the ocean of a changing climate <strong>(James A. Yoder and all.,2014).</strong></p> <p>Data visualization by video graphics technology is a digital modeling technique also a description or analogy used to help visualize something that cannot be observed directly which exploits the bases of scientific knowledge in a data processing system by the use of mathematical and statistical tools and analysis and forecasting methods to visualize what is hidden behind the data. This work is inspired by the general principle of numerical modeling and data processing, which takes into consideration (the observation of natural phenomena, and the statistical processing of scientific data, which are at the base of the functioning of natural variation).</p> <p>We see on the same simulation scale several other spatial and temporal scale, for example the simulation of SST of several years with a large gap between the years, also the simulation of the displacement of surface currents with the variations of the SST, in other words the document can be used in pedagogy.</p> <p>&nbsp;</p> <p>Bibliographic reference:<br> -Monitoring Earth&#39;s Ocean, Land, and Atmosphere from Space-Sensors, Systems, and Applications, edited by Abraham Schnapf, American Institute of Aeronautics and Astronautics, 1985<br> -Optical Radiometry for Ocean Climate Measurements, Elsevier Science &amp; Technology, 2014</p> <p>&nbsp;</p> <p>&nbsp;</p>

restrictedcc-by-4.0Jul 2023View details →
zenodo24/100

Visualization of the Multidimensional Volumetric Data-base by Video - Mapping Technology in field of Operational Oceanography (Algerian basin) (zooplankton expressed as carbon in sea water - mass concentration of chllorophyl a in sea water,Wekeo Data ) During 2022 year : (educational support resource in space oceanography)

<p>The multidimensional view of the Earth and its immediate environment that is provided by space borne sensors, operating at many wavelengths and directed at many different phenomena, has revolutionized man&#39;s understanding of his planet and the surrounding space environment.<strong>(John H. McElroy.,1985)</strong>,</p> <p>Earth observation satellites measuring in the visible and infrared spectral domain provide a global perspective for many&nbsp; required to determine the role of the ocean in the global climate system, as well as the effects on the ocean of a changing climate&nbsp;<strong>(James A. Yoder and all.,2014)</strong>.</p> <p>Data visualization by video graphics technology is a digital modeling technique also a description or analogy used to help visualize something that cannot be observed directly which exploits the bases of scientific knowledge in a data processing system by the use of mathematical and statistical tools and analysis and forecasting methods to visualize what is hidden behind the data. This work is inspired by the general principle of numerical modeling and data processing, which takes into consideration (the observation of natural phenomena, and the statistical processing of scientific data, which are at the base of the functioning of natural variation)</p> <p>&nbsp;</p> <p><strong>Bibliographic reference:</strong><br> <strong>-Monitoring Earth&#39;s Ocean, Land, and Atmosphere from Space-Sensors, Systems, and Applications, edited by Abraham Schnapf, American Institute of Aeronautics and Astronautics, 1985<br> -Optical Radiometry for Ocean Climate Measurements, Elsevier Science &amp; Technology, 2014</strong></p> <p>&nbsp;</p>

restrictedcc-by-4.0Jul 2023View details →
nasa24/100

Ecology and Oceanography of Harmful Algal Blooms (ECOHAB)

ECOHAB is a peer-reviewed, national, competitive program that funds regional-scale and targeted studies. Regional ecosystem investigations of the causes and impacts of HABs leading to development of model-based operational ecological forecasting capabilities in areas with severe, recurrent blooms are a high priority.

restrictednotspecifiedApr 2025View details →
nasa20/100

Physical Oceanography Distributed Active Archive Center (PO.DAAC)

PO.DAAC is an element of the Earth Observing System Data Information System (EOSDIS). PO.DAAC's primary responsibility is to provide distribution and archive support for NASA's physical oceanography missions such as TOPEX/Poseidon and SeaWinds on QuikSCAT. However, PO.DAAC additionally collaborates with other institutes to acquire complementary data products and value-added services.

restrictednotspecifiedMar 2025View details →
zenodo12/100

Physical oceanography, biotic and abiotic carbon data in the deep sea on the northern slope of the South China Sea in June 2015

<p>The datasets are used for the study of the effects of mesoscale eddies on biological carbon&nbsp;pumps&nbsp;in deep sea water&nbsp;in&nbsp;the&nbsp;northern South China Sea. Thus the physical oceanography, biotic and abiotic carbon data are included in the datasets.</p>

restrictedAug 2022View details →
nasa12/100

JPL Physical Oceanography Distributed Active Archive Center (PODAAC) Dataset Metadata API

PO.DAAC provides several ways to discover and access physical oceanography data, from the PO.DAAC Web Portal to FTP access to front-end user interfaces (see http://podaac.jpl.nasa.gov). That same data can also be discovered and accessed through PO.DAAC Web Services, enabling efficient machine-to-machine communication and data transfers.

restrictednotspecifiedMar 2025View details →

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Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record