Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-677-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-677-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An inventory of Arctic Ocean data in the World Ocean Database
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
Tim P. Boyer
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
Olga K. Baranova
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
James R. Reagan
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
Earth System Science Interdisciplinary Center/Cooperative Institute
for Climate and Satellites – Maryland, University of Maryland, College Park, MD, USA
Dan Seidov
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
Igor V. Smolyar
NOAA National Centers for Environmental Information, Silver Spring, Maryland, USA
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3,194 | 1,202 | 174 | 4,570 | 133 | 123 |
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Total article views: 3,936 (including HTML, PDF, and XML)
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Total article views: 634 (including HTML, PDF, and XML)
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Viewed (geographical distribution)
Total article views: 4,570 (including HTML, PDF, and XML)
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Total article views: 3,936 (including HTML, PDF, and XML)
Thereof 3,484 with geography defined
and 452 with unknown origin.
Total article views: 634 (including HTML, PDF, and XML)
Thereof 621 with geography defined
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11 citations as recorded by crossref.
- Artificial Neural Network Model for Estimating Ocean Heat Content in the Sea Ice-Covered Arctic Regions Using Satellite Data K. Prakash & P. Shanmugam 10.1109/ACCESS.2022.3213942
- Temperature and Salinity Variability in the SODA3, ECCO4r3, and ORAS5 Ocean Reanalyses, 1993–2015 J. Carton et al. 10.1175/JCLI-D-18-0605.1
- Measuring Global Ocean Heat Content to Estimate the Earth Energy Imbalance B. Meyssignac et al. 10.3389/fmars.2019.00432
- Maximum power point tracking method based on impedance matching for a micro hydropower generator J. Wang et al. 10.1016/j.apenergy.2023.121003
- UDASH – Unified Database for Arctic and Subarctic Hydrography A. Behrendt et al. 10.5194/essd-10-1119-2018
- High‐Resolution Mg/Ca and δ18O Patterns in Modern Neogloboquadrina pachyderma From the Fram Strait and Irminger Sea C. Livsey et al. 10.1029/2020PA003969
- Modeling and experiment validation of a seawater micro hydropower system for marine animal telemetry tag J. Wang & Z. Cui 10.1016/j.renene.2021.04.065
- Assessment of Arctic snow stratigraphy and water equivalent using a portable Frequency Modulated Continuous Wave RADAR D. Kramer et al. 10.1016/j.coldregions.2022.103683
- Seasonal Water Mass Transformation in the Eastern Indian Ocean from In Situ Observations N. Purba et al. 10.3390/atmos15010001
- A Bayesian Approach for Inferring Sea Ice Loads M. Parno et al. 10.1115/1.4050281
- The Role of the Russian Shelf in Seasonal and Interannual Variability of Arctic Sea Surface Salinity and Freshwater Content S. Hall et al. 10.1029/2022JC019247
2 citations as recorded by crossref.
Latest update: 14 Dec 2024
Short summary
The World Ocean Database (WOD) contains over 1.3 million oceanographic casts collected in the Arctic Ocean basin and its surrounding marginal seas. WOD
provides a
one-stopsource of Arctic Ocean profile data in a uniform data and metadata format, with quality control applied, which makes it simple for scientists to apply the information to their research.
The World Ocean Database (WOD) contains over 1.3 million oceanographic casts collected in the...
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