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  • 1
    Publication Date: 2023-02-24
    Keywords: Acoustic Doppler Current Profiler; ADCP; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; Seward Johnson; Shipboard Acoustic Doppler Current Profiling (SADCP); Ship velocity, absolute east-west, standard deviation; Ship velocity, absolute east-west components means; Ship velocity, absolute north-south components mean; Ship velocity, absolute north-south standard deviation; SJ9506; SJ9506_00184; Temperature, technical; Temperature, technical, standard deviation; WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/tab-separated-values, 2135 data points
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2023-02-24
    Keywords: Acoustic Doppler Current Profiler; ADCP; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; Seward Johnson; Shipboard Acoustic Doppler Current Profiling (SADCP); Ship velocity, absolute east-west, standard deviation; Ship velocity, absolute east-west components means; Ship velocity, absolute north-south components mean; Ship velocity, absolute north-south standard deviation; SJ9508; SJ9508_00185; Temperature, technical; Temperature, technical, standard deviation; WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/tab-separated-values, 3167 data points
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  • 3
    Publication Date: 2023-02-24
    Keywords: 32OC340; 32OC340_00485; Acoustic Doppler Current Profiler; ADCP; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; Oceanus; Shipboard Acoustic Doppler Current Profiling (SADCP); Ship velocity, absolute east-west, standard deviation; Ship velocity, absolute east-west components means; Ship velocity, absolute north-south components mean; Ship velocity, absolute north-south standard deviation; Temperature, technical; Temperature, technical, standard deviation; WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/tab-separated-values, 10298 data points
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  • 4
    Publication Date: 2023-02-24
    Keywords: 32OC343; 32OC343_00486; Acoustic Doppler Current Profiler; ADCP; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; LATITUDE; LONGITUDE; Oceanus; Shipboard Acoustic Doppler Current Profiling (SADCP); Ship velocity, absolute east-west, standard deviation; Ship velocity, absolute east-west components means; Ship velocity, absolute north-south components mean; Ship velocity, absolute north-south standard deviation; Temperature, technical; Temperature, technical, standard deviation; WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/tab-separated-values, 6006 data points
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  • 5
    Publication Date: 2023-02-24
    Keywords: Acoustic Doppler Current Profiler; ADCP; Current velocity, east-west; Current velocity, north-south; DATE/TIME; DEPTH, water; EN304; EN304_00206; Endeavor; LATITUDE; LONGITUDE; Shipboard Acoustic Doppler Current Profiling (SADCP); Ship velocity, absolute east-west, standard deviation; Ship velocity, absolute east-west components means; Ship velocity, absolute north-south components mean; Ship velocity, absolute north-south standard deviation; Temperature, technical; Temperature, technical, standard deviation; WOCE; World Ocean Circulation Experiment
    Type: Dataset
    Format: text/tab-separated-values, 3120 data points
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  • 6
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 123 (2018): 4988-5003, doi:10.1029/2017JC013338.
    Description: The focus of this study is on the relative roles of winds and buoyancy in driving the Nova Scotia Current (NSC) utilizing detailed hydrographic glider transects along the Halifax Line. We define a Hydrographic Wind Index (HWI) using a simplistic two‐layer model to represent the NSC and its frontal system. The HWI is based on local characteristics of the density front extracted from the glider data (e.g., frontal slope). The impact of wind‐driven isopycnal tilting on the frontal slope is estimated and corrected for to accurately scale the buoyancy‐driven component of the NSC. Observations from independent current profilers deployed across the NSC confirm that the HWI captures the low‐frequency variability of the NSC. The monthly wind‐driven flow is estimated to represent between 1.0% (±0.1%) and 48% (±1%) of the total alongshore currents, with a yearly mean of about 36% (±1%). We demonstrate that using local conditions is more appropriate to the study of buoyancy‐driven currents ranging over distances on the order of urn:x-wiley:jgrc:media:jgrc22972:jgrc22972-math-0001(100 km), compared to the traditional approach based on upstream conditions. Contrary to the traditional approach, the HWI is not affected by the advective time lag associated with the downshelf propagation of the buoyant water coming from the upstream source. However, the HWI approach requires high‐resolution data sets, as errors on the estimates of the buoyancy‐ and wind‐driven flows become large as the sampling resolution decreases. Despite being data intensive, we argue that the HWI is also applicable to multisource currents, where upstream conditions are difficult to define.
    Description: Ocean Tracking Network (OTN) Grant Number: 375118-08; Natural Sciences and Engineering Research Council of Canada (NSERC); Canadian Foundation for Innovation Grant Number: 13011; Social Sciences and Humanities Research Council Grant Number: 871-2009-0001; University in Bergen through the POME exchange program
    Description: 2019-01-28
    Keywords: Coastal current ; Underwater glider ; Buoyancy ; Winds ; Upwelling ; Ocean tracking network
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 7
    Publication Date: 2020-05-15
    Description: There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017–2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 8
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Smith, G. C., Allard, R., Babin, M., Bertino, L., Chevallier, M., Corlett, G., Crout, J., Davidson, F., Delille, B., Gille, S. T., Hebert, D., Hyder, P., Intrieri, J., Lagunas, J., Larnicol, G., Kaminski, T., Kater, B., Kauker, F., Marec, C., Mazloff, M., Metzger, E. J., Mordy, C., O'Carroll, A., Olsen, S. M., Phelps, M., Posey, P., Prandi, P., Rehm, E., Reid, P., Rigor, I., Sandven, S., Shupe, M., Swart, S., Smedstad, O. M., Solomon, A., Storto, A., Thibaut, P., Toole, J., Wood, K., Xie, J., Yang, Q., & WWRP PPP Steering Grp. Polar ocean observations: A critical gap in the observing system and its effect on environmental predictions from hours to a season. Frontiers in Marine Science, 6, (2019): 429, doi:10.3389/fmars.2019.00429.
    Description: There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017–2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.
    Description: The development of the new generation of floats (PRO-ICE) to be operated under ice was funded by the French project NAOS. Twelve PRO-ICE were funded by NAOS and nine by the Canadian Foundation for Innovation (FCI-30124). The GreenEdge project is funded by the following French and Canadian programs and agencies: ANR (Contract #111112), CNES (project #131425), IPEV (project #1164), CSA, Fondation Total, ArcticNet, LEFE and the French Arctic Initiative (GreenEdge project). The INTAROS project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 727890. The setup of the ArcMBA system and the experiment described in section “Quantitative Network Design” were funded by the European Space Agency through its support to science element (contract #4000117710/16/I-NB). SSw was supported by a Wallenberg Academy Fellowship (WAF 2015.0186). The work at CLS (GL, PPr, and PT) has been funded by internal investment, in relation with on-going CNES and ESA funded studies making use of radar data over Polar regions. EMODNET (BK) is funded by the European Commission. NRL Funding (for RA, JC, DH, EM, PPo, OS) provided by NRL Research Option “Determining the Impact of Sea Ice Thickness on the Arctic’s Naturally Changing Environment (DISTANCE), ONR 6.2 Data Assimilation and under program element 0602435N (JC, RA, DH). JT’s Arctic research activities are supported by the U.S. National Science Foundation and ONR. SG was funded by NSF grants/awards PLR-1425989 and OCE 1658001. IR is funded by contributors to the US IABP (including CG, DOE, NASA, NIC, NOAA, NSF, ONR). CAFS is supported by the NOAA ESRL Physical Sciences Division (AS and JI). LB and JX are funded by CMEMS. The WWRP PPP Steering Group is funded by a WMO trust fund with support from AWI for the ICO. The publication fee is provided by ECCC.
    Keywords: Polar observations ; Operational oceanography ; Ocean data assimilation ; Ocean modeling ; Forecasting ; Sea ice ; Air-sea-ice fluxes ; YOPP
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 9
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Testor, P., de Young, B., Rudnick, D. L., Glenn, S., Hayes, D., Lee, C. M., Pattiaratchi, C., Hill, K., Heslop, E., Turpin, V., Alenius, P., Barrera, C., Barth, J. A., Beaird, N., Becu, G., Bosse, A., Bourrin, F., Brearley, J. A., Chao, Y., Chen, S., Chiggiato, J., Coppola, L., Crout, R., Cummings, J., Curry, B., Curry, R., Davis, R., Desai, K., DiMarco, S., Edwards, C., Fielding, S., Fer, I., Frajka-Williams, E., Gildor, H., Goni, G., Gutierrez, D., Haugan, P., Hebert, D., Heiderich, J., Henson, S., Heywood, K., Hogan, P., Houpert, L., Huh, S., Inall, M. E., Ishii, M., Ito, S., Itoh, S., Jan, S., Kaiser, J., Karstensen, J., Kirkpatrick, B., Klymak, J., Kohut, J., Krahmann, G., Krug, M., McClatchie, S., Marin, F., Mauri, E., Mehra, A., Meredith, M. P., Meunier, T., Miles, T., Morell, J. M., Mortier, L., Nicholson, S., O'Callaghan, J., O'Conchubhair, D., Oke, P., Pallas-Sanz, E., Palmer, M., Park, J., Perivoliotis, L., Poulain, P., Perry, R., Queste, B., Rainville, L., Rehm, E., Roughan, M., Rome, N., Ross, T., Ruiz, S., Saba, G., Schaeffer, A., Schonau, M., Schroeder, K., Shimizu, Y., Sloyan, B. M., Smeed, D., Snowden, D., Song, Y., Swart, S., Tenreiro, M., Thompson, A., Tintore, J., Todd, R. E., Toro, C., Venables, H., Wagawa, T., Waterman, S., Watlington, R. A., & Wilson, D. OceanGliders: A component of the integrated GOOS. Frontiers in Marine Science, 6, (2019): 422, doi:10.3389/fmars.2019.00422.
    Description: The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.
    Description: The editorial team would like to recognize the support of the global glider community to this paper. Our requests for data and information were met with enthusiasm and welcome contributions from around the globe, clearly demonstrating to us a point made in this paper that there are many active and dedicated teams of glider operators and users. We should also acknowledge the support that OceanGliders has received from the WMO/IOC JCOMM-OCG and JCOMMOPS that have allowed this program to develop, encouraging us to articulate a vision for the role of gliders in the GOOS. We acknowledge support from the EU Horizon 2020 AtlantOS project funded under grant agreement No. 633211 and gratefully acknowledge the many agencies and programs that have supported underwater gliders: AlterEco, ANR, CFI, CIGOM, CLASS Ellet Array, CNES, CNRS/INSU, CONACyT, CSIRO, DEFRA, DFG/SFB-754, DFO, DGA, DSTL, ERC, FCO, FP7, and H2020 Europen Commission, HIMIOFoTS, Ifremer, IMOS, IMS, IOOS, IPEV, IRD, Israel MOST, JSPS, MEOPAR, NASA, NAVOCEANO (Navy), NERC, NFR, NJDEP, NOAA, NRC, NRL, NSF, NSERC, ONR, OSNAP, Taiwan MOST, SANAP-NRF, SENER, SIMS, Shell Exploration and Production Company, Sorbonne Université, SSB, UKRI, UNSW, Vettleson, Wallenberg Academy Fellowship, and WWF.
    Keywords: In situ ocean observing systems ; Gliders ; Boundary currents ; Storms ; Water transformation ; Ocean data management ; Autonomous oceanic platforms ; GOOS
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
    Publication Date: 2022-01-31
    Description: The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.
    Type: Article , PeerReviewed
    Format: text
    Format: text
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