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774 Research products, page 1 of 78

  • Publications
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  • 2018-2022
  • SEANOE

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  • Open Access
    Authors: 
    Oelsmann, Julius; Passaro, Marcello; Sanchez, Laura; Dettmering, Denise; Schwatke, Christian; Seitz, Florian;
    Publisher: SEANOE

    This dataset contains estimates of piecewise trends and discontinuities in vertical land motion (VLM) time series. The time series are based on two techniques, the Global Navigation Satellite System (GNSS) and differences of satellite altimetry and tide gauge measurements (SATTG). SATTG data are based on monthly PSMSL tide gauge observations (Permanent Service for Mean Sea Level, Holgate et al. [2013]) and multi-mission satellite altimetry from DGFI-TUM. The coastal along-track altimetry SLA data feature latest corrections and adjustments, as well as coastal retracking (using the ALES retracker (Passaro et al., 2014)). The GNSS time series are obtained from the Nevada Geodetic Laboratory (NGL) of the University of Nevada (Blewitt et al. [2016], http://geodesy.unr.edu). This dataset contains information of piecewise trends, uncertainties, as well as discontinuity epochs and sizes in 606 SATTG and 381 GNSS time series. These parameters are estimated with a Bayesian change point detection method (DiscoTimeS), as described in ‘Bayesian modelling of piecewise trends and discontinuities to improve the estimation of coastal vertical land motion’.

  • Open Access
    Authors: 
    Waterisotopes-CISE-LOCEAN;
    Publisher: SEANOE
    Project: EC | TRIATLAS (817578)

    LOCEAN has been in charge of collecting sea water for the analysis of water isotopes on a series of cruises or ships of opportunity mostly in the equatorial Atlantic, in the North Atlantic, in the southern Indian Ocean, in the southern Seas, Nordic Seas, and in the Arctic. The LOCEAN data set of the oxygen and hydrogen isotope (δ18O and δD) of marine water covers the period 1998 to 2019, but the effort is ongoing. Most data prior to 2010 (only δ18O) were analyzed using isotope ratio mass spectrometry (Isoprime IRMS) coupled with a Multiprep system (dual inlet method), whereas most data since 2010 (and a few earlier data) were obtained by cavity ring down spectrometry (CRDS) on a Picarro CRDS L2130-I, or less commonly on a Picarro CRDS L2120-I. Occasionally, some data were also run by Marion Benetti on an Isoprime IRMS coupled to a GasBench (dual inlet method) at the university of Iceland (Reykjavik). On the LOCEAN Picarro CRDS, most samples were initially analyzed after distillation, but since 2016, they have often been analyzed using a wire mesh to limit the spreading of sea salt in the vaporizer. Some of the samples on the CRDS were analyzed more than once on different days, when repeatability for the same sample was not sufficient or the daily run presented a too large drift. Accuracy is best when samples are distilled, and for δD are better on the Picarro CRDS L2130-I than on the Picarro CRDS L2120-I. Usually, we found that the reproducibility of the δ18O measurements is within ± 0.05 ‰ and of the δD measurements within ± 0.30 ‰, which should be considered an upper estimate of the error on the measurement on a Picarro CRDS. The water samples were kept in darkened glass bottles (20 to 50 ml) with special caps, and were often (but not always) taped afterwards. Once brought back in Paris, the samples were often stored in a cold room (with temperature close to 4°C), in particular if they were not analyzed within the next three months. There is however the possibility that some samples have breathed during storage. We found it happening on a number of samples, more commonly when they were stored for more than 5 years before being analyzed. We also used during one cruise bottles with not well-sealed caps (M/V Nuka Arctica in April 2019), which were analyzed within 3 months, but for which close to one third of the samples had breathed. We have retained those analyses, but added a flag ‘3’ meaning probably bad, at least on d-excess (outside of regions where sea ice forms or melts, for the analyses done on the Picarro CRDS, excessive evaporation is usually found with a d-excess criterium (which tends to be too low); for the IRMS analyses, it is mostly based when excessive scatter is found in the S- δ18O scatter plots or between successive data, in which case some outliers were flagged at ‘3’). In some cases when breathing happened, we found that d-excess can be used to produce a corrected estimate of δ18O and δD (Benetti et al., 2016). When this method was used a flag ‘1’ is added, indicating ‘probably good’ data, and should be thought as not as accurate as the data with no ‘correction’, which are flagged ‘2’ or ‘0’. We have adjusted data to be on an absolute scale based on the study of Benetti et al. (2017), and on further tests with the different wire meshes used more recently. We have also checked the consistency of the runs in time, as there could have been changes in the internal standards used. On the Isoprime IRMS, it was mostly done using different batches of ‘Eau de Paris’ (EDP), whereas on the Picarro CRDS, we used three internal standards kept in metal tanks with a slight overpressure of dry air). The internal standards have been calibrated using VSMOW and GISP, and were also sent to other laboratories to evaluate whether they had drifted since the date of creation (as individual sub-standards have typically stored for more than 5-years). These comparisons are still not fully statisfactory to evaluate possible drifts in the sub-standards. Individual files correspond to regional subsets of the whole dataset. The file names are based on two letters for the region (see below) followed by –Wisotopes and a version number (-V0, …): example SO-Wisotopes-V0; the highest version number corresponds to the latest update of the regional data set. The region two letters are the followings: - SO: Southern Ocean including cruise station and surface data mostly from 2017 in the Weddell Sea (WAPITI Cruise JR160004, DOI:10.17882/54012), as well as in the southern Ocean - SI: OISO cruise station and surface data in the southern Indian Ocean (since 1998) (DOI:10.18142/228) - EA: Equatorial Atlantic cruise station and surface data (2005 to 2020), in particular from French PIRATA (DOI:10.18142/14) and EGEE cruises (DOI:10.18142/95) - NA: North Atlantic station and surface data from Oceanographic cruises as well as from ships of opportunity (this includes in particular OVIDE cruise data since 2002 (DOI:10.17882/46448), CATARINA, BOCATS1 and BOCATS2 (PID2019-104279GB-C21/AEI/10.13039/501100011033) cruises funded by the Spanish Research Agency, RREX2017 2017 cruise data (DOI:10.17600/17001400), SURATLANT data set since 2011 (DOI:10.17882/54517), Nuka Arctica data since 2012, STRASSE (DOI:10.17600/12040060) and MIDAS cruise data in 2012-2013, as well as surface data from various ships of opportunity in 2012-2020) - NS: Nordic Sea data from cruises in 2002-2018 - AS: Arctic data from two Tara cruises (in 2006-2008 and 2013) - PM: miscellaneous data in tropical Pacific and Mediterranean Sea The files are in csv format reported, and starting with version V1, it is reported as: - Cruise name, station id, bottle number, day, month, year, hour, minute, latitude, longitude, pressure (db), temperature (°C), it, salinity (pss-78), is, dissolved oxygen (micromol/kg), io2, δ18O, iO, d D, iD, d-excess, id, method type - Temperature is an in situ temperature - Salinity is a practical salinity it, is, io2, iO, iD, id are quality indices equal to: - 0 no quality check (but presumably good data) - 1 probably good data - 2 good data - 3 probably bad data - 4 certainly bad data - 9 missing data (and the missing data are reported with an unlikely missing value) The method type is 1 for IRMS measurements, 2 for CRDS measurement of a saline water sample, 3 for CRDS measurement of a distilled water sample.

  • Open Access
    Authors: 
    DCE-Benthos Network, French Mediterranen Lagoon Monitoring Network;
    Publisher: SEANOE

    French benthic invertebrates composition and abundance taxa data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts and Mediterranean coast (Quadrige program code : REBENT_FAU, RSL_FAU). Protocols are implemented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 498 ODV files have been generated from period 01/01/2003 to 31/12/2021.

  • Open Access
    Authors: 
    Oulhen, Erwan; Reinaud, Jean; Carton, Xavier;
    Publisher: SEANOE

    The merger of two surface quasi-geostrophic vortices is examined in detail. As the two vortices collapse towards each other in the merging process, they trap their external fronts between them; these fronts are inserted into the final merged vortex, where they form a central, nearly parallel, sheared velocity strip, sen- sitive to barotropic instability. As a result, this strip breaks up into an alley of small vortices. Subsequently, these small vortices may undergo merger and grow in size in the core of the large merged vortex. The number of small trapped vortices decreases correspondingly. Finally, a single or two small vortices remain. These processes are analysed using a numerical model of the surface quasi-geostrophic equations. The sensitivity of this process to the initial vortex characteristics is explored. A parallel is drawn between this problem and the instability of a rectilinear strip of temperature with a central gap. The application of this problem to the Ocean is discussed.

  • Open Access
    Authors: 
    Copernicus Marine in situ TAC;
    Publisher: SEANOE

    The latest version of Copernicus surface and sub-surface water velocity product is distributed from Copernicus Marine catalogue: - https://resources.marine.copernicus.eu/product-detail/INSITU_GLO_UV_L2_REP_OBSERVATIONS_013_044/INFORMATION This delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface currents and current vertical profiles. It concerns three delayed time datasets dedicated to near-surface currents measurements coming from three platforms (Lagrangian surface drifters, High Frequency radars and Argo floats) and velocity profiles within the water column coming from the Acoustic Doppler Current Profiler (ADCP, vessel mounted only) .

  • Open Access
    Authors: 
    Cazenave, Anny; Gouzenes, Yvan; Birol, Florence; Legér, Fabien; Passaro, Marcello; Calafat, Francisco M; Shaw, Andrew; Niño, Fernando; Legeais, Jean François; Oelsmann, Julius; +1 more
    Publisher: SEANOE

    Until recently, classical radar altimetry could not provide reliable sea level data within 10 km to the coast. However dedicated reprocessing of radar waveform together with geophysical corrections adapted for the coastal regions now allows to fill this gap at a large number of coastal sites. In the context of the Climate Change Initiative Sea Level project of the European Space Agency, we have recently performed a complete reprocessing of high resolution (20 Hz, i.e., 350m) along-track altimetry data of the Jason-1, Jason-2 and Jason-3 missions over January 2002 to December 2019 along the coastal zones of Northeast Atlantic, Mediterranean Sea, whole African continent, North Indian Ocean, Southeast Asia, Australia and North and South America. This reprocessing has provided valid sea level data in the 0-20 km band from the coast. A total of 756 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span. In the coastal regions devoid from tide gauges (e.g., African coastlines), these virtual stations offer a unique tool for estimating sea level change close to the coast (typically up to 3 km to the coast but in many instances up to 1 km or even closer). Results show that at about 80% of the virtual stations, the rate of sea level rise at the coast is similar to the rate offshore (15 km away from the coast). In the remaining 20%, the sea level rate in the last 3-4 km to the coast is either faster or slower than offshore.

  • Open Access
    Authors: 
    Vivier, Frederic; Lourenco, Antonio;
    Publisher: SEANOE

    This data set collected along the drift of the Ice-T buoy between the North Pole and Fram Strait/ East Greenland Current includes sea ice thickness, atmospheric pressure, air temperature, sea ice temperature profiles and upper ocean salinity and temperature at 6 m depth. The data set is composed of one self-contained netcdf file per deployment. Air temperature corresponds to the first column of the temperature array. The origin of the vertical coordinate in the sea ice for temperature measurement is the surface of the ocean at the time of deployment. The Ice-T (Ice-Thickness) buoy is a sea-ice mass balance buoy developed at LOCEAN-IPSL, Paris.

  • Open Access
    Authors: 
    Sévellec, Florian; Colin De Verdière, Alain; Kolodziejczyk, Nicolas;
    Publisher: SEANOE

    This dataset correponds to a 1ox1o of gridded diffusivity coefficients (in m2 s-1). It is a global coverage at 1000-m depth. This diffusivities are computed using local-analog method based on deep Argo float trajectory from the ANDRO dataset. The ANDRO dataset used in this study corresponds to the 2019 Release (key: 66657) and is freely available through the SEANOE platform (https://doi.org/10.17882/47077). The dataset provide longitudes and latitudes and the zonal, meridional, and cross diffusivity coefficients.

  • Open Access
    Authors: 
    Andreani, Muriel; Escartin, Javier;
    Publisher: SEANOE

    Arc-en-Sub 2022 cruise ROV VICTOR Navigation (M. Andreani & J. Escartin) ROV Victor navigation is acquired during the cruise and post-processed by IFREMER post-cruise. Both the shipboard and the post-processed navigation data show inconsistencies and errors such as gaps. A final navigation file is provided and contains location of the vehicle based primarily on the post-processed navigation, altitude and depth of the vehicle based on the ROV onboard data, and of the CTD temperature. This navigation is used to geolocate all cruise observations, samples, and measurements, and is considered as the reference. The onboard data extracted from the ROV data streams (shipboard navigation), and the post-processed navigations, with files for each individual dive, are also provided for reference. For the final navigation, files with a sampling rate of 1-second and a subsampled 1-minute record are provided. Corrections include: - Standardisation of flags and no-data values (NaN) - Fill major gaps in post-processed navigation with location from ROV shipboard locations - Interpolation of minor gaps in either the shipboard or the post-processed navigation ########################################### 1.- Table with summary ROV dive information (dates, times, dive times, track lengths) in Excel .xlsx and comma separated values .csv ########################################### Files: AES_ROV_Dives.xlsx AES_ROV_Dives.csv ########################################### 2.- ROV VICTOR final navigation files ########################################### We provide a 1-s and a 1-m final navigation file, combining all dives in each case, that will be considered as the reference navigation for the cruise, and will provide the location for all samples and observations. The navigation files are named: AES_ROVNav_Final_1s.txt AES_ROVNav_Final_1m.txt These files are obtained from the IFREMER renavigated files for the vehicle position, and from shipboard data for other parameters. Corrections include removal of flags (use of NaNs instead), interpolation for short data gaps in the processed files, and the use of shipboard navigation data to fill larger data gaps from the processed files. The vehicle depth and altitude are those from the ROV streams. Both files are text tables with the following columns: 1 - Dive number 2 - Absolute date (from datenum matlab function) 3 4 5 - Year month day 6 7 8 - hour minute second 9 10 - Lat Lon Final (renav+filled phins gaps) 11 - Depth Final (ship) 12 - Altitude (ship) 13 - Temperature, °C ########################################### 3.- ROV VICTOR navigation files extracted onboard from the ROV data streams (NMEA files). ########################################### Individual navigation and ROV data files were created onboard and are provided in a single compressed file: ARCENSUB_Victor_ShipboardNav.zip This file contains a navigation and data file for each dive, named AES_VXXX_2205DDHHMM_victor_nav_sensors.txt where XXX is the absolute dive number, followed by the year (22), month (05), day (DD), hour (HH) and minute (MM) The columns, given in the first line of the file, include at a 0,5s interval: #YEAR MONTH DAY HOUR MIN SEC LAT LON DEPTH ALT HEADING ROLL PITCH VEL_X VEL_Y VEL_Z TEMP(CelsiusDeg) ########################################### 4.- Processed ROV VICTOR navigation (DELPHINS processing by IFREMER) ########################################### Processed navigation files provided by IFREMER, together with a report, are provided in a single compressed file: ARCENSUB_Victor_ProcessedNav.zip This file includes: - The processing report: 22_128-Compte-rendu-traitement-Mission-AES-V.pdf - Navigation files for each dive named AES_V_XXX_YY.txt where XXX is the absolute dive number and YY the incremental cruise dive number - Map of the navigation for each dive named AES_V_XXX_YY.jpg (naming as above) Each navigation file includes the following parameters acquired every 0.5s: date time latitude longitude immersion heading pitch roll eastingSd northingSd immersionS headingSd pitchSd rollSd

  • Open Access
    Authors: 
    Dominguez-Carrió, Carlos; Riera, Joan Lluís; Robert, Katleen; Zabala, Mikel; Requena, Susana; Gori, Andrea; Orejas, Covadonga; Lo Iacono, Claudio; Estournel, Claude; Corbera, Guillem; +5 more
    Publisher: SEANOE

    In 2014, the continental shelf and submarine canyon off Cap de Creus (NW Mediterranean) were included in the Site of Community Importance (SCI) “South-West Gulf of Lions canyons system” of the Natura 2000 Network of protected areas. Before the declaration of the SCI (2007-2103), 60 underwater video transects were performed in the area by means of ROVs and a manned submersible, covering more than 30 km of seafloor. Based on the annotation of the video images, we identified the main invertebrate megabenthic communities dwelling from the shelf (70 m depth) down to the bottom of the canyon head (400 m depth). The results of the multivariate analyses indicated that this marine area hosted several benthic communities dominated by suspension- and filter-feeding species, including octocoral gardens, soft-coral assemblages, crinoid fields, sponge grounds and cold-water corals. This dataset includes (1) the geographical location of the benthic communities identified in the video footage, as determined by the clustering analysis, (2) the intra-community diversity associated to the benthic communities, provided as the number of megafauna species identified in each sampling unit and the exponential of Shannon, and (3) the spatial distribution of the benthic communities mapped by means of the Random Forest classification algorithm. This dataset is related to the article “Diversity, structure and spatial distribution of megabenthic communities in Cap de Creus continental shelf and submarine canyon (NW Mediterranean)” submitted to Progress in Oceanography by Dominguez-Carrió et al., which contains further information on how the data were obtained and processed.

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774 Research products, page 1 of 78
  • Open Access
    Authors: 
    Oelsmann, Julius; Passaro, Marcello; Sanchez, Laura; Dettmering, Denise; Schwatke, Christian; Seitz, Florian;
    Publisher: SEANOE

    This dataset contains estimates of piecewise trends and discontinuities in vertical land motion (VLM) time series. The time series are based on two techniques, the Global Navigation Satellite System (GNSS) and differences of satellite altimetry and tide gauge measurements (SATTG). SATTG data are based on monthly PSMSL tide gauge observations (Permanent Service for Mean Sea Level, Holgate et al. [2013]) and multi-mission satellite altimetry from DGFI-TUM. The coastal along-track altimetry SLA data feature latest corrections and adjustments, as well as coastal retracking (using the ALES retracker (Passaro et al., 2014)). The GNSS time series are obtained from the Nevada Geodetic Laboratory (NGL) of the University of Nevada (Blewitt et al. [2016], http://geodesy.unr.edu). This dataset contains information of piecewise trends, uncertainties, as well as discontinuity epochs and sizes in 606 SATTG and 381 GNSS time series. These parameters are estimated with a Bayesian change point detection method (DiscoTimeS), as described in ‘Bayesian modelling of piecewise trends and discontinuities to improve the estimation of coastal vertical land motion’.

  • Open Access
    Authors: 
    Waterisotopes-CISE-LOCEAN;
    Publisher: SEANOE
    Project: EC | TRIATLAS (817578)

    LOCEAN has been in charge of collecting sea water for the analysis of water isotopes on a series of cruises or ships of opportunity mostly in the equatorial Atlantic, in the North Atlantic, in the southern Indian Ocean, in the southern Seas, Nordic Seas, and in the Arctic. The LOCEAN data set of the oxygen and hydrogen isotope (δ18O and δD) of marine water covers the period 1998 to 2019, but the effort is ongoing. Most data prior to 2010 (only δ18O) were analyzed using isotope ratio mass spectrometry (Isoprime IRMS) coupled with a Multiprep system (dual inlet method), whereas most data since 2010 (and a few earlier data) were obtained by cavity ring down spectrometry (CRDS) on a Picarro CRDS L2130-I, or less commonly on a Picarro CRDS L2120-I. Occasionally, some data were also run by Marion Benetti on an Isoprime IRMS coupled to a GasBench (dual inlet method) at the university of Iceland (Reykjavik). On the LOCEAN Picarro CRDS, most samples were initially analyzed after distillation, but since 2016, they have often been analyzed using a wire mesh to limit the spreading of sea salt in the vaporizer. Some of the samples on the CRDS were analyzed more than once on different days, when repeatability for the same sample was not sufficient or the daily run presented a too large drift. Accuracy is best when samples are distilled, and for δD are better on the Picarro CRDS L2130-I than on the Picarro CRDS L2120-I. Usually, we found that the reproducibility of the δ18O measurements is within ± 0.05 ‰ and of the δD measurements within ± 0.30 ‰, which should be considered an upper estimate of the error on the measurement on a Picarro CRDS. The water samples were kept in darkened glass bottles (20 to 50 ml) with special caps, and were often (but not always) taped afterwards. Once brought back in Paris, the samples were often stored in a cold room (with temperature close to 4°C), in particular if they were not analyzed within the next three months. There is however the possibility that some samples have breathed during storage. We found it happening on a number of samples, more commonly when they were stored for more than 5 years before being analyzed. We also used during one cruise bottles with not well-sealed caps (M/V Nuka Arctica in April 2019), which were analyzed within 3 months, but for which close to one third of the samples had breathed. We have retained those analyses, but added a flag ‘3’ meaning probably bad, at least on d-excess (outside of regions where sea ice forms or melts, for the analyses done on the Picarro CRDS, excessive evaporation is usually found with a d-excess criterium (which tends to be too low); for the IRMS analyses, it is mostly based when excessive scatter is found in the S- δ18O scatter plots or between successive data, in which case some outliers were flagged at ‘3’). In some cases when breathing happened, we found that d-excess can be used to produce a corrected estimate of δ18O and δD (Benetti et al., 2016). When this method was used a flag ‘1’ is added, indicating ‘probably good’ data, and should be thought as not as accurate as the data with no ‘correction’, which are flagged ‘2’ or ‘0’. We have adjusted data to be on an absolute scale based on the study of Benetti et al. (2017), and on further tests with the different wire meshes used more recently. We have also checked the consistency of the runs in time, as there could have been changes in the internal standards used. On the Isoprime IRMS, it was mostly done using different batches of ‘Eau de Paris’ (EDP), whereas on the Picarro CRDS, we used three internal standards kept in metal tanks with a slight overpressure of dry air). The internal standards have been calibrated using VSMOW and GISP, and were also sent to other laboratories to evaluate whether they had drifted since the date of creation (as individual sub-standards have typically stored for more than 5-years). These comparisons are still not fully statisfactory to evaluate possible drifts in the sub-standards. Individual files correspond to regional subsets of the whole dataset. The file names are based on two letters for the region (see below) followed by –Wisotopes and a version number (-V0, …): example SO-Wisotopes-V0; the highest version number corresponds to the latest update of the regional data set. The region two letters are the followings: - SO: Southern Ocean including cruise station and surface data mostly from 2017 in the Weddell Sea (WAPITI Cruise JR160004, DOI:10.17882/54012), as well as in the southern Ocean - SI: OISO cruise station and surface data in the southern Indian Ocean (since 1998) (DOI:10.18142/228) - EA: Equatorial Atlantic cruise station and surface data (2005 to 2020), in particular from French PIRATA (DOI:10.18142/14) and EGEE cruises (DOI:10.18142/95) - NA: North Atlantic station and surface data from Oceanographic cruises as well as from ships of opportunity (this includes in particular OVIDE cruise data since 2002 (DOI:10.17882/46448), CATARINA, BOCATS1 and BOCATS2 (PID2019-104279GB-C21/AEI/10.13039/501100011033) cruises funded by the Spanish Research Agency, RREX2017 2017 cruise data (DOI:10.17600/17001400), SURATLANT data set since 2011 (DOI:10.17882/54517), Nuka Arctica data since 2012, STRASSE (DOI:10.17600/12040060) and MIDAS cruise data in 2012-2013, as well as surface data from various ships of opportunity in 2012-2020) - NS: Nordic Sea data from cruises in 2002-2018 - AS: Arctic data from two Tara cruises (in 2006-2008 and 2013) - PM: miscellaneous data in tropical Pacific and Mediterranean Sea The files are in csv format reported, and starting with version V1, it is reported as: - Cruise name, station id, bottle number, day, month, year, hour, minute, latitude, longitude, pressure (db), temperature (°C), it, salinity (pss-78), is, dissolved oxygen (micromol/kg), io2, δ18O, iO, d D, iD, d-excess, id, method type - Temperature is an in situ temperature - Salinity is a practical salinity it, is, io2, iO, iD, id are quality indices equal to: - 0 no quality check (but presumably good data) - 1 probably good data - 2 good data - 3 probably bad data - 4 certainly bad data - 9 missing data (and the missing data are reported with an unlikely missing value) The method type is 1 for IRMS measurements, 2 for CRDS measurement of a saline water sample, 3 for CRDS measurement of a distilled water sample.

  • Open Access
    Authors: 
    DCE-Benthos Network, French Mediterranen Lagoon Monitoring Network;
    Publisher: SEANOE

    French benthic invertebrates composition and abundance taxa data are collected during monitoring surveys on the English Channel / Bay of Biscay coasts and Mediterranean coast (Quadrige program code : REBENT_FAU, RSL_FAU). Protocols are implemented in the Water Framework Directive. Data are transmitted in a Seadatanet format (CDI + ODV) to EMODnet Biology european database. 498 ODV files have been generated from period 01/01/2003 to 31/12/2021.

  • Open Access
    Authors: 
    Oulhen, Erwan; Reinaud, Jean; Carton, Xavier;
    Publisher: SEANOE

    The merger of two surface quasi-geostrophic vortices is examined in detail. As the two vortices collapse towards each other in the merging process, they trap their external fronts between them; these fronts are inserted into the final merged vortex, where they form a central, nearly parallel, sheared velocity strip, sen- sitive to barotropic instability. As a result, this strip breaks up into an alley of small vortices. Subsequently, these small vortices may undergo merger and grow in size in the core of the large merged vortex. The number of small trapped vortices decreases correspondingly. Finally, a single or two small vortices remain. These processes are analysed using a numerical model of the surface quasi-geostrophic equations. The sensitivity of this process to the initial vortex characteristics is explored. A parallel is drawn between this problem and the instability of a rectilinear strip of temperature with a central gap. The application of this problem to the Ocean is discussed.

  • Open Access
    Authors: 
    Copernicus Marine in situ TAC;
    Publisher: SEANOE

    The latest version of Copernicus surface and sub-surface water velocity product is distributed from Copernicus Marine catalogue: - https://resources.marine.copernicus.eu/product-detail/INSITU_GLO_UV_L2_REP_OBSERVATIONS_013_044/INFORMATION This delayed mode product designed for reanalysis purposes integrates the best available version of in situ data for ocean surface currents and current vertical profiles. It concerns three delayed time datasets dedicated to near-surface currents measurements coming from three platforms (Lagrangian surface drifters, High Frequency radars and Argo floats) and velocity profiles within the water column coming from the Acoustic Doppler Current Profiler (ADCP, vessel mounted only) .

  • Open Access
    Authors: 
    Cazenave, Anny; Gouzenes, Yvan; Birol, Florence; Legér, Fabien; Passaro, Marcello; Calafat, Francisco M; Shaw, Andrew; Niño, Fernando; Legeais, Jean François; Oelsmann, Julius; +1 more
    Publisher: SEANOE

    Until recently, classical radar altimetry could not provide reliable sea level data within 10 km to the coast. However dedicated reprocessing of radar waveform together with geophysical corrections adapted for the coastal regions now allows to fill this gap at a large number of coastal sites. In the context of the Climate Change Initiative Sea Level project of the European Space Agency, we have recently performed a complete reprocessing of high resolution (20 Hz, i.e., 350m) along-track altimetry data of the Jason-1, Jason-2 and Jason-3 missions over January 2002 to December 2019 along the coastal zones of Northeast Atlantic, Mediterranean Sea, whole African continent, North Indian Ocean, Southeast Asia, Australia and North and South America. This reprocessing has provided valid sea level data in the 0-20 km band from the coast. A total of 756 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span. In the coastal regions devoid from tide gauges (e.g., African coastlines), these virtual stations offer a unique tool for estimating sea level change close to the coast (typically up to 3 km to the coast but in many instances up to 1 km or even closer). Results show that at about 80% of the virtual stations, the rate of sea level rise at the coast is similar to the rate offshore (15 km away from the coast). In the remaining 20%, the sea level rate in the last 3-4 km to the coast is either faster or slower than offshore.

  • Open Access
    Authors: 
    Vivier, Frederic; Lourenco, Antonio;
    Publisher: SEANOE

    This data set collected along the drift of the Ice-T buoy between the North Pole and Fram Strait/ East Greenland Current includes sea ice thickness, atmospheric pressure, air temperature, sea ice temperature profiles and upper ocean salinity and temperature at 6 m depth. The data set is composed of one self-contained netcdf file per deployment. Air temperature corresponds to the first column of the temperature array. The origin of the vertical coordinate in the sea ice for temperature measurement is the surface of the ocean at the time of deployment. The Ice-T (Ice-Thickness) buoy is a sea-ice mass balance buoy developed at LOCEAN-IPSL, Paris.

  • Open Access
    Authors: 
    Sévellec, Florian; Colin De Verdière, Alain; Kolodziejczyk, Nicolas;
    Publisher: SEANOE

    This dataset correponds to a 1ox1o of gridded diffusivity coefficients (in m2 s-1). It is a global coverage at 1000-m depth. This diffusivities are computed using local-analog method based on deep Argo float trajectory from the ANDRO dataset. The ANDRO dataset used in this study corresponds to the 2019 Release (key: 66657) and is freely available through the SEANOE platform (https://doi.org/10.17882/47077). The dataset provide longitudes and latitudes and the zonal, meridional, and cross diffusivity coefficients.

  • Open Access
    Authors: 
    Andreani, Muriel; Escartin, Javier;
    Publisher: SEANOE

    Arc-en-Sub 2022 cruise ROV VICTOR Navigation (M. Andreani & J. Escartin) ROV Victor navigation is acquired during the cruise and post-processed by IFREMER post-cruise. Both the shipboard and the post-processed navigation data show inconsistencies and errors such as gaps. A final navigation file is provided and contains location of the vehicle based primarily on the post-processed navigation, altitude and depth of the vehicle based on the ROV onboard data, and of the CTD temperature. This navigation is used to geolocate all cruise observations, samples, and measurements, and is considered as the reference. The onboard data extracted from the ROV data streams (shipboard navigation), and the post-processed navigations, with files for each individual dive, are also provided for reference. For the final navigation, files with a sampling rate of 1-second and a subsampled 1-minute record are provided. Corrections include: - Standardisation of flags and no-data values (NaN) - Fill major gaps in post-processed navigation with location from ROV shipboard locations - Interpolation of minor gaps in either the shipboard or the post-processed navigation ########################################### 1.- Table with summary ROV dive information (dates, times, dive times, track lengths) in Excel .xlsx and comma separated values .csv ########################################### Files: AES_ROV_Dives.xlsx AES_ROV_Dives.csv ########################################### 2.- ROV VICTOR final navigation files ########################################### We provide a 1-s and a 1-m final navigation file, combining all dives in each case, that will be considered as the reference navigation for the cruise, and will provide the location for all samples and observations. The navigation files are named: AES_ROVNav_Final_1s.txt AES_ROVNav_Final_1m.txt These files are obtained from the IFREMER renavigated files for the vehicle position, and from shipboard data for other parameters. Corrections include removal of flags (use of NaNs instead), interpolation for short data gaps in the processed files, and the use of shipboard navigation data to fill larger data gaps from the processed files. The vehicle depth and altitude are those from the ROV streams. Both files are text tables with the following columns: 1 - Dive number 2 - Absolute date (from datenum matlab function) 3 4 5 - Year month day 6 7 8 - hour minute second 9 10 - Lat Lon Final (renav+filled phins gaps) 11 - Depth Final (ship) 12 - Altitude (ship) 13 - Temperature, °C ########################################### 3.- ROV VICTOR navigation files extracted onboard from the ROV data streams (NMEA files). ########################################### Individual navigation and ROV data files were created onboard and are provided in a single compressed file: ARCENSUB_Victor_ShipboardNav.zip This file contains a navigation and data file for each dive, named AES_VXXX_2205DDHHMM_victor_nav_sensors.txt where XXX is the absolute dive number, followed by the year (22), month (05), day (DD), hour (HH) and minute (MM) The columns, given in the first line of the file, include at a 0,5s interval: #YEAR MONTH DAY HOUR MIN SEC LAT LON DEPTH ALT HEADING ROLL PITCH VEL_X VEL_Y VEL_Z TEMP(CelsiusDeg) ########################################### 4.- Processed ROV VICTOR navigation (DELPHINS processing by IFREMER) ########################################### Processed navigation files provided by IFREMER, together with a report, are provided in a single compressed file: ARCENSUB_Victor_ProcessedNav.zip This file includes: - The processing report: 22_128-Compte-rendu-traitement-Mission-AES-V.pdf - Navigation files for each dive named AES_V_XXX_YY.txt where XXX is the absolute dive number and YY the incremental cruise dive number - Map of the navigation for each dive named AES_V_XXX_YY.jpg (naming as above) Each navigation file includes the following parameters acquired every 0.5s: date time latitude longitude immersion heading pitch roll eastingSd northingSd immersionS headingSd pitchSd rollSd

  • Open Access
    Authors: 
    Dominguez-Carrió, Carlos; Riera, Joan Lluís; Robert, Katleen; Zabala, Mikel; Requena, Susana; Gori, Andrea; Orejas, Covadonga; Lo Iacono, Claudio; Estournel, Claude; Corbera, Guillem; +5 more
    Publisher: SEANOE

    In 2014, the continental shelf and submarine canyon off Cap de Creus (NW Mediterranean) were included in the Site of Community Importance (SCI) “South-West Gulf of Lions canyons system” of the Natura 2000 Network of protected areas. Before the declaration of the SCI (2007-2103), 60 underwater video transects were performed in the area by means of ROVs and a manned submersible, covering more than 30 km of seafloor. Based on the annotation of the video images, we identified the main invertebrate megabenthic communities dwelling from the shelf (70 m depth) down to the bottom of the canyon head (400 m depth). The results of the multivariate analyses indicated that this marine area hosted several benthic communities dominated by suspension- and filter-feeding species, including octocoral gardens, soft-coral assemblages, crinoid fields, sponge grounds and cold-water corals. This dataset includes (1) the geographical location of the benthic communities identified in the video footage, as determined by the clustering analysis, (2) the intra-community diversity associated to the benthic communities, provided as the number of megafauna species identified in each sampling unit and the exponential of Shannon, and (3) the spatial distribution of the benthic communities mapped by means of the Random Forest classification algorithm. This dataset is related to the article “Diversity, structure and spatial distribution of megabenthic communities in Cap de Creus continental shelf and submarine canyon (NW Mediterranean)” submitted to Progress in Oceanography by Dominguez-Carrió et al., which contains further information on how the data were obtained and processed.

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