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88 results for “Argo”
Mediterranean Quality checked BGC-Argo 2013-2022 dataset
<p>BGC Argo profiles were downloaded from the Coriolis GDAC (Argo, 2022; last visited July 2022). We collected both AM and DM synthetic profiles and selected data labelled as good, probably good, changed, and interpolated (quality check - QC - flags 1, 2, 5, and 8).</p> <p>Moreover, if the vertical resolution of the profiles exceeded 2m, the data were averaged to 2m resolution. Finally, a moving weighted average was calculated to remove eventual small fluctuations in the data profiles. This moving average takes into account the 2 upper and 2 lower neighbouring points and a Gaussian function of the distance to the central point for the weights.</p> <p>Specific quality check procedures were applied to the variables based on our knowledge and use of BGC-Argo data in the Mediterranean Sea. For chlorophyll, the profiles were shifted to have a value of 0 at 400-600 m (Cossarini et al., 2019; Teruzzi et al., 2021); for oxygen a check for anomalous drifts at depth was computed (Amadio et al., 2024); and for nitrate negative surface values were replaced by 0.05 mmol/m3 (Teruzzi et al., 2021).<span> </span>The Python package “Bit.Sea” (/Float), available at <a href="https://doi.org/10.5281/zenodo.8283692"><span>https://doi.org/10.5281/zenodo.8283692</span></a> (Bolzon et al., 2023), was used for the quality check.</p> <p>The dataset is used in the Mediterranean Biogeochemical Center of the Copernicus Marine Service (Coppini et al., 2023) for assimilation and validation (Amadio et al., 2024), and neural network application (Pietropolli et al., 2023). </p>
Formation of winter barrier layers in the northern South China Sea: A study based on Argo profiling data from 2008 to 2020
<p>The data was used in the paper “Formation of winter barrier layers in the northern South China Sea: A study based on Argo profiling data from 2008 to 2020”.</p> <p>The data include interpolated Argo temperature/salinity (T/S) profiles for the period 2008-2020 in the 15°N–23°N, 109°E–121°E region, as well as derived mixed layer depth (MLD), isothermal layer depth (ILD), and barrier layer thickness (BLT). The original archival data were obtained from the French Argo Data Center (ftp://ftp.ifremer.fr/ifremer/argo/geo/pacific_ocean).</p>
Data Argo floats Cant
<p>Data of the Argo floats with the estimation of anthropogenic carbon</p>
ARGO_BGC dataset for the Labrador Sea region
<p> </p> <ul> <li><strong>ARGO_allVars_1mRes_450.tgz</strong>: archive contains Matlab binary files consisting of all ARGO_BGC float data in the Labrador Sea. Profile data were interpolated to 1m vertical resolution and are given up to a water depth of 450 meter. Dataset includes information on date, latitude, longitude, salinity, temperature, Chlorophyll-a, particle backscatter (bbp), and (not available on all floats) Oxygen, Nitrogen and Photosynthetically available radiation (PAR).</li> <li><strong>ARGO_physic_5mRes_5000.tgz</strong>: archive contains Matlab binary files consisting of all ARGO physical data in the Labrador Sea. Profile data were interpolated to 5m vertical resolution and are given up to a water depth of 5000 meter. Dataset includes information on date, latitude, longitude, salinity, temperature.</li> <li><strong>CMEMS_along_ARGO_physicsFine.tgz</strong>: archive contains Matlab binary files consisting of CMEMS high resolution physical model data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, salinity, temperature and CMEMS model depths.</li> <li><strong>CMEMS_along_ARGO_chlCoarse.tgz:</strong> archive contains Matlab binary files consisting of CMEMS coarse BGC-model data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, Chlorophyll-a and CMEMS model depths.</li> <li><strong>CMEMS_along_ARGO_chlOCL3.tgz</strong>: archive contains Matlab binary files consisting of CMEMS Level 3 Chlorophyll-a remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a.</li> <li><strong>CMEMS_along_ARGO_chlOCL4.tgz</strong>: archive contains Matlab binary files consisting of CMEMS Level 4 Chlorophyll-a remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a.</li> <li><strong>MODIS_along_ARGO.tgz</strong>: archive contains Matlab binary files consisting of MODIS-Aqua Level 3 remote sensing data extracted along ARGO pathes. Dataset includes information on date, latitude, longitude, (surface) Chlorophyll-a, (surface) particle backscatter and Photosynthetically available radiation (PAR).</li> </ul>
FIGURE 2. Aiphanes argos. A in A new, critically endangered species of Aiphanes (Arecaceae) from Colombia
FIGURE 2. Aiphanes argos. A, inflorescence with developing fruits; B, ripe fruits; C. the rocky canyon of the Samana Norte River, habitat of Aiphanes argos. (Saúl E. Hoyos-Gómez).
FIGURE 1. Aiphanes argos. A in A new, critically endangered species of Aiphanes (Arecaceae) from Colombia
FIGURE 1. Aiphanes argos. A, habitat and habit; B, Aiphanes argos (right) contrasted with the co-occurring rheophytic Geonoma interrupta subsp. rivalis (left). Note the inflorescence of Aiphanes projecting above leaves (arrow); C, detail of pinnae with praemorse apices and spines on the margins; D, inflorescence at anthetic stage. (A, C, Saúl E. Hoyos-Gómez; B, D, Rodrigo Bernal).
FIGURE 1–3. 1. Garrisonia aurindae male, Fig. 2, 7. Tauriphila argo, Fig. 3 in Garrisonia aurindae gen. and spec. nov. from the State of Bahia, Brazil (Anisoptera: Libellulidae)
FIGURE 1–3. 1. Garrisonia aurindae male, Fig. 2, 7. Tauriphila argo, Fig. 3. Tauriphila risi: (1–3) wings.
Datasets for the comparison between POC estimated from BGC-Argo floats and PISCES model simulations
<p>This dataset is composed of two main folders.</p> <p><strong>clim_3D</strong>: contains 4 files in 3 directories:</p> <ul> <li>BGC-Argo/bbp700_nemo_clim.nc: global monthly climatology of BGC-Argo b<sub>bp700</sub> measurements on the ORCA2_L31 NEMO grid.</li> <li>BGC-Argo/bbp700_nemo_climseas.nc: seasonal climatology (JFM, ...OND) of BGC-Argo b<sub>bp700</sub> measurements on the ORCA2_L31 NEMO grid.</li> <li>biomes/nemobiomes.nc: biomes of Fay and McKinley 2014 (ESSD) reprojected onto the ORCA2_L31 NEMO grid.</li> <li>PISCES/PISCES_1m_19600101_19601231_ptrc_T.nc: PISCES tracers (living organisms and detrial organic carbon), monthly climatology based on pre-industrial simulation described by Aumont et al. 2017 (Biogeosciences).</li> </ul> <p><strong>CATS_1D:</strong> contains 66 folders. The folders are named as <fwmo>_<yyyy>_<orca1cell>, where</p> <ul> <li>fwmo = World Meteorological Organization (WMO) float number</li> <li>yyyy = year</li> <li>orca1cell = number of the NEMO model horizontal grid cell (ORCA1 grid) used to run the PISCES 1D offline simulation.</li> </ul> <p>Each folder contains:</p> <ul> <li>BGC-Argo observations for a given Argo float and year, bined onto the model vertical grid and 5-day peiods: 'Mprof*.nc'</li> <li>Dynamical fields used to run PISCES 1D offline simulations: 'dyna_grid_T.nc'</li> <li>Output of the simulations: PISCES tracers at 5-day resolution: 'PISCES_5d_*_ptrc_T.nc'</li> <li>List of horizontal model grid cells that were visited by the Argo float on a given year: 'xymatch_<fwmo>.csv'. If the list is queried for the grid cell number <orca1cell>, one can obtain the corresponding longitude (xmap), latitude (ymap), and the x and y indices of the grid (plus/minus 1). These indices correspond to the 3x3 horizontal grid of the dynamical fields and the PISCES 1D output.</li> </ul> <p> </p> <ul> </ul>
Data from: Evaluation of Argos telemetry accuracy in the High-Arctic and implications for the estimation of home-range size
Open the record for dataset details and reuse information.
Fig. 2 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 2: A: Confidence level along depth for Argo-model average temperature profile differences in South Adriatic (blue) & Otranto Strait (green). B: Confidence level along depth for Argo-model average temperature profile differences in Northern (yellow) and Southern (red) Ionian. C: Confidence level along depth for Argo-model average salinity profile differences in South Adriatic (blue) & Otranto Strait (green). D: Confidence level along depth for Argo-model average salinity profile differences in Northern (yellow) and Southern (red) Ionian. E: Confidence level along depth for Argo-model average temperature (green) and salinity (brown) profile differences in the whole study area. The shaded rectangular denotes the area of statistical significant differences with a confidence of 95% between the Argo and model distributions (null-hypothesis rejected, p <0.05).
Ocean eddy kinetic energy at 1000 m depth estimated from Argo drift data from July 1997 to December 2015
<p><strong>Eddy kinetic energy at 1000 dbar depth estimated from Argo drift data from July 1997 to December 2015</strong><br><br>These are the data used to draw Fig.1 of Katsumata (2017b).<br>Argo drift data from YoMaHa (Lebedev et al. 2017) is averaged<br>in a quasi-circle with a radius of 300 km, deformed to follow<br>bathymetry, and deviation from the average is our eddy here.<br><br>Detail of the method is found in Katsumata (2017a).<br><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017a)</a><br><a href="https://doi.org/10.1175/JPO-D-16-0150.1">Katsumata (2017b)</a><br>Lebedev, K., H. Yoshinari, N. A. Maximenko, and P. W. Hacker,<br> (2007) YoMaHa’07: Velocity data assessed from trajectories of<br> Argo floats at parking level and at the sea surface. IPRC Tech.<br> Note 4, 16 pp.<br> <a href="https://doi.org/10.1175/JPO-D-16-0150.1">http://apdrc.soest.hawaii.edu/projects/yomaha/</a></p> <p> </p>
Vectorized logs, bed numbers, sample locations, biostratigraphy and astrochronology of the Barranco Cavila, Arroyo Gilico, Rio Argos, La Charce-Pommerol, Vergol-Morénas, Angles and Reynier sections
<p>This is a vectorized figure showing the astrochronology, bed number, detailed sample locations and correlations of sections from the Subbetic Domain (SE Spain) and Vocontian Basin (SE France), measured from the latest Berriasian to the earliest Aptian.</p> <p>The sections shown are:</p> <ul> <li>Barranco Cavila: 38°3′10” ; N 1°53′20” W</li> <li>Arroyo Gilico: 38°9′35” N ; 1°40′41” W</li> <li>Río Argos: 38°04’15” N ; 1°56’58” E</li> <li>La Charce: 44°28‘12“ N ; 5°26‘23“ E</li> <li>Pommerol: 44°26‘18“ N ; 5°27‘33“ E</li> <li>Angles: 43°56‘15“N ; 6°32‘02“ E</li> <li>Morénas: 44°13‘52“ N ; 5°25‘21“ E</li> <li>Vergol: 44°12‘11“N ; 5°25‘04“E</li> <li>Reynier: 44°17‘58“ N ; 6°07‘02“ E</li> </ul>
Data Argo Cant GBC
<p>Whole database of our Argo-based Cant estimates</p>
Accuracy of the New Barrett TAL Formula With the Argos Measurements: A Multicenter Prospective Study
ClinicalTrials.gov study NCT06085131. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Safety and Performance Study of the ARGOS-IO System in Patients Undergoing Boston Keratoprosthesis Implantation
ClinicalTrials.gov study NCT02945176. IPD Sharing: NO. Countries: 1. Publications: 0.
SPURS-2 Argo float CTD profile data from the E. Tropical Pacific field campaign
The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is a NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project is comprised of two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. Part of the Argo global network of autonomous, self-reporting samplers, Argo floats drift horizontally and move vertically through the water column generally on 10 day cycles, collecting high-quality temperature, conductivity and salinity depth (CTD) profiles from the upper 2000m. Twenty five floats were deployed during SPURS-2 within the campaign spatial domain and time period, yielding approximately 1,893 profiles. These were standard Argo floats with the addition of acoustic rain gauges (PAL) in some cases. SPURS-2 ARGO data files are organized per float and profile with the vertical conductivity, salinity, temperature, pressure, depth observations per the netCDF ARGO file specification with some augmented global metadata attributes.
Argo float CTD profile data within the scope of the SPURS-1 N. Atlantic field campaign
The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is an oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project involves two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-1 campaign involved a series of 5 cruises during 2012 - 2013 seeking to characterize the salinity structure and balance in a high salinity, high evaporation, and low rainfall region of the subtropical North Atlantic. It aims to resolve processes responsible for maintaining the subtropical surface salinity maximum in this region and within a 900 x 800-mile square study area centered at 25N, 38W. Part of the Argo global network of autonomous, self-reporting samplers, Argo floats drift horizontally and move vertically through the water column generally on 10 day cycles, collecting high-quality temperature, conductivity and salinity depth profiles from the upper 2000m. Approximately 24 floats were deployed during SPURS-1 within the campaign domain, mainly during the Knorr cruise (6 Sept-9 Oct,2012). These were standard Argo floats with the addition of surface temperature and salinity (STS) sensors and acoustic rain gauges (PAL). Data accessible here only include the standard ARGO profiles, not the STS or PAL data. SPURS-1 ARGO data files are oganized per float and each contain profile trajectory series of conductivity, salinity, temperature, pressure, depth observations.
SPURS-2 Passive Accoustic Listener (PAL) data from ARGO float deployments during the E. Tropical Pacific field campaign
The SPURS (Salinity Processes in the Upper Ocean Regional Study) project is a NASA-funded oceanographic process study and associated field program that aim to elucidate key mechanisms responsible for near-surface salinity variations in the oceans. The project is comprised of two field campaigns and a series of cruises in regions of the Atlantic and Pacific Oceans exhibiting salinity extremes. SPURS employs a suite of state-of-the-art in-situ sampling technologies that, combined with remotely sensed salinity fields from the Aquarius/SAC-D, SMAP and SMOS satellites, provide a detailed characterization of salinity structure over a continuum of spatio-temporal scales. The SPURS-2 campaign involved two month-long cruises by the R/V Revelle in August 2016 and October 2017 combined with complementary sampling on a more continuous basis over this period by the schooner Lady Amber. Focused around a central mooring located near 10N,125W, the objective of SPURS-2 was to study the dynamics of the rainfall-dominated surface ocean at the western edge of the eastern Pacific fresh pool subject to high seasonal variability and strong zonal flows associated with the North Equatorial Current and Countercurrent. Part of the Argo global network of autonomous, self-reporting samplers, Argo floats drift horizontally and move vertically through the water column generally on 10 day cycles, collecting high-quality temperature, conductivity and salinity depth (CTD) profiles from the upper 2000m. Four of the Twenty five floats deployed during SPURS-2 within the campaign spatial domain and time period were additionally equipped with acoustic rain gauges (PAL - Passive Acoustic Listeners). SPURS-2 ARGO-PAL data files are in netCDF/CF-compliant data format and organized per float. Float identifiers associated with ARGO CTD data are referenced in the metadata of the related PAL files.
ARGO ship classification dataset
<p>The ARGO ship classification dataset holds 1750 labelled images from PlanetScope-4-Band satelites. The dataset creation process and results on the dataset are published in the demo paper:</p> <p>{CITE}</p> <p>The imagery is provided as numpy binary files. All image data is licensed by Planet Labs PBC. The channel ordering is BGRN. The dataset is provided in two folders named "ship" and "non_ship". Those folders correspond to the original labels created during automated dataset creation. The files are numbered.</p> <p>Two additional .csv files are provided. The shipsAIS_2017_Zone17.csv file holds the AIS information on the imagery contained in the ship folder. The data was retrieved from marinecadastre.gov.</p> <p>During the experiments errors in the automatically created dataset emerged which are further described in the paper. The manual relabelling is supplied in the corrected_labels.csv file.</p>
O'ZBEK HAMDA INGLIZ TILLARIDA ARGO VA JARGONLAR TARJIMASINING SOTSIOLINGVISTIK XUSUSIYATLARI
<p><em><span>Ushbu maqola o‘zbek va ingliz tillarida argo va jargonlarning tarjimasi bilan bog‘liq sotsiolingvistik xususiyatlarni o‘rganishga qaratilgan. Argo va jargonlar muayyan ijtimoiy guruhlar tomonidan qo‘llaniladigan maxsus til shakllari bo‘lib, ularning tarjimasi til va madaniyat o‘rtasidagi tafovutlar, sotsiolingvistik kontekst va pragmatik ma’nolarni saqlash zarurati tufayli qiyin kechadi. Maqolada argo va jargonlarning tarjima jarayonida duch kelinadigan muammolar, tarjimonning roli va ularning sotsiolingvistik jihatdan moslashuvi muhokama qilinadi. Tarjima jarayonida madaniy va ijtimoiy konnotatsiyalarni to‘g‘ri yetkazish, shuningdek, ushbu maxsus til shakllarining asl ma’nolarini saqlash uchun ijodiy yondashuvlar muhim ahamiyatga ega.</span></em></p>
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