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88 results for “Argos”
Fig. 10 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 10: Temperature (A) and salinity (C) average profiles with the associated STD for model (red) and Argo (blue), calculated from all the associated profiles of the study area (Fig. 1). Profile differences (Argo – model) of the average temperature (green line) and salinity (brown line) (B). T-S diagram of all Argo and model associated profiles for two depth layer zones (Argo: 200-800m light blue, 800-2000 m dark blue) (Model: 200-800 m pink, 800-2000 m red) (D).
Fig. 9 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 9: Temperature (A) and salinity (C) average profiles with the associated STD for model (red) and Argo (blue), calculated from the associated profiles during the "winter" periods (November – April). The associated profiles for the "summer" periods (May – October) are shown in (B) and (D) for the temperature and salinity respectively.
Fig. 7 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 7: A: Argo salinity average profiles in Southern Adriatic (SA) and Otranto Strait (OS) for the years 2010 (green) and 2012 (purple). B: Argo salinity average profiles in the Northern Ionian (NI) for the years 2008 (light blue), 2009 (dark blue), 2010 (green), 2011 (red) and 2012 (purple). C: Model salinity average profiles in Southern Adriatic (SA) and Otranto Strait (OS) for the years 2010 (green) and 2012 (purple). D: Argo salinity average profiles in the Northern Ionian (NI) for the years 2008 (light blue), 2009 (dark blue), 2010 (green), 2011 (red) and 2012 (purple).
Fig. 8 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 8: A: Argo salinity average profiles in the south-eastern Ionian for the years 2008 (light blue), 2009 (dark blue), 2010 (green), 2011 (red) and 2012 (purple). B: Model salinity average profiles in the south-eastern Ionian for the years 2008 (light blue), 2009 (dark blue), 2010 (green), 2011 (red) and 2012 (purple).
Fig. 6 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 6: Temperature (A) and salinity (B) average profiles with the associated STD for model (red) and Argo (blue), calculated from the available profiles in the southern Ionian region. Hovmöller diagrams of the differences between Argo and model associated profiles over time for temperature (C) and salinity (D) in the southern Ionian.
Fig. 5 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 5: Temperature (A) and salinity (B) average profiles with the associated STD for model (red) and Argo (blue), calculated from the available profiles in the northern Ionian region. Hovmöller diagrams of the differences between Argo and model associated profiles over time for temperature (C) and salinity (D) in the northern Ionian.
Fig. 3 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 3: Temperature (A) and salinity (B) average profiles with the associated STD for model (red) and Argo (blue), calculated from the available profiles in the southern Adriatic region. Hovmöller diagrams of the differences between Argo and model associated profiles over time for temperature (C) and salinity (D) in the south Adriatic.
Fig. 4 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 4: Temperature (A) and salinity (B) average profiles with the associated STD for model (red) and Argo (blue), calculated from the available profiles in the Otranto Strait. Hovmöller diagrams of the differences between Argo and model associated profiles over time for temperature (C) and salinity (D) in the Otranto Strait.
Fig. 1 in Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea Abstract
Fig. 1: SANI model bathymetry (A). The geographical area covered by SANI model (red rectangular) and the divided sub-regions SA (Southern Adiatic - yellow), OS (Otranto Strait - green), NI (Northern Ionian – brown) and SI (Southern Ionian – blue). All the available (966) Argo profiles for the period 2008-2012 from 21 individual floats denoted with different colours according to their WMO number (B).
Dataset: Argo Blockchain plc 8.75% Senior Notes due 2026 (ARBKL) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Argo Blockchain plc (ARBK) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
BGC-Argo radiometry matchups with L2 satellite images from MODIS, VIIRS and OLCI sensors
<p> Diffuse attenuation coefficients(Kd) were computed from measured downwelling irradiance measurements from BGC-Argo floats. Matchups between satellite images and float profiles were then performed. Estimates of Kd at two different wavelengths and<br> band-integrated (PAR) were obtained from Remote Sensing Reflectance using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B).</p>
Argo database
<p>Database for annotating ARGs (<code>SARG+ ver. 2025-05-01</code>) and assigning taxonomic labels (<code>GTDB R226</code>) to ARG-containing reads.</p>
Ocean Heat Content Anomalies in the North Atlantic based on mapping Argo data using local Gaussian processes defined over space
<p>Monthly Ocean Heat Content Anomalies (OHCA) in the top 2000 dbar of the ocean are calculated (during 2005-2022, in the North Atlantic, north of 20N) subtracting the time mean over the period 2005-2021 from the monthly time series of OHC. OHC fields are mapped using a locally stationary Gaussian process (defined over space) with data-driven decorrelation scales (Kuusela and Stein, 2018). A linear time trend was included in the estimate of the mean field (along with spatial terms and harmonics for the annual cycle). In this product, mapping is done in latitude and longitude with monthly subsets of data. Mapping is done separately for different vertical sections: 15-20 dbar, 15-300 dbar, 300-700 dbar, 700-1850 dbar, 1800-1850 dbar. The 15-20 dbar (1800-1850 dbar) section is used to estimate OHCA for 0-15 dbar (1850-2000 dbar), where observations are sparser. Different vertical sections are combined to estimate global OHCA for 0-2000 dbar. Regions of the ocean that are shallower than 300 m or are not sufficiently well sampled by the Argo array are not included. </p>
"Mercury about to kill Argos" by B. Thorvaldsen
Sculpture "Mercury about to kill Argos" by Bertel Thorvaldsen ID no.: ND 11280 Museum: The National Museum in Kraków https://muzea.malopolska.pl/en/objects-list/15 Object copyright: The National Museum in Kraków Digitalisation: RDW MIC, Małopolska's Virtual Museums project Source: Objaverse 1.0 / Sketchfab
Supplementary scripts and data for Bastin et al.: Atlantic Equatorial Deep Jets in Argo Float Data, Journal of Physical Oceanography
<p>Analysis scripts used to obtain the results in the paper</p> <p>Bastin, S., M. Claus, P. Brandt and R. J. Greatbatch: Atlantic Equatorial Deep Jets in Argo Float Data. Submitted to Journal of Physical Oceanography.</p>
Combined high-depth Illumina+PacBio Sequencing of several samples from FDA-ARGOS
<p>The (real) sequencing data is compiled from a concatenation of sequencing runs from Database for Reference Grade Microbial Sequences (FDA-ARGOS). Specifically, the following samples were sequenced with both Illumina and PacBio. The sample accessions are shown below.</p> <pre><code> BioSample Run Platform Organism bases source <chr> <chr> <chr> <chr> <dbl> <chr> 1 SAMN06173354 SRR5409204 ILLUMINA Bacillus anthracis 1778000000 Colorado Serum Co., Anthrax Spore Vaccine 2 SAMN06173354 SRR5409205 PACBIO_SMRT Bacillus anthracis 2420000000 Colorado Serum Co., Anthrax Spore Vaccine 3 SAMN06173356 SRR5448657 ILLUMINA Bacillus circulans 2311000000 swab with brown-gray powder 4 SAMN06173356 SRR5448656 PACBIO_SMRT Bacillus circulans 242000000 swab with brown-gray powder 5 SAMN04875535 SRR4123920 ILLUMINA Elizabethkingia anophelis 1357000000 blood 6 SAMN04875535 SRR4123919 PACBIO_SMRT Elizabethkingia anophelis 2173000000 blood 7 SAMN06173306 SRR5413253 ILLUMINA Escherichia coli O157 3051000000 clinical isolate 8 SAMN06173306 SRR5413252 PACBIO_SMRT Escherichia coli O157 915000000 clinical isolate 9 SAMN06173318 SRR5413272 ILLUMINA Mycobacterium avium subsp. paratuberculosis 1032000000 feces 10 SAMN06173318 SRR5413271 PACBIO_SMRT Mycobacterium avium subsp. paratuberculosis 462000000 feces 11 SAMN07312468 SRR5879398 ILLUMINA Mycobacterium tuberculosis 1054000000 human 12 SAMN07312468 SRR5879396 PACBIO_SMRT Mycobacterium tuberculosis 1854000000 human 13 SAMN04875542 SRR4123931 ILLUMINA Neisseria gonorrhoeae 1053000000 ATCC strain 14 SAMN04875542 SRR4123930 PACBIO_SMRT Neisseria gonorrhoeae 1117000000 ATCC strain </code></pre> <p>Samples were selected with the SRA Run selector. The SraRunTable.txt file was exported containing the metadata for each sample, and fastq-dump from the SRA toolkit was used to write out fastq files for each run, with paired Illumina data being split into separate _1.fastq.gz and _2.fastq.gz files. </p>
Hovmöller diagram of ARGO subsurface temperature anomalies with histograms of daily profile data count
<p>Hovmöller diagram of ARGO subsurface temperature anomalies with histograms of daily profile data count over two different zones in the pacific ocean. The anomalies were computed from GODAS reanalysis over a 1981-2010 climatology .</p>
Normal and abnormal eddy dataset based on the intersection of altimeters and Argos
<p>The current mainstream identification method of eddy based on the altimeter is not completely certain in determining the polarity of eddies, so we use the Argo arrays covering the global ocean to screen out abnormal eddies with subsurface potential density anomaly features opposite to surface height anomaly features, including abnormal anticyclonic eddies and abnormal cyclonic eddies. Meanwhile, for further comparing the differences between the natures of normal and abnormal eddies, we also screen out the normal eddies whose subsurface potential density anomaly features are same as surface height anomaly features, including normal anticyclonic eddies and normal cyclonic eddies. The dataset stores the location coordinate, radius, amplitude and lifetime of the eddy, as well as the float number, profile number, location coordinate, date of record of the profile in this eddy and the potential density anomaly in the depth range of 0-1000 m.</p>
ESM4.1 and Argo float 7647 ESPER, eOMP files and scripts
<p>This dataset contains NOAA GFDL's ESM4.1 outputs for the California Current System interpolated to 1˚ latitude/longitude resolution and a netCDF file containing data from Argo float 7647. The jupyter notebook files are examples of how to run eOMP analysis using these data and the pyompa scripts described in Shrikumar et al. (2022). The Argo float data does not include phosphate and silicate, which were not measured. These variables are estimated using ESPER routines (Carter et al., 2021) as described in the matlab file. </p> <p>Shrikumar, A., Lawrence, R., Casciotti, K.L.. PYOMPA version 0.3: Technical Note. <em>Authorea</em>. February 04, 2022. doi:10.1002/essoar.10507053.4</p> <p>Carter, B.R., Bittig, H.C., Fassbender, A.J., Sharp, J.D., Takeshita, Y., Xu, Y-Y., Álvarez, M., Wanninkhof, R., Feely, R.A., Barbero, L., 2021. New and updated global empirical seawater property estimation routines. Limnol Oceanogr Methods, 19: 785-809. doi:10.1002/lom3.10461</p>
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OpenNeuro
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