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Dataset Title:  Depth profiles of dissolved O2 saturation and isotopologues from the R/V
Yellowfin and R/V Kilo Moana from 2016-09-14 to 2017-08-28
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_753594)
Range: longitude = -158.0 to -118.4°E, latitude = 22.75 to 60.0°N, depth = 5.0 to 3004.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  description {
    String bcodmo_name "site_descrip";
    String description "description of the site";
    String long_name "Description";
    String units "unitless";
  }
  date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20160914, 20170828;
    String bcodmo_name "date";
    String description "date of observation in YYYYMMDD format";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 22.75, 60.0;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude north";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -158.0, -118.4;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude east";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 5.0, 3004.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "niskin bottle closing depth";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  O2_O2sat {
    Float32 _FillValue NaN;
    Float32 actual_range 0.063, 1.118;
    String bcodmo_name "O2sat";
    String description "Dissolved O2 saturation";
    String long_name "O2 O2sat";
    String units "unitless";
  }
  d18O {
    Float32 _FillValue NaN;
    Float32 actual_range -1.921, 18.315;
    String bcodmo_name "delta18O";
    String description "18O value of O2 relative to air-O2";
    String long_name "D18 O";
    String units "parts per thousand";
  }
  D17O {
    Float32 _FillValue NaN;
    Float32 actual_range 21.308, 159.091;
    String bcodmo_name "delta17O";
    String description "17Δ value of O2 relative to air-O2; λ = 0.518";
    String long_name "D17 O";
    String units "parts per million";
  }
  D35 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.689, 2.026;
    String bcodmo_name "dissolved Oxygen";
    String description "35 value of O2";
    String long_name "D35";
    String units "parts per thousand";
  }
  D36 {
    Float32 _FillValue NaN;
    Float32 actual_range 1.191, 3.145;
    String bcodmo_name "dissolved Oxygen";
    String description "36 value of O2";
    String long_name "D36";
    String units "parts per thousand";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"In general, procedures followed those of Reuer et al. 2007. Briefly, 1 and 2-L
bottles were pre-poisoned with 200 \\u03bcL and 400 \\u03bcL saturated HgCl2
solution, dried, and then evacuated to a pressure of < 10-3 mbar before the
gas-tight valve was closed. The Louwer-Hapert 9mm valve sidearm was then
filled with distilled water and capped, making sure to remove all visible
bubbles, to retard any atmospheric leaks. During sampling, water from the
bottom of the Niskin flask was allowed to flow into the sidearm for several
seconds (to flush out the distilled water) before the vacuum valve was opened
to allow water to be siphoned into the sampling bottle. After
sampling\\u2014each bottle typically being half full\\u2014the sidearm was
filled again with seawater and capped until analysis. All gas samples were
analyzed within 4 months of sampling.
 
Before gas analysis, bottles were gently agitated on a shaker table for 48h to
equilibrate dissolved gases with the\\u00a0  
 headspace at room temperature (25C). Next, bottles were inverted and the
seawater pumped out. Finally, the headspace gases were extracted and purified
according to Li et al. (2019), Yeung et al. (2016), and Yeung et al. (2018),
in which O2 is separated from Ar and N2 by gas chromatography. O2/Ar ratios
are standardized relative to atmospheric O2 and air dissolved in distilled
water. Bulk \\u03b418O and 17\\u0394 values are standardized against atmospheric
O2 and O2 derived from laser-fluorination of San Carlos Olivine (Yeung et al.
2018). Clumped-isotope \\u039435 and \\u039436 values are standardized against
laboratory-generated photolytic and heated-gas standards (Yeung et al. 2014).
 
O2/Ar ratios were determined by integrating the peak areas for each species on
an Aglient 7890B gas chromatograph utilizing thermal conductivity detection.
Dissolved O2 saturation was determined from these O2/Ar measurements and
checked independently through manometric determination of O2 yield and
weighing the seawater from which it was extracted. Isotopologue analyses were
performed on a custom Nu Instruments Perspective IS high-resolution isotope
ratio mass spectrometer at Rice University.  
 \\u200b  
 Data was processed as was done in Yeung et al. (2018) for \\u03b418O and
17\\u0394 values and Yeung et al. (2016) for clumped-isotope values. Dissolved
oxygen saturation is calculated using potential temperature and salinity and
the O2 and Ar saturation calculated using MATLAB programs by Roberta Hamme
(O2sol and Arsol from
[https://web.uvic.ca/~rhamme/download.html](\\\\\"https://web.uvic.ca/~rhamme/download.html\\\\\")).
These calculated values were compared to measured values to determine
O2/O2sat.";
    String awards_0_award_nid "750417";
    String awards_0_award_number "OCE-1436590";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1436590";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Donald L. Rice";
    String awards_0_program_manager_nid "51467";
    String awards_1_award_nid "750424";
    String awards_1_award_number "OCE-1533501";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1533501";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Henrietta N Edmonds";
    String awards_1_program_manager_nid "51517";
    String awards_2_award_nid "750426";
    String awards_2_award_number "OCE-1436326";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1436326";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "Henrietta N Edmonds";
    String awards_2_program_manager_nid "51517";
    String awards_3_award_nid "750436";
    String awards_3_award_number "OCE-1559004";
    String awards_3_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1559004";
    String awards_3_funder_name "NSF Division of Ocean Sciences";
    String awards_3_funding_acronym "NSF OCE";
    String awards_3_funding_source_nid "355";
    String awards_3_program_manager "Dr Simone Metz";
    String awards_3_program_manager_nid "51479";
    String awards_4_award_nid "750441";
    String awards_4_award_number "OCE-1559215";
    String awards_4_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1559215";
    String awards_4_funder_name "NSF Division of Ocean Sciences";
    String awards_4_funding_acronym "NSF OCE";
    String awards_4_funding_source_nid "355";
    String awards_4_program_manager "Dr Simone Metz";
    String awards_4_program_manager_nid "51479";
    String cdm_data_type "Other";
    String comment 
"Depth profiles of dissolved O2 saturation and isotopologues 
  PI: Laurence Yeung 
  Version: 2018-11-30";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2019-01-23T19:38:07Z";
    String date_modified "2019-12-05T14:16:36Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.753594.1";
    Float64 Easternmost_Easting -118.4;
    Float64 geospatial_lat_max 60.0;
    Float64 geospatial_lat_min 22.75;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -118.4;
    Float64 geospatial_lon_min -158.0;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 3004.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-16T21:26:35Z (local files)
2024-04-16T21:26:35Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_753594.das";
    String infoUrl "https://www.bco-dmo.org/dataset/753594";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Seawater was sampled from Niskin bottles associated with CTD casts on each cruise.";
    String instruments_0_dataset_instrument_nid "753610";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "Niskin bottles";
    String instruments_1_acronym "Mass Spec";
    String instruments_1_dataset_instrument_description "Isotopologue analyses were performed on a custom Nu Instruments Perspective IS high-resolution isotope ratio mass spectrometer at Rice University.";
    String instruments_1_dataset_instrument_nid "753609";
    String instruments_1_description "General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_1_instrument_name "Mass Spectrometer";
    String instruments_1_instrument_nid "685";
    String instruments_1_supplied_name "mass spectrometer";
    String keywords "bco, bco-dmo, biological, chemical, d17, D17O, d18, d18O, d35, d36, data, dataset, date, depth, description, dmo, erddap, latitude, longitude, management, O2, O2_O2sat, o2sat, oceanography, office, oxygen, preliminary";
    String license "https://www.bco-dmo.org/dataset/753594/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/753594";
    Float64 Northernmost_Northing 60.0;
    String param_mapping "{'753594': {'Latitude': 'flag - latitude', 'Depth': 'flag - depth', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753594/parameters";
    String people_0_affiliation "Rice University";
    String people_0_person_name "Laurence Yeung";
    String people_0_person_nid "750420";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Southern California";
    String people_1_affiliation_acronym "USC";
    String people_1_person_name "William M. Berelson";
    String people_1_person_nid "50600";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of California-Los Angeles";
    String people_2_affiliation_acronym "UCLA";
    String people_2_person_name "Dr Edward Young";
    String people_2_person_nid "555513";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Rice University";
    String people_3_person_name "Huanting Hu";
    String people_3_person_nid "783415";
    String people_3_role "Scientist";
    String people_3_role_type "originator";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Mathew Biddle";
    String people_4_person_nid "708682";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "O2 isotopologues in the N. Pacific,CDISK 4";
    String projects_0_acronym "O2 isotopologues in the N. Pacific";
    String projects_0_description 
"NSF Abstact:
Marine oxygen is strongly linked to the cycling of organic matter in the marine environment, and as such, its budget is central to addressing many of the outstanding questions in oceanography. In this study, researchers will measure the amounts of three isotopes of oxygen that can combine to make up the molecular oxygen gas dissolved in oceanic waters. When oxygen reacts with other substances, the three isotopes can behave in slightly different ways depending on the type of reactions; this makes it possible to identify the kinds of processes that have led to the existence of the oxygen found at different places in the ocean. These results are expected to yield new insights into how oxygen interacts with organisms, organic matter, minerals, and other substances under a variety marine environmental conditions, with important implications for future studies of ocean productivity and hypoxic (low oxygen) zones in the ocean. A female graduate student will gain hands-on experience with these new methods, and results from the research will be disseminated to the general public through social media and a video.
In this project, researchers will make simultaneous measurements of five stable isotopic variants of O2, known as quintuple-isotopologue analysis, to provide new constraints on marine oxygen cycling. Using a combined field and experimental study they will evaluate the potential for the quintuple-isotopologue method to trace marine O2 cycling. Utilizing these novel analytical methods, they will analyze depth profiles and dark bottle incubations of O2 isotopologues in the water column at San Pedro Ocean Time Series (SPOT). These measurements, combined with nutrient profiles and complementary laboratory experiments, will yield a first-order understanding of how photosynthesis, respiration, and mixing affect the isotopologue composition of dissolved marine O2.";
    String projects_0_end_date "2015-03";
    String projects_0_geolocation "San Pedro Ocean Time Series (33.5 N 118.4 W)";
    String projects_0_name "Collaborative Research:  New Constraints on Marine Oxygen Cycling";
    String projects_0_project_nid "750418";
    String projects_0_start_date "2014-09";
    String projects_1_acronym "CDISK 4";
    String projects_1_description 
"NSF Abstract:
Ocean acidification (OA) is the decrease in seawater pH due to increased oceanic uptake of anthropogenic carbon dioxide (CO2) from the atmosphere. The impact of this uptake in the marine environment is lessened by the dissolution of calcium carbonate (CaCO3) to calcium and carbonate ions, allowing carbonate ions to bind free hydrogen ions that cause the decrease in pH. Researchers from the University of Southern California and California Institute of Technology have developed a new method for determining carbonate dissolution rates that work in both laboratory and field settings. Preliminary data using this technique has revealed a distinct difference in measured rates between those obtained in the laboratory and those in the field. It is crucial that laboratory and field measurements be standardized to be able to accurately study and compare dissolution rate studies. As such, the researchers will perform extensive fieldwork and laboratory to bridge the gap between these dissolution rate measurements. Results will be widely useful to the ocean chemistry community, especially modelers, wishing to study any aspect of ocean carbonate chemistry, as well as paleoceanographers using carbonate material to study past ocean conditions. Graduate students will be co-mentored by the researchers, and the University of Southern California?s (USC) Young Researcher Program will allow the researchers to involve local high school students. USC International Relations students will be involved in the project, not only gaining scientific experience, but also will learn the policy aspect of the science.
Calcium carbonate (CaCO3) dissolution helps to mitigate the effects of ocean acidification (OA) and is a key factor in the ocean?s alkalinity balance. The researchers have recently developed a novel tracer methodology which can monitor carbonate dissolution rates in both the lab and field. This method traces the transfer of 13C from labeled solids to seawater. Using this method has led to breakthroughs in understanding the controls of CaCO3 dissolution kinetics, but it has also revealed that the measurements made in a lab and in the field are not entirely in line. It is crucial to be able to correlate these two measurements to be able to fully study and understand the dynamics of CaCO3 dissolution. Therefore, the researchers will extend their previous work to standardize the results of measurements in the lab with those in the ocean. The North Pacific Ocean with a gradient in carbonate saturation states will be used for the field study, and lab-based experiments will allow the researchers to constrain variables such as pressure, the dissolved inorganic carbon/alkalinity ratio, and concentrations of phosphate. This research will further understanding of OA, the mechanisms controlling carbonate dissolution, and how the ocean modulates its alkalinity budget.";
    String projects_1_end_date "2020-03";
    String projects_1_geolocation "NE Pacific transect (22.75 N to 60 N, 150-160 W)";
    String projects_1_name "Collaborative Research: CaCO3 Dissolution in the North Pacific Ocean: Comparison of Lab and Field Rates with Biogenic and Abiogenic Carbonates";
    String projects_1_project_nid "750437";
    String projects_1_start_date "2016-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 22.75;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Seawater was sampled from Niskin bottles associated with CTD casts on each cruise. Water for these dissolved gas isotope samples was the first to be sampled from a given Niskin bottle. When possible, bottles from the same cast were sampled, but depth profiles often came from separate casts at the same site.";
    String title "Depth profiles of dissolved O2 saturation and isotopologues from the R/V Yellowfin and R/V Kilo Moana from 2016-09-14 to 2017-08-28";
    String version "1";
    Float64 Westernmost_Easting -158.0;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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