Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  Concentration measurements of water column phosphate, nitrate and nitrite,
dissolved organic phosphorus, methane, and ethylene from samples collected
during the R/V Neil Armstrong cruise AR16 in the western North Atlantic Ocean
in May 2017
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_769203)
Range: longitude = -71.33867 to -64.1875°E, latitude = 29.05817 to 40.4025°N, depth = 5.0 to 1000.0m, time = 2017-05-04T14:35:52Z to 2017-05-20T16:41:58Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
Graph Type:  ?
X Axis: 
Y Axis: 
Constraints ? Optional
Constraint #1 ?
Constraint #2 ?
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
Graph Settings
Marker Type:   Size: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
(Please be patient. It may take a while to get the data.)
Then set the File Type: (File Type information)
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
Time range:    |<   -       
[The graph you specified. Please be patient.]


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 {
  Cruise {
    String bcodmo_name "cruise_id";
    String description "cruise identifier";
    String long_name "Cruise";
    String units "unitless";
  Station {
    Byte _FillValue 127;
    Byte actual_range 1, 9;
    String bcodmo_name "station";
    String description "station number";
    String long_name "Station";
    String units "unitless";
  Cast {
    Byte _FillValue 127;
    Byte actual_range 3, 87;
    String bcodmo_name "cast";
    String description "cast number";
    String long_name "Cast";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 29.05817, 40.4025;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude north (positive values = 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 -71.33867, -64.1875;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude east (negative values = West)";
    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";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.493908552e+9, 1.495298518e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "date and time (UTC) formatted to ISO8601 standard; format: yyyy-mm-ddTHH:MM:SS";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 5.0, 1000.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "sample 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";
  CH4 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.59, 4.0;
    String bcodmo_name "CH4";
    String description "methane";
    String long_name "CH4";
    String units "nanomoles per liter (nmol L-1)";
  C2H4 {
    String bcodmo_name "unknown";
    String description "ethylene";
    String long_name "C2 H4";
    String units "nanomoles per liter (nmol L-1)";
  NOx {
    String bcodmo_name "NO3_NO2";
    String description "nitrate + nitrite";
    String long_name "NOx";
    String units "micromoles per liter (umol L-1)";
  LLN {
    Float32 _FillValue NaN;
    Float32 actual_range 0.002, 0.441;
    String bcodmo_name "Low Level Nitrogen";
    String description "low level nitrogen (nitrate + nitrite)";
    String long_name "LLN";
    String units "micromoles per liter (umol L-1)";
  PO4 {
    String bcodmo_name "PO4";
    String description "phosphate";
    String long_name "PO4";
    String units "micromoles per liter (umol L-1)";
  SRP {
    Float32 _FillValue NaN;
    Float32 actual_range 0.001, 0.132;
    String bcodmo_name "Soluble reactive phosphorus";
    String description "soluble reactive phosphorus";
    String long_name "SRP";
    String units "micromoles per liter (umol L-1)";
  TDP {
    Float32 _FillValue NaN;
    Float32 actual_range 0.09, 1.66;
    String bcodmo_name "Total Dissolved Phosphorus";
    String description "total dissolved phosphorus";
    String long_name "TDP";
    String units "micromoles per liter (umol L-1)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Sampling was conducted aboard the R/V Neil Armstrong (cruise AR16) in May
2017. Seawater was collected from Niskin bottles deployed on a rosette with a
Samples for seawater methane (CH4) and ethylene (C2H4) concentration
measurements were collected from the CTD rosette in 250 mL glass serum vials
(pre-combusted) crimp-sealed with aluminum collars and with Teflon-lined
septa. Samples were typically analyzed the same day of sampling aboard the R/V
Armstrong with an Agilent 7980A gas chromatograph equipped with a flame
ionization detector (FID) and a gas stripping and cryo-trap concentration
method as described previously (Repeta et al. 2016). The FID was calibrated by
injecting different sized loops of a gas mixture standard containing 10 ppm of
CH4 and C2H4 in pure nitrogen gas (Scott-Marrin, Riverside, CA, USA).
Samples for nutrient analyses were collected in acid-clean HDPE plastic
bottles. Samples were shipped frozen to the Center for Microbial Oceanography:
Research and Education at the University of Hawaii at Manoa where they were
stored frozen until analysis.
Seawater phosphate (PO4) concentrations were determined following the
autoanalyzer colorimetric procedure of Foreman et al. (2019). Seawater
nitrate+nitrite (NOx) concentrations were determined following the
autoanalyzer colorimetric procedure outlined of Foreman et al. (2016). Both
PO4 and NOx analyses were performed on a SEAL Analytics autoanalyzer model 3
Seawater samples with low level N+N (LLN) concentrations were measured using
the modified chemiluminescent method based on titanium (III) trichloride
reduction of N+N to nitric oxide gas and detection with an Antek model 7090 as
described by Foreman et al. (2016).
MAGIC soluble reactive phosphorus (SRP) concentrations (i.e. phosphate) were
determined in seawater samples using the MAGnesium Induced Coprecipitation
(MAGIC) technique as described by Karl and Tien (1992) with modifications
based on Thompson-Bulldis and Karl (1998) and Cavendar-Bares et al. (2001) to
increase the concentration factor of phosphate. Specifically, SRP was
concentrated from 150 mL sweater samples using 0.75 mL (0.5% v/v) of 1M NaOH
to precipitate Mg(OH)\\u2082 and the Mg(OH)\\u2082 pellets were dissolved with
5.25 mL of 0.1M HCl.
Total dissolved P (TDP) concentrations were measured by a photo-oxidation
procedure in which controlled exposure to ultraviolet (UV) radiation converts
organic P in seawater to phosphate which is then measured by the modified
molybdenum blue method adapted for the autoanalyzer technique. The UV photo-
oxidation methodology for TDP analysis is described in Foreman et al. (2019).
The difference between TDP and PO4 or TDP and SRP is calculated to estimate
the concentration of dissolved organic phosphorus (DOP) in seawater.";
    String awards_0_award_nid "765013";
    String awards_0_award_number "OCE-1634080";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1634080";
    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 "Dr Simone Metz";
    String awards_0_program_manager_nid "51479";
    String cdm_data_type "Other";
    String comment 
"Water column methane, ethylene, and corresponding nutrients from R/V Armstrong cruise AR16 
  PI: Daniel J. Repeta (WHOI) 
  Co-PIs: David M. Karl (University of Hawaii) 
  Version date hisotry:  
   19 July 2019 (current) - version 2; detection limits of ethylene gas were re-calculated. 
   11 June 2019 - version 1; original submission. 
  Note: nd = not determined; bdl = below detection limit.";
    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 "2019-05-31T16:07:12Z";
    String date_modified "2019-07-22T17:48:47Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.769203.2";
    Float64 Easternmost_Easting -64.1875;
    Float64 geospatial_lat_max 40.4025;
    Float64 geospatial_lat_min 29.05817;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.1875;
    Float64 geospatial_lon_min -71.33867;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1000.0;
    Float64 geospatial_vertical_min 5.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-22T19:29:38Z (local files)
2024-04-22T19:29:38Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_769203.das";
    String infoUrl "https://www.bco-dmo.org/dataset/769203";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "769221";
    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 "Gas Chromatograph";
    String instruments_1_dataset_instrument_nid "769222";
    String instruments_1_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
    String instruments_1_instrument_name "Gas Chromatograph";
    String instruments_1_instrument_nid "661";
    String instruments_1_supplied_name "Agilent 7980A";
    String instruments_2_dataset_instrument_nid "769225";
    String instruments_2_description 
"The chemiluminescence method for gas analysis of oxides of nitrogen relies on the measurement of light produced by the gas-phase titration of nitric oxide and ozone. A chemiluminescence analyzer can measure the concentration of NO/NO2/NOX.

One example is the Teledyne Model T200: http://www.teledyne-api.com/products/T200.asp";
    String instruments_2_instrument_name "Chemiluminescence NOx Analyzer";
    String instruments_2_instrument_nid "542895";
    String instruments_2_supplied_name "Antek model 7090";
    String instruments_3_acronym "FID";
    String instruments_3_dataset_instrument_nid "769223";
    String instruments_3_description "A flame ionization detector (FID) is a scientific instrument that measures the concentration of organic species in a gas stream. It is frequently used as a detector in gas chromatography. Standalone FIDs can also be used in applications such as landfill gas monitoring, fugitive emissions monitoring and internal combustion engine emissions measurement in stationary or portable instruments.";
    String instruments_3_instrument_name "Flame Ionization Detector";
    String instruments_3_instrument_nid "644600";
    String instruments_3_supplied_name "Agilent 7980A";
    String instruments_4_acronym "Seal Analytical AutoAnalyser 3HR";
    String instruments_4_dataset_instrument_nid "769224";
    String instruments_4_description "A fully automated Segmented Flow Analysis (SFA) system, ideal for water and seawater analysis. It comprises a modular system which integrates an autosampler, peristaltic pump, chemistry manifold and detector. The sample and reagents are pumped continuously through the chemistry manifold, and air bubbles are introduced at regular intervals forming reaction segments which are mixed using glass coils. The AA3 uses segmented flow analysis principles to reduce inter-sample dispersion, and can analyse up to 100 samples per hour using stable LED light sources.";
    String instruments_4_instrument_name "Seal Analytical AutoAnalyser 3HR";
    String instruments_4_instrument_nid "765117";
    String instruments_4_supplied_name "SEAL Analytics autoanalyzer model 3 HR";
    String keywords "bco, bco-dmo, biological, C2H4, cast, ch4, chemical, cruise, data, dataset, date, depth, dmo, erddap, iso, latitude, lln, longitude, management, nox, oceanography, office, phosphate, po4, preliminary, srp, station, tdp, time";
    String license "https://www.bco-dmo.org/dataset/769203/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/769203";
    Float64 Northernmost_Northing 40.4025;
    String param_mapping "{'769203': {'Latitude': 'flag - latitude', 'Depth': 'flag - depth', 'Longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/769203/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Daniel J. Repeta";
    String people_0_person_nid "50621";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Hawaii at Manoa";
    String people_1_affiliation_acronym "SOEST";
    String people_1_person_name "David M. Karl";
    String people_1_person_nid "50750";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Hawaii at Manoa";
    String people_2_affiliation_acronym "SOEST";
    String people_2_person_name "Oscar A. Sosa";
    String people_2_person_nid "769207";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Shannon Rauch";
    String people_3_person_nid "51498";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "PHAT";
    String projects_0_acronym "PHAT";
    String projects_0_description 
"NSF Award Abstract:
The \"marine methane paradox\" refers to observations of high concentrations of methane in surface waters of the ocean, even though these waters are well-oxygenated and high in sulfate, both features which generally do not favor the production of methane. This project aims to elucidate on the cause of this paradox. Based on preliminary results, the investigator identified the potential for methane production stimulated by microbial cycling of dissolved organic matter. Polysaccharides (carbonates such as starch) are a major component of high molecular weight dissolved organic matter (HMWDOM) and they can incorporate esters of methylphosphonate, which may be allowing for the production of methane in surface waters. When these HMWDOM polysaccharides were introduced to seawater samples, the researchers saw production of methane with an anomalous stable carbon isotope ratio comparable to what is seen in the paradoxical surface waters enriched in methane. By making measurements of trace gases, HMWDOM phosphonate, and stable carbon isotope measurements in the western North Atlantic Ocean, the investigator and his collaborators will reassess the preliminary data and the implications of these results for the entire oceanographic cycling of methane. Both educational and outreach efforts have been included. For the educational component, a postdoc, a graduate student, and summer undergraduate students will be work on the project, whereas for the outreach activities, the proponent plans to develop curricula on basic science and oceanography for high school students, include a high school teacher in the research cruise, and integrate results into an organic geochemistry course, the lectures of which will be publically available online.
This project seeks to evaluate the possibility that the \"marine methane paradox\", or the super-saturation of methane in high sulfate, well-oxygenated surface waters, is caused by microbial cycling of dissolved organic matter (DOM). There has been a great deal of preliminary evidence to support this theory. For example, samples from station ALOHA were amended with purified high molecular weight DOM (HMWDOM) polysaccharides, and methane, ethylene, and propylene productions were stimulated. HMWDOM polysaccharides incorporate esters of methylphosphonate (MPn), 2-hydroxyethylphosphonates (2-HEP), and other minor phosphonates, which are likely facilitating the production of methane, ethylene, and propylene. Carbon isotope data supports that this theory is the process behind the marine methane paradox; the d13C value of methane produced from HMWDOM polysaccharide enriched samples agrees well with the anomalous value associated with the super-saturated surface water. Only a small fraction of HMWDOM polysaccharides can easily explain the marine methane paradox, and this process could just as easily fully revise the current understanding of large scale methane cycling between the ocean and atmosphere. The researchers will assess the preliminary evidence and evaluate the microbial DOM cycling theory by making paired trace gas and HMWDOM phosphonate, as well as stable carbon isotope measurements in the western North Atlantic Ocean.";
    String projects_0_end_date "2019-08";
    String projects_0_geolocation "Sargasso Sea, Western North Atlantic Ocean";
    String projects_0_name "Methane, Ethylene, and Dissolved Organic Phosphorus Cycling in the Western North Atlantic Ocean";
    String projects_0_project_nid "765014";
    String projects_0_start_date "2016-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 29.05817;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "Cruise";
    String summary "Concentration measurements of water column phosphate, nitrate and nitrite, dissolved organic phosphorus, methane, and ethylene from samples collected during the R/V Niel Armstrong cruise AR16 in the western North Atlantic Ocean in May 2017. Seawater was collected from Niskin bottles deployed on a rosette with a CTD.";
    String time_coverage_end "2017-05-20T16:41:58Z";
    String time_coverage_start "2017-05-04T14:35:52Z";
    String title "Concentration measurements of water column phosphate, nitrate and nitrite, dissolved organic phosphorus, methane, and ethylene from samples collected during the R/V Neil Armstrong cruise AR16 in the western North Atlantic Ocean in May 2017";
    String version "2";
    Float64 Westernmost_Easting -71.33867;
    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
For example,
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.

ERDDAP, Version 2.02
Disclaimers | Privacy Policy | Contact