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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  [Dissolved phenols] - Concentrations of dissolved organic carbon and phenols
from Polarstern cruise PS 94-ARK-XXIX/3 from August to October
2015 (Development and application of a high sensitivity, ultra low volume
method to measure biomarkers of terrigenous organic matter in the open ocean)
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_767285)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Station (unitless) ?          4    157
 Cast (unitless) ?          1    9
 Bottle (unitless) ?          1    24
 time (Date Time UTC, UTC) ?          2015-08-20T00:45Z    2015-10-07T20:43Z
  < slider >
 latitude (degrees_north) ?          73.2525    89.1667
  < slider >
 longitude (degrees_east) ?          -179.9473    179.8463
  < slider >
 depth (m) ?          7.3    4000.9
  < slider >
 Temp (Temperature, degrees Celsius) ?          -1.7956    7.2796
 Salinity (PSU) ?          27.2066    35.158
 DOC (micromoles per liter (umol/L)) ?          40.6    146.4
 Phenols (picomoles per liter (pmol/L)) ?          0.0    19823.5
 
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.Hover here to see a list of options. Click on an option to select it.")

File type: (more information)

(Documentation / Bypass this form ? )
 
(Please be patient. It may take a while to get the data.)


 

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Station {
    Int16 _FillValue 32767;
    Int16 actual_range 4, 157;
    String bcodmo_name "station";
    String description "Station";
    String long_name "Station";
    String units "unitless";
  }
  Cast {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 9;
    String bcodmo_name "cast";
    String description "Cast";
    String long_name "Cast";
    String units "unitless";
  }
  Bottle {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 24;
    String bcodmo_name "bottle";
    String description "Bottle";
    String long_name "Bottle";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4400315e+9, 1.44425058e+9;
    String axis "T";
    String bcodmo_name "unknown";
    String description "Date and time (UTC); format: yyyy-mm-ddTHH:MM";
    String ioos_category "Time";
    String long_name "Date Time UTC";
    String source_name "Date_Time_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 73.2525, 89.1667;
    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 -179.9473, 179.8463;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude east (postive values = 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 7.3, 4000.9;
    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";
  }
  Temp {
    Float32 _FillValue NaN;
    Float32 actual_range -1.7956, 7.2796;
    String bcodmo_name "temperature";
    String description "Temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  Salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 27.2066, 35.158;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Salinity";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "PSU";
  }
  DOC {
    Float32 _FillValue NaN;
    Float32 actual_range 40.6, 146.4;
    String bcodmo_name "DOC";
    String description "DOC";
    String long_name "DOC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGZZZX/";
    String units "micromoles per liter (umol/L)";
  }
  Phenols {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 19823.5;
    String bcodmo_name "unknown";
    String description "Phenols";
    String long_name "Phenols";
    String units "picomoles per liter (pmol/L)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Samples were filtered straight from Niskin bottles following established
protocols for trace-metal clean sampling (Sample handling protocols for
GEOTRACES cruises).
 
Samples for DOC concentration were acidified to pH 2.5 and analyzed by high-
temperature combustion on a Shimadzu TOC-L. DOC was calculated as the mean of
between three and five injections using a six-point standard curve.
 
Lignin-derived phenols were determined following Yan and Kaiser (2018; Anal.
Chem), and Yan and Kaiser (2018; Analytica Chimica Acta). Briefly, C18
extracts were redissolved in 200 \\u03bcL of 1.1 mol L\\u22121 argon- sparged
(10 min) NaOH in a 400 uL Teflon vial (Savillex Corp) and amended with
containing 500 mg CuO, and amended with 10\\u03bcL of10 mmolL\\u22121 CuSO4 and
10\\u03bc L of 0.2 molL\\u22121 ascorbic acid. Oxidation was at 150 C for 120
minutes. Following oxidation, the samples were spiked with with a surrogate
standard mixture of p- hydroxybenzoic acid-13C7, vanillin-13C6, and
syringaldehyde-13C6 and acidified to pH \\u2248 2.5 with 6 mol L\\u22121
sulfuric acid in the reaction vials.\\u00a0 Clean-up of samples was performed
with Waters HLB cartrides and final sample eluates were dried under ultra-high
purity argon. Phenols were quantified by liquid chromatography/electrospray
ionization-tandem mass spectrometry using a five-point calibration curve
bracketing the concentration range. Quantified phenols (TDLP included
vanillin, acetovanillone, vanillic acid, syringaldehyde, acetosyringone,
syringic acid, coumaric acid, ferulic acid, p-hydroxy-benzaldehyde, p-hydroxy-
acetophenone, and p-hydroxy-benzoic acid.
 
Samples were filtered straight from Niskin bottles following established
protocols for trace-metal clean sampling (Sample handling protocols for
GEOTRACES cruises)
 
Samples for DOC concentration were acidified to pH 2.5 and analyzed by high-
temperature combustion on a Shimadzu TOC-L. DOC was calculated as the mean of
between three and five injections using a six-point standard curve.
 
Lignin-derived phenols were determined following Yan and Kaiser (2018; Anal.
Chem), and Yan and Kaiser (2018; Analytica Chimica Acta). Briefly, C18
extracts were redissolved in 200 \\u03bcL of 1.1 mol L\\u22121 argon- sparged
(10 min) NaOH in a 400 uL Teflon vial (Savillex Corp) and amended with
containing 500 mg CuO, and amended with 10\\u03bcL of10 mmolL\\u22121 CuSO4 and
10\\u03bc L of 0.2 molL\\u22121 ascorbic acid. Oxidation was at 150 C for 120
minutes. Following oxidation, the samples were spiked with with a surrogate
standard mixture of p- hydroxybenzoic acid-13C7, vanillin-13C6, and
syringaldehyde-13C6 and acidified to pH \\u2248 2.5 with 6 mol L\\u22121
sulfuric acid in the reaction vials.\\u00a0 Clean-up of samples was performed
with Waters HLB cartrides and final sample eluates were dried under ultra-high
purity argon. Phenols were quantified by liquid chromatography/electrospray
ionization-tandem mass spectrometry using a five-point calibration curve
bracketing the concentration range. Quantified phenols: TDLP included
vanillin, acetovanillone, vanillic acid, syringaldehyde, acetosyringone,
syringic acid, coumaric acid, ferulic acid, p-hydroxy-benzaldehyde, p-hydroxy-
acetophenone, and p-hydroxy-benzoic acid.";
    String awards_0_award_nid "763578";
    String awards_0_award_number "OCE-1536506";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1536506";
    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 "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Dissolved phenols for Polarstern cruise PS94 ARK-XXIX/3 
  PI: Karl Kaiser (TAMU) 
  Version date: 10-May-2019";
    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 "2019-05-10T17:14:03Z";
    String date_modified "2019-06-04T19:19:57Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.767285.1";
    Float64 Easternmost_Easting 179.8463;
    Float64 geospatial_lat_max 89.1667;
    Float64 geospatial_lat_min 73.2525;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.8463;
    Float64 geospatial_lon_min -179.9473;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 4000.9;
    Float64 geospatial_vertical_min 7.3;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-21T08:41:34Z (local files)
2024-11-21T08:41:34Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_767285.html";
    String infoUrl "https://www.bco-dmo.org/dataset/767285";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "767339";
    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_nid "767346";
    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 "liquid chromatography/electrospray ionization-tandem mass spectrometry";
    String instruments_2_acronym "Shimadzu TOC-L";
    String instruments_2_dataset_instrument_nid "767340";
    String instruments_2_description 
"A Shimadzu TOC-L Analyzer measures DOC by high temperature combustion method.

Developed by Shimadzu, the 680 degree C combustion catalytic oxidation method is now used worldwide. One of its most important features is the capacity to efficiently oxidize hard-to-decompose organic compounds, including insoluble and macromolecular organic compounds. The 680 degree C combustion catalytic oxidation method has been adopted for the TOC-L series.

http://www.shimadzu.com/an/toc/lab/toc-l2.html";
    String instruments_2_instrument_external_identifier "http://onto.nerc.ac.uk/CAST/124.html";
    String instruments_2_instrument_name "Shimadzu TOC-L Analyzer";
    String instruments_2_instrument_nid "527277";
    String instruments_2_supplied_name "Shimadzu TOC-L";
    String keywords "bco, bco-dmo, biological, bottle, cast, chemical, commerce, data, dataset, date, density, department, depth, Depth_water, dmo, doc, earth, Earth Science > Oceans > Salinity/Density > Salinity, erddap, latitude, longitude, management, ocean, oceanography, oceans, office, phenols, practical, preliminary, salinity, science, sea, sea_water_practical_salinity, seawater, station, Temp, temperature, time, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/767285/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/767285";
    Float64 Northernmost_Northing 89.1667;
    String param_mapping "{'767285': {'Depth_water': 'flag - depth', 'Latitude': 'flag - latitude', 'Date_Time_UTC': 'flag - time', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/767285/parameters";
    String people_0_affiliation "Texas A&M, Galveston";
    String people_0_affiliation_acronym "TAMUG";
    String people_0_person_name "Karl Kaiser";
    String people_0_person_nid "732803";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Shannon Rauch";
    String people_1_person_nid "51498";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Lignin phenol method development";
    String projects_0_acronym "Lignin phenol method development";
    String projects_0_description 
"NSF Award Abstract:
The distribution and fate of land-derived, or terrigenous, organic matter in the ocean has long been of interest to oceanographers, but that interest has grown considerably as research on the marine and global carbon cycle intensifies. Lignin is a major structural polymer found only in vascular plants, making lignin a unique tracer of terrigenous organic matter input to the marine environment. The current analytical tool for analyzing lignin, breaking it into a suite of identifiable phenolic compounds, is complex, time consuming and requires 10 to 30 liters of water. Given these limitations, applications of lignin phenols as tracers of terrestrial organic carbon in the ocean have been sparse. Through this project, the researchers aim to redesign existing chemical methodology together with modified instrumental detection for even 3 times greater sensitivity using a sample of less than 200 milliliters. Outfitting the scientific community with new methodology to sensitively trace this marker of terrigenous organic carbon will provide a clearer understanding of organic matter fluxes between and within terrestrial and oceanic reservoirs, and potentially establish lignin phenols as a robust oceanographic tracer. This project will support the development of the next generation of scientists, including an early career investigator, and graduate and undergraduate students.
Lignin phenol measurements have been used to study general distribution patterns and mechanisms of decomposition of terrigenous dissolved organic carbon (tDOC) in the global ocean. The distribution pattern of tDOC among ocean basins is generally consistent with the global pattern of riverine discharge to the ocean basins. However, large scale generalizations required and more fully resolved distributions of lignin as a tracer of tDOC are hampered by the difficulties and limitations associated with the present lignin phenol method. The main objectives of this project are to (1) develop methodology for measuring dissolved lignin in ultra-low volumes at high sensitivity in open ocean seawater and (2) apply the new method to study terrigenous tDOC processing and transport in the Eurasian Basin of the Arctic Ocean, where large Siberian rivers deliver the bulk of tDOC to the shelf areas. Results from this research will help evaluate lignin phenols as robust oceanographic tracers, useful to study physical mixing in the Arctic Ocean and potentially improve our understanding of the fate and removal of terrigenous organic carbon in the oceans. Addressing the second objective would provide well-constrained decay constants for lignin and tDOC in the Arctic Ocean and provide novel information on halocline formation. Integration of tDOC budgets, freshwater budgets, and circulation and atmospheric patterns will ultimately improve understanding of biogeochemical cycles in the Arctic Ocean and its role in global climate.";
    String projects_0_end_date "2018-12";
    String projects_0_geolocation "Arctic Ocean";
    String projects_0_name "Development and application of a high sensitivity, ultra low volume method to measure biomarkers of terrigenous organic matter in the open ocean";
    String projects_0_project_nid "763579";
    String projects_0_start_date "2016-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 73.2525;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Concentrations of dissolved organic carbon and phenols from Polarstern cruise PS 94-ARK-XXIX/3 from August to October 2015.";
    String time_coverage_end "2015-10-07T20:43Z";
    String time_coverage_start "2015-08-20T00:45Z";
    String title "[Dissolved phenols] - Concentrations of dissolved organic carbon and phenols from Polarstern cruise PS 94-ARK-XXIX/3 from August to October 2015 (Development and application of a high sensitivity, ultra low volume method to measure biomarkers of terrigenous organic matter in the open ocean)";
    String version "1";
    Float64 Westernmost_Easting -179.9473;
    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.


 
ERDDAP, Version 2.22
Disclaimers | Privacy Policy | Contact