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

ERDDAP > tabledap > Data Access Form ?

Dataset Title:  ASPIRE station data used to develop 1-D and 3-D numerical models from the
Nathaniel B. Palmer in the Amundsen Sea from 2010-12-14 through 2011-01-05
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_765081)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 Station (unitless) ?          5    66
 latitude (degrees_north) ?          -73.97    -72.72
  < slider >
 longitude (degrees_east) ?          -118.03    -112.0
  < slider >
 LocalDate (unitless) ?              
 depth (m) ?          0.754120210610568    199.838
  < slider >
 Chla (miligram per meter cubed (mg m-3)) ?          0.019042985422406    21.7872622257445
 DissFe (milimole per meter cubed (mmol m-3)) ?          0.0681900013988428    0.442996041975175
 TotalDIN (milimole per meter cubed (mmol m-3)) ?          7.3131    32.6
 PON (mmol m-3) ?          0.0470999603174603    11.5051108730159
Server-side Functions ?
 distinct() ?
? (" ")

File type: (more info)

(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 {
    Byte _FillValue 127;
    Byte actual_range 5, 66;
    String description "ASPIRE station identifier";
    String ioos_category "Identifier";
    String long_name "Station";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -73.97, -72.72;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude with north values positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "lats";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -118.03, -112.0;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude with east values positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "lons";
    String standard_name "longitude";
    String units "degrees_east";
  LocalDate {
    String description "Date of ASPIRE sampling in yyyy-mm-dd format";
    String ioos_category "Time";
    String long_name "Local Date";
    String source_name "LocalDate";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.7541202106105679, 199.838;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth of sampling";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  Chla {
    Float64 _FillValue NaN;
    Float64 actual_range 0.019042985422406, 21.7872622257445;
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "Chlorophyll a concentration";
    String ioos_category "Ocean Color";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "miligram per meter cubed (mg m-3)";
  DissFe {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0681900013988428, 0.442996041975175;
    String description "Particulate organic nitrogen.";
    String ioos_category "Unknown";
    String long_name "Diss Fe";
    String units "milimole per meter cubed (mmol m-3)";
  TotalDIN {
    Float32 _FillValue NaN;
    Float32 actual_range 7.3131, 32.6;
    String description "Total dissolved inorganic nitrogen";
    String ioos_category "Unknown";
    String long_name "Total DIN";
    String units "milimole per meter cubed (mmol m-3)";
  PON {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0470999603174603, 11.5051108730159;
    String description "Particulate organic nitrogen.";
    String ioos_category "Unknown";
    String long_name "PON";
    String units "mmol m-3";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Dissolved inorganic nutrient samples were pre-filtered through 0.45-\\u03bcm
polycarbonate syringe filters, kept refrigerated, and analyzed onboard the
ship within 1 day of sampling. Nitrate (NO3\\u2212), nitrite (NO2\\u2212), am-
monium (NH4+), phosphate (HPO42\\u2212), and silicic acid (Si(OH)4) were
measured using a five-channel Lachat Instruments QuikChem FIA+ 8000s series
autoanalyzer in conjunction with a Lachat Instruments XYZ AutoSampler (ASX-500
Series), two Lachat Instruments RP-100 Series peristaltic Reagent Pumps, and
Omnion Software, version\\u00a0
Seawater samples were analyzed for dissolved Fe over the period of January to
August 2012, using an automated flow injection ICP-MS method developed at
Rutgers University (Lagerstr\\u00f6m et al., 2013). Briefly, the automated
device loaded a 9 mL aliquot of seawater, buffered online to pH 7.0 with 3 mL
of acetic acid/ammonium hydroxide buffer, onto a column packed with Nobias PA1
chelating resin (Hitachi High-Technologies). The column was eluted with 1.5 M
nitric acid directly into the nebulizer of an Element-1 sector field ICP-MS
(Thermo-Finnigan, Bremen, Germany). The eluate, a 200-fold concentrate of the
sample, was analyzed in medium resolution and temporal peak integration was
performed in Matlab using a script written in-house. Quantification was
carried out using isotope dilution (Fe, Ni, Cu and Zn) or a matrix-matched
external standard curve (Mn).\\u00a0
Samples for particulate organic carbon (POC) and nitrogen (PN) were collected
by cleanly filtering 100\\u2013600 mL of seawater onto a 25-mm diameter,
combusted GF/F filter (nominal pore size of 0.7 \\u03bcm) which was then folded
sample side in and frozen at \\u221280\\u00b0C. Samples were processed at
Rutgers University and analyzed using a Carlo-Erba CHN analyzer (Hedges and
Stern, 1984).\\u00a0
Water column Chl a concentration (used as a proxy for algal biomass) was
measured onboard ship using acetone extraction and a spectrofluorometer
(Alderkamp et al., 2015). Shipboard values were calibrated against a second
set of samples collected similarly, flash-frozen in liquid N2, stored at
\\u221280\\u00b0C, and analyzed at Mote Marine Lab using HPLC (Wright et al.,
1991; see Alderkamp et al., 2015).";
    String awards_0_award_nid "54676";
    String awards_0_award_number "ANT-0839069";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0839069";
    String awards_0_funder_name "NSF Antarctic Sciences";
    String awards_0_funding_acronym "NSF ANT";
    String awards_0_funding_source_nid "369";
    String awards_0_program_manager "Dr Peter Milne";
    String awards_0_program_manager_nid "51468";
    String awards_1_award_nid "54969";
    String awards_1_award_number "ANT-0944727";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0944727";
    String awards_1_funder_name "NSF Antarctic Sciences";
    String awards_1_funding_acronym "NSF ANT";
    String awards_1_funding_source_nid "369";
    String awards_1_program_manager "Dr Peter Milne";
    String awards_1_program_manager_nid "51468";
    String awards_2_award_nid "54970";
    String awards_2_award_number "ANT-0839012";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0839012";
    String awards_2_funder_name "NSF Antarctic Sciences";
    String awards_2_funding_acronym "NSF ANT";
    String awards_2_funding_source_nid "369";
    String awards_2_program_manager "Dr Diana Nemergut";
    String awards_2_program_manager_nid "51502";
    String awards_3_award_nid "54971";
    String awards_3_award_number "ANT-0838995";
    String awards_3_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0838995";
    String awards_3_funder_name "NSF Antarctic Sciences";
    String awards_3_funding_acronym "NSF ANT";
    String awards_3_funding_source_nid "369";
    String awards_3_program_manager "Dr Peter Milne";
    String awards_3_program_manager_nid "51468";
    String awards_4_award_nid "54972";
    String awards_4_award_number "ANT-0838975";
    String awards_4_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0838975";
    String awards_4_funder_name "NSF Antarctic Sciences";
    String awards_4_funding_acronym "NSF ANT";
    String awards_4_funding_source_nid "369";
    String awards_4_program_manager "Dr Peter Milne";
    String awards_4_program_manager_nid "51468";
    String awards_5_award_nid "713341";
    String awards_5_award_number "OPP-1443657";
    String awards_5_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1443657";
    String awards_5_funder_name "NSF Office of Polar Programs (formerly NSF PLR)";
    String awards_5_funding_acronym "NSF OPP";
    String awards_5_funding_source_nid "713360";
    String awards_5_program_manager "Dr Peter Milne";
    String awards_5_program_manager_nid "51468";
    String awards_6_award_nid "713354";
    String awards_6_award_number "OPP-1443604";
    String awards_6_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1443604";
    String awards_6_funder_name "NSF Office of Polar Programs (formerly NSF PLR)";
    String awards_6_funding_acronym "NSF OPP";
    String awards_6_funding_source_nid "713360";
    String awards_6_program_manager "Dr Peter Milne";
    String awards_6_program_manager_nid "51468";
    String awards_7_award_nid "713355";
    String awards_7_award_number "OPP-1443315";
    String awards_7_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1443315";
    String awards_7_funder_name "NSF Office of Polar Programs (formerly NSF PLR)";
    String awards_7_funding_acronym "NSF OPP";
    String awards_7_funding_source_nid "713360";
    String awards_7_program_manager "Dr Peter Milne";
    String awards_7_program_manager_nid "51468";
    String awards_8_award_nid "713356";
    String awards_8_award_number "OPP-1443569";
    String awards_8_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1443569";
    String awards_8_funder_name "NSF Office of Polar Programs (formerly NSF PLR)";
    String awards_8_funding_acronym "NSF OPP";
    String awards_8_funding_source_nid "713360";
    String awards_8_program_manager "Dr Peter Milne";
    String awards_8_program_manager_nid "51468";
    String cdm_data_type "Other";
    String comment 
"ASPIRE station data used to develop 1-D and 3-D numerical models from the Nathaniel B. Palmer in the Amundsen Sea from 2010-12-14 through 2011-01-05 
  PI: Patricia L. Yager 
  Version: 2019-04-17";
    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 2.2d  13 Jun 2019";
    String date_created "2019-04-17T18:32:58Z";
    String date_modified "2019-04-17T20:15:36Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.765081.1";
    Float64 Easternmost_Easting -112.0;
    Float64 geospatial_lat_max -72.72;
    Float64 geospatial_lat_min -73.97;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -112.0;
    Float64 geospatial_lon_min -118.03;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 199.838;
    Float64 geospatial_vertical_min 0.7541202106105679;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2019-10-20T00:20:43Z (local files)
2019-10-20T00:20:43Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_765081.html";
    String infoUrl "https://www.bco-dmo.org/dataset/765081";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "24 � 10 L Niskin bottle rosette sampler (General Oceanics)";
    String instruments_0_dataset_instrument_nid "765099";
    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 bottle";
    String instruments_1_acronym "Nutrient Autoanalyzer";
    String instruments_1_dataset_instrument_description "Nitrate (NO3−), nitrite (NO2−), am- monium (NH4+), phosphate (HPO42−), and silicic acid (Si(OH)4) were measured using a five-channel Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer in conjunction with a Lachat Instruments XYZ AutoSampler (ASX-500 Series)";
    String instruments_1_dataset_instrument_nid "765100";
    String instruments_1_description "Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified.  In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB04/";
    String instruments_1_instrument_name "Nutrient Autoanalyzer";
    String instruments_1_instrument_nid "558";
    String instruments_1_supplied_name "Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer";
    String instruments_2_acronym "CTD SBE 911plus";
    String instruments_2_dataset_instrument_description "Hydrographic profiles and discrete water samples were collected from each station using a conventional shipboard conductivity-temperature-depth (CTD; Sea-Bird 911+) sensor.";
    String instruments_2_dataset_instrument_nid "765098";
    String instruments_2_description "The Sea-Bird SBE 911plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure.  The SBE 911plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9plus and SBE 11plus is called a SBE 911plus.  The SBE 9plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3plus and SBE 4). The SBE 9plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0058/";
    String instruments_2_instrument_name "CTD Sea-Bird SBE 911plus";
    String instruments_2_instrument_nid "591";
    String instruments_2_supplied_name "Sea-Bird 911+";
    String instruments_3_acronym "CHN_EA";
    String instruments_3_dataset_instrument_description "Samples were processed at Rutgers University and analyzed using a Carlo-Erba CHN analyzer (Hedges and Stern, 1984).";
    String instruments_3_dataset_instrument_nid "765101";
    String instruments_3_description "A CHN Elemental Analyzer is used for the determination of carbon, hydrogen, and  nitrogen content in organic and other types of materials, including  solids, liquids, volatile, and viscous samples.";
    String instruments_3_instrument_name "CHN Elemental Analyzer";
    String instruments_3_instrument_nid "625";
    String instruments_3_supplied_name "Carlo-Erba CHN analyzer";
    String keywords "bco, bco-dmo, biological, chemical, chemistry, Chla, chlorophyll, chlorophyll-a, color, concentration, concentration_of_chlorophyll_in_sea_water, data, dataset, date, depth, din, diss, DissFe, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, identifier, latitude, local, longitude, management, ocean, ocean color, oceanography, oceans, office, pon, preliminary, science, sea, seawater, station, time, total, TotalDIN, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/765081";
    Float64 Northernmost_Northing -72.72;
    String param_mapping "{'765081': {'Depth': 'flag - depth', 'lons': 'flag - longitude', 'lats': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/765081/parameters";
    String people_0_affiliation "University of Georgia";
    String people_0_affiliation_acronym "UGA";
    String people_0_person_name "Patricia L. Yager";
    String people_0_person_nid "51130";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Rutgers University";
    String people_1_person_name "Robert M. Sherrell";
    String people_1_person_nid "50919";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Georgia";
    String people_2_affiliation_acronym "UGA";
    String people_2_person_name "Hilde Oliver";
    String people_2_person_nid "765085";
    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 "Mathew Biddle";
    String people_3_person_nid "708682";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Collaborative Research: Investigating the Role of Mesoscale Processes and Ice Dynamics in Carbon and Iron Fluxes in a Changing Amundsen Sea (INSPIRE)";
    String projects_0_acronym "INSPIRE";
    String projects_0_description 
"The Amundsen Sea, in the remote Pacific sector of the Southern Ocean, is one of the least well studied Antarctic continental shelf regions. It shares characteristics in common with other Antarctic ice shelf regions, but exhibits unique aspects also. The Amundsen Sea Polynya (ASP), an open region at the base of several of the terminal glaciers draining the West Antarctic Ice sheet exhibits: 1) large intrusions of heat delivered from the warming modified circumpolar deep water (mCDW) rising up onto the continental shelf, 2) the fastest melting ice sheets in Antarctica, 3) the most productive coastal polynya (161 g C m-2) together with a significant atmospheric CO2 sink, and 4) some of the most rapidly declining regions of seasonal off-shore sea ice on Earth.
Following on from an earlier oceanographic field program, the Amundsen Sea Polynya International Research Expedition (ASPIRE; 2011), this study seeks to better synthesize and model the relative contributions of both physical ocean-ice linkages and biological production and carbon export terms and to compare these with other circumpolar Antarctic regions. A central feature will be the use of a regionally coupled physical-biogeochemical model to follow the dynamics of the large phytoplankton blooms that occur annually in the Amundsen Sea Polyna. This study will provides a means to locate the Amundsen Sea properties along the continuum of Antarctic ice shelf systems, and to understand how these system might change in response to climate change.
Pedagogical techniques will be used to provide educational outreach for three distinct target populations: secondary students, pre-service science teachers, and in-service science teachers. Partnerships will be developed with science teacher educators to implement the STEM career-development lessons in undergraduate and graduate level science teacher education courses.";
    String projects_0_end_date "2018-06";
    String projects_0_geolocation "The study area is the continental shelf of the Amundsen Sea, Antarctica, 71-75S, 100-130W.";
    String projects_0_name "Collaborative Research: Investigating the Role of Mesoscale Processes and Ice Dynamics in Carbon and Iron Fluxes in a Changing Amundsen Sea (INSPIRE)";
    String projects_0_project_nid "713342";
    String projects_0_start_date "2015-07";
    String publisher_name "Mathew Biddle";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -73.97;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Hydrographic profiles and discrete water samples were collected from each station using a conventional shipboard conductivity-temperature-depth (CTD; Sea-Bird 911+) sensor and a 24 \\u00d7 10 L Niskin bottle rosette sampler (General Oceanics). Potential temperature (\\u03b8) and salinity (S) were recorded continuously as a function of depth and at the moment of Niskin bottle closure (see Yager et al., 2016).\\r\\n\\r\\nTrace-metal samples were collected similarly using a trace-metal-clean CTD-rosette system (see Sherrell et al., 2015) that was deployed at the same location just before or after the conventional CTD.";
    String title "ASPIRE station data used to develop 1-D and 3-D numerical models from the Nathaniel B. Palmer in the Amundsen Sea from 2010-12-14 through 2011-01-05";
    String version "1";
    Float64 Westernmost_Easting -118.03;
    String xml_source "osprey2erddap.update_xml() v1.5-beta";


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 1.82
Disclaimers | Privacy Policy | Contact