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Dataset Title:  Basic CTD hydrography data collected during R/V Savannah cruises conducted in
the South Atlantic Bight off the coast of Georgia from 2015-2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_815732)
Range: longitude = -81.12151 to -76.33408°E, latitude = 31.005318 to 31.865276°N, depth = 1.0 to 254.0m, time = 2015-03-16T15:56:47Z to 2017-01-27T20:46:05Z
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 {
  Cruise_ID {
    String bcodmo_name "cruise_id";
    String description "Cruise ID number";
    String long_name "Cruise ID";
    String units "unitless";
  }
  Cast_ID {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 314;
    String bcodmo_name "cast";
    String description "Cast ID number";
    String long_name "Cast ID";
    String units "unitless";
  }
  Station_ID {
    String bcodmo_name "station";
    String description "Station ID number";
    String long_name "Station ID";
    String units "unitless";
  }
  UTC_Date {
    String bcodmo_name "date";
    String description "Date (UTC); format: MM/DD/YYYY";
    String long_name "UTC Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  UTC_Time {
    String bcodmo_name "time";
    String description "Time (UTC); format: hh:mm:ss";
    String long_name "UTC Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.426521407e+9, 1.485549965e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and time (UTC) formatted to ISO8601 standard: YYYY-MM-DDThh:mm:ssZ";
    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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 31.005317, 31.865276;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    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 -81.121513, -76.334083;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    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 1.0, 254.0;
    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";
  }
  Strain_Gauge_Pressure {
    Float32 _FillValue NaN;
    Float32 actual_range 1.461, 371.188;
    String bcodmo_name "pressure";
    String description "Pressure";
    String long_name "Strain Gauge Pressure";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
    String units "psi";
  }
  Conductivity {
    Float64 _FillValue NaN;
    Float64 actual_range -0.783839, 81.265259;
    String bcodmo_name "conductivity";
    Float64 colorBarMaximum 40.0;
    Float64 colorBarMinimum 30.0;
    String description "Conductivity";
    String long_name "Sea Water Electrical Conductivity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
    String units "millisiemens per centimeter (mS/cm)";
  }
  Salinity {
    Float32 _FillValue NaN;
    Float32 actual_range -0.6235, 50.4499;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Salinty";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "PSU";
  }
  Temperature {
    Float64 _FillValue NaN;
    Float64 actual_range 8.46, 58.276982;
    String bcodmo_name "temperature";
    String description "Water temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  Potential_Temp {
    Float32 _FillValue NaN;
    Float32 actual_range 8.4334, 36.335;
    String bcodmo_name "potemp";
    String description "Potential temperature";
    String long_name "Potential Temp";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/POTMCV01/";
    String units "degrees Celsius";
  }
  Density {
    Float64 _FillValue NaN;
    Float64 actual_range 28.1058, 1035.8587;
    String bcodmo_name "density";
    String description "density";
    String long_name "Density";
    String units "kilograms per cubic meter (kg/m^3)";
  }
  Sigma_theta {
    Float32 _FillValue NaN;
    Float32 actual_range -3.9216, 35.8509;
    String bcodmo_name "sigma_theta";
    String description "Sigma theta density";
    String long_name "Sea Water Sigma Theta";
    String units "kilograms per cubic meter (kg/m^3)";
  }
  Oxygen_mLL {
    Float64 _FillValue NaN;
    Float64 actual_range -0.8435, 1023.4389;
    String bcodmo_name "dissolved Oxygen";
    String description "Oxygen concentration";
    String long_name "Oxygen M LL";
    String units "milliliters per liter (ml/l)";
  }
  Oxygen_pcnt {
    Float32 _FillValue NaN;
    Float32 actual_range -18.651, 217.53;
    String bcodmo_name "O2sat";
    String description "Oxygen percent saturation";
    String long_name "Oxygen Pcnt";
    String units "unitless (percent)";
  }
  PAR_Irradiance {
    Float32 _FillValue NaN;
    Float32 actual_range -379.4, 2820.0;
    String bcodmo_name "PAR";
    String description "PAR irradiance";
    String long_name "PAR Irradiance";
    String units "unitless";
  }
  ISUS {
    Float64 _FillValue NaN;
    Float64 actual_range -9.5045132, 97.974;
    String bcodmo_name "unknown";
    String description "Satlantic ISUS (nitrate sensor) measurement in volts";
    String long_name "ISUS";
    String units "volts";
  }
  flag {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 430.0;
    String bcodmo_name "flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "Flag";
    String long_name "Flag";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Data were collected using a\\u00a0Sea-Bird Scientific SBE 911 CTD carousel with
SBE-25 CTD and Satlantic ISUS.\\u00a0";
    String awards_0_award_nid "516650";
    String awards_0_award_number "OCE-1436458";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1436458";
    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 "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"CTD Hydrography 
   R/V Savannah cruises, 2015-2017 
  PI: Peter Lee (College of Charleston) 
  Version date: 19 June 2020";
    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 dataset_current_state "Final and no updates";
    String date_created "2020-06-18T19:23:38Z";
    String date_modified "2020-06-23T14:55:35Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.815732.1";
    Float64 Easternmost_Easting -76.334083;
    Float64 geospatial_lat_max 31.865276;
    Float64 geospatial_lat_min 31.005317;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -76.334083;
    Float64 geospatial_lon_min -81.121513;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 254.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-16T19:15:12Z (local files)
2024-04-16T19:15:12Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_815732.das";
    String infoUrl "https://www.bco-dmo.org/dataset/815732";
    String institution "BCO-DMO";
    String instruments_0_acronym "CTD SBE 25";
    String instruments_0_dataset_instrument_nid "815845";
    String instruments_0_description "The Sea-Bird SBE 25 SEALOGGER CTD is battery powered and is typically used to record data in memory, eliminating the need for a large vessel, electrical sea cable, and on-board computer. All SBE 25s can also operate in real-time, transmitting data via an opto-isolated RS-232 serial port. Temperature and conductivity are measured by the SBE 3F Temperature sensor and SBE 4 Conductivity sensor (same as those used on the premium SBE 9plus CTD). The SBE 25 also includes the SBE 5P (plastic) or 5T (titanium) Submersible Pump and TC Duct. The pump-controlled, TC-ducted flow configuration significantly reduces salinity spiking caused by ship heave, and in calm waters allows slower descent rates for improved resolution of water column features. Pressure is measured by the modular SBE 29 Temperature Compensated Strain-Gauge Pressure sensor (available in eight depth ranges to suit the operating depth requirement). The SBE 25's modular design makes it easy to configure in the field for a wide range of auxiliary sensors, including optional dissolved oxygen (SBE 43), pH (SBE 18 or SBE 27), fluorescence, transmissivity, PAR, and optical backscatter sensors. More information from Sea-Bird Electronics: http:www.seabird.com.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0040/";
    String instruments_0_instrument_name "CTD Sea-Bird 25";
    String instruments_0_instrument_nid "421";
    String instruments_0_supplied_name "SBE-25 CTD";
    String instruments_1_acronym "CTD SBE 911";
    String instruments_1_dataset_instrument_nid "815846";
    String instruments_1_description "The Sea-Bird SBE 911 is a type of CTD instrument package.  The SBE 911 includes the SBE 9 Underwater Unit and the SBE 11 Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 and SBE 11 is called a SBE 911.  The SBE 9 uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 and SBE 4). The SBE 9 CTD can be configured with 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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0035/";
    String instruments_1_instrument_name "CTD Sea-Bird 911";
    String instruments_1_instrument_nid "422";
    String instruments_1_supplied_name "Sea-Bird Scientific SBE 911 CTD carousel";
    String instruments_2_acronym "ISUS Nitrate";
    String instruments_2_dataset_instrument_nid "815847";
    String instruments_2_description "The Satlantic ISUS nitrate sensor is an in-situ UV absorption sensor which calculates nitrate concentration  from the seawater spectrum. The ISUS V2  has a 1cm path length, a 200-400 nm  wavelength range., and is depth rated to 1000 m. Satlantic's ISUS V3 nitrate sensor uses advanced UV absorption technology to measure  nitrate concentration in real-time.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0135/";
    String instruments_2_instrument_name "ISUS Nitrate sensor";
    String instruments_2_instrument_nid "618";
    String instruments_2_supplied_name "Satlantic ISUS";
    String keywords "available, bco, bco-dmo, biological, cast, Cast_ID, chemical, conductivity, cruise, Cruise_ID, data, dataset, date, density, depth, dmo, earth, Earth Science > Oceans > Salinity/Density > Conductivity, Earth Science > Oceans > Salinity/Density > Density, Earth Science > Oceans > Salinity/Density > Salinity, electrical, erddap, flag, gauge, irradiance, iso, isus, latitude, longitude, management, O2, ocean, oceanography, oceans, office, oxygen, Oxygen_mLL, Oxygen_pcnt, par, PAR_Irradiance, pcnt, photosynthetically, potential, Potential_Temp, practical, preliminary, pressure, radiation, salinity, science, sea, sea_water_electrical_conductivity, sea_water_practical_salinity, sea_water_sigma_theta, seawater, sigma, Sigma_theta, station, Station_ID, strain, Strain_Gauge_Pressure, temperature, theta, time, UTC_Date, UTC_Time, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/815732/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/815732";
    Float64 Northernmost_Northing 31.865276;
    String param_mapping "{'815732': {'Latitude': 'flag - latitude', 'Depth': 'flag - depth', 'Longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/815732/parameters";
    String people_0_affiliation "College of Charleston - Hollings Marine Lab";
    String people_0_affiliation_acronym "CoC-HML";
    String people_0_person_name "Peter Lee";
    String people_0_person_nid "516649";
    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 "B12 Impacts on DMSP";
    String projects_0_acronym "B12 Impacts on DMSP";
    String projects_0_description 
"Description from NSF award abstract:
Vitamin B12 and nitrogen are nutrients critical to phytoplankton growth. Since B12 is produced solely by bacteria, phytoplankton must acquire their B12 from bacteria. Nitrogen is used to produce the amino acid methionine and B12 is required by the enzymes that form methionine. Methionine is the precursor to the algal metabolite dimethylsulfoniopropionate (DMSP). Bacteria degrade this compound to the climatically-active compound dimethylsulfide (DMS). Subsequent DMS transfer into the atmosphere is considered a significant driver of cloud formation and a possible climate feedback mechanism. DMSP can also be degraded via a secondary pathway to form methylmercaptopropionate (MMPA), which is not released to the atmosphere. Consequently, DMSP formation and the extent of DMSP degradation to DMS or MMPA are susceptible to B12 availability. Nitrogen availability influences this effect by controlling methionine production. Thus, the overarching premise for this study is that B12 availability regulates oceanic DMSP and DMS formation, and is synergistically impacted by nitrogen limitation. By providing a mechanistic understanding of relevant biogeochemical parameters this study will significantly improve the incorporation of sulfur-related microbial processes into climate models.
This project will combine established biogeochemistry-based measurements with cutting-edge metabolomics, transcriptomics and proteomics techniques in laboratory and field studies. Culture experiments will examine the interactive effect of B12 and nitrogen availability on DMSP formation in several ecologically-relevant phytoplankton taxa. Second, the microbial degradation of DMSP and DMS in relation to B12 availability will be examined using several environmentally-important bacteria and archaea. Finally, field studies will examine the seasonal variability of B12, DMSP and DMS, and the relative importance of DMS and MMPA formation in the South Atlantic Bight. Gene and protein expression will be assessed at each level of this study to identify gene products, metabolic pathways, and cellular mechanisms underlying the interconnections between B12, sulfur, and nitrogen cycles. The results generated will have a major impact on current understanding of the role of B12 and nitrogen on the DMSP and DMS cycling, as well as the potential role of these stressors in global climate change. In addition to providing evidence for microbe-based mechanisms behind the modulation of oceanic DMS, this project will (1) furnish an explanation for \"summer DMS paradox\", thus having significant implications for the development of future DMS models, (2) assess the interactive impact of B12 and nitrogen availability on intracellular DMSP production and (3) provide insight as to whether B12 may play a far more critical role in modulating climate feedback mechanisms on phytoplankton productivity.";
    String projects_0_end_date "2019-01";
    String projects_0_geolocation "North Atlantic Ocean in the South Atlantic Bight off the coast of Georgia; Navy Op Area NA06";
    String projects_0_name "RUI: Vitamin B12 and nitrogen regulation of oceanic dimethylsulfoniopropionate and dimethylsulfide";
    String projects_0_project_nid "516651";
    String projects_0_start_date "2014-08";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 31.005317;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Basic CTD data collected using a Sea-Bird Scientific SBE 911 during several R/V Savannah cruises conducted from 2015 to 2017 along a transect from shelf waters to oligotrophic waters in the South Atlantic Bight off the coast of Georgia (Navy Op Area NA06).";
    String time_coverage_end "2017-01-27T20:46:05Z";
    String time_coverage_start "2015-03-16T15:56:47Z";
    String title "Basic CTD hydrography data collected during R/V Savannah cruises conducted in the South Atlantic Bight off the coast of Georgia from 2015-2017";
    String version "1";
    Float64 Westernmost_Easting -81.121513;
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

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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