BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[HydEst TM-CTD bottle sensor data] - Trace metal CTD bottle sensor data from the Hydrothermal Estuaries expedition to the Juan de Fuca hydrothermal plume, Northeast Pacific Ocean, aboard R/V Atlantis (AT50-15) in August and September 2023 (Collaborative Research: Hydrothermal Estuaries: What Sets the Hydrothermal Flux of Fe and Mn to the Oceans?)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_1008499_v1)
Range:	longitude = -129.235 to -129.0603°E, latitude = 47.92356 to 48.00336°N, depth = 1794.396 to 2534.257m, time = 2023-08-28T07:15:00Z to 2023-09-15T10:11:00Z
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| 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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  EXPOCODE {
    String long_name "Expocode";
    String units "unitless";
  }
  CRUISE_ID {
    String long_name "Cruise_id";
    String units "unitless";
  }
  CRUISE_NAME {
    String long_name "Cruise_name";
    String units "unitless";
  }
  EVENTNO {
    String long_name "Eventno";
    String units "unitless";
  }
  STNNBR {
    Int32 actual_range 2, 19;
    String long_name "Stnnbr";
    String units "unitless";
  }
  CASTNO {
    Int32 actual_range 1, 7;
    String long_name "Castno";
    String units "unitless";
  }
  START_DATE_PDT {
    String long_name "Start_date_pdt";
    String units "unitless";
  }
  START_TIME_PDT {
    String long_name "Start_time_pdt";
    String units "unitless";
  }
  ISO_DATE_TIME_START_PDT {
    String long_name "Iso_date_time_start_pdt";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.6932069e+9, 1.69477266e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_date_time_start_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  END_DATE_PDT {
    String long_name "End_date_pdt";
    String units "unitless";
  }
  END_TIME_PDT {
    String long_name "End_time_pdt";
    String units "unitless";
  }
  ISO_DATE_TIME_END_PDT {
    String long_name "Iso_date_time_end_pdt";
    String units "unitless";
  }
  ISO_DATE_TIME_END_UTC {
    Float64 actual_range 1.69321416e+9, 1.69477956e+9;
    String ioos_category "Time";
    String long_name "Iso_date_time_end_utc";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 47.92356, 48.00336;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Start_event_lat";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -129.235, -129.0603;
    String axis "X";
    String ioos_category "Location";
    String long_name "Start_event_lon";
    String standard_name "longitude";
    String units "degrees_east";
  }
  END_EVENT_LAT {
    Float32 actual_range 47.92355, 48.00336;
    String long_name "End_event_lat";
    String units "degrees_north";
  }
  END_EVENT_LON {
    Float32 actual_range -129.235, -129.0603;
    String long_name "End_event_lon";
    String units "degrees_east";
  }
  BTMDEPTH {
    Int32 actual_range 2084, 2564;
    String long_name "Btmdepth";
    String units "meters";
  }
  BTLNBR {
    Int32 actual_range 1, 14;
    String long_name "Btlnbr";
    String units "unitless";
  }
  BTLPOS {
    Int32 actual_range 1, 12;
    String long_name "Btlpos";
    String units "unitless";
  }
  SAMPNO {
    Int32 actual_range 1001, 1322;
    String long_name "Sampno";
    String units "unitless";
  }
  BTL_FLAG_W {
    Int32 actual_range 1, 3;
    String long_name "Btl_flag_w";
    String units "unitless";
  }
  CTDPRS {
    Float32 actual_range 1817.454, 2571.347;
    String long_name "Ctdprs";
    String units "decibars";
  }
  CTDPRS_FLAG_W {
    Int32 actual_range 1, 2;
    String long_name "Ctdprs_flag_w";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 1794.396, 2534.257;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Ctddepth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  CTDTMP {
    Float32 actual_range 1.8066, 2.123;
    String long_name "Ctdtmp";
    String units "degrees Celsius";
  }
  CTDTMP_FLAG_W {
    Int32 actual_range 1, 2;
    String long_name "Ctdtmp_flag_w";
    String units "unitless";
  }
  CTDSAL {
    Float32 actual_range 34.5565, 34.6203;
    String long_name "Ctdsal";
    String units "PSS-78";
  }
  CTDSAL_FLAG_w {
    Int32 actual_range 1, 2;
    String long_name "Ctdsal_flag_w";
    String units "unitless";
  }
  CTDOXY {
    Float32 actual_range 43.68, 72.062;
    String long_name "Ctdoxy";
    String units "micromoles per kilogram (umol/kg)";
  }
  CTDOXY_FLAG_W {
    Int32 actual_range 1, 2;
    String long_name "Ctdoxy_flag_w";
    String units "unitless";
  }
  TRANSM {
    Float32 actual_range -0.0426, 97.4839;
    String long_name "Transm";
    String units "percent (%)";
  }
  TRANSM_FLAG_W {
    Int32 actual_range 1, 4;
    String long_name "Transm_flag_w";
    String units "unitless";
  }
  TURBIDITY {
    Float32 actual_range 0.024, 0.568;
    String long_name "Turbidity";
    String units "Volts";
  }
  TURBIDITY_FLAG_W {
    Int32 actual_range 1, 2;
    String long_name "Turbidity_flag_w";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.26008/1912/bco-dmo.1008499.1";
    Float64 Easternmost_Easting -129.0603;
    Float64 geospatial_lat_max 48.00336;
    Float64 geospatial_lat_min 47.92356;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -129.0603;
    Float64 geospatial_lon_min -129.235;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 2534.257;
    Float64 geospatial_vertical_min 1794.396;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2026-10-05T19:59:03Z (local files)
2026-10-05T19:59:03Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_1008499_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/1008499";
    String institution "BCO-DMO";
    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.";
    Float64 Northernmost_Northing 48.00336;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 47.92356;
    String summary "This dataset includes the processed bottle-CTD sensor data collected with depth profiles of a trace metal clean CTD owned by the Fitzsimmons lab and deployed on the Hydrothermal Estuaries cruise to the Endeavour hydrothermal plume, Juan de Fuca Ridge, Northeast Pacific Ocean aboard R/V Atlantis (AT50-15) from August to September 2023. Data are only shown for the depths on which Niskin-X bottles were closed. Bottles were closed on the upcast only, and every depth has duplicate bottles fired to satisfy our water budget requirements. Station locations were selected using modeling estimates and sensor data from the AUV Sentry; a station upstream of the hydrothermal plume was also sampled as a background. Each station (except for the background) targeted the most concentrated plume at sequential distances aimed to represent increasing plume age.";
    String time_coverage_end "2023-09-15T10:11:00Z";
    String time_coverage_start "2023-08-28T07:15:00Z";
    String title "[HydEst TM-CTD bottle sensor data] - Trace metal CTD bottle sensor data from the Hydrothermal Estuaries expedition to the Juan de Fuca hydrothermal plume, Northeast Pacific Ocean, aboard R/V Atlantis (AT50-15) in August and September 2023 (Collaborative Research: Hydrothermal Estuaries: What Sets the Hydrothermal Flux of Fe and Mn to the Oceans?)";
    Float64 Westernmost_Easting -129.235;
  }
}

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.

(easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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