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Dataset Title:  PMEL Atmospheric Chemistry MAGE-92 DMS data Subscribe RSS
Institution:  NOAA   (Dataset ID: ACG_MAGE-92_Vickers_dms)
Range: longitude = -140.115 to -118.457°E, latitude = -12.545 to 33.5885°N, altitude = 18.0 to 18.0m, time = 1992-02-21T23:30:00Z to 1992-03-20T03:30:00Z
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Subset | 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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 6.98715e+8, 7.010622e+8;
    String axis "T";
    String comment "Start of sampling period";
    String coords "time";
    String ioos_category "Time";
    String long_name "Datetime UTC";
    String source_name "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";
  }
  trajectory_id {
    String cf_role "trajectory_id";
    String coords "time";
    String ioos_category "Identifier";
    String long_name "Trajectory ID";
  }
  duration {
    Int32 _FillValue 2147483647;
    Int32 actual_range 3600, 3600;
    String coords "time";
    String ioos_category "Time";
    String long_name "Duration";
    String units "second";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -12.545, 33.5885;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String coords "time";
    String instrument "GPS";
    String ioos_category "Location";
    String long_name "Latitude";
    String source "surface observation";
    String standard_name "latitude";
    String units "degrees_north";
    Float64 valid_max 90.0;
    Float64 valid_min -90.0;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -140.115, -118.457;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String coords "time";
    String instrument "GPS";
    String ioos_category "Location";
    String long_name "Longitude";
    String source "surface observation";
    String standard_name "longitude";
    String units "degrees_east";
    Float64 valid_max 180.0;
    Float64 valid_min -180.0;
  }
  altitude {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "up";
    Float64 actual_range 18.0, 18.0;
    String axis "Z";
    Float64 colorBarMinimum 0.0;
    String coords "time";
    String ioos_category "Location";
    String long_name "height above mean sea level";
    String positive "up";
    String standard_name "altitude";
    String units "m";
    Float64 valid_min 0.0;
  }
  dms_seawater {
    Float64 _FillValue NaN;
    Float64 actual_range 0.658, 5.375;
    String coords "time";
    String instrument "Custom purge and trap gas chromatograph";
    String ioos_category "Unknown";
    String long_name "Seawater DMS concentration";
    String source "surface ocean observation";
    String units "nmol L-1";
  }
  dms_air {
    Float64 _FillValue NaN;
    Float64 actual_range 98.0, 706.0;
    String coords "time";
    String instrument "Custom purge and trap gas chromatograph";
    String ioos_category "Unknown";
    String long_name "Atmospheric DMS concentration";
    String source "surface ocean observation";
    String units "nmol L-1";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Trajectory";
    String cdm_trajectory_variables "trajectory_id";
    String comment 
"Air and seawater samples for DMS were analyzed using an automated purge and trap system. Air samples were collected through a Teflon line which ran approximately 60 m from the top of the aerosol sampling mast to the instrument. One hundred mL min-1 of the 4 L min-1 flow were pulled through a KI solution at the instrument to eliminate oxidant interferences (Cooper et al., 1993). The air sample volume ranged from 0.5 to 1.5 L depending on the DMS concentration. Water vapor was removed by passing the flow through a -25°C Teflon tube filled with silanized glass wool. DMS was then trapped in another -25°C Teflon tube filled with Tenax. During the sample trapping period, methylethyl sulfide (MES) was added to the sample stream as an internal standard. At the end of the sampling/purge period, the coolant was pushed away from the trap and the trap was electrically heated. DMS was desorbed onto a DB-1 megabore fused silica column where the sulfur compounds were separated isothermally at 50°C quantified with either a Flame Photo Detector (FPD) or a Sulfur Chemiluminescence Detector (SCD). The instrument was calibrated gravimetrically with calibrated permeation tubes. More details of the analysis can be found in Bates et al. (1998b).

Seawater samples for DMS analysis were collected from the ship’s seawater pumping system at a depth of approximately 5 m below the ship’s waterline. Periodically, a 5 mL water sample was valved from the ship’s water line into a Teflon gas stripper. The sample was purged with hydrogen for 5 min. DMS and other sulfur gases in the hydrogen purge gas were collected on the Tenax trap held at -25°C as for the air samples.";
    String contributor_name "Coffman, Derek/NOAA-PMEL/Address: 7600 Sand Pt. Wy. NE,Seattle,WA 98115 /email: derek.coffman@noaa.gov";
    String Conventions "COARDS, CF-1.6, ACDD-1.3, NCCSV-1.0";
    String creator_email "derek.coffman@noaa.gov";
    String creator_name "Coffman, Derek";
    String creator_url "https://www.pmel.noaa.gov/";
    String dimensions "time=653";
    Float64 Easternmost_Easting -118.457;
    String featureType "Trajectory";
    Float64 geospatial_lat_max 33.5885;
    Float64 geospatial_lat_min -12.545;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -118.457;
    Float64 geospatial_lon_min -140.115;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 18.0;
    Float64 geospatial_vertical_min 18.0;
    String geospatial_vertical_positive "up";
    String geospatial_vertical_units "m";
    String history 
"2025-12-12T21:41:01Z (local files)
2025-12-12T21:41:01Z https://data.pmel.noaa.gov/pmel/tabledap/ACG_MAGE-92_Vickers_dms.das";
    String infoUrl "https://www.pmel.noaa.gov/acg/data/index.html";
    String institution "NOAA";
    String keywords "above, altitude, atmosphere, atmospheric, chemistry, concentration, data, datetime, dms, dms_air, dms_seawater, duration, earth, Earth Science > Atmosphere > Altitude > Station Height, environmental, flux, global, gofs, height, identifier, jgofs, joint, laboratory, latitude, level, longitude, mage, mage-92, marine, mean, noaa, ocean, pacific, pmel, science, sea, seawater, station, study, time, trajectory, trajectory_id, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "These data were produced by NOAA and are not subject to copyright protection in the United States. NOAA waives any potential copyright and related rights in these data worldwide through the Creative Commons Zero 1.0 Universal Public Domain Dedication (CC0-1.0).";
    Float64 Northernmost_Northing 33.5885;
    String platform "Vickers";
    String product_version "0";
    String project "MAGE-92";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -12.545;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "trajectory_id, duration, altitude";
    String summary 
"This was the first field project of the International Global Atmospheric Chemistry Program's Marine Aerosol and Gas Exchange project (IGAC-MAGE). The experiment was planned to coordinate with the Joint Global Ocean Flux Study (JGOFS) in order to complement their oceanographic program with trace gas and atmospheric chemistry measurements. The specific goals of the IGAC/MAGE 1992 equatorial field program were to:

1. Calculate air-sea exchange of short-lived biogenic trace gases using shipboard measurements of the important seawater and atmospheric species, air-sea exchange models and micro-budget flux estimates.

2. Measure deposition of nutrients to the sea surface and the effects of these nutrients on ocean primary productivity.

3. Compare the atmospheric chemistry and aerosol properties over productive (equatorial) and oligotrophic (12°S) waters.

4. Calculate the cycling of trace gases in the upper water column using measurements of the key species as a function of depth and microbiological rate studies.";
    String time_coverage_end "1992-03-20T03:30:00Z";
    String time_coverage_start "1992-02-21T23:30:00Z";
    String title "PMEL Atmospheric Chemistry MAGE-92 DMS data";
    Float64 Westernmost_Easting -140.115;
  }
}

 

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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