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Dataset Title:  Chlorophyll data associated with salp swarm collections in the Slope Waters
off northeastern USA from R/V Oceanus OC370, OC379, OC381 in the slope waters
off NJ, DE, MD from 2001-2002 (SalpSwarmDyn project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_3150)
Range: depth = 10.0 to 800.0m
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 designation";
    String long_name "Cruise Id";
  }
  sample {
    String bcodmo_name "sample";
    String description "sample identification or number";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
  }
  day_local {
    String bcodmo_name "day_local";
    String description "day, local time";
    String long_name "Day Local";
  }
  month_local {
    String bcodmo_name "month_local";
    String description "month of year, local time";
    String long_name "Month Local";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2001, 2002;
    String bcodmo_name "year";
    String description "year, reported as YYYY";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
  }
  yrday_local {
    Int16 _FillValue 32767;
    Int16 actual_range 153, 269;
    String bcodmo_name "yrday_local";
    String description "local day and decimal time, as 326.5 for the 326th day of the year, or November 22 at 1200 hours (noon)";
    String long_name "Yrday Local";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 10.0, 800.0;
    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";
  }
  filter {
    String bcodmo_name "unknown";
    String description "size or type of filter: gff=glass fiber filter";
    String long_name "Filter";
    String units "microns";
  }
  chl_a {
    Float32 _FillValue NaN;
    Float32 actual_range -0.54, 3.699;
    String bcodmo_name "chlorophyll a";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "total chlorophyll-a pigment";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "microgram/liter";
  }
  phaeo {
    Float32 _FillValue NaN;
    Float32 actual_range -0.323, 2.141;
    String bcodmo_name "phaeopigment";
    String description "total phaeopigment";
    String long_name "Phaeo";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHAEFMP1/";
    String units "microgram/liter";
  }
  pig_tot {
    Float32 _FillValue NaN;
    Float32 actual_range 0.002, 5.533;
    String bcodmo_name "unknown";
    String description "total pigments";
    String long_name "Pig Tot";
    String units "microgram/liter";
  }
  chl_per_tot {
    Float32 _FillValue NaN;
    Float32 actual_range -0.337, 2.931;
    String bcodmo_name "unknown";
    String description "ratio of chlorophyll to total pigments";
    String long_name "Chl Per Tot";
  }
  comments {
    String bcodmo_name "comment";
    String description "free text comments";
    String long_name "Comments";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Seawater was collected with Niskin bottles at several depths and filtered
through both GFF filters and 2 \\u00b5m pore glass fibre filters for analysis
of Chlorophyll a and total phaeopigment. Immediately after water samples were
filtered, filter pads were transferred into 6 ml of 90% acetone and the
pigment was extracted in a dark refrigerator for 24 hours. Filter pads were
removed and the test tubes centrifuged just prior to reading the fluorescence.
Following the initial fluorescence reading, samples were acidified with ~0.2ml
of HCl and reread. The fluorometer was calibrated using a spectrophotometer
during each cruise using standard Chl-a derived from spinach. Chlorophyll-a
and phaeopigments were calculated from standard equations (Strickland and
Parsons 1972).";
    String awards_0_award_nid "54765";
    String awards_0_award_number "OCE-0002540";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0002540";
    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 "Phillip R. Taylor";
    String awards_0_program_manager_nid "50451";
    String cdm_data_type "Other";
    String comment 
"Chlorophyl from CTD's and Dives 
  PI: Patricia Kremer (Univ. Connecticut) 
  2001-2001, Mid-Atlantic Bight and Southern New England Slope Waters";
    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 "2010-06-16T20:40:40Z";
    String date_modified "2020-01-22T18:32:10Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.3150.1";
    Float64 geospatial_vertical_max 800.0;
    Float64 geospatial_vertical_min 10.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-08-05T18:31:33Z (local files)
2020-08-05T18:31:33Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_3150.das";
    String infoUrl "https://www.bco-dmo.org/dataset/3150";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "4890";
    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 keywords "bco, bco-dmo, biological, chemical, chemistry, chl, chl_a, chl_per_tot, chlorophyll, comments, concentration, concentration_of_chlorophyll_in_sea_water, cruise, cruise_id, data, dataset, day, day_local, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, filter, local, management, month, month_local, ocean, oceanography, oceans, office, per, phaeo, pig, pig_tot, preliminary, sample, science, sea, seawater, tot, water, year, yrday, yrday_local";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/3150/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/3150";
    String param_mapping "{'3150': {'depth': 'flag - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/3150/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Dr Laurence P. Madin";
    String people_0_person_nid "50426";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Connecticut";
    String people_1_affiliation_acronym "UConn";
    String people_1_person_name "Dr Patricia Kremer";
    String people_1_person_nid "50949";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "SalpSwarmDyn";
    String projects_0_acronym "SalpSwarmDyn";
    String projects_0_description "Salps are holoplanktonic grazers that have a life history, feeding biology and population dynamic strikingly different from copepods or other crustacean zooplankton. They can occur in very dense populations that cover large areas, and these blooms have been shown to have major impacts due to grazing and production of fast?sinking fecal pellets. However the conditions supporting bloom formation, and the energetics, reproduction and behavior of the bloom?forming salps are still poorly understood. This study will focus on two species of salps that are global in their distribution and representative of two genera that commonly form large blooms. Salpa aspera regularly occurs during the summer in high concentrations in the slope waters of the Mid?Atlantic Bight, while Thalia democratica regularly forms dense populations during the winter spring in the Georgia Bight. The investigators will examine feeding, metabolism, growth, reproduction and population dynamics of these salps. They will use two independent modeling approaches, grounded in experimental and field data, to extend their observations to other time and space scales. interpret ouexperimental and modeling results will be interpreted within the context of the environmental conditions to which the salps are exposed. This integrated approach will provide the best basis for understanding how salp blooms form and persist. Results of this study will extend to other species that occur in high densities in many locations, allowing scientists to better evaluate the importance of salps in biogeochemical cycles and in structuring the pelagic environment.";
    String projects_0_end_date "2002-09";
    String projects_0_geolocation "slope water off mid-Atlantic Bight";
    String projects_0_name "Salp Swarm Dynamics";
    String projects_0_project_nid "2075";
    String projects_0_start_date "2002-06";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Chlorophyll data associated with salp swarm collections in the Slope Waters off northeastern USA from R/V Oceanus OC370, OC379, OC381 in the slope waters off NJ, DE, MD from 2001-2002.";
    String title "Chlorophyll data associated with salp swarm collections in the Slope Waters off northeastern USA from R/V Oceanus OC370, OC379, OC381 in the slope waters off NJ, DE, MD from 2001-2002 (SalpSwarmDyn project)";
    String version "1";
    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.


 
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