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Dataset Title:  1995 and 1996 fairly raw chlorophyll data, Georges Bank collected from the
GLOBEC Broadscale cruises from the Gulf of Maine and Georges Bank (GB project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_2298)
Range: longitude = -68.9567 to -65.6483°E, latitude = 40.4383 to 42.335°N, depth = 1.0 to 207.0m
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 {
  cruiseid {
    String bcodmo_name "cruiseid";
    String description "cruise identification";
    String long_name "Cruiseid";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 1995, 1996;
    String bcodmo_name "year";
    String description "year";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
  }
  cast {
    Byte _FillValue 127;
    Byte actual_range 2, 39;
    String bcodmo_name "cast";
    String description "CTD rosette cast number";
    String long_name "Cast";
  }
  station_std {
    Byte _FillValue 127;
    Byte actual_range 3, 39;
    String bcodmo_name "station_std";
    String description "standard broad-scale station number";
    String long_name "Station Std";
    String units "integer";
  }
  day_local {
    String bcodmo_name "day_local";
    String description "local-time day";
    String long_name "Day Local";
    String units "1 to 31";
  }
  month_local {
    String bcodmo_name "month_local";
    String description "local-time month";
    String long_name "Month Local";
    String units "1 to 12";
  }
  time_local {
    String bcodmo_name "time_local";
    String description "local time of cast";
    String long_name "Time Local";
  }
  yrday_local {
    Float32 _FillValue NaN;
    Float32 actual_range 12.2688, 200.3049;
    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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 40.4383, 42.335;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude in decimal degrees: North is positive; negative denotes South";
    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 -68.9567, -65.6483;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude in decimal degrees: East is positive; negative denotes West";
    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";
  }
  bottle {
    Byte _FillValue 127;
    Byte actual_range 1, 6;
    String bcodmo_name "bottle";
    String description "bottle number on this cast";
    String long_name "Bottle";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.0, 207.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth of sample";
    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";
  }
  fraction {
    String bcodmo_name "unknown";
    String description "size fraction of phytoplankton sampled";
    String long_name "Fraction";
    String units "microns";
  }
  chl_a {
    Float32 _FillValue NaN;
    Float32 actual_range -0.34, 13.52;
    String bcodmo_name "chlorophyll a";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "chlorophyll a, as calculated from fluorescence";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "micrograms/liter";
  }
  chl_a_avg {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 12.39;
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "chlorophyll a average, based on three replicates";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String units "micrograms/liter";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"The 1995 and 1996 bottle data were collected with a GO rosette mounted above
the MK5 CTD. Water for chlorophyll extractions was taken at priority 1 and 2
stations and at 3 'standard' depths (according to a protocal set up by Ted
Durbin and Dian Gifford at the University of Rhode Island). For each bottle, 3
replicate samples were run for consistency. 50 mls were filtered for 3 size
fractions: total chlorophyll, chlorophyll from water filtered through a <20
micron mesh and chlorophyll from water filtered through a <5 micron mesh. This
means that for any one station, there were 27 test tubes: 3 depths, 3
replicates, 3 size fractions. The samples were usually read at sea (after the
24 hour acetone extraction). If not, Ted Durbin's Lab read them when the ship
returned.";
    String awards_0_award_nid "54610";
    String awards_0_award_number "unknown GB NSF";
    String awards_0_funder_name "National Science Foundation";
    String awards_0_funding_acronym "NSF";
    String awards_0_funding_source_nid "350";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "54626";
    String awards_1_award_number "unknown GB NOAA";
    String awards_1_funder_name "National Oceanic and Atmospheric Administration";
    String awards_1_funding_acronym "NOAA";
    String awards_1_funding_source_nid "352";
    String cdm_data_type "Other";
    String comment 
"Bottle data from Dave Mountain and Maureen Taylor 
    These data are raw and uncorrected.  10/20/04";
    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 "2009-11-24T18:42:55Z";
    String date_modified "2019-01-30T16:27:12Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.2298.1";
    Float64 Easternmost_Easting -65.6483;
    Float64 geospatial_lat_max 42.335;
    Float64 geospatial_lat_min 40.4383;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -65.6483;
    Float64 geospatial_lon_min -68.9567;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 207.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-04-18T12:10:11Z (local files)
2024-04-18T12:10:11Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_2298.das";
    String infoUrl "https://www.bco-dmo.org/dataset/2298";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Niskin Bottles mounted on a Rosette.";
    String instruments_0_dataset_instrument_nid "4098";
    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, bottle, cast, chemical, chemistry, chl_a, chl_a_avg, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, cruiseid, data, dataset, day, day_local, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, erddap, fraction, latitude, local, longitude, management, month, month_local, ocean, oceanography, oceans, office, preliminary, profiler, salinity, salinity-temperature-depth, science, sea, seawater, station, station_std, std, temperature, time, time_local, water, year, yrday, yrday_local";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/2298/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/2298";
    Float64 Northernmost_Northing 42.335;
    String param_mapping "{'2298': {'lat': 'master - latitude', 'depth': 'flag - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/2298/parameters";
    String people_0_affiliation "Northeast Fisheries Science Center - Woods Hole";
    String people_0_affiliation_acronym "NOAA NEFSC";
    String people_0_person_name "Dr David Mountain";
    String people_0_person_nid "50431";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "National Marine Fisheries Service";
    String people_1_affiliation_acronym "NMFS";
    String people_1_person_name "Dr David Mountain";
    String people_1_person_nid "50431";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "National Marine Fisheries Service";
    String people_2_affiliation_acronym "NMFS";
    String people_2_person_name "Ms Maureen Taylor";
    String people_2_person_nid "50450";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "GB";
    String projects_0_acronym "GB";
    String projects_0_description 
"The U.S. GLOBEC Georges Bank Program is a large multi- disciplinary multi-year oceanographic effort. The proximate goal is to understand the population dynamics of key species on the Bank - Cod, Haddock, and two species of zooplankton (Calanus finmarchicus and Pseudocalanus) - in terms of their coupling to the physical environment and in terms of their predators and prey. The ultimate goal is to be able to predict changes in the distribution and abundance of these species as a result of changes in their physical and biotic environment as well as to anticipate how their populations might respond to climate change.
The effort is substantial, requiring broad-scale surveys of the entire Bank, and process studies which focus both on the links between the target species and their physical environment, and the determination of fundamental aspects of these species' life history (birth rates, growth rates, death rates, etc).
Equally important are the modelling efforts that are ongoing which seek to provide realistic predictions of the flow field and which utilize the life history information to produce an integrated view of the dynamics of the populations.
The U.S. GLOBEC Georges Bank Executive Committee (EXCO) provides program leadership and effective communication with the funding agencies.";
    String projects_0_geolocation "Georges Bank, Gulf of Maine, Northwest Atlantic Ocean";
    String projects_0_name "U.S. GLOBEC Georges Bank";
    String projects_0_project_nid "2037";
    String projects_0_project_website "http://globec.whoi.edu/globec_program.html";
    String projects_0_start_date "1991-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 40.4383;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Raw Extracted Chlorophyll Data from Broadscale CTD stations in the Gulf of Maine, 1995 and 1996.";
    String title "1995 and 1996 fairly raw chlorophyll data, Georges Bank collected from the GLOBEC Broadscale cruises from the Gulf of Maine and Georges Bank (GB project)";
    String version "1";
    Float64 Westernmost_Easting -68.9567;
    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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