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Dataset Title:  CTD cast data from 45 R/V Alpha Helix and R/V Wecoma Long-Term Observation
Program (LTOP) cruises to the Coastal Gulf of Alaska from 1997-2004 as part of
the U.S. GLOBEC program (NEP project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_2470)
Range: longitude = -150.9358 to -143.6689°E, latitude = 57.7995 to 61.2601°N, depth = -999.0 to 8.83m
Information:  Summary ? | License ? | 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 {
  cruiseid {
    String bcodmo_name "cruiseid";
    String description "Cruise identifier, e.g. HX217 represents R/V Alpha Helix cruise number 217.";
    String long_name "Cruiseid";
    String units "no units";
  }
  ship {
    String bcodmo_name "ship";
    String description "name of the ship or vessel (See also platform.)";
    String long_name "Ship";
    String units "no units";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 1997, 2004;
    String bcodmo_name "year";
    String description "year, e.g. 1997";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "no units";
  }
  station {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 143;
    String bcodmo_name "station";
    String description "consecutive station number";
    String long_name "Station";
    String units "no units";
  }
  stn_id {
    String bcodmo_name "station";
    String description "station identification code";
    String long_name "Stn Id";
    String units "no units";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 57.7995, 61.2601;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude, in decimal degrees, north is positive";
    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 -150.9358, -143.6689;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude, in decimal degrees, east is positive";
    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_w {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 4200;
    String bcodmo_name "depth_w";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "water depth, in meters";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  press_min {
    Byte _FillValue 127;
    Byte actual_range 0, 0;
    String bcodmo_name "press_bar";
    String description "minimum pressure during cast";
    String long_name "Press Min";
    String units "millibars";
  }
  press_max {
    Int16 _FillValue 32767;
    Int16 actual_range 3, 1783;
    String bcodmo_name "press_bar";
    String description "maximum pressure during cast";
    String long_name "Press Max";
    String units "millibars";
  }
  month_gmt {
    String bcodmo_name "month_gmt";
    String description "Month of year, GMT time , i.e. 01-12.";
    String long_name "Month Gmt";
    String units "no units";
  }
  day_gmt {
    String bcodmo_name "day_gmt";
    String description "Day, GMT time e.g. 22.";
    String long_name "Day Gmt";
    String units "no units";
  }
  time_gmt {
    String bcodmo_name "time_gmt";
    String description "time of day, reported in GMT time, 24 hour clock";
    String long_name "Time Gmt";
    String units "hhmm";
  }
  press {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 1783;
    String bcodmo_name "press_bar";
    String description "pressure at ctd sampling point";
    String long_name "Press";
    String units "millibars";
  }
  temp {
    Float32 _FillValue NaN;
    Float32 actual_range 1.592, 17.206;
    String bcodmo_name "temp2";
    String description "water temperature, as observed by a CTD unit";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPS601/";
    String units "degrees Celsius";
  }
  salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 15.493, 34.558;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "salinity, calculated from the CTD 'primary sensors' of conductivity and temperature.";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "Practical salinity scale, dimensionless";
  }
  sigma_t {
    Float32 _FillValue NaN;
    Float32 actual_range 11.353, 27.614;
    String bcodmo_name "sigma-t";
    String description "sigma-theta density";
    String long_name "Sigma T";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/SIGTEQST/";
    String units "kilograms per meters cubed - 1000";
  }
  dyn_height {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 3.47374;
    String bcodmo_name "dynh_0";
    String description "dynamic height, referenced to surface";
    String long_name "Dyn Height";
    String units "meters";
  }
  fluor {
    Float32 _FillValue NaN;
    Float32 actual_range -999.0, 5.278;
    String bcodmo_name "fluorescence";
    String description "fluorescence";
    String long_name "Fluor";
    Float32 missing_value NaN;
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "?";
  }
  ac3_fluor {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 4.99;
    String bcodmo_name "fluorescence";
    String description "fluorescence";
    String long_name "Ac3 Fluor";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "?";
  }
  trans {
    Float32 _FillValue NaN;
    Float32 actual_range -3.28, 5.02;
    String bcodmo_name "trans_v";
    String description "light transmission";
    String long_name "Trans";
    String units "volts";
  }
  PAR {
    Float32 _FillValue NaN;
    Float32 actual_range -999.0, 5.0;
    String bcodmo_name "PAR";
    Float64 colorBarMaximum 70.0;
    Float64 colorBarMinimum 0.0;
    String description "downwell Photosynthetically Available Radiation";
    String long_name "Downwelling Photosynthetic Photon Radiance In Sea Water";
    Float32 missing_value NaN;
    String units "uE/cm2/sec";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range -999.0, 8.83;
    String axis "Z";
    String bcodmo_name "unknown";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth from instrument to bottom";
    String ioos_category "Location";
    String long_name "Depth";
    Float64 missing_value NaN;
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  interp_code {
    Byte _FillValue 127;
    Byte actual_range 0, 3;
    String bcodmo_name "unknown";
    String description "?";
    String long_name "Interp Code";
    String units "?";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Progress Report: April 1999  
 Project Title: The Gulf of Alaska GLOBEC LTOP Program  
 Investigators: Thomas Weingartner (PI), A. J. Paul (PI), Ken Coyle (PI), Lew
Haldorson (PI), Dean Stockwell (PI), Terry Whitledge (PI), Jennifer Boldt,
Seth Danielson, Alexei Pinchuk, and Amy Ruehs (All at University of Alaska),
and Tom Royer (PI; Old Dominion Univ.)
 
The LTOP monitoring in the Gulf of Alaska completed its first year of sampling
which included week-long cruises using the Alpha Helix in October 1997, and
March, April, May, July, October, and December 1998. Sampling on all cruises
included occupying stations along the Seward Line, which extends from the
inner shelf to the edge of the continental slope. At each station CTD profiles
and water samples for nutrients, chlorophyll and zooplankton nauplii were
collected. Additional sampling includes MOCNESS tows at each of these stations
with the tow depths chosen on the basis of backscatter from a 4- frequency,
split-beam towed transducer array. The MOCNESS samples allow verification of
the acoustical results and provide samples for species identification and
additional analyses. The transducer is towed continually along the line and in
conjunction with underway measurements of sea surface temperature, salinity,
fluorescence and ADCP data provide data at very high spatial resolution. This
standard sampling was supplemented during the July and October cruises with
coincidental trawls from a charterd fishing vessel and surface gill nets from
the Alpha Helix. We have also provided samples and/or sampling opportunities
to other scientists for measurements of stable isotope composition of biota,
dissolved carbon, bacteria, microzooplankton, seabird and marine mammal, and
circulation.
 
The data suggest that the shelf is organized into three distinct dynamic and
biological regimes. The innermost portion of the shelf consists of the Alaska
Coastal Current, which is a high speed, persistent, dilute coastal current
which is generally low in nutrients and chlorophyll. The inner shelf is
segregated from the midshelf region by a salinity front. Nutrient
concentrations, chlorophyll biomass, zooplankton, fish and seabird abundances
appear to be consistently high just offshore of this front. However, it is not
clear if this region of locally high biological productivity is associated
with frontal processes or with the locally complicated bathymetry and
coastline curvature. Over the midshelf region the circulation is weak and
variable and biological abundances appear to be patchy in time and space. This
region of the shelf often contains eddies having a diamter of ~50km. A third
regime straddles the shelfbreak salinity front. Flow here is also swift (and
often reflects shoreward movement of the Alaskan Stream) and nutrient,
chlorophyll and zooplankton conentrations tend to be relatively high. Fish,
seabird, and mammal abundances are also relatively high in this region. There
is some suggestion that the vertebrate community structure here differs from
that of the inner shelf.
 
Time permitting we augment the sampling along the Seward Line with additional
alongshore transects. While these are relatively few in number they suggest
that biological production is highly patchy owing perhaps to very complicated
bathymetry.
 
The first year of sampling occurred during an El Nino year and the physical
effects of this phenomenom included unusually warm (~1-2C above normal) and
fresh (.15 psu) waters over the uper 200 m of the shelf. By summer, deep water
temperatures were returning to normal and deep water salinities were above
normal. The reason for the latter is not known but it implies either
abnormally high upwelling rates or changes in the the composition of the
offshore water masses that annually flow inshore. Higher salinities imply
higher nutrient concentrations. However, it is not clear that changes in deep
nutrient concentrations in the deep water on the shelf affect surface
production.
 
Additional information about the GLOBEC LTOP in the Coastal Gulf of Alaska,
including plots of cruise results, station locations, etc., can be obtained
at: [http://www.ims.uaf.edu/GLOBEC/](\\\\\"http://www.ims.uaf.edu/GLOBEC/\\\\\")";
    String awards_0_award_nid "54767";
    String awards_0_award_number "OCE-0109078";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0109078";
    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 awards_1_award_nid "55044";
    String awards_1_award_number "unknown NEP 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 
"ctd_lev1 datafile: CTD_HX201.dat  
  ctd_lev2 datafile: CTD_HX201_1.dat";
    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 "2009-11-29T11:22:08Z";
    String date_modified "2019-11-28T15:08:27Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.2470.1";
    Float64 Easternmost_Easting -143.6689;
    Float64 geospatial_lat_max 61.2601;
    Float64 geospatial_lat_min 57.7995;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -143.6689;
    Float64 geospatial_lon_min -150.9358;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 8.83;
    Float64 geospatial_vertical_min -999.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-03-28T21:27:07Z (local files)
2024-03-28T21:27:07Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_2470.das";
    String infoUrl "https://www.bco-dmo.org/dataset/2470";
    String institution "BCO-DMO";
    String instruments_0_acronym "CTD";
    String instruments_0_dataset_instrument_description "CTD measurements taken, CTD unit unidentified";
    String instruments_0_dataset_instrument_nid "4145";
    String instruments_0_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column.  The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or  radiometers.  It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.  This instrument designation is used when specific make and model are not known.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_0_instrument_name "CTD profiler";
    String instruments_0_instrument_nid "417";
    String instruments_0_supplied_name "Conductivity, Temperature, Depth";
    String keywords "ac3, ac3_fluor, active, available, bco, bco-dmo, biological, chemical, code, cruiseid, data, dataset, day, day_gmt, density, depth, depth_to_bottom, depth_w, dmo, downwelling, downwelling_photosynthetic_photon_radiance_in_sea_water, dyn, dyn_height, earth, Earth Science > Oceans > Ocean Optics > Photosynthetically Active Radiation, Earth Science > Oceans > Ocean Optics > Radiance, Earth Science > Oceans > Salinity/Density > Salinity, erddap, fluor, height, interp, interp_code, latitude, longitude, management, max, min, month, month_gmt, ocean, oceanography, oceans, office, optics, PAR, photon, photosynthetic, photosynthetically, practical, preliminary, press, press_max, press_min, radiance, radiation, salinity, science, sea, sea_water_practical_salinity, seawater, ship, sigma, sigma_t, station, stn, stn_id, temperature, time, time_gmt, trans, water, year";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/2470/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/2470";
    Float64 Northernmost_Northing 61.2601;
    String param_mapping "{'2470': {'lat': 'flag - latitude', 'depth_to_bottom': 'flag - depth', 'lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/2470/parameters";
    String people_0_affiliation "University of Alaska Fairbanks";
    String people_0_affiliation_acronym "UAF";
    String people_0_person_name "Dr Thomas J. Weingartner";
    String people_0_person_nid "50468";
    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 "Ms Dicky Allison";
    String people_1_person_nid "50382";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "NEP";
    String projects_0_acronym "NEP";
    String projects_0_description 
"Program in a Nutshell
Goal:  To understand the effects of climate variability and climate change on the distribution, abundance and production of marine animals (including commercially important living marine resources) in the eastern North Pacific. To embody this understanding in diagnostic and prognostic ecosystem models, capable of capturing the ecosystem response to major climatic fluctuations.
Approach: To study the effects of past and present climate variability on the population ecology and population dynamics of marine biota and living marine resources, and to use this information as a proxy for how the ecosystems of the eastern North Pacific may respond to future global climate change. The strong temporal variability in the physical and biological signals of the NEP will be used to examine the biophysical mechanisms through which zooplankton and salmon populations respond to physical forcing and biological interactions in the coastal regions of the two gyres. Annual and interannual variability will be studied directly through long-term observations and detailed process studies; variability at longer time scales will be examined through retrospective analysis of directly measured and proxy data. Coupled biophysical models of the ecosystems of these regions will be developed and tested using the process studies and data collected from the long-term observation programs, then further tested and improved by hindcasting selected retrospective data series.";
    String projects_0_geolocation "Northeast Pacific Ocean, Gulf of Alaska";
    String projects_0_name "U.S. GLOBEC Northeast Pacific";
    String projects_0_project_nid "2038";
    String projects_0_project_website "http://nepglobec.bco-dmo.org";
    String projects_0_start_date "1997-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 57.7995;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "press_min";
    String summary "CTD cast data from 45 R/V Alpha Helix and R/V Wecoma Long-Term Observation Program (LTOP) cruises to the Coastal Gulf of Alaska from 1997-2004 as part of the U.S. GLOBEC program (NEP project)";
    String title "CTD cast data from 45 R/V Alpha Helix and R/V Wecoma Long-Term Observation Program (LTOP) cruises to the Coastal Gulf of Alaska from 1997-2004 as part of the U.S. GLOBEC program (NEP project)";
    String version "1";
    Float64 Westernmost_Easting -150.9358;
    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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