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Dataset Title:  [ccs_proc_CTD] - CTD data from California Current System (CCS) Process/
Mesoscale Cruises on the R/Vs New Horizon, Revelle, Thompson, and Wecoma in the
Northeast Pacific from 2000-2002 as part of the U.S. GLOBEC program (NEP
project) (U.S. GLOBEC Northeast Pacific) Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_2462)
Range: longitude = -126.1972 to -123.692°E, latitude = 38.7977 to 44.675°N
Information:  Summary ? | License ? | FGDC | 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 identifier, e.g. W0005 R/V Wecoma cruise 0005.";
    String long_name "Cruiseid";
    String units "unitless";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2000, 2002;
    String bcodmo_name "year";
    String description "Year, e.g. 2002.";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  station {
    String bcodmo_name "station";
    String description "Consecutive station number.";
    String long_name "Station";
    String units "unitless";
  }
  station_name {
    String bcodmo_name "station";
    String description "Station code.";
    String long_name "Station Name";
    String units "unitless";
  }
  day {
    String bcodmo_name "day_local";
    String description "Day of month (local time).";
    String long_name "Day";
    String units "unitless";
  }
  month {
    String bcodmo_name "month_local";
    String description "Month of measurement (0 to 12); local time.";
    String long_name "Month";
    String units "unitless";
  }
  time2 {
    String bcodmo_name "time_local";
    String description "Time of day, local time, using 2400 clock format.";
    String long_name "Time";
    String units "unitless";
  }
  depth_w {
    Int16 _FillValue 32767;
    Int16 actual_range 26, 4684;
    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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 38.7977, 44.675;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude; 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 -126.1972, -123.692;
    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";
  }
  press {
    Float64 _FillValue NaN;
    Float64 actual_range -0.2, 1014.0;
    String bcodmo_name "pressure";
    String description "Pressure.";
    String long_name "Press";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
    String units "decibars";
  }
  temp {
    Float32 _FillValue NaN;
    Float32 actual_range 3.49, 18.287;
    String bcodmo_name "temperature";
    String description "Water temperature.";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  sal {
    Float32 _FillValue NaN;
    Float32 actual_range 2.549, 34.427;
    String bcodmo_name "sal";
    String description "salinity, calculated from the CTD 'primary sensors' of conductivity and temperature. See 'Processing Description'.";
    String long_name "Sal";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "Practical Salinity Scale, dimensionless";
  }
  potemp {
    Float32 _FillValue NaN;
    Float32 actual_range 3.418, 18.286;
    String bcodmo_name "potemp";
    String description "Potential temperature.";
    String long_name "Potemp";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/POTMCV01/";
    String units "International Practical Temperature Scale - 68 ,or 90";
  }
  sigma_0 {
    Float32 _FillValue NaN;
    Float32 actual_range 1.544, 27.38;
    String bcodmo_name "sigma_0";
    String description "Sigma-theta density.";
    String long_name "Sigma 0";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/SIGTPR01/";
    String units "not supplied";
  }
  sp_vol_an {
    Float32 _FillValue NaN;
    Float32 actual_range 77.2, 2579.7;
    String bcodmo_name "unknown";
    String description "Specific volume anomaly.";
    String long_name "Sp Vol An";
    String units "CL/T";
  }
  DYN_HT {
    Float32 _FillValue NaN;
    Float32 actual_range -0.043, 14.08;
    String bcodmo_name "dynh_0";
    String description "Dynamic height.";
    String long_name "DYN HT";
    String units "J/KG";
  }
  flvolt {
    Float32 _FillValue NaN;
    Float32 actual_range 0.008, 13.38;
    String bcodmo_name "fluor voltage";
    String description "Fluoresence";
    String long_name "Flvolt";
    String units "volts";
  }
  trans {
    Float32 _FillValue NaN;
    Float32 actual_range -99.9, 91.0;
    String bcodmo_name "transmission";
    String description "light transmission, as percent";
    String long_name "Trans";
    Float32 missing_value NaN;
    String units "%";
  }
  trans_v {
    Float32 _FillValue NaN;
    Float32 actual_range 3.254, 4.722;
    String bcodmo_name "trans_v";
    String description "light transmission, as volts";
    String long_name "Trans V";
    String units "volts";
  }
  O2_v {
    Float32 _FillValue NaN;
    Float32 actual_range 0.011, 1.0e+22;
    String bcodmo_name "O2_v";
    String description "Oxygen current";
    String long_name "O2 V";
    String units "volts";
  }
  O2_temp {
    Float32 _FillValue NaN;
    Float32 actual_range 3.88, 1.0e+22;
    String bcodmo_name "unknown";
    String description "oxygen temperature";
    String long_name "O2 Temp";
    String units "degrees C";
  }
  O2S {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.0e+22;
    String bcodmo_name "O2sat";
    String description "O2 saturation (guessing from O2S and units)";
    String long_name "O2 S";
    String units "ml per liter";
  }
  O2 {
    Float32 _FillValue NaN;
    Float32 actual_range -0.1, 1.0e+22;
    String bcodmo_name "dissolved Oxygen";
    String description "dissolved oxygen";
    String long_name "O2";
    String units "milliliter/liter";
  }
  PAR {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 3.516;
    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";
    String units "uE/cm2/sec";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Physical Influences on Populations in the California Current (Botsford, L.
[Univ. Calif. Davis (UCD)], Hastings, A. M. [UCD], Largier, J. [Scripps
Institute of Oceanography]) We propose to formulate models spanning the
individual level to the metapopulation level for two genera of interest to
GLOBEC in the CCS: ( 1) the two CCS salmon species identified by GLOBEC, coho
salmon (Oncorhynchus kisutch) and chinook salmon (O. tshawytscha) and (2)
Dungeness crab (Cancer magister), a species which covaries with salmon, is a
significant prey of both species, and is subject to similar mesoscale
circulation patterns. The ultimate purpose of these models will be to link the
different scales of variability and levels of ecological organization in the
various retrospective, monitoring and process studies so that the effects of
changes in the physical environment on populations can be projected. Also, we
will answer a number of questions through modeling and analysis of existing
data, that will allow better focus of field studies on critical issues.
 
While upwelling and the regime shift in the mid-1970s are believed to have
affected survival through this period, results of field studies of the cause
are equivocal. We will develop a model to evaluate the interaction of time of
ocean entry, size at entry, varying growth rate, and size dependent mortality
rate on the fraction surviving this phase, and use it to compare the various
field results in a common context. The results will help to focus field
studies, and the model will provide a framework for evaluation of those
studies. Even though Core Hypothesis III focuses on the juvenile stage, ENSO
events are known to have a dramatic effect on survival of pre-spawning adults.
Because the behavior of random populations of semelparous, anadromous species
is poorly understood, the relative effects of environmental variability on
their persistence and productivity is unknown. We will formulate a population
model to determine which variable life history stage has the greater effect so
that the GLOBEC process studies can focus on the appropriate one. We will
formulate a metapopulation model to evaluate whether covariability between the
environmental influences on different subpopulations affect persistence, and
if it does, whether more productive populations can \\\"rescue\\\" extinct less
productive populations?
 
We will also model and analyze the Dungeness crab population because the
dramatic fluctuations in their abundance along the coast may be caused by the
same environmental factor(s) that cause the salmon populations to vary, and
may also be a cause of that variability through predation. We will apply a new
approach to population analysis that answers the question: which environmental
forcing function can combine with known density-dependent recruitment
mechanisms to produce the observed variability in crab catch? (abstract)
 
This page was last updated on March 15, 2007.
 
Hal Batchelder  
 College of Oceanic and Atmospheric Sciences  
 Oregon State University  
 Corvallis, OR 97331-5503  
 phone: 541-737-4500; FAX 541-737-2064";
    String awards_0_award_nid "54778";
    String awards_0_award_number "OCE-0003273";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0003273";
    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 
"Displayed by /home/groups/home/Scripts/nepctd_level1.pl, v1.01/October 13, 2011 
   For /home/groups/home/data1/nep/ccs/process/ctd/nh0005, NEP1, NH0005, 2000 
 Displayed by /home/groups/home/Scripts/nepctd_level2.pl, v1.00/October 18, 1999 
    Using data file /home/groups/home/data1/nep/ccs/process/ctd/nh0005/nh0005c.cr3";
    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 "2009-11-29T11:17:40Z";
    String date_modified "2019-10-31T15:05:57Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.2462.1";
    Float64 Easternmost_Easting -123.692;
    Float64 geospatial_lat_max 44.675;
    Float64 geospatial_lat_min 38.7977;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -123.692;
    Float64 geospatial_lon_min -126.1972;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T05:52:24Z (local files)
2024-11-08T05:52:24Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_2462.das";
    String infoUrl "https://www.bco-dmo.org/dataset/2462";
    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 "4197";
    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 instruments_1_acronym "CTD";
    String instruments_1_dataset_instrument_nid "4793";
    String instruments_1_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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_1_instrument_name "CTD profiler";
    String instruments_1_instrument_nid "417";
    String instruments_1_supplied_name "Conductivity, Temperature, Depth";
    String keywords "active, altimetry, available, bco, bco-dmo, biological, chemical, cruiseid, data, dataset, day, depth, depth_w, dmo, downwelling, downwelling_photosynthetic_photon_radiance_in_sea_water, dyn, DYN_HT, earth, Earth Science > Oceans > Ocean Optics > Photosynthetically Active Radiation, Earth Science > Oceans > Ocean Optics > Radiance, erddap, flvolt, laboratory, latitude, longitude, management, month, name, O2, O2_temp, O2_v, O2S, ocean, oceanography, oceans, office, optics, oxygen, PAR, photon, photosynthetic, photosynthetically, potemp, preliminary, press, radiance, radiation, sal, satellite, science, sea, seawater, sigma, sigma_0, sp_vol_an, station, station_name, temperature, time, time2, trans, trans_v, v, vol, water, year";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/2462/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/2462";
    Float64 Northernmost_Northing 44.675;
    String param_mapping "{'2462': {'lat': 'master - latitude', 'press': 'flag - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/2462/parameters";
    String people_0_affiliation "Oregon State University";
    String people_0_affiliation_acronym "OSU-CEOAS";
    String people_0_person_name "Hal Batchelder";
    String people_0_person_nid "50383";
    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 38.7977;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "CTD data from California Current System (CCS) Process/Mesoscale Cruises on the R/Vs New Horizon, Revelle, Thompson, and Wecoma in the Northeast Pacific from 2000-2002 as part of the U.S. GLOBEC program.";
    String title "[ccs_proc_CTD] - CTD data from California Current System (CCS) Process/Mesoscale Cruises on the R/Vs New Horizon, Revelle, Thompson, and Wecoma in the Northeast Pacific from 2000-2002 as part of the U.S. GLOBEC program (NEP project) (U.S. GLOBEC Northeast Pacific)";
    String version "1";
    Float64 Westernmost_Easting -126.1972;
    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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