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Dataset Title:  Profile data from WireWalker deployments at Mission Beach, California in 2016
at a 50m depth
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_742124)
Range: depth = 0.0 to 42.75m, time = 2016-06-13T17:56Z to 2016-06-28T14:50Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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[The graph you specified. Please be patient.]


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 {
  dnum {
    Float64 _FillValue NaN;
    Float64 actual_range 736494.747862654, 736509.618519454;
    String bcodmo_name "DateTime";
    String description "Matlab time/date format (datenum, UTC)";
    String long_name "Dnum";
    String units "unitless";
  date {
    String bcodmo_name "date";
    String description "Date (UTC) in format 'yyyy-mm-dd'";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String time_precision "1970-01-01";
    String units "unitless";
  time2 {
    String bcodmo_name "time";
    String description "Time (UTC) in format 'HH:MM:SS'";
    String long_name "Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.46584056e+9, 1.4671254e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Timestamp (UTC) in standard ISO 8601:2004(E) format YYYY-mm-ddTHH:MMZ";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String source_name "ISO_DateTime_UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 42.75;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "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";
  mask {
    Byte _FillValue 127;
    Byte actual_range 1, 1;
    String bcodmo_name "q_flag";
    Float64 colorBarMaximum 150.0;
    Float64 colorBarMinimum 0.0;
    String description "Mask (values 0 or 1) indicating the reliability of interpolated values. NaN values in the mask indicate times when there was a significant gap between profiles, and where the interpolation may be less reliable. For best data, one should focus on points when the mask value is equal to 1.";
    String long_name "Mask";
    String units "unitless";
  DO {
    Float32 _FillValue NaN;
    Float32 actual_range 9.076, 132.262;
    String bcodmo_name "dissolved Oxygen";
    String description "dissolved oxygen saturation";
    String long_name "DO";
    String units "percent (%)";
  B {
    Float32 _FillValue NaN;
    Float32 actual_range 97.063, 1659.433;
    String bcodmo_name "Acc_bksctr";
    String description "backscatter";
    String long_name "B";
    String units "counts";
  chl {
    Float32 _FillValue NaN;
    Float32 actual_range 53.372, 1098.083;
    String bcodmo_name "chlorophyll a";
    String description "chlorophyll (fluorescence)";
    String long_name "CHL";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "counts";
  phyco {
    Float32 _FillValue NaN;
    Float32 actual_range 5.201, 56.334;
    String bcodmo_name "phyco";
    String description "phycoerythrin";
    String long_name "Phyco";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHYCSPP4/";
    String units "counts";
  C {
    Float32 _FillValue NaN;
    Float32 actual_range 36.927, 48.024;
    String bcodmo_name "conductivity";
    String description "conductivity";
    String long_name "C";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/CNDC/";
    String units "millisiemens per centimeter (mS/cm)";
  T {
    Float32 _FillValue NaN;
    Float32 actual_range 10.093, 21.906;
    String bcodmo_name "temperature";
    String description "temperature";
    String long_name "T";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  P {
    Float32 _FillValue NaN;
    Float32 actual_range 0.5, 42.25;
    String bcodmo_name "pressure";
    String description "pressure";
    String long_name "P";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
    String units "decibars (dbar)";
  S {
    Float32 _FillValue NaN;
    Float32 actual_range 33.144, 34.94;
    String bcodmo_name "sal";
    String description "salinity";
    String long_name "S";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "Practical Salinity Units (PSU)";
  rho {
    Float32 _FillValue NaN;
    Float32 actual_range 1023.124, 1026.139;
    String bcodmo_name "density";
    String description "density";
    String long_name "Rho";
    String units "kilograms per meter cubed (kg/m3)";
  n2 {
    String bcodmo_name "unknown";
    String description "buoyancy frequency";
    String long_name "N2";
    String units "per seconds squared (s-2)";
  dPt {
    Float32 _FillValue NaN;
    Float32 actual_range -1.32, 7.415;
    String bcodmo_name "unknown";
    String description "dPdt";
    String long_name "D PT";
    String units "decibars per second (dbar/s)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Instruments were mounted on a WireWalker profiler
and data collected during ascent only. The interval between profiles was
dependent on sea state.\\u00a0The WireWalker instrument was deployed on 50-m
depth contour off Mission Beach, CA near a thermistor chain and in line with
Internal Waves on the Continental Margin (IWAVES) stations.\\u00a0For more
information about\\u00a0IWAVES\\u00a0stations see\\u00a0Lerczark, 2001.
    String awards_0_award_nid "652178";
    String awards_0_award_number "OCE-1459393";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1459393";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
  PI: Peter Franks 
  Data version 1: 2018-07-24";
    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 "2018-07-24T19:23:31Z";
    String date_modified "2020-01-02T16:52:04Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.742124.1";
    Float64 geospatial_vertical_max 42.75;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-11-25T13:29:36Z (local files)
2020-11-25T13:29:36Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_742124.das";
    String infoUrl "https://www.bco-dmo.org/dataset/742124";
    String institution "BCO-DMO";
    String instruments_0_acronym "Fluorometer";
    String instruments_0_dataset_instrument_nid "742519";
    String instruments_0_description "A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/113/";
    String instruments_0_instrument_name "Fluorometer";
    String instruments_0_instrument_nid "484";
    String instruments_0_supplied_name "WET Labs fluorometer and ECO puck";
    String instruments_1_acronym "Dissolved Oxygen Sensor";
    String instruments_1_dataset_instrument_nid "742548";
    String instruments_1_description "An electronic device that measures the proportion of oxygen (O2) in the gas or liquid being analyzed";
    String instruments_1_instrument_name "Dissolved Oxygen Sensor";
    String instruments_1_instrument_nid "705";
    String instruments_1_supplied_name "RINKO III";
    String instruments_2_dataset_instrument_nid "742518";
    String instruments_2_description "Electronic devices that record data over time or in relation to location either with a built-in instrument or sensor or via external instruments and sensors.";
    String instruments_2_instrument_name "Data Logger";
    String instruments_2_instrument_nid "731353";
    String instruments_2_supplied_name "RBRMaestro";
    String keywords "bco, bco-dmo, biological, chemical, chl, chlorophyll, data, dataset, date, depth, dmo, dnum, dPt, erddap, iso, management, mask, oceanography, office, phyco, preliminary, rho, time, time2";
    String license "https://www.bco-dmo.org/dataset/742124/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/742124";
    String param_mapping "{'742124': {'depth': 'master - depth', 'ISO_DateTime_UTC': 'master - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/742124/parameters";
    String people_0_affiliation "University of California-San Diego";
    String people_0_affiliation_acronym "UCSD-SIO";
    String people_0_person_name "Peter Franks";
    String people_0_person_nid "652182";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-San Diego";
    String people_1_affiliation_acronym "UCSD-SIO";
    String people_1_person_name "Andrew J Lucas";
    String people_1_person_nid "51684";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of California-San Diego";
    String people_2_affiliation_acronym "UCSD-SIO";
    String people_2_person_name "Jessica C Garwood";
    String people_2_person_nid "742127";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Amber York";
    String people_3_person_nid "643627";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "QuIPP";
    String projects_0_acronym "QuIPP";
    String projects_0_description 
"Coastal waters are among the most heavily used and threatened systems on the planet. Successful prediction and management of coastal resources can only come from a deep understanding of the dynamics of the species in these regions. Fluctuations of coastal invertebrate and vertebrate populations are often driven by the supply of planktonic larvae to the adult habitat by ocean currents. Numerous studies have associated the cross-shelf transport of plankton - including the larvae of economically valuable species - with the internal tide: a wave in the ocean's interior that oscillates at the tidal frequency. Though the interactions of plankton with internal waves have been studied for decades, it has not been possible to track individual plankton underwater. Thus, the dynamics underlying the cross-shelf transport of plankton in internal waves and internal tides remain conjectural. This project will use undersea swarms of novel, autonomous plankton-mimicking drifting robots to quantify, in situ, the cross-shore transport of plankton driven by high-frequency internal waves and the internal tide. This research will significantly enhance our understanding of the distributions, settling patterns, and population connectivity of coastal species. One PhD student will be supported and educational outreach in collaboration with the Ocean Discovery Program in San Diego will support curricula creation, after-school programs, and teacher development.
These researchers have recently gained the capability to deploy swarms of plankton-mimicking, autonomous, drifting robots in the ocean. These robots, Autonomous Underwater Explorers (AUEs), are 1.5-liter cylinders with temperature and pressure sensors, a hydrophone, and a piston that regulates buoyancy. Subsurface three-dimensional localization is accomplished through an acoustic long-baseline navigation system. The three-dimensional position of each AUE is obtained every 12 seconds with ~1 m horizontal and";
    String projects_0_end_date "2018-06";
    String projects_0_name "Quantifying plankton dynamics in the internal tide using swarms of buoyancy-controlled robots";
    String projects_0_project_nid "652179";
    String projects_0_start_date "2015-07";
    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 "Profile data from WireWalker deployments at Mission Beach, California in 2016 at a 50m depth.";
    String time_coverage_end "2016-06-28T14:50Z";
    String time_coverage_start "2016-06-13T17:56Z";
    String title "Profile data from WireWalker deployments at Mission Beach, California in 2016 at a 50m depth";
    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
For example,
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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