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Dataset Title:  Biogeochemical data collected during the Flower Garden Banks Rapid Response
Cruise, FGB-RR16, on R/V Manta in the Flower Garden Banks National Marine
Sanctuary from July to August 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_787575)
Range: longitude = -93.93 to -93.517°E, latitude = 27.75 to 28.033°N, depth = 0.7 to 241.2m, time = 2016-07-31T14:03:35Z to (now?)
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 {
  Cast {
    String bcodmo_name "cast";
    String description "cast number";
    String long_name "Cast";
    String units "unitless";
  }
  Salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 31.36, 36.46;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "salinity";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.7, 241.2;
    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";
  }
  Date {
    String bcodmo_name "date";
    String description "Date; format: yyyy-mm-dd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  GMT_Time {
    String bcodmo_name "time_gmt";
    String description "Time (GMT); format: hh:mm:ss";
    String long_name "GMT Time";
    String units "unitless";
  }
  Local_Time {
    String bcodmo_name "time_local";
    String description "Local time; format: hh:mm:ss";
    String long_name "Local Time";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 27.75, 28.033;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude";
    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 -93.93, -93.517;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Temp {
    Float32 _FillValue NaN;
    Float32 actual_range 14.23, 31.89;
    String bcodmo_name "temperature";
    String description "temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  DIC {
    Float32 _FillValue NaN;
    Float32 actual_range 1967.75, 2189.22;
    String bcodmo_name "DIC";
    String description "dissolved inorganic carbon";
    String long_name "DIC";
    String units "micromoles per kilogram (umol kg-1)";
  }
  TA {
    Float32 _FillValue NaN;
    Float32 actual_range 2283.84, 2405.74;
    String bcodmo_name "TALK";
    String description "total alkalinity";
    String long_name "TA";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP014/";
    String units "micromoles per kilogram (umol kg-1)";
  }
  pH {
    Float32 _FillValue NaN;
    Float32 actual_range 7.9, 8.09;
    String bcodmo_name "pH";
    Float64 colorBarMaximum 9.0;
    Float64 colorBarMinimum 7.0;
    String description "pH";
    String long_name "Sea Water Ph Reported On Total Scale";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
    String units "total scale";
  }
  fCO2 {
    Float32 _FillValue NaN;
    Float32 actual_range 360.1, 583.9;
    String bcodmo_name "fugacity of CO2";
    String description "carbon dioxide fugacity";
    String long_name "F CO2";
    String units "microatmospheres (uatm)";
  }
  Omega_Ar {
    Float32 _FillValue NaN;
    Float32 actual_range 1.8, 4.02;
    String bcodmo_name "OM_ar";
    String description "aragonite saturation state";
    String long_name "Omega Ar";
    String units "unitless";
  }
  p_dens {
    Float32 _FillValue NaN;
    Float32 actual_range 18.36, 26.79;
    String bcodmo_name "density";
    String description "potenial density";
    String long_name "P Dens";
    String units "kilograms per cubic meter (kg m-3)";
  }
  O2 {
    Float32 _FillValue NaN;
    Float32 actual_range 1.84, 4.76;
    String bcodmo_name "dissolved Oxygen";
    String description "dissolved oxygen";
    String long_name "O2";
    String units "milliliters per liter (ml l-1)";
  }
  NO3 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 73.2;
    String bcodmo_name "NO3";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "nitrate";
    String long_name "Mole Concentration Of Nitrate In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/NTRAIGGS/";
    String units "micromolar (uM)";
  }
  HPO4 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 2.91;
    String bcodmo_name "PO4";
    String description "phosphate";
    String long_name "HPO4";
    String units "micromolar (uM)";
  }
  HSIO3 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.47, 31.56;
    String bcodmo_name "SiO3";
    String description "silicate";
    String long_name "HSIO3";
    String units "micromolar (uM)";
  }
  NH4 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 50.7;
    String bcodmo_name "Ammonium";
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String description "ammonia";
    String long_name "Mole Concentration Of Ammonium In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AMONAAZX/";
    String units "micromolar (uM)";
  }
  NO2 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.08;
    String bcodmo_name "NO2";
    Float64 colorBarMaximum 1.0;
    Float64 colorBarMinimum 0.0;
    String description "nitrite";
    String long_name "Mole Concentration Of Nitrite In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/NTRIAAZX/";
    String units "micromolar (uM)";
  }
  Urea {
    Float32 _FillValue NaN;
    Float32 actual_range 0.14, 19.94;
    String bcodmo_name "Urea";
    String description "urea";
    String long_name "Urea";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/UREAAAZX/";
    String units "micromolar (uM)";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.469973815e+9, NaN;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and time (GMT) formatted to ISO 8601 standard. Format: yyyy-mm-ddTHH:MM:SSZ";
    String ioos_category "Time";
    String long_name "ISO Date Time GMT";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"The CTD (SBE-25) was equipped with 6 4L niskin bottles and was used to measure
temperature and salinity. Niskins were used to collect water samples for
carbonate chemistry (i.e., DIC and TA), oxygen, and nutrients. Water samples
for DIC and TA were collected according to the methods in Dickson et al.
(2007), and analyzed at TAMU using a VINDTA 3C. Certified Reference Materials
(CRMs) were provided by A. Dickson at Scripps Institute of Oceanography
(Dickson et al. 2007) and were used to calibrate for TA and DIC. The
reproducibility of these samples was 1.43 \\u00b1 1.07 \\u03bcmol kg-1 for TA
and 2.64 \\u00b1 1.24 \\u03bcmol kg-1 for DIC. Dissolved oxygen (DO) was
measured using Winkler titrations. After collecting the water from the Niskin
into flasks, aliquots of manganese chloride and sodium hydroxide-sodium iodide
were added. The titration was performed directly after water collection using
sodium thiosulfate; Winkler titration was performed with an amperometric dead-
stop endpoint determination with a double platinum electrode. Nutrient samples
(nitrate, nitrite, ammonium, phosphate, and silicate) were collected into
polycarbonate flasks after filtration through GF/C 0.7-um pore size filters,
frozen, and analyzed ashore using standard World Ocean Circulation Experiment
(WOCE) segmented flow methodologies using an Astoria Analyzer (Astoria-
Pacific) (Gordon 1994 ).
 
Sampling gaps are reported as \\\"nd\\\" in the dataset.";
    String awards_0_award_nid "746819";
    String awards_0_award_number "OCE-1800913";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1800913";
    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 "Daniel Thornhill";
    String awards_0_program_manager_nid "722161";
    String cdm_data_type "Other";
    String comment 
"Biogeochemical data 
   collected during the Flower Garden Banks Rapid Response Cruise 
  PI: K. Shamberger (Texas A&M) 
  Version date: 17 Jan 2020";
    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 "2020-01-16T19:59:26Z";
    String date_modified "2020-02-06T21:25:33Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.787575.1";
    Float64 Easternmost_Easting -93.517;
    Float64 geospatial_lat_max 28.033;
    Float64 geospatial_lat_min 27.75;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -93.517;
    Float64 geospatial_lon_min -93.93;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 241.2;
    Float64 geospatial_vertical_min 0.7;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2020-10-31T22:22:48Z (local files)
2020-10-31T22:22:48Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_787575.das";
    String infoUrl "https://www.bco-dmo.org/dataset/787575";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_nid "787751";
    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 "4L niskin bottles";
    String instruments_1_acronym "CTD SBE 25";
    String instruments_1_dataset_instrument_nid "787750";
    String instruments_1_description "The Sea-Bird SBE 25 SEALOGGER CTD is battery powered and is typically used to record data in memory, eliminating the need for a large vessel, electrical sea cable, and on-board computer. All SBE 25s can also operate in real-time, transmitting data via an opto-isolated RS-232 serial port. Temperature and conductivity are measured by the SBE 3F Temperature sensor and SBE 4 Conductivity sensor (same as those used on the premium SBE 9plus CTD). The SBE 25 also includes the SBE 5P (plastic) or 5T (titanium) Submersible Pump and TC Duct. The pump-controlled, TC-ducted flow configuration significantly reduces salinity spiking caused by ship heave, and in calm waters allows slower descent rates for improved resolution of water column features. Pressure is measured by the modular SBE 29 Temperature Compensated Strain-Gauge Pressure sensor (available in eight depth ranges to suit the operating depth requirement). The SBE 25's modular design makes it easy to configure in the field for a wide range of auxiliary sensors, including optional dissolved oxygen (SBE 43), pH (SBE 18 or SBE 27), fluorescence, transmissivity, PAR, and optical backscatter sensors. More information from Sea-Bird Electronics: http:www.seabird.com.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0040/";
    String instruments_1_instrument_name "CTD Sea-Bird 25";
    String instruments_1_instrument_nid "421";
    String instruments_1_supplied_name "CTD SBE-25";
    String instruments_2_acronym "Nutrient Autoanalyzer";
    String instruments_2_dataset_instrument_nid "787754";
    String instruments_2_description "Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified.  In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB04/";
    String instruments_2_instrument_name "Nutrient Autoanalyzer";
    String instruments_2_instrument_nid "558";
    String instruments_2_supplied_name "Astoria Analyzer";
    String instruments_3_acronym "Winkler Titrator";
    String instruments_3_dataset_instrument_nid "787753";
    String instruments_3_description "A Winkler Oxygen Titration system is used for determining concentration of dissolved oxygen in seawater.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12/";
    String instruments_3_instrument_name "Winkler Oxygen Titrator";
    String instruments_3_instrument_nid "588";
    String instruments_3_supplied_name "Winkler titration";
    String instruments_4_acronym "inorganic carbon and alkalinity analyser";
    String instruments_4_dataset_instrument_nid "787752";
    String instruments_4_description "The Versatile INstrument for the Determination of Total inorganic carbon and titration Alkalinity (VINDTA) 3C is a laboratory alkalinity titration system combined with an extraction unit for coulometric titration, which simultaneously determines the alkalinity and dissolved inorganic carbon content of a sample. The sample transport is performed with peristaltic pumps and acid is added to the sample using a membrane pump. No pressurizing system is required and only one gas supply (nitrogen or dry and CO2-free air) is necessary. The system uses a Metrohm Titrino 719S, an ORION-Ross pH electrode and a Metrohm reference electrode. The burette, the pipette and the analysis cell have a water jacket around them. Precision is typically +/- 1 umol/kg for TA and/or DIC in open ocean water.";
    String instruments_4_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0481/";
    String instruments_4_instrument_name "MARIANDA VINDTA 3C total inorganic carbon and titration alkalinity analyser";
    String instruments_4_instrument_nid "686";
    String instruments_4_supplied_name "VINDTA 3C";
    String keywords "ammonia, ammonium, bco, bco-dmo, biological, carbon, carbon dioxide, cast, chemical, chemistry, co2, concentration, data, dataset, date, dens, density, depth, dic, dioxide, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Ammonia, Earth Science > Oceans > Ocean Chemistry > Nitrate, Earth Science > Oceans > Ocean Chemistry > pH, Earth Science > Oceans > Salinity/Density > Salinity, erddap, fCO2, GMT_Time, hpo4, hsio3, iso, ISO_DateTime_GMT, latitude, local, Local_Time, longitude, management, mole, mole_concentration_of_ammonium_in_sea_water, mole_concentration_of_nitrate_in_sea_water, mole_concentration_of_nitrite_in_sea_water, n02, nh4, nitrate, nitrite, NO2, no3, O2, ocean, oceanography, oceans, office, omega, Omega_Ar, oxygen, p_dens, practical, preliminary, reported, salinity, scale, science, sea, sea_water_ph_reported_on_total_scale, sea_water_practical_salinity, seawater, Temp, temperature, time, total, urea, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/787575/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/787575";
    Float64 Northernmost_Northing 28.033;
    String param_mapping "{'787575': {'ISO_DateTime_GMT': 'flag - time', 'Lat': 'flag - latitude', 'Depth': 'flag - depth', 'Long': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/787575/parameters";
    String people_0_affiliation "Texas A&M University";
    String people_0_affiliation_acronym "TAMU";
    String people_0_person_name "Kathryn E.F. Shamberger";
    String people_0_person_nid "488857";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Hawaii";
    String people_1_person_name "Andrea Kealoha";
    String people_1_person_nid "787663";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String project "Rapid Reefs Harvey";
    String projects_0_acronym "Rapid Reefs Harvey";
    String projects_0_description 
"NSF Award Abstract:
Coral reefs are ecologically and economically important ecosystems, and are threatened by a variety of global (climate change) and local (overfishing, pollution) stressors. Anthropogenic climate change is increasing the frequency and severity of storms, which can physically damage reef structures and reduce reef health through changes in seawater quality. In August of 2017, Hurricane Harvey caused widespread flooding in southeast Texas when it released more than 50 trillion liters of rain, which then accumulated along the Texas Shelf. This runoff is expected to impact nearby coral reefs in the Flower Garden Banks National Marine Sanctuary (FGBNMS, northwest Gulf of Mexico) via eddies and jets that transport coastal waters offshore. Findings from this project will allow managers to quickly predict whether extreme storm events are likely to induce reef mortality and ecosystem decline due to freshwater accumulation, by tracking of low salinity water masses coupled with microbial community characterization and metrics of coral health. These data are critical to managing coastal ecosystems, including the high coral cover reefs in the FGBNMS, and will help stakeholders (e.g., diving and fishing communities) plan for and minimize disruption to their livelihoods following these storms. Results will be communicated broadly across scientific arenas, in graduate and undergraduate education and training programs, and to the general public through outreach. The investigators have seven 7 square meter 2-D Reef Replicas from 2014 depicting representative FGBNMS reef bottoms, and will construct additional 2-D Reef Replicas from both banks following the arrival of Harvey runoff, allowing the public to directly experience and quantify the effects of Hurricane Harvey on local reefs using quadrats and identification guides. This project will also synergize with NSF REU programs at Boston University and Texas A&M University, providing transformative research experiences for undergraduates. One post-doctoral scholar, four graduate students, a technician and more than 5 undergraduates will be involved in all aspects of the research. All datasets will be made freely available to the public, and will serve as an important set of baselines for future lines of inquiry into the processes by which hurricanes and other extreme storms impact reef health.
Hurricanes and other extreme storm events can decimate coral reefs through wave-driven physical damage. Freshwater runoff from extreme storms is also potentially detrimental to reefs but has received comparatively less attention. This research will provide unprecedented resolution on how hurricanes and other extreme storm events may trigger cascading interactions among water chemistry, declines in metazoan health and shifts in their associated microbial communities, ultimately resulting in coral reef decline. The freshwater runoff initiated by Hurricane Harvey is likely to impact reefs within the FGBNMS, one of the few remaining coral-dominated reefs in the greater Caribbean. The effects of Harvey runoff will be compared to a previously documented storm-driven runoff event that was associated with invertebrate mortality on the same reef system. Sampling seawater chemistry, microbial communities (water column and benthic), and host gene expression and proteomics before, immediately after, and six months after Harvey runoff enters the FGBNMS will allow us to identify commonalities among large-scale freshwater runoff events and track the response of benthic invertebrate health, microbial community diversity, and the trajectory of reef community recovery or decline. The investigators will determine if changes in water chemistry induce pelagic microbial shifts, if microbial communities typically associated with corals and sponges are altered, and whether feedbacks occur between these potential drivers of benthic invertebrate mortality.";
    String projects_0_end_date "2019-11";
    String projects_0_geolocation "Flower Garden Banks National Marine Sanctuary, Northwest Gulf of Mexico";
    String projects_0_name "RAPID: Collaborative Research: Impact of freshwater runoff from Hurricane Harvey on coral reef benthic organisms and associated microbial communities";
    String projects_0_project_nid "746814";
    String projects_0_start_date "2017-12";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 27.75;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset combines the biogeochemical data collected during the Flower Garden Banks Rapid Response Cruise which occurred following the discovery of the localized mortality event.";
    String time_coverage_start "2016-07-31T14:03:35Z";
    String title "Biogeochemical data collected during the Flower Garden Banks Rapid Response Cruise, FGB-RR16, on R/V Manta in the Flower Garden Banks National Marine Sanctuary from July to August 2016";
    String version "1";
    Float64 Westernmost_Easting -93.93;
    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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