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Dataset Title:  Abundance and size distribution of marine snow aggregates from profiles
conducted during R/V Polar Star cruises in the Ross Sea, Antarctica between
2001 and 2005.
  RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_719478)
Range: longitude = -178.771 to 180.0°E, latitude = -77.668 to -76.4095°N, depth = 22.88 to 671.66m, time = 2001-12-22T08:32:00Z 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

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cruise_name {
    String description "Name of the cruise which includes the  year  number and sequence number (For example, IVARS 1-1 is the first year and the first of two cruise)";
    String ioos_category "Unknown";
    String long_name "Cruise Name";
    String units "unitless";
  }
  Canister {
    String description "An internal reference to the film canister, if applicable.  This is included to enable future resarchers to positively identify the correct film";
    String ioos_category "Unknown";
    String long_name "Canister";
    String units "unitless";
  }
  Station {
    String description "Station number as assigned during the cruise.  Many are at the same location but individual numbers are used to allow separation based on time";
    String ioos_category "Identifier";
    String long_name "Station";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -77.668, -76.4095;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude. Negative = South";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -178.771, 180.0;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude. Negative = West";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 22.88, 671.66;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  date_local {
    String description "Calendar Date in local (Christchurch, NZ) (NZST/NZDT)";
    String ioos_category "Time";
    String long_name "Date Local";
    String source_name "date_local";
    String units "unitless";
  }
  In_water_time_local {
    String description "Local time (HH:MM:SS) when the camera lowering began. Local time (Christchurch, NZ) (NZST/NZDT)";
    String ioos_category "Time";
    String long_name "In Water Time Local";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.00900992e+9, NaN;
    String axis "T";
    String description "Timestamp (UTC) when the camera lowering began in standard ISO 8601:2004(E) format YYYY-mm-ddTHH:MM:SSZ";
    String ioos_category "Time";
    String long_name "In Water Date Time UTC";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  particles_per_L {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1507.92;
    String description "Total number of particles larger than 0.5mm in diameter per liter number/liter";
    String ioos_category "Unknown";
    String long_name "Particles Per L";
    String units "count";
  }
  bin_0_0_to_0_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 164.51;
    String description "Number of particles per liter number/liter between 0 and 0.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin 0 0 To 0 5";
    String units "count";
  }
  bin_gt_0_5_to_1_0 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 905.56;
    String description "Number of particles per liter number/liter between 0.5 and 1.0mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 0 5 To 1 0";
    String units "count";
  }
  bin_gt_1_0_to_1_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 302.97;
    String description "Number of particles per liter number/liter between 1.0 and 1.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 1 0 To 1 5";
    String units "count";
  }
  bin_gt_1_5_to_2_0 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 92.83;
    String description "Number of particles per liter number/liter between 1.5 and 2.0mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 1 5 To 2 0";
    String units "count";
  }
  bin_gt_2_0_to_2_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 40.56;
    String description "Number of particles per liter number/liter between 2.0 and 2.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 2 0 To 2 5";
    String units "count";
  }
  bin_gt_2_5_to_3_0 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 16.22;
    String description "Number of particles per liter number/liter between 2.5 and 3.0mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 2 5 To 3 0";
    String units "count";
  }
  bin_gt_3_0_to_3_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 8.11;
    String description "Number of particles per liter number/liter between 3.0 and 3.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 3 0 To 3 5";
    String units "count";
  }
  bin_gt_3_5_to_4_0 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 5.16;
    String description "Number of particles per liter number/liter between 3.5 and 4.0mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 3 5 To 4 0";
    String units "count";
  }
  bin_gt_4_0_to_4_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 4.06;
    String description "Number of particles per liter number/liter between 4.0 and 4.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 4 0 To 4 5";
    String units "count";
  }
  bin_gt_4_5 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 52.36;
    String description "Number of particles per liter number/liter larger than 4.5mm in size";
    String ioos_category "Unknown";
    String long_name "Bin Gt 4 5";
    String units "count";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Methodology:
 
A marine snow imaging system was lowered through the water column to acquire
photographs of aggregates. The imaging system consisted of a collimated strobe
system and either a 35-mm film camera (Lobsiger Deepslope 6000; Years 1 - 3)
or a digital camera (Insite Pacific Scorpio; Year 4) mounted on an aluminum
frame. The system was lowered at a rate of 10 m min-1 through the water
column, acquiring ca. six images min-1 at an interval of ca. 1.7 m throughout
the entire water column. Illumination was provided by a pair of strobe lights
(Deep Sea Power and Light) positioned to produce an 8.4-cm deep beam of
uniform, collimated light 66 or 79 cm from the camera lens (Fig. 2).
Aggregates larger than 0.5 mm within this volume (3 - 15 L, depending on the
camera, lens and resultant geometry) are quantified from images taken by a
camera that is mounted perpendicular to the long axis of the light beam, which
can subsequently be distinguished and quantified by digital analysis. Ambient
light illuminates particles in front of and behind this light beam and
invalidates the calculation of illuminated volume. Thus, profiles were
obtained near local midnight whenever possible (24-h photoperiods occurred
throughout all cruises) to minimize this interference; images with the frame
visible, due to ambient light, were discarded. The depth of first aggregate
counts ranged from 30 - 88 m (a function of water clarity and solar angle). A
Sea-Bird SeaCat CTD and 25-cm SeaTech transmissometer mounted on the camera
frame provided continuous measurements of temperature, salinity and optical
transmission. These data were used to calculate the depth at which each image
was acquired. All film (Tmax 400) and images were returned to the laboratory
for processing except for short sections viewed at sea to assess camera
operation. The films were developed and then digitized to JPG format either in
house, using a Nikon camera and macro lens (3767 x 2368), or commercially
(3544 x 2341).";
    String awards_0_award_nid "686845";
    String awards_0_award_number "PLR-0087401";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0087401";
    String awards_0_funder_name "NSF Division of Polar Programs";
    String awards_0_funding_acronym "NSF PLR";
    String awards_0_funding_source_nid "490497";
    String awards_0_program_manager "Dr Roberta Marinelli";
    String awards_0_program_manager_nid "51469";
    String cdm_data_type "Other";
    String comment 
"Particles per liter 
  PI: Vernon Asper 
  Data Version 1: 2019-05-28";
    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 2.2d  13 Jun 2019";
    String date_created "2017-11-16T20:55:23Z";
    String date_modified "2019-06-13T15:32:39Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.719478.1";
    Float64 Easternmost_Easting 180.0;
    Float64 geospatial_lat_max -76.4095;
    Float64 geospatial_lat_min -77.668;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 180.0;
    Float64 geospatial_lon_min -178.771;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 671.66;
    Float64 geospatial_vertical_min 22.88;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2019-07-23T11:48:31Z (local files)
2019-07-23T11:48:31Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_719478.das";
    String infoUrl "https://www.bco-dmo.org/dataset/719478";
    String institution "BCO-DMO";
    String instruments_0_acronym "Sea Tech Transmissometer";
    String instruments_0_dataset_instrument_nid "770287";
    String instruments_0_description "The Sea Tech Transmissometer can be deployed in either moored or profiling mode to estimate the concentration of suspended or particulate matter in seawater. The transmissometer measures the beam attenuation coefficient in the red spectral band (660 nm) of the laser lightsource over the instrument's path-length (e.g. 20 or 25 cm).  This instrument designation is used when specific make and model are not known. The Sea Tech Transmissometer was manufactured by Sea Tech, Inc. (Corvalis, OR, USA).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0003/";
    String instruments_0_instrument_name "Sea Tech Transmissometer";
    String instruments_0_instrument_nid "476";
    String instruments_1_acronym "CTD SEACAT";
    String instruments_1_dataset_instrument_nid "770288";
    String instruments_1_description "The CTD SEACAT recorder is an instrument package manufactured by Sea-Bird Electronics. The first Sea-Bird SEACAT Recorder was the original SBE 16 SEACAT developed in 1987. There are several model numbers including the SBE 16plus (SEACAT C-T Recorder (P optional))and the SBE 19 (SBE 19plus SEACAT Profiler measures conductivity, temperature, and pressure (depth)). More information from Sea-Bird Electronics.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/350/";
    String instruments_1_instrument_name "CTD Sea-Bird SEACAT";
    String instruments_1_instrument_nid "479";
    String instruments_2_acronym "camera";
    String instruments_2_dataset_instrument_description "see methodology";
    String instruments_2_dataset_instrument_nid "719486";
    String instruments_2_description "All types of photographic equipment including stills, video, film and digital systems.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/311/";
    String instruments_2_instrument_name "Camera";
    String instruments_2_instrument_nid "520";
    String instruments_2_supplied_name "Custom-built marine snow imaging system";
    String keywords "bco, bco-dmo, bin, bin_0_0_to_0_5, bin_gt_0_5_to_1_0, bin_gt_1_0_to_1_5, bin_gt_1_5_to_2_0, bin_gt_2_0_to_2_5, bin_gt_2_5_to_3_0, bin_gt_3_0_to_3_5, bin_gt_3_5_to_4_0, bin_gt_4_0_to_4_5, bin_gt_4_5, biological, canister, chemical, cruise, cruise_name, data, dataset, date, depth, dmo, erddap, identifier, In_water_DateTime_UTC, In_water_time_local, latitude, local, longitude, management, name, oceanography, office, particles, particles_per_L, per, preliminary, station, time, water";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/719478";
    Float64 Northernmost_Northing -76.4095;
    String param_mapping "{'719478': {'Latitude': 'flag - latitude', 'In_water_DateTime_UTC': 'master - time', 'depth': 'flag - depth', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/719478/parameters";
    String people_0_affiliation "University of Southern Mississippi";
    String people_0_person_name "Dr Vernon L. Asper";
    String people_0_person_nid "50598";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Virginia Institute of Marine Science";
    String people_1_affiliation_acronym "VIMS";
    String people_1_person_name "Walker O. Smith";
    String people_1_person_nid "50593";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Amber York";
    String people_2_person_nid "643627";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Interannual Variability in the Antarctic-Ross Sea (IVARS): Nutrients and Seasonal Production";
    String projects_0_acronym "IVARS";
    String projects_0_description 
"NSF Award Abstract:
During the past few decades of oceanographic research, it has been recognized that significant variations in biogeochemical processes occur among years. Interannual variations in the Southern Ocean are known to occur in ice extent and concentration, in the composition of herbivore communities, and in bird and marine mammal distributions and reproductive success. However, little is known about the interannual variations in production of phytoplankton or the role that these variations play in the food web. This project will collect time series data on the seasonal production of phytoplankton in the southern Ross Sea, Antarctica. Furthermore, it will assess the interannual variations of the production of the two major functional groups of the system, diatoms and Phaeocystis Antarctica, a colonial haptophyte. The Ross Sea provides a unique setting for this type of investigation for a number of reasons. For example, a de facto time-series has already been initiated in the Ross Sea through the concentration of a number of programs in the past ten years. It also is well known that the species diversity is reduced relative to other systems and its seasonal production is as great as anywhere in the Antarctic. Most importantly, seasonal production of both the total phytoplankton community (as well as its two functional groups) can be estimated from late summer nutrient profiles. The project will involve short cruises on the US Coast Guard ice breakers in the southern Ross Sea that will allow the collection of water column nutrient and particulate after data at specific locations in the late summer of each of five years. Additionally, two moorings with in situ nitrate analyzers moored at fifteen will be deployed, thus collecting for the first time in the in the Antarctic a time-series of euphotic zone nutrient concentrations over the entire growing season. All nutrient data will be used to calculate seasonal production for each year in the southern Ross Sea and compared to previously collected information, thereby providing an assessment of interannual variations in net community production. Particulate matter data will allow us to estimate the amount of export from the surface layer by late summer, and therefore calculate the interannual variability of this ecosystem process. Interannual variations of seasonal production (and of the major taxa of producers) are a potentially significant feature in the growth and survival of higher trophic levels within the food web of the Ross Sea. They are also important in order to understand the natural variability in biogeochemical processes of the region. Because polar regions such as the Ross Sea are predicted to be impacted by future climate change, biological changes are also anticipated. Placing these changes in the context of natural variability is an essential element of understanding and predicting such alterations. This research thus seeks to quantify the natural variability of an Antarctic coastal system, and ultimately understand its causes and impacts on food webs and biogeochemical cycles of the Ross Sea.
Related publications:Smith, W.O., Jr., M.S. Dinniman, J.M. Klinck, and E. Hofmann. 2003. Biogeochemical climatologies in the Ross Sea, Antarctica: seasonal patterns of nutrients and biomass. Deep-Sea Res. II 50: 3083-3101.
Smith, W.O., Jr., A.R. Shields, J.A. Peloquin, G. Catalano, S. Tozzi, M.S. Dinniman and V.A. Asper. 2006. Biogeochemical budgets in the Ross Sea:� variations among years. Deep-Sea Res. II 53: 815-833.
Tremblay, J.-E. and W.O. Smith, Jr.� 2007. Phytoplankton processes in polynyas.� In:� Polynyas: Windows to the World’s Oceans (W.O. Smith, Jr. and D.G. Barber, eds.), Elsevier, Amsterdam, Pp. 239-270.
Smith, W.O. Jr. and D.G. Barber (Eds.).� 2007. Polynyas: Windows to the World’s Oceans. Elsevier, Amsterdam. 437 pp.
Smith, W.O. Jr. and D.G. Barber. 2007. Polynyas and climate change: a view to the future.� In: Polynyas: Windows to the World’s Oceans (W.O. Smith, Jr. and D.G. Barber, eds.), Elsevier, Amsterdam, Pp. 409-417.
Smith, W.O. Jr., D.G. Ainley and R. Cattaneo-Vietti. 2007. Trophic interactions within the Ross Sea continental shelf ecosystem. Phil. Trans. Roy. Soc., ser. B 362: 95-111.
Peloquin, J. A., and W. O. Smith, Jr.� 2007. Phytoplankton blooms in the Ross Sea, Antarctica: Interannual variability in magnitude, temporal patterns, and composition. J. Geophys. Res. 112: C08013, doi:10.1029/2006JC003816.
Smith, W.O. Jr. and J.C. Comiso. 2009. Southern Ocean primary productivity: variability and a view to the future. In Smithsonian at the Poles: Contributions to International Polar Year Science (I. Krupnik, M.A. Lang, and S.E. Miller, Eds.), Smithsonian Inst. Scholarly Press, Washington, D.C., pp. 309-318.
Smith, W.O. Jr., M. Dinniman, G.R. DiTullio, S. Tozzi, O. Mangoni, M. Modigh and V. Saggiomo. 2010. Phytoplankton photosynthetic pigments in the Ross Sea: Patterns and relationships among functional groups. J. Mar. Systems 82: 177-185.
Smith, W.O. Jr., V. Asper, S. Tozzi, X. Liu and S.E. Stammerjohn. 2011a. Surface layer variability in the Ross Sea, Antarctica as assessed by in situ fluorescence measurements. Prog. Oceanogr.� 88: 28-45 (doi: 10.1016/j.pocean.2010.08.002).
Smith, W.O. Jr., A.R. Shields, J. Dreyer, J.A. Peloquin and V. Asper. 2011b. Interannual variability in vertical export in the Ross Sea: magnitude, composition, and environmental correlates. Deep-Sea Res. I 58: 147-159.
Liu, X. and W.O. Smith, Jr.� 2012. A statistical analysis of the controls on phytoplankton distribution in the Ross Sea, Antarctica. J. Mar. Systems 94: 135-144.
Smith, W.O. Jr., P.N. Sedwick, K.R. Arrigo, D.G. Ainley, and A.H. Orsi. 2012. The Ross Sea in a sea of change. Oceanography 25: 44-57.
Peloquin, J., C. Swan, N. Gruber, M. Vogt, H. Claustre, J. Ras, J. Uitz, J-C. Marty, R. Barlow, M. Behrenfeld, R. Bidigare, H. Dierssen, G. DiTullio, E.�Fernandez, C. Gallienne, S.�Gibb, R. Goericke, L. Harding, E. Head, P. Holligan, S. Hooker, D. Karl, T. Knap, M. Landry, R. Letelier, C.A. Llewellyn, M.�Lomas, M. Lucas, A. Mannino, J.-C.�Marty, B. G. Mitchell, F. M�ller-Karger, N. Nelson, C.�O'Brien, B. Prezelin, D. Repeta, W. O. Smith, Jr., D. Smythe-Wright, R.�Stumpf, A.�Subramaniam, K.�Suzuki, C. Trees, M. Vernet, K. Wasmund, and S. Wright. 2014. The MAREDAT global database of high performance liquid chromatography marine pigment measurements.� Earth System Science Data�5:�109-123.
Smith, W.O. Jr., D.G. Ainley, K.R. Arrigo, and M.S. Dinniman. 2014. The oceanography and ecology of the Ross Sea.� Annu. Rev. Mar. Sci. 6: 469-487.
Smith, W.O., Jr. and K. Donaldson. 2015. Photosynthesis-irradiance responses in the Ross Sea, Antarctica: a meta-analysis. Biogeosciences 12: 1-11.
Asper, V.L. and W.O. Smith, Jr. Variations in the abundance and distribution of aggregates in the Ross Sea, Antarctica. Deep-Sea Res. I (submitted).
Smith, W.O., Jr. and D.E. Kaufman. Particulate organic carbon climatologies in the Ross Sea: evidence for seasonal acclimations within phytoplankton. Prog. Oceanogr. (submitted).";
    String projects_0_end_date "2006-03";
    String projects_0_geolocation "Southern Ross Sea";
    String projects_0_name "Interannual Variability in the Antarctic-Ross Sea (IVARS): Nutrients and Seasonal Production";
    String projects_0_project_nid "686846";
    String projects_0_start_date "2001-04";
    String publisher_name "Amber York";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -77.668;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Abundance and size distribution of marine snow aggregates from profiles conducted during R/V Polar Star cruises in the Ross Sea, Antarctica between 2001 and 2005.";
    String time_coverage_start "2001-12-22T08:32:00Z";
    String title "Abundance and size distribution of marine snow aggregates from profiles conducted during R/V Polar Star cruises in the Ross Sea, Antarctica between 2001 and 2005.";
    String version "2";
    Float64 Westernmost_Easting -178.771;
    String xml_source "osprey2erddap.update_xml() v1.5-beta";
  }
}

 

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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