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Dataset Title:  Current velocities from ADCP from an R/V Lowell Weicker cruise in Fisher's
Island Sound (NY/CT) in May 2012
  RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_3713)
Range: longitude = -71.99368 to -71.93639°E, latitude = 41.29669 to 41.3061°N, depth = 1.5 to 25.0m
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 {
  month_local {
    String description "Two-digit month, local time (e.g. 05 = May)";
    String ioos_category "Time";
    String long_name "Month Local";
    String units "unitless";
  }
  day_local {
    Byte _FillValue 127;
    Byte actual_range 30, 30;
    String description "2-digit day of month, local time";
    String ioos_category "Time";
    String long_name "Day Local";
    String units "unitless";
  }
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2012, 2012;
    String description "4-digit year, local time";
    String ioos_category "Time";
    String long_name "Year";
    String units "unitless";
  }
  sta {
    Byte _FillValue 127;
    Byte actual_range 1, 5;
    String description "Station ID number.";
    String ioos_category "Unknown";
    String long_name "Sta";
    String units "unitless";
  }
  cast {
    Byte _FillValue 127;
    Byte actual_range 0, 4;
    String description "Cast number.";
    String ioos_category "Unknown";
    String long_name "Cast";
    String units "unitless";
  }
  time_start_local {
    String description "Local time at start of the measurements.";
    String ioos_category "Time";
    String long_name "Time Start Local";
    String units "HHMM.mm";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 41.29669, 41.3061;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude at start of measurement. North = positive.";
    String ioos_category "Location";
    String long_name "Latitude";
    String source_name "lat_start";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -71.99368, -71.93639;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude at start of measurement. West = negative.";
    String ioos_category "Location";
    String long_name "Longitude";
    String source_name "lon_start";
    String standard_name "longitude";
    String units "degrees_east";
  }
  ISO_DateTime_Local {
    String description "Date and time formatted to ISO8601 standard (local time). See time_diff for time zone info. Format:�yyyy-MM-dd'T'HH:mm:ss'Z'";
    String ioos_category "Time";
    String long_name "ISO Date Time Local";
    String source_name "ISO_DateTime_Local";
    String units "unitless";
  }
  time_diff {
    Byte _FillValue 127;
    Byte actual_range 4, 4;
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum -10.0;
    String description "The number of hours added to local time to convert to GMT.";
    String ioos_category "Time";
    String long_name "Time Diff";
    String units "hours";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.5, 25.0;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth, in meters. Velocity components are given at every 0.5 meter.";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  u_m {
    Float32 _FillValue NaN;
    Float32 actual_range -0.2936, 0.5865;
    String description "Eastward component of current velocity, in meters per second. Eastward flow is positive.";
    String ioos_category "Unknown";
    String long_name "U M";
    String units "m/s";
  }
  v_m {
    Float32 _FillValue NaN;
    Float32 actual_range -0.1182, 0.2457;
    String description "Northward component of current velocity, in meters per second. Northward flow is positive.";
    String ioos_category "Unknown";
    String long_name "V M";
    String units "m/s";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Current velocities were collected at 5 stations by ADCP aboard a one-day
cruise in Fisher's Island Sound on R/V Lowell Weicker.";
    String awards_0_award_nid "54721";
    String awards_0_award_number "OCE-1129734";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1129734";
    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 "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "54820";
    String awards_1_award_number "OCE-1130033";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1130033";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Dr David  L. Garrison";
    String awards_1_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Current Velocities measured with Acoustic Doppler Current Profiler 
 R/V Lowell Weicker - 30 May 2012 
 PI: George B. McManus (UConn) 
 Co-PI: Laura A. Katz (Smith College) 
 Version: 06 Sept 2012";
    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 "2012-09-06T17:20:34Z";
    String date_modified "2018-12-07T18:00:01Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.3713.1";
    Float64 Easternmost_Easting -71.93639;
    Float64 geospatial_lat_max 41.3061;
    Float64 geospatial_lat_min 41.29669;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -71.93639;
    Float64 geospatial_lon_min -71.99368;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 25.0;
    Float64 geospatial_vertical_min 1.5;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2019-08-24T14:33:18Z (local files)
2019-08-24T14:33:18Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_3713.das";
    String infoUrl "https://www.bco-dmo.org/dataset/3713";
    String institution "BCO-DMO";
    String instruments_0_acronym "ADCP";
    String instruments_0_dataset_instrument_nid "5765";
    String instruments_0_description 
"The ADCP measures water currents with sound, using a principle of sound waves called the Doppler effect. A sound wave has a higher frequency, or pitch, when it moves to you than when it moves away. You hear the Doppler effect in action when a car speeds past with a characteristic building of sound that fades when the car passes.
The ADCP works by transmitting \"pings\" of sound at a constant frequency into the water. (The pings are so highly pitched that humans and even dolphins can't hear them.) As the sound waves travel, they ricochet off particles suspended in the moving water, and reflect back to the instrument. Due to the Doppler effect, sound waves bounced back from a particle moving away from the profiler have a slightly lowered frequency when they return. Particles moving toward the instrument send back higher frequency waves. The difference in frequency between the waves the profiler sends out and the waves it receives is called the Doppler shift. The instrument uses this shift to calculate how fast the particle and the water around it are moving.
Sound waves that hit particles far from the profiler take longer to come back than waves that strike close by. By measuring the time it takes for the waves to bounce back and the Doppler shift, the profiler can measure current speed at many different depths with each series of pings. (More from WHOI instruments listing).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/115/";
    String instruments_0_instrument_name "Acoustic Doppler Current Profiler";
    String instruments_0_instrument_nid "405";
    String instruments_0_supplied_name "Acoustic Doppler Current Profiler";
    String keywords "bco, bco-dmo, biological, cast, chemical, data, dataset, date, day, day_local, depth, diff, dmo, erddap, iso, latitude, local, longitude, management, month, month_local, oceanography, office, preliminary, sta, start, time, time_diff, time_start_local, u, u_m, v, v_m, year";
    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/3713";
    Float64 Northernmost_Northing 41.3061;
    String param_mapping "{'3713': {'depth': 'flag - depth', 'lon_start': 'flag - longitude', 'lat_start': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/3713/parameters";
    String people_0_affiliation "University of Connecticut";
    String people_0_affiliation_acronym "UConn - Avery Point";
    String people_0_person_name "Dr George B. McManus";
    String people_0_person_nid "51375";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Smith College";
    String people_1_person_name "Dr Laura A. Katz";
    String people_1_person_nid "51376";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Connecticut";
    String people_2_affiliation_acronym "UConn - Avery Point";
    String people_2_person_name "Dr George B. McManus";
    String people_2_person_nid "51375";
    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 "Shannon Rauch";
    String people_3_person_nid "51498";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Diversity and dynamics of planktonic ciliates - what can next-generation sequencing technologies tell us?";
    String projects_0_acronym "CiliateSequencing";
    String projects_0_description 
"The Ocean's biomass and diversity are predominantly microbial, yet this aspect of diversity remains underexplored. Efforts in recent years have begun to document microbial diversity in marine systems, and to elucidate the processes that structure assemblages across space and time. This project focuses on two important sister clades of microbial eukaryotes, the oligotrich and choreotrich ciliates. These organisms comprise a major component of planktonic food webs as they graze on phytoplankton, and are in turn eaten by zooplankton and larval fish.
Earlier molecular work on ciliate diversity relied on light microscopy, construction of clone libraries and Sanger sequencing. This revealed a high degree of cryptic diversity (similar species that are genetically distinct), which is surprising, given the long-held idea that all microbes are globally distributed and that few species exist, at least as compared to animals and plants. This past work also showed that ciliate assemblages contain a few highly abundant forms and many rare ones, consistent with the concept of a \"rare biosphere\". However, these methods are limited by high costs of both labor and materials, so that efforts to sample any local assemblage comprehensively usually resulted in undersaturation (repeated sampling continued to uncover new species). Next generation approaches are needed to truly assess the depths of biodiversity in planktonic ciliates.
This project brings together investigators with strengths in ecology, taxonomy and oceanography (PI McManus) and in molecular evolution, systematics and bioinformatics (PI Katz). Pyrosequencing will be used to sample the oligotrich and choreotrich ciliates ’to exhaustion’ in coastal environments. Denaturing gradient gel electrophoresis (DGGE), a technique that generates a fingerprint of the diversity in a sample, will be used to pre-select samples for pyrosequencing based on where strong gradients are observed in the composition of assemblages in relation to environmental factors (density fronts, thermolclines, etc.). Using these approaches, combined with the informatics pipeline already in place, this project will address three specific objectives:
Objective 1. Determine the spatial scale of variability in ciliate diversity by measuring how ciliate assemblages change over meter, kilometer, 100 km, and basin scales.
Objective 2. Assess the contributions of different size classes of ciliates to overall assemblage diversity.
Objective 3. Experimentally evaluate factors that control the temporal shift of individual species from rarity to commonness in a natural assemblage, and vice versa.
Note: See the related collaborative project, \"Patterns of diversity in planktonic ciliates: spatio-temporal scales and community assembly in the coastal ocean\", funded by awards OCE-1435515 and OCE-1436003.";
    String projects_0_end_date "2015-08";
    String projects_0_geolocation "NW Atlantic Continental Shelf";
    String projects_0_name "Diversity and dynamics of planktonic ciliates - what can next-generation sequencing technologies tell us?";
    String projects_0_project_nid "2164";
    String projects_0_project_website "http://microzooplankton.uconn.edu";
    String projects_0_start_date "2012-07";
    String publisher_name "Shannon Rauch";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 41.29669;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String subsetVariables "month_local, day_local, year, time_diff";
    String summary "This dataset contains northward and eastward components of current velocity measured by Acoustic Doppler Current Profiler (ADCP). Velocity components are given at every 0.5 meter depth.";
    String title "Current velocities from ADCP from an R/V Lowell Weicker cruise in Fisher's Island Sound (NY/CT) in May 2012";
    String version "1";
    Float64 Westernmost_Easting -71.99368;
    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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