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Dataset Title:  Temperature mooring data collected at Station AT55 in Lake Michigan from
August 1, 2017 to April 20, 2018.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_734541)
Range: longitude = -87.7713 to -87.75322°E, latitude = 43.069916 to 43.095°N, time = 2017-08-01T19:12:00Z to 2018-04-20T19:12:00Z
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 {
  HAB_cm {
    Int16 _FillValue 32767;
    Int16 actual_range 15, 5500;
    String bcodmo_name "altitude";
    String description "Height above bottom";
    String ioos_category "Unknown";
    String long_name "HAB Cm";
    String units "centimeters (cm)";
  HAB_m {
    Float32 _FillValue NaN;
    Float32 actual_range 0.15, 55.0;
    String bcodmo_name "altitude";
    String description "Height above bottom";
    String ioos_category "Unknown";
    String long_name "HAB M";
    String units "meters (m)";
  temp {
    Float64 _FillValue NaN;
    Float64 actual_range 1.615, 26.7438889;
    String bcodmo_name "temperature";
    String description "average temperatures measured at various heights above the bed";
    String ioos_category "Temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.50161472e+9, 1.52425152e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date and Time formatted according to ISO 8601 date/time convention";
    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 "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 43.069917, 43.095;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude with positive values northward";
    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 -87.7713, -87.753217;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude with negative values westward";
    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";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description "\"\"";
    String awards_0_award_nid "670677";
    String awards_0_award_number "OCE-1658390";
    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 cdm_data_type "Other";
    String comment 
"Station AT55 Temperature mooring data 
  PI: C. Troy 
  Version: 2 
  Last updated: 2019-05-17 
  Note: This dataset is very large and will take longer than usual to load.";
    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 "2018-04-26T18:26:27Z";
    String date_modified "2019-05-20T16:54:30Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.734541.2";
    Float64 Easternmost_Easting -87.753217;
    Float64 geospatial_lat_max 43.095;
    Float64 geospatial_lat_min 43.069917;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -87.753217;
    Float64 geospatial_lon_min -87.7713;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-12-05T08:31:14Z (local files)
2020-12-05T08:31:14Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_734541.das";
    String infoUrl "https://www.bco-dmo.org/dataset/734541";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_nid "734546";
    String instruments_0_description "Records temperature data over a period of time.";
    String instruments_0_instrument_name "Temperature Logger";
    String instruments_0_instrument_nid "639396";
    String instruments_0_supplied_name "Sea-bird Scientific (SBE56)";
    String instruments_1_dataset_instrument_nid "734547";
    String instruments_1_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_1_instrument_name "Data Logger";
    String instruments_1_instrument_nid "731353";
    String instruments_1_supplied_name "RBR TDR- 2050, RBR TR-1060)";
    String instruments_2_dataset_instrument_nid "734548";
    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 "Onset (HOBO)";
    String keywords "algal, bco, bco-dmo, biological, bloom, chemical, data, dataset, date, dmo, erddap, hab, HAB_cm, HAB_m, harmful, iso, latitude, longitude, management, oceanography, office, preliminary, temperature, time";
    String license "https://www.bco-dmo.org/dataset/734541/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/734541";
    Float64 Northernmost_Northing 43.095;
    String param_mapping "{'734541': {'lat': 'flag - latitude', 'lon': 'flag - longitude', 'ISO_DateTime_UTC': 'master - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/734541/parameters";
    String people_0_affiliation "Purdue University";
    String people_0_person_name "Cary Troy";
    String people_0_person_nid "670685";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Wisconsin";
    String people_1_affiliation_acronym "UW-Milwaukee";
    String people_1_person_name "Harvey Bootsma";
    String people_1_person_nid "670682";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Purdue University";
    String people_2_person_name "David Cannon";
    String people_2_person_nid "767967";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "University of Wisconsin";
    String people_3_affiliation_acronym "UW-Milwaukee";
    String people_3_person_name "Qian Liao";
    String people_3_person_nid "670687";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Mathew Biddle";
    String people_4_person_nid "708682";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Megan Switzer";
    String people_5_person_nid "708683";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders";
    String projects_0_acronym "Filter Feeders Physics and Phosphorus";
    String projects_0_description 
While benthic filter feeders are known to influence plankton and nutrient dynamics in shallow marine and freshwater systems, their role is generally considered to be minor in large, deep systems. However, recent evidence indicates that profundal quagga mussels (Dreissena rostriformis bugensis) have dramatically altered energy flow and nutrient cycling in the Laurentian Great Lakes and other larges aquatic systems, so that conventional nutrient-plankton paradigms no longer apply. Observed rates of phosphorus grazing by profundal quagga mussels in Lake Michigan exceed the passive settling rates by nearly an order of magnitude, even under stably stratified conditions. We hypothesize that the apparently enhanced particle deliver rate to the lake bottom results from high filtration capacity combined with vertical mixing processes that advect phytoplankton from the euphotic zone to the near-bottom layer. However, the role of hydrodynamics is unclear, because these processes are poorly characterized both within the hypolimnion as a whole and within the near-bottom layer. In addition, the implications for phytoplankton and nutrient dynamics are unclear, as mussels are also important nutrient recyclers. In the proposed interdisciplinary research project, state-of-the-art instruments and analytical tools will be deployed in Lake Michigan to quantify these critical dynamic processes, including boundary layer turbulence, mussel grazing, excretion and egestion, and benthic fluxes of carbon and phosphorus. Empirical data will be used to calibrate a 3D hydrodynamic-biogeochemical model to test our hypotheses.
Intellectual Merit:
This collaborative biophysical project is structured around two primary questions: 1) What role do profundal dreissenid mussels play in large lake carbon and nutrient cycles? 2) How are mussel grazing and the fate of nutrients recycled by mussels modulated by hydrodynamics at scales ranging from mm (benthic boundary layer) to meters (entire water column)? The project will improve the ability to model nutrient and carbon dynamics in coastal and lacustrine waters where benthic filter-feeders are a significant portion of the biota. By so doing, it will address the overarching question of how plankton and nutrient dynamics in large, deep lakes with abundant profundal filter feeders differ from the conventional paradigm described by previous models. Additionally, the project will quantify and characterize boundary layer turbulence for benthic boundary layers in large, deep lakes, including near-bed turbulence produced by benthic filter feeders.
Broader Impacts:
The project will provide new insight into the impacts of invasive dreissenid mussels, which are now threatening many large lakes and reservoirs across the United States. Dreissenid mussels appear to be responsible for a number of major changes that have occurred in the Great Lakes, including declines of pelagic plankton populations, declines in fish populations, and, ironically, nuisance algal blooms in the nearshore zone. As a result, conventional management models no longer apply, and managers are uncertain about appropriate nutrient loading targets and fish stocking levels. The data and models resulting from this project will help to guide those decisions. Additionally, the project will provide insight to bottom boundary layer physics, with applicability to other large lakes, atidal coastal seas, and the deep ocean. The project will leverage the collaboration and promote interdisciplinary education for undergraduate and graduate students from two universities (UW-Milwaukee and Purdue). The project will support 3 Ph.D. students and provide structured research experiences to undergraduates through a summer research program. The project will also promote education of future aquatic scientists by hosting a Biophysical Coupling Workshop for graduate students who participate in the annual IAGLR conferences, and the workshop lectures will be published for general access through ASLO e-Lectures and on an open-access project website.
Background publications are available at:https://onlinelibrary.wiley.com/doi/10.1002/2014JC010506/fullhttp://link.springer.com/article/10.1007/s00348-012-1265-9http://aslo.net/lomethods/free/2009/0169.pdfhttp://www.sciencedirect.com/science/article/pii/S0380133015001458
Note: This is an NSF Collaborative Research Project.";
    String projects_0_geolocation "Lake Michigan";
    String projects_0_name "Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders";
    String projects_0_project_nid "670679";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 43.069917;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "A fixed mooring was established to measure water column temperatures in Lake Michigan near Milwaukee, WI, from Aug 1 \\u2013 Aug 17, 2017 at a 55 meters depth site and again during 2018 from April 5 \\u2013 April 20, 2018. The mooring involved a large tripod to which a surface line was attached and along this line were temperature sensors at various depths.";
    String time_coverage_end "2018-04-20T19:12:00Z";
    String time_coverage_start "2017-08-01T19:12:00Z";
    String title "Temperature mooring data collected at Station AT55 in Lake Michigan from August 1, 2017 to April 20, 2018.";
    String version "2";
    Float64 Westernmost_Easting -87.7713;
    String xml_source "osprey2erddap.update_xml() v1.0";


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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