Accessing BCO-DMO data
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BCO-DMO ERDDAP
Accessing BCO-DMO data |
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| Dataset Title: | [ADCP Lake Michigan 2018] - Velocity observations from a mooring at Station AT55 in Lake Michigan from 2018-04-05 to 2018-04-20 (Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_767737) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
HAB_cm {
Float32 _FillValue NaN;
Float32 actual_range 13.0, 5087.0;
String bcodmo_name "altitude";
String description "Height above bottom";
String long_name "HAB Cm";
String units "centimeters (cm)";
}
HAB_m {
Float32 _FillValue NaN;
Float32 actual_range 0.13, 50.87;
String bcodmo_name "altitude";
String description "Height above bottom";
String long_name "HAB M";
String units "meters (m)";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 43.0699, 43.0699;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "latitude with positive values indicating 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 -87.7532, -87.7532;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longitude with positive values indicating eastward";
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";
}
component {
String bcodmo_name "unknown";
String description "directional component of the average water column velocity (EAST; NORTH; UP)";
String long_name "Component";
String units "unitless";
}
filename {
String bcodmo_name "file_name";
String description "name of the file from which the data was extracted (minus the .txt extension)";
String long_name "Filename";
String units "unitless";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.52294544e+9, 1.52425164e+9;
String axis "T";
String bcodmo_name "ISO_DateTime_UTC";
String description "The columns YEAR MONTH DAY HOUR MINUTE SECOND combined into the ISO 8601 time representation";
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";
}
vel {
Float64 _FillValue NaN;
Float64 actual_range -1.62370233139501, 1.4918961779052902;
String bcodmo_name "unknown";
String description "Average water column velocity";
String long_name "Vel";
String units "meters per second (m/s)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
String acquisition_description
"All velocity data was averaged over 10 minutes of sampling before being
interpolated onto a common time vector. Individual instrument accuracies,
ranges, and resolutions are included.
ADCPs were used to sample current velocities at 2 Hz, with the Nortek
Signature 500 (287cm \\u2013 5087cm above bed, 2m bin size) measuring
continuously and the Nortek Aquadopp HR Profiler (13.1cm \\u2013 133.1cm above
bed, 3cm cell size) burst sampling for ~8.5minutes every 10 minutes. All data
were quality controlled according to manufacturer recommendations and
measurements with poor amplitudes and correlations were removed before
averaging.\\u00a0";
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
"Lake Michigan Velocity Mooring Data, Station AT55, April 2018 (Milwaukee)
PI: Cary Troy
Version: 2019-05-14";
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 "2019-05-14T18:18:46Z";
String date_modified "2019-05-20T16:56:10Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.767737.1";
Float64 Easternmost_Easting -87.7532;
Float64 geospatial_lat_max 43.0699;
Float64 geospatial_lat_min 43.0699;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -87.7532;
Float64 geospatial_lon_min -87.7532;
String geospatial_lon_units "degrees_east";
String history
"2024-11-23T16:42:06Z (local files)
2024-11-23T16:42:06Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_767737.html";
String infoUrl "https://www.bco-dmo.org/dataset/767737";
String institution "BCO-DMO";
String instruments_0_acronym "ADCP";
String instruments_0_dataset_instrument_description
"ADCPs were used to sample current velocities at 2 Hz, with the Nortek Signature 500 (287cm – 5087cm above bed, 2m bin size) measuring continuously and the Nortek Aquadopp HR Profiler (13.1cm – 133.1cm above bed, 3cm cell size) burst sampling for ~8.5minutes every 10 minutes.
Nortek Aquadopp HR Profiler (2 MHz)
Measurement Locations: 13.1 cm - 133.1 cm
Burst interval: 600s
Sample rate: 2 Hz
Samples/burst: 1024
Cell size: 3cm
All data is quality controlled according to manufacturer recommendations, removing all measurements with amplitudes below 60 dB and correlations below 70%. Data is then averaged over a single burst (1024 samples)
Nortek Signature 500 (500kHz)
Measurement Locations: 287 cm - 5087 cm
Burst interval: continuous sampling
Sample rate: 2 Hz
Samples/burst: continuous
Cell size: 2m
Nominal Velocity Range: 1m/s
All data is quality controlled according to manufacturer recommendations, removing all measurements with amplitudes below 30 dB and correlations below 50%. Data is then averaged over 600s (1200samples).";
String instruments_0_dataset_instrument_nid "767808";
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 "ADCP Nortek (Aquadopp HR Profiler, Signature 500)";
String keywords "algal, bco, bco-dmo, biological, bloom, chemical, component, data, dataset, date, dmo, erddap, filename, hab, HAB_cm, HAB_m, harmful, iso, latitude, longitude, management, oceanography, office, preliminary, time, vel";
String license "https://www.bco-dmo.org/dataset/767737/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/767737";
Float64 Northernmost_Northing 43.0699;
String param_mapping "{'767737': {'lat': 'flag - latitude', 'lon': 'flag - longitude', 'ISO_DateTime_UTC': 'master - time'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/767737/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 project "Filter Feeders Physics and Phosphorus";
String projects_0_acronym "Filter Feeders Physics and Phosphorus";
String projects_0_description
"Overview:
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 43.0699;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "latitude,longitude";
String summary "A fixed mooring was established to measure water column velocities in Lake Michigan near Milwaukee, WI, during 2018 from April 5 \\u2013 April 20, 2018 at a 55m depth site. The mooring involved a large tripod, upon which two ADCPs (Nortek Aquadopp HR profiler and Nortek Signature 500) were mounted to measure water column velocities between 13cm and 5087cm above the bed.";
String time_coverage_end "2018-04-20T19:14:00Z";
String time_coverage_start "2018-04-05T16:24:00Z";
String title "[ADCP Lake Michigan 2018] - Velocity observations from a mooring at Station AT55 in Lake Michigan from 2018-04-05 to 2018-04-20 (Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders)";
String version "1";
Float64 Westernmost_Easting -87.7532;
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection constraints.
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.