Accessing BCO-DMO data
Brought to you by BCO-DMO
|
|
BCO-DMO ERDDAP
Accessing BCO-DMO data |
log in
Brought to you by BCO-DMO |
| Dataset Title: | [MCTD Lake Michigan 2017, 2018 & 2019] - Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019. (Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders) 
|
| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_768011) |
| Information: | Summary
| License
| FGDC
| ISO 19115
| Metadata
| Background
| Subset
| Files
| Make a graph
|
Attributes {
s {
profile_name {
String bcodmo_name "cast";
String description "profile name extracted from submitted file name";
String long_name "Profile Name";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 43.069917, 43.069917;
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 -87.753217, -87.753217;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longituide with positive values 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";
}
DOY_GMT {
Float64 _FillValue NaN;
Float64 actual_range 95.7570647922617, 110.754786829747;
String bcodmo_name "unknown";
String description "time corresponding to each profile name. Times are taken as the average of measurement times for a given profile. Time units are days in GMT.";
String long_name "DOY GMT";
String units "unitless";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.52295181e+9, 1.524247613e+9;
String axis "T";
String bcodmo_name "ISO_DateTime_UTC";
String description "Date and time formatted following ISO8601 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";
}
pressure {
Float64 _FillValue NaN;
Float64 actual_range 1.76301003345858, 51.8271251079746;
String bcodmo_name "pressure";
String description "average pressure at measurement location";
String long_name "Pressure";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PRESPR01/";
String units "decibar (dbar)";
}
temp {
Float64 _FillValue NaN;
Float64 actual_range 2.59696745459734, 3.31354022090128;
String bcodmo_name "temperature";
String description "average temperature";
String long_name "Temperature";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius";
}
S2 {
Float64 _FillValue NaN;
Float64 actual_range 0.0186852554110757, 1.6843117779088101;
String bcodmo_name "unknown";
String description "average total velocity shear (S2=[dU/dz]2+[dV/dz]2";
String long_name "S2";
String units "1/s2";
}
turb {
Float64 _FillValue NaN;
Float64 actual_range 0.799901315748123, 0.996168509579626;
String bcodmo_name "turbidity";
String description "average turbidity";
String long_name "Turb";
String units "FTU";
}
chlor {
Float64 _FillValue NaN;
Float64 actual_range 0.799901315748123, 0.996168509579626;
String bcodmo_name "fluorescence";
String description "average fluorescence";
String long_name "Chlor";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
String units "ppb";
}
dissipation {
Float64 _FillValue NaN;
Float64 actual_range 2.0905364546678e-10, 6.233666502474389e-6;
String bcodmo_name "unknown";
String description "turbulent kinetic energy dissipation calculated from shear signal";
String long_name "Dissipation";
String units "Watts per kilogram (W/kg)";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
String acquisition_description
"129 microstructure profiles were collected over three days (April 5th, 12th,
and 20th). Measurements were collected using an RSI MicroCTD (Rockland
Scientific International, Inc.) which sampled shear and temperature
microstructure at 512Hz, free-falling at a velocity of 0.8 m/s (vertical
resolution: ~1.5mm). Shear microstructure was analyzed to obtain turbulent
kinetic energy dissipation (see data processing). Velocity shear was measured
using two velocity shear probes (RSI; accuracy: 5%) oriented perpendicularly
to collect orthogonal shear components. Microstructure temperatures were
collected using 2 FP07 probes (accuracy: 0.005 ), with the resulting
measurements averaged to produce the single temperature estimate included in
the attached files. Turbidity (accuracy: 2%) and fluorescence (accuracy: 1%)
measurements were collected using a JAC-CLTU sensor (JFE Advantech Co.,
Ltd).\\u00a0\\u00a0
Microstructure profiles were collected manually by letting the instrument free
fall through the water column. Profiles were timed and manually stopped to
prevent the instrument from crashing into the bed and damaging sensors";
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 Microstructure Data, Station AT55, April 2018
PI: Cary Troy
Version: 2019-05-15";
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 "2019-05-15T15:02:41Z";
String date_modified "2019-05-20T16:54:49Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.768011.1";
Float64 Easternmost_Easting -87.753217;
Float64 geospatial_lat_max 43.069917;
Float64 geospatial_lat_min 43.069917;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -87.753217;
Float64 geospatial_lon_min -87.753217;
String geospatial_lon_units "degrees_east";
String history
"2024-11-10T21:37:55Z (local files)
2024-11-10T21:37:55Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_768011.html";
String infoUrl "https://www.bco-dmo.org/dataset/768011";
String institution "BCO-DMO";
String instruments_0_acronym "CTD";
String instruments_0_dataset_instrument_description "Measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.) which sampled shear and temperature microstructure at 512Hz, free-falling at a velocity of 0.8 m/s (vertical resolution: ~1.5mm).";
String instruments_0_dataset_instrument_nid "768014";
String instruments_0_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column. The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or radiometers. It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast. This instrument designation is used when specific make and model are not known.";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
String instruments_0_instrument_name "CTD profiler";
String instruments_0_instrument_nid "417";
String instruments_0_supplied_name "RSI MicroCTD (Rockland Scientific International, Inc.)";
String keywords "bco, bco-dmo, biological, chemical, chlor, chlorophyll, data, dataset, date, dissipation, dmo, doy, DOY_GMT, erddap, iso, latitude, longitude, management, name, oceanography, office, preliminary, pressure, profile, profile_name, temperature, time, turb";
String license "https://www.bco-dmo.org/dataset/768011/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/768011";
Float64 Northernmost_Northing 43.069917;
String param_mapping "{'768011': {'latitude': 'flag - latitude', 'longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/768011/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 43.069917;
String standard_name_vocabulary "CF Standard Name Table v55";
String subsetVariables "latitude,longitude";
String summary "Turbulent microstructure profiles were collected near Milwaukee, WI, during 2018 between April 5 \\u2013 April 20, 2018 at a 55m depth site. Microstructure measurements were collected using an RSI MicroCTD (Rockland Scientific International, Inc.), which measures velocity shear, temperature, turbidity, and chlorophyll concentrations. High resolution velocity shear (512 Hz) measurements were used to estimate turbulent kinetic energy dissipation throughout the water column. Microstructure profiles were collected during fair weather conditions on April 5th, 12th, and 20th.";
String time_coverage_end "2018-04-20T18:06:53Z";
String time_coverage_start "2018-04-05T18:10:10Z";
String title "[MCTD Lake Michigan 2017, 2018 & 2019] - Microstructure profiles at Station AT55 in Lake Michigan from 2017, 2018 and 2019. (Collaborative Research: Regulation of plankton and nutrient dynamics by hydrodynamics and profundal filter feeders)";
String version "1";
Float64 Westernmost_Easting -87.753217;
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.