Accessing BCO-DMO data
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| Dataset Title: | Particulate organic matter data set from samples collected using ship\u2019s surface underway system taken on board of the R/V Oceanus OC1701A, OC1611B, OC1603B, OC1602A, OC1601A in the Oregon Coast (47-43 N, 126-124 W) from 2016 to 2017. 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_817952) |
| Information: | Summary
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| ISO 19115
| Metadata
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Attributes {
s {
Cruise {
String bcodmo_name "cruise_id";
String description "Cruise designation";
String long_name "Cruise";
String units "unitless";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 43.49702, 45.73821;
String axis "Y";
String bcodmo_name "latitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "Latitude measured by ship’s navigation system for sample/data collection, southern hemisphere is negative";
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 -125.0027, -124.00166;
String axis "X";
String bcodmo_name "longitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "Longitude as measured by ship’s navigation system for sample/data collection, western hemisphere is negative";
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";
}
Date_Time_PST {
String bcodmo_name "date_local";
String description "Date and time of sample and data collection (pacific standard time)";
String long_name "Date Time PST";
String source_name "Date_Time_PST";
String time_precision "1970-01-01T00:00Z";
String units "unitless";
}
Temperature {
Float32 _FillValue NaN;
Float32 actual_range 8.42, 13.05;
String bcodmo_name "temperature";
String description "Temperature in degrees Celsius measured at seachest in ship’s underway system at the time of sample collection";
String long_name "Temperature";
String units "degrees Celsius (°C)";
}
Salinity {
Float32 _FillValue NaN;
Float32 actual_range 26.0, 32.69;
String bcodmo_name "sal";
Float64 colorBarMaximum 37.0;
Float64 colorBarMinimum 32.0;
String description "Salinity measured by TSG lab unit in ship’s underway system at the time of sample collection";
String long_name "Sea Water Practical Salinity";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
String units "unitless";
}
PN {
Float32 _FillValue NaN;
Float32 actual_range 0.09, 7.88;
String bcodmo_name "PON";
String description "Particulate Nitrogen concentrations measured in filtered samples collected from ship’s undereway system using a semi-automated filtration system. Concentrations have been blank corrected.";
String long_name "PN";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP013/";
String units "micromoles N per liter of water (um/L)";
}
POC {
Float32 _FillValue NaN;
Float32 actual_range 0.8, 49.25;
String bcodmo_name "POC";
String description "Particulate Organic Carbon concentrations measured in filtered samples collected from ship’s undereway system using a semi-automated filtration system. Concentrations have been blank corrected.";
String long_name "Particulate Organic Carbon";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CORGCAP1/";
String units "micromoles C per liter of water (um/L)";
}
Beam_attenuation {
Float32 _FillValue NaN;
Float32 actual_range 0.08, 3.84;
String bcodmo_name "beam_cp";
String description "Corrected beam attenuation values measured at the time of sample collection by Oceanus Wetlabs C-STAR transmissometer installed inline the ship’s underway system. Corrected values for beam attenuation were determined using the approach described in Goñi et al., submitted, Goñi et al., 2019 and Holser et al., 2011.";
String long_name "Beam Attenuation";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ATTNZZ01/";
String units "1/m";
}
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.45351248e+9, 1.4845437e+9;
String axis "T";
String bcodmo_name "ISO_DateTime_UTC";
String description "Date and time of sample and data collection in UTC, standard ISO format (yyyy-mm-ddThh:mmZ)";
String ioos_category "Time";
String long_name "ISO Date Time UTC";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
String standard_name "time";
String time_origin "01-JAN-1970 00:00:00";
String time_precision "1970-01-01T00:00Z";
String units "seconds since 1970-01-01T00:00:00Z";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
String acquisition_description
"Full details for collection and analyses of underway POM samples are provided
by Holser et al., 2011 and Go\\u00f1i et al., 2019 and Go\\u00f1i et al.,
submitted. Brief summaries are provided below.
Samples for this study were collected aboard RV Oceanus using the surface
underway scientific system.
Aboard the vessel we had access to uncontaminated seawater and collected
samples at specific times that allowed us to determine location (latitude and
longitude) and seawater characteristics (temperature and salinity) from the
ships\\u2019 navigation and sensor panels. We used a semi-automated filtration
system (SAFS) described by Go\\u00f1i et al., (2019) connected to Oceanus
surface underway water to collect particulate organic matter samples. Surface
underway water was connected to the SAFS through a manual flow-control valve
via opaque polyethylene tubing.\\u00a0 A fly wheel flow meter was placed in-
line and connected to a laptop computer using a data acquisition system to
measure and record flows during the filtration stage. A switching valve with 8
ports was placed downstream from the flow meter and controlled by the
laptop.\\u00a0 Under stand-by conditions, flow was directed to the
\\u2018waste\\u2019 port, which was fitted with unobstructed tubing that drained
into one of the ship\\u2019s sinks and flowed back to sea.\\u00a0 The 8-sample
ports were fitted with tubing, quick-turn sockets\\u00a0 and in-line stainless
steel 13-mm Swinney filter holders.\\u00a0 The flow from these filters was
directed to the same sink as the \\u2018waste\\u2019 flow.\\u00a0 In each holder,
we placed one pre-combusted (400 oC for 3 hours) 13-mm glass fiber filter
supported by a stainless steel screen and locked into place with a Teflon
o-ring that prevents leakage and results in a filtration area of 78.5 mm2.
Once filters were fitted in each of the sample ports, the filtration program
was started to collect samples at selected intervals.
Once the filtration run was completed, the filter housings were removed from
the SAFS, opened, and each individual filter folded into pre-cleaned silver
capsules, which were placed into sample trays that were frozen until CN
analyses.\\u00a0 Each sample was assigned a specific time stamp (start-end of
filtration process) that coincided with the ship\\u2019s clock and allowed us
to retrieve location and oceanographic data for each sample, as well as
determine an overall filtration volume, which was used to calculate
particulate nitrogen and carbon concentrations once their contents were
determined.\\u00a0 During normal operations, we stacked two filter holders at
specific positions in order to collect both particles from a sample using the
first filter as well as measure blanks associated with dissolved organic
matter sorption as filtered water goes through the second filter.
Carbon and nitrogen analyses were conducted using high temperature
combustion/reduction according to Holser et al., 2011 and Go\\u00f1i et al.,
2019. Sample and blank filters were exposed to concentrated hydrochloric acid
fumes to remove carbonates and run in two CN analyzers (NC2500 Thermoquest and
ECS 4010 Costech) using the manufacturers\\u2019 recommendations for carbon and
nitrogen analyses (e.g., specified temperatures for combustion and reduction
furnaces, O2 loops/pressure, and the use of a water trap). In each run of a
full auto-sampler, we typically included 6 standards (e.g., cystine, atropine)
with different and known amounts of carbon and nitrogen to develop distinct
calibration curves for each run. All filters were treated the same and we used
the DOM blanks to correct for DOC and DN sorption. Detection limits for OC and
N were 0.04 and 0.03 micromoles, respectively. Replicate analyses of selected
samples yielded average standard errors for both measurements of ~2% of
measured values.
References cited: Holser et al., 2011; Go\\u00f1i et al., 2019; Go\\u00f1i et
al., submitted.";
String awards_0_award_nid "772629";
String awards_0_award_number "OCE-1459480";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1459480";
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 "Henrietta N Edmonds";
String awards_0_program_manager_nid "51517";
String cdm_data_type "Other";
String comment
"Underway POM
PI: Miguel Goni
Data Version 1: 2020-07-08";
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 dataset_current_state "Final and no updates";
String date_created "2020-07-07T13:42:53Z";
String date_modified "2020-07-24T00:55:12Z";
String defaultDataQuery "&time<now";
String doi "10.26008/1912/bco-dmo.817952.1";
Float64 Easternmost_Easting -124.00166;
Float64 geospatial_lat_max 45.73821;
Float64 geospatial_lat_min 43.49702;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -124.00166;
Float64 geospatial_lon_min -125.0027;
String geospatial_lon_units "degrees_east";
String history
"2024-04-16T11:01:29Z (local files)
2024-04-16T11:01:29Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_817952.html";
String infoUrl "https://www.bco-dmo.org/dataset/817952";
String institution "BCO-DMO";
String instruments_0_acronym "WL CSTAR Trans";
String instruments_0_dataset_instrument_description "Particle beam attenuation (Cp) was measured by a 25-cm, 650 nm wavelength WET Labs C-Star transmissometer installed inside the ship in line with the flow-through system.";
String instruments_0_dataset_instrument_nid "818039";
String instruments_0_description "A highly integrated opto-electronic design to provide a low cost, compact solution for underwater measurements of beam transmittance. The instrument is capable of either free space measurements, or through the use of an optical flow tube, flow-through sampling with a pump. It can be used in profiling, moored, or underway applications. more information from Wet Labs";
String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0160/";
String instruments_0_instrument_name "Wet Labs CSTAR Transmissometer";
String instruments_0_instrument_nid "593";
String instruments_0_supplied_name "WET Labs C-Star transmissometer";
String instruments_1_acronym "SBE 48";
String instruments_1_dataset_instrument_description "Surface water temperature was measured outside the ship by a hull-mounted (3 m) sensor (SBE 48).";
String instruments_1_dataset_instrument_nid "818036";
String instruments_1_description "The SBE 48 is a high-accuracy temperature recorder with non-volatile memory, designed for shipboard determination of sea surface temperature. Installed with magnets just below the water line, the SBE 48's temperature sensor is in contact with the inside of the ship's hull. For more information, see the SBE48 Manual.";
String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/134/";
String instruments_1_instrument_name "Sea-Bird SBE 48 Hull Temperature Sensor";
String instruments_1_instrument_nid "648";
String instruments_1_supplied_name "SBE 48";
String instruments_2_acronym "SBE 38";
String instruments_2_dataset_instrument_description "Surface water temperature was measured inside the ship by a flow-through system sensor (SBE 38).";
String instruments_2_dataset_instrument_nid "818037";
String instruments_2_description "Sea-Bird SBE 38 Remote Digital Immersion Thermometer is a seawater temperature sensor in a 10,500 meter (34,400 ft) titanium pressure housing. Real-time temperature data is transmitted in ASCII characters (degrees C or raw counts) via an RS-232 or optional RS-485 serial interface for display or logging by PC or data logger. The SBE 38's measurement range is -5 to +35 C; absolute accuracy is better than 0.001 C (1 mK) and resolution is approximately 0.00025 C (0.25 mK).";
String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0191/";
String instruments_2_instrument_name "Sea-Bird SBE 38 Remote Digital Immersion Thermometer";
String instruments_2_instrument_nid "673";
String instruments_2_supplied_name "SBE 38";
String instruments_3_acronym "SBE 45 MicroTSG";
String instruments_3_dataset_instrument_description "Salinity was measured by a SBE 45 thermosalinograph installed inside the ship in line with the flow-through system.";
String instruments_3_dataset_instrument_nid "818038";
String instruments_3_description
"A small externally powered, high-accuracy instrument, designed for shipboard determination of sea surface (pumped-water) conductivity and temperature. It is constructed of plastic and titanium to ensure long life with minimum maintenance. It may optionally be interfaced to an external SBE 38 hull temperature sensor.
Sea Bird SBE 45 MicroTSG (Thermosalinograph)";
String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0190/";
String instruments_3_instrument_name "Sea-Bird SBE 45 MicroTSG Thermosalinograph";
String instruments_3_instrument_nid "528063";
String instruments_3_supplied_name "SBE 45 thermosalinograph";
String keywords "attenuation, bco, bco-dmo, beam, Beam_attenuation, biological, carbon, chemical, cruise, data, dataset, date, density, dmo, earth, Earth Science > Oceans > Salinity/Density > Salinity, erddap, iso, ISO_DateTime_UTC, latitude, longitude, management, ocean, oceanography, oceans, office, organic, particulate, POC, practical, preliminary, pst, salinity, science, sea, sea_water_practical_salinity, seawater, temperature, time, water";
String keywords_vocabulary "GCMD Science Keywords";
String license "https://www.bco-dmo.org/dataset/817952/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/817952";
Float64 Northernmost_Northing 45.73821;
String param_mapping "{'817952': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/817952/parameters";
String people_0_affiliation "Oregon State University";
String people_0_affiliation_acronym "OSU-CEOAS";
String people_0_person_name "Miguel A. Goni";
String people_0_person_nid "772632";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "University of Hawaii at Manoa";
String people_1_affiliation_acronym "SOEST";
String people_1_person_name "Angelicque E. White";
String people_1_person_nid "51091";
String people_1_role "Co-Principal Investigator";
String people_1_role_type "originator";
String people_2_affiliation "Oregon State University";
String people_2_affiliation_acronym "OSU-CEOAS";
String people_2_person_name "Emmanuel Alegria";
String people_2_person_nid "819312";
String people_2_role "Scientist";
String people_2_role_type "originator";
String people_3_affiliation "Oregon State University";
String people_3_affiliation_acronym "OSU-CEOAS";
String people_3_person_name "Elizabeth R. Corvi";
String people_3_person_nid "819310";
String people_3_role "Scientist";
String people_3_role_type "originator";
String people_4_affiliation "Oregon State University";
String people_4_affiliation_acronym "OSU-CEOAS";
String people_4_person_name "Katie Watkins-Brandt";
String people_4_person_nid "556130";
String people_4_role "Scientist";
String people_4_role_type "originator";
String people_5_affiliation "Oregon State University";
String people_5_affiliation_acronym "OSU-CEOAS";
String people_5_person_name "Kylie A. Welch";
String people_5_person_nid "819311";
String people_5_role "Scientist";
String people_5_role_type "originator";
String people_6_affiliation "Oregon State University";
String people_6_affiliation_acronym "OSU-CEOAS";
String people_6_person_name "Miguel A. Goni";
String people_6_person_nid "772632";
String people_6_role "Contact";
String people_6_role_type "related";
String people_7_affiliation "Woods Hole Oceanographic Institution";
String people_7_affiliation_acronym "WHOI BCO-DMO";
String people_7_person_name "Karen Soenen";
String people_7_person_nid "748773";
String people_7_role "BCO-DMO Data Manager";
String people_7_role_type "related";
String project "CCAW";
String projects_0_acronym "CCAW";
String projects_0_description
"NSF Award Abstract:
As is true for many coastal regions worldwide, the Pacific Northwest margin is characterized by intense seasonal contrasts in conditions controlling carbon flux between the atmosphere, land, and ocean. During the wintertime, rapid and intense flooding of small coastal rivers and the associated inputs of freshwater, nutrients, and organic matter are commonplace in the Pacific Northwest. Impacts of these wintertime terrestrial-ocean transfers by small, flood-prone rivers on the upwelling regions, such as the Pacific Northwest, have been underestimated at both global and regional scales. In order to gain a complete and predictive understanding of carbon cycling in ocean margins, the biogeochemistry of periods of intense terrestrial-ocean transfers needs to be comprehensively studied. This project will evaluate the dynamics of organic matter cycling along an upwelling-dominated margin during the wintertime period of active terrestrial inputs and biological cycling using a combination of shipboard, glider, moored and remote measurements. New developments in ocean observational technologies through the Ocean Observatories Initiative (OOI)* and existing scientific infrastructure along the Oregon coast will be instrumental in achieving this goal. This work will provide research opportunities for undergraduate and graduate students, and outreach will be conducted through the Centers for Ocean Science Education Excellence Pacific Partnership, local coastal community colleges, and interpretative centers such as Oregon State University Hatfield Center, the Umpqua Discovery Center, and Oregon Coast Aquarium in an effort to educate students and the public about the research.
Globally, most studies of carbon cycling in eastern boundary regimes have focused on the upwelling phase during the summer months, resulting in a much poorer understanding of non-upwelling periods. As is many coastal upwelling systems, wintertime conditions along the Pacific Northwest margin are characterized by southerly, downwelling-favorable winds and moisture-laden storms that result in seasonal flooding by the numerous small to medium-sized rivers in the region. Elevated discharges by these coastal rivers translate into large inputs of land-derived biogeochemical relevant constituents, including freshwater, dissolved inorganic nutrients, and dissolved and particulate organic matter, which collectively rival or exceed those of the Columbia River. To understand the impact of flood-derived terrestrial inputs on the biogeochemistry of the coastal zone along the Pacific Northwest margin, researchers will conduct a detailed investigation of biogeochemical processes in the water column along the Newport Hydrographic Line off the central Oregon coast during fall/winter conditions. The project includes an intensive field effort that takes advantage of ship-based and autonomous platforms to gain comprehensive wintertime coverage. Among the project outcomes, this effort will lead to a revised paradigm of the biogeochemical drivers of carbon cycling in coastal margins.
*The Ocean Observatories Initiative (OOI) is an NSF-funded, networked infrastructure of science-driven sensor systems to measure the physical, chemical, geological and biological variables in the ocean and seafloor. For more information about OOI, please visit the website: www.oceanobservatories.org";
String projects_0_end_date "2019-02";
String projects_0_geolocation "Oregon Coast (47-43 N, 126-124 W)";
String projects_0_name "Coastal Ocean Carbon Cycling during Wintertime Conditions";
String projects_0_project_nid "772630";
String projects_0_start_date "2015-03";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 43.49702;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Particulate organic matter data set and added temperature and salinity from samples collected using ship\\u2019s surface underway system taken on board of the R/V Oceanus OC1701A, OC1611B, OC1603B, OC1602A, OC1601A in the Oregon Coast (47-43 N, 126-124 W) from 2016 to 2017.";
String time_coverage_end "2017-01-16T05:15Z";
String time_coverage_start "2016-01-23T01:28Z";
String title "Particulate organic matter data set from samples collected using ship\\u2019s surface underway system taken on board of the R/V Oceanus OC1701A, OC1611B, OC1603B, OC1602A, OC1601A in the Oregon Coast (47-43 N, 126-124 W) from 2016 to 2017.";
String version "1";
Float64 Westernmost_Easting -125.0027;
String xml_source "osprey2erddap.update_xml() v1.5";
}
}
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.