ERDDAP > tabledap > Data Access Form

Dataset Title:	[Santa Clara River C isotope data 2023-24] - 14C and 13C measurements of particulate and sedimentary organic carbon from the Santa Clara River, California, during the 2023–2024 El Niño event (RAPID: The effect of El Nino on delivery of organic carbon in the Santa Clara River, CA)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_1006750_v1)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
UCID_sample_number (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"UCID24094"	"UCID24236"
sample_type (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"POC"	"SOC"
site_name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"SCR"	"SCR"
filter_number (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Filter 34"	"Silt B"
date_collected (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2023-12-21"	"2024-04-01"
D14C (‰)	!= =~ <= >= = < >		!= =~ <= >= = < >		-934.0	-138.0
D14C_error (‰)	!= =~ <= >= = < >		!= =~ <= >= = < >		3.0	214.0
d13C (‰)	!= =~ <= >= = < >		!= =~ <= >= = < >		-30.7	-17.91
d13C_error (‰)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.2	1.0
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		34.23	34.23
longitude (degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		-119.262	-119.259

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" UCID_sample_number sample_type site_name filter_number date_collected D14C D14C_error d13C d13C_error latitude longitude UCID_sample_number sample_type site_name filter_number date_collected D14C D14C_error d13C d13C_error latitude longitude UCID_sample_number sample_type site_name filter_number date_collected D14C D14C_error d13C d13C_error latitude longitude UCID_sample_number sample_type site_name filter_number date_collected D14C D14C_error d13C d13C_error latitude longitude UCID_sample_number sample_type site_name filter_number date_collected D14C D14C_error d13C d13C_error latitude longitude ")

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  UCID_sample_number {
    String long_name "Ucid_sample_number";
    String units "unitless";
  }
  sample_type {
    String long_name "Sample_type";
    String units "unitless";
  }
  site_name {
    String long_name "Site_name";
    String units "unitless";
  }
  filter_number {
    String long_name "Filter_number";
    String units "unitless";
  }
  date_collected {
    String long_name "Date_collected";
    String units "unitless";
  }
  D14C {
    Float32 actual_range -934.0, -138.0;
    String long_name "D14c";
    String units "‰";
  }
  D14C_error {
    Float32 actual_range 3.0, 214.0;
    String long_name "D14c_error";
    String units "‰";
  }
  d13C {
    Float32 actual_range -30.7, -17.91;
    String long_name "D13c";
    String units "‰";
  }
  d13C_error {
    Float32 actual_range 0.2, 1.0;
    String long_name "D13c_error";
    String units "‰";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 34.23, 34.23;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -119.262, -119.259;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.1006750.1";
    Float64 Easternmost_Easting -119.259;
    Float64 geospatial_lat_max 34.23;
    Float64 geospatial_lat_min 34.23;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -119.259;
    Float64 geospatial_lon_min -119.262;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-09-10T18:46:21Z (local files)
2026-09-10T18:46:21Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_1006750_v1.html";
    String infoUrl "https://osprey.bco-dmo.org/dataset/1006750";
    String institution "BCO-DMO";
    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.";
    Float64 Northernmost_Northing 34.23;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 34.23;
    String summary 
"Radiocarbon (Δ14C) and stable carbon isotope (δ13C) values were measured in particulate organic carbon (POC) from river water and sedimentary organic carbon (SOC) from river silt and beach sand collected by Niels Hauksson from the Santa Clara River (SCR), California, during the 2023–2024 El Niño event from December 2023 to April 2024. The SCR watershed has experienced significant change over the past decades due to both urban development and increased drought. The dataset contains measurements of POC samples from Santa Clara River water and sedimentary organic carbon (SOC) from river silt and beach sand, including sample collection information, Δ14C and δ13C measurements and associated analytical uncertainties, and sample collection coordinates.

This analysis is helping to establish whether the observed change in the aged OC end member is the result of variation in precipitation or due to other alterations in the watershed. If precipitation is the main control of the aged end member, we can estimate how the expected changes in local climate will affect the OC exported by the SCR. Dr. Hauksson, undergrad student Taylor Hart and PI Ellen Druffel analyzed the samples and are writing the papers with these data.";
    String title "[Santa Clara River C isotope data 2023-24] - 14C and 13C measurements of particulate and sedimentary organic carbon from the Santa Clara River, California, during the 2023–2024 El Niño event (RAPID: The effect of El Nino on delivery of organic carbon in the Santa Clara River, CA)";
    Float64 Westernmost_Easting -119.262;
  }
}

 

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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 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.

• (easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
• (easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
• (not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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