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Dataset Title:  [Warm Core Ring Census (1980-2017)] - Yearly census of Gulf Stream Warm Core
Ring formation from 1980 to 2017 (Collaborative Research: GLOBEC Pan Regional
Synthesis: The Effect of Varying Freshwater Inputs on Regional Ecosystems in
the North Atlantic)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_810182)
Range: longitude = -75.0 to -54.96°E, latitude = 35.78 to 43.82°N
Information:  Summary ? | License ? | FGDC | 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 {
  WCR_Name {
    String bcodmo_name "sample";
    String description "Warm Core Ring identifier";
    String long_name "WCR Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  DOB {
    String bcodmo_name "date";
    String description "Date WCR was first seen";
    String long_name "DOB";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "DOB";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -75.0, -54.96;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "WCR formation location: longitude where ring was first seen; east is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "Longitude_F";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 35.78, 43.82;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "WCR formation location: latitude WCR was first seen; north is positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "Latitude_F";
    String standard_name "latitude";
    String units "degrees_north";
  }
  Area_km2 {
    Float64 _FillValue NaN;
    Float64 actual_range 1581.87, 250999.26;
    String bcodmo_name "surface_area";
    String description "area of WCR";
    String long_name "Area Km2";
    String units "square kilometers (km^2)";
  }
  DOA {
    String bcodmo_name "date";
    String description "Date WCR was last seen";
    String long_name "DOA";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  Longitude_D {
    Float32 _FillValue NaN;
    Float32 actual_range -75.08, -54.01;
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "WCR demise location: longitude where ring was last seen; east is positive";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "decimal degrees";
  }
  Latitude_D {
    Float32 _FillValue NaN;
    Float32 actual_range 32.27, 43.73;
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "WCR demise location: latitude where ring was lat seen; north is positive";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "decimal degrees";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"The census data is an analysis product from a set of charts prepared by
Jenifer Clark (JC). An example chart is shown in Figure 1a of Gangopadhyay et
al. (2019). The collection of charts of the GS and surrounding waters has been
annotated with satellite data indicating temperature. Using infra-red (IR)
imagery, satellite altimetry data, and surface in-situ temperature data,
oceanographic analyses were produced for this region in the form of 2-3 day
composite charts in a consistent manner. These charts show the location,
extent and temperature signature of currents (GS, shelf-slope front), warm and
cold-core rings (WCRs and CCRs), other eddies, shingles, intrusions, and other
water mass boundaries in the Gulf of Maine, over Georges Bank and in the
Middle Atlantic Bight.
 
The basis data source of those charts was individual
IR\\u00a0temperature\\u00a0images from the NOAA polar-orbiting satellites
(NOAA-5 in the early 1980s to NOAA-18 recently) at 6-12 hourly intervals.
These images were captured by the Advanced Very High Resolution Radiometer
(AVHRR) and AVHRR2 instruments, both of\\u00a0which had a resolution of 1.1 km
over the last four decades. Each individual image has a different lookup table
(or colormap) for temperature that resolves 256 distinct sets of intensity,
hue, and saturation of color within the available and retrievable IR signal
range.\\u00a0 This allows for accurate identification of the small-scale
features in each image. The analyst locates all of the small scale features in
each individual satellite SST image within a three-day period. The locations
and boundaries of the features (GS, WCR, CCR , and other smaller scale
entities) are remapped onto a 3-day composite image for that period.\\u00a0The
3-day composite image has a fixed and broad (5-30\\u00b0C) range of temperature
with similar 256-set indexing, which by itself could not resolve the features.
Note that individual images with high-resolution within a narrower band of
temperature range also have clouds, which are eliminated (or at least
minimized) during the process of generating the 3-day composites.\\u00a0 The
3-day composite helps to visualize the whole GS and its rings in a broader
region (like Figure 1a); while the individual images help resolve the features
at a very high resolution. The 3-day composite images are regularly produced
by NOAA and/or the Johns Hopkins University Applied Physics Lab (fermi) group
(see [http://fermi.jhuapl.edu](\\\\\"http://fermi.jhuapl.edu\\\\\") for more
details).";
    String awards_0_award_nid "810174";
    String awards_0_award_number "OCE-0815679";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0815679";
    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 "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "810186";
    String awards_1_award_number "OCE-1657853";
    String awards_1_data_url "https://www.nsf.gov/awardsearch/showAward?AWD_ID=1657853";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Dr Baris M. Uz";
    String awards_1_program_manager_nid "713922";
    String awards_2_award_nid "810188";
    String awards_2_award_number "NOAA-NA11NOS0120038";
    String awards_2_funder_name "National Oceanic and Atmospheric Administration";
    String awards_2_funding_acronym "NOAA";
    String awards_2_funding_source_nid "352";
    String cdm_data_type "Other";
    String comment 
"Warm Core Ring Census, 1980-2017 
   A. Gangopadhyay (UMass-Dartmouth), G. Gawarkiewicz (WHOI) 
   Yearly census of Warm Core Ring formation from 1980 to 2017 in the N. Atlantic 
   version date: 2020-05-06";
    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 "2020-04-29T14:32:35Z";
    String date_modified "2020-05-08T17:49:41Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.810182.1";
    Float64 Easternmost_Easting -54.96;
    Float64 geospatial_lat_max 43.82;
    Float64 geospatial_lat_min 35.78;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -54.96;
    Float64 geospatial_lon_min -75.0;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-14T03:17:41Z (local files)
2024-11-14T03:17:41Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_810182.das";
    String infoUrl "https://www.bco-dmo.org/dataset/810182";
    String institution "BCO-DMO";
    String keywords "area, Area_km2, bco, bco-dmo, biological, chemical, data, dataset, dmo, doa, dob, erddap, km2, latitude, Latitude_D, longitude, Longitude_D, management, name, oceanography, office, preliminary, time, wcr, WCR_Name";
    String license "https://www.bco-dmo.org/dataset/810182/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/810182";
    Float64 Northernmost_Northing 43.82;
    String param_mapping "{'810182': {'Latitude_F': 'flag - latitude', 'Longitude_F': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/810182/parameters";
    String people_0_affiliation "University of Massachusetts Dartmouth";
    String people_0_affiliation_acronym "UMass Dartmouth";
    String people_0_person_name "Avijit Gangopadhyay";
    String people_0_person_nid "810178";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Glen Gawarkiewicz";
    String people_1_person_nid "734777";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Nancy Copley";
    String people_2_person_nid "50396";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "GLOBEC_PRS_Freshwater Inputs";
    String projects_0_acronym "GLOBEC_PRS_Freshwater Inputs";
    String projects_0_description 
"This research addresses several mechanisms by which freshwater influx might impact the primary production of Calanus finmarchicus in the northern North Atlantic Ocean. Variability in the winter North Atlantic Oscillation index is related to changes in various physical and biological parameters across the entire North Atlantic, but the mechanisms underlying those relationships are not well known. Understanding basin-to-regional connections is important for interpreting patterns of variability observed on both sides of the Atlantic during the core GLOBEC study period (1993-1999) and from earlier observations, and inferring process, whether local or remote, from those observed patterns. The proposed research is focused on: (1) comparing and contrasting the impact of freshwater influx to the eastern and western sides of the North Atlantic, (2) understanding the development and maintenance of a possible three-gyre configuration of Calanus finmarchicus distribution in the North Atlantic, and (3) predicting the projected trends and variations in the North Atlantic Ocean based on IPCC projections for upcoming decades.
This project seeks a synthetic understanding of how basin- and global-scales changes in climate force physical processes that in turn determine local- and regional-scale biological communities, with a particular focus on freshwater forcing of circulation, mixing, and marine ecosystems within the North Atlantic Ocean. It is pan-regional in scope, building upon the successes of the U.S. GLOBEC program in the Western North Atlantic (and its other regions) to address climate variability issues spanning the entire northern North Atlantic Ocean. Its research approaches include: synthesis of datasets across the North Atlantic, multi-scale coupled physical/biological modeling, and comparative regional studies. In all these respects it responds directly to the U.S. GLOBEC Pan-Regional Synthesis Announcement of Opportunity.
Two graduate students will participate in this project. Results will be disseminated by peer-reviewed scientific publications, presentations at national conferences, and to other Pan-Regional GLOBEC investigators. Model output will be made available via the Rutgers OPeNDAP server. The investigators will give public lectures in Schools of Massachusetts, Maine and New Jersey on the importance of NAO and its impact on the regional ecosystem as part of an ongoing K-12 outreach program. The forecast scenarios for the next two decades will increase awareness of Climate Change. Dr. Fei Chai is a New Investigator to the GLOBEC program and will bring considerable expertise from his associations in the Pacific and in the Climate Change communities. Finally, this project sets the stage for post-GLOBEC end-to-end studies in the North Atlantic (e.g., the BASIN program).";
    String projects_0_end_date "2013-06";
    String projects_0_geolocation "North Atlantic";
    String projects_0_name "Collaborative Research: GLOBEC Pan Regional Synthesis: The Effect of Varying Freshwater Inputs on Regional Ecosystems in the North Atlantic";
    String projects_0_project_nid "810175";
    String projects_0_start_date "2008-07";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 35.78;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Yearly census of Gulf Stream Warm Core Ring formation from 1980 to 2017. This continuous census file contains the formation and demise times and locations, and the area at formation for all 961 WCRs formed between 1980 and 2017 that lived for a week or more. Each row represents a unique Warm Core Ring and is identified by a unique alphanumeric code 'WEyyyymmddA', where 'WE' represents a Warm Eddy (as identified in the analysis charts); 'yyyymmdd' is the year, month and day of formation; and the last character 'A' represents the sequential sighting of the eddies in a particular year. For example, the first ring in 2017 having a trailing alphabet of 'E' indicates that four rings were carried over from 2016 which are still observed on January 1, 2017.";
    String title "[Warm Core Ring Census (1980-2017)] - Yearly census of Gulf Stream Warm Core Ring formation from 1980 to 2017 (Collaborative Research: GLOBEC Pan Regional Synthesis: The Effect of Varying Freshwater Inputs on Regional Ecosystems in the North Atlantic)";
    String version "1";
    Float64 Westernmost_Easting -75.0;
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

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
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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