BCO-DMO ERDDAP
Accessing BCO-DMO data

Data Access Form

Dataset Title:	[In-field temperature data Kane'ohe Bay] - In-field temperature data Kane'ohe Bay, O'ahu, Hawai'i from 2013 to 2023 (RAPID: Collaborative Research: Disentangling the effects of heat stress versus bleaching phenotype on coral performance)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_905047_v1)
Information:	Summary \| License \| Metadata \| Background \| Files \| Make a graph

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Variable	Minimum	Maximum
time (Iso_datetime_utc, UTC)	2013-11-29T01:17:00Z	2023-09-19T19:30:00Z

Temperature (degrees C)	"20.805"	"31.166"
Date (unitless)	"01/01/2014"	"12/31/2022"
time_local (Time, unitless)	"0:00"	"9:50:00"
Site (unitless)	"CRIMP"	"Reef13"
hour (unitless)	0	23
year (unitless)	2013	2023
day (unitless)	1	31
month (unitless)	1	12

Server-side Functions

distinct()

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File type: (more information)

(Documentation / Bypass this form )

(Please be patient. It may take a while to get the data.)

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.38568782e+9, 1.6951518e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Temperature {
    String long_name "Temperature";
    String units "degrees C";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  time_local {
    String long_name "Time";
    String units "unitless";
  }
  Site {
    String long_name "Site";
    String units "unitless";
  }
  hour {
    Int32 actual_range 0, 23;
    String long_name "Hour";
    String units "unitless";
  }
  year {
    Int32 actual_range 2013, 2023;
    String long_name "Year";
    String units "unitless";
  }
  day {
    Int32 actual_range 1, 31;
    String long_name "Day";
    String units "unitless";
  }
  month {
    Int32 actual_range 1, 12;
    String long_name "Month";
    String units "unitless";
  }
 }
  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.905047.1";
    String history 
"2024-11-21T08:30:35Z (local files)
2024-11-21T08:30:35Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_905047_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/905047";
    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.";
    String sourceUrl "(local files)";
    String summary "Increasingly frequent marine heatwaves are devastating coral reefs. Corals that survive these extreme events must rapidly recover if they are to withstand subsequent events, and long-term survival in the face of rising ocean temperatures may hinge on recovery capacity and acclimatory gains in heat tolerance over an individual's lifespan. To better understand coral recovery trajectories in the face of successive marine heatwaves, we monitored the responses of bleaching-susceptible and bleaching-resistant individuals of two dominant coral species in Hawaiʻi, Montipora capitata and Porites compressa, over a decade that included three marine heatwaves. This dataset includes the in situ temperature data from Kāne'ohe Bay, O'ahu, Hawai'i from 2013-2023.";
    String time_coverage_end "2023-09-19T19:30:00Z";
    String time_coverage_start "2013-11-29T01:17:00Z";
    String title "[In-field temperature data Kane'ohe Bay] - In-field temperature data Kane'ohe Bay, O'ahu, Hawai'i from 2013 to 2023 (RAPID: Collaborative Research: Disentangling the effects of heat stress versus bleaching phenotype on coral performance)";
  }
}

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.

(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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