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Dataset Title:  [MBRS SST 2003-2015: MUR] - Sea surface temperature JPL MUR data, Belize
Mesoamerican Barrier Reef System (MBRS), 2003-2015 (Investigating the influence
of thermal history on coral growth response to recent and predicted end-of-
century ocean warming across a cascade of ecological scales)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_734406)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 site (unitless) ?          1    14
 lat (Latitude, decimal degrees) ?          16.13    17.824
 longitude (degrees_east) ?          -88.629    -88.002
  < slider >
 date (unitless) ?          "2003-01-01"    "2015-11-18"
 temp (Temperature, degrees Celsius) ?          23.95    31.664
 temp_se (degrees Celsius) ?          0.0    0.42
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more information)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  site {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 14;
    String bcodmo_name "site";
    String description "site identifier";
    String long_name "Site";
    String units "unitless";
  }
  lat {
    Float32 _FillValue NaN;
    Float32 actual_range 16.13, 17.824;
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; 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";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -88.629, -88.002;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; 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 "long";
    String standard_name "longitude";
    String units "degrees_east";
  }
  date {
    String bcodmo_name "date";
    String description "date; formatted as yyyy-mm-dd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  temp {
    Float32 _FillValue NaN;
    Float32 actual_range 23.95, 31.664;
    String bcodmo_name "temperature";
    String description "daily 1-km horizontal resolution sea surface temperature estimate from the Jet Propulsion Laboratory's Multi-Scale High Resolution SST (JPL MUR SST)";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
  temp_se {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.42;
    String bcodmo_name "temperature";
    String description "temperature standard error";
    String long_name "Temp Se";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees Celsius";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Conventional 1-km resolution satellite-derived SST measurements (infrared, IR)
are contaminated by clouds, creating data-void areas. Microwave (MW) data sets
can penetrate clouds to gain better temporal coverage, but with a much coarser
spatial resolution (25 km) [36]. MUR combines these two datasets to present a
more comprehensive and complete SST product. It employs multi-resolution
variational analysis (MRBA) as an interpolation method to combine high
resolution datasets with more conventional datasets, generating a product that
contains no cloud contamination [36]. MUR reports estimates of foundation SST,
or SST at the base of the diurnal thermocline (~5-10m depth). Comparison of
in-situ temperature (recorded by HOBO\\u00ae v2 data loggers), MUR, and other
SST products revealed that MUR outperforms other products in estimating in-
situ temperature, although it also underestimates the temperature corals
experience at depth (S1 Fig). However, due to its temporal coverage and
temporal resolution, high spatial resolution, lack of cloud contamination, and
smaller method error compared to similar products such as Group for High
Resolution SST (GHRSST), MUR was determined to be the ideal SST product for
use in the current study.";
    String awards_0_award_nid "635862";
    String awards_0_award_number "OCE-1459522";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1459522";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Sea surface temperature time-series 
     Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015 
     Daily 1-km horizontal resolution SST estimates from  
     the Jet Propulsion Laboratory's Multi-Scale High Resolution SST (JPL MUR SST) (https://podaac.jpl.nasa.gov) 
   PI's: K. Castillo, J. Baumann 
   version: 2018-04-16 
   Published in Baumann et al, PLoS ONE (2016) 11(9) DOI: 10.1371/journal.pone.0162098 
   NOTE: data from 2012 are given twice at each site; only the first set,  
      along with the 2003-2011 data,  was used in the original analysis in Baumann et al (2016)";
    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 "2018-04-25T19:16:20Z";
    String date_modified "2019-12-11T18:41:10Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.734406.1";
    Float64 Easternmost_Easting -88.002;
    Float64 geospatial_lon_max -88.002;
    Float64 geospatial_lon_min -88.629;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-12-21T16:21:26Z (local files)
2024-12-21T16:21:26Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_734406.html";
    String infoUrl "https://www.bco-dmo.org/dataset/734406";
    String institution "BCO-DMO";
    String instruments_0_acronym "AVHRR";
    String instruments_0_dataset_instrument_description "One of several instruments used by NASA to produce sea surface temperature data products.";
    String instruments_0_dataset_instrument_nid "734436";
    String instruments_0_description "\"The AVHRR instrument consists of an array of small sensors that record (as digital numbers) the amount of visible and infrared radiation reflected and (or) emitted from the Earth's surface\" (more information).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/122/";
    String instruments_0_instrument_name "Advanced Very High Resolution Radiometer";
    String instruments_0_instrument_nid "455";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, dmo, erddap, latitude, longitude, management, oceanography, office, preliminary, site, temp_se, temperature, time";
    String license "https://www.bco-dmo.org/dataset/734406/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/734406";
    String param_mapping "{'734406': {'long': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/734406/parameters";
    String people_0_affiliation "University of North Carolina at Chapel Hill";
    String people_0_affiliation_acronym "UNC-Chapel Hill";
    String people_0_person_name "Karl D. Castillo";
    String people_0_person_nid "51711";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of North Carolina at Chapel Hill";
    String people_1_affiliation_acronym "UNC-Chapel Hill";
    String people_1_person_name "Justin Baumann";
    String people_1_person_nid "733684";
    String people_1_role "Student";
    String people_1_role_type "related";
    String people_2_affiliation "University of North Carolina at Chapel Hill";
    String people_2_affiliation_acronym "UNC-Chapel Hill";
    String people_2_person_name "Justin Baumann";
    String people_2_person_nid "733684";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Thermal History and Coral Growth";
    String projects_0_acronym "Thermal History and Coral Growth";
    String projects_0_description 
"Description from NSF award abstract:
Rising global ocean surface temperatures have reduced coral growth rates, thereby negatively impacting the health of coral reef ecosystems worldwide. Recent studies on tropical reef building corals reveal that corals' growth in response to ocean warming may be influenced by their previous seawater temperature exposure - their thermal history. Although these recent findings highlight significant variability in coral growth in response to climate change, uncertainty remains as to the spatial scale at which corals' thermal history influences how they have responded to ocean warming and how they will likely respond to predicted future increases in ocean temperature. This study investigates the influence of thermal history on coral growth in response to recent and predicted seawater temperatures increases across four ecologically relevant spatial scales ranging from reef ecosystems, to reef communities, to reef populations, to an individual coral colony. By understanding how corals have responded in the past across a range of ecological scales, the Principal Investigator will be able to improve the ability to predict their susceptibility and resilience, which could then be applied to coral reef conservation in the face of climate change. This research project will broaden the participation of undergraduates from underrepresented groups and educate public radio listeners using minority voices and narratives. The scientist will leverage current and new partnerships to recruit and train minority undergraduates, thus allowing them to engage high school students near field sites in Florida, Belize, and Panama. Through peer advising, undergraduates will document this research on a digital news site for dissemination to the public. The voice of the undergraduates and scientist will ground the production of a public radio feature exploring the topic of acclimatization and resilience - a capacity for stress tolerance within coral reef ecosystems. This project will provide a postdoctoral researcher and several graduate students with opportunities for field and laboratory research training, teaching and mentoring, and professional development. The results will allow policy makers from Florida, the Mesoamerican Barrier Reef System countries, and several Central American countries to benefit from Caribbean-scale inferences that incorporate corals' physiological abilities, thereby improving coral reef management for the region.
Coral reefs are at significant risk due to a variety of local and global scale anthropogenic stressors. Although various stressors contribute to the observed decline in coral reef health, recent studies highlight rising seawater temperatures due to increasing atmospheric carbon dioxide concentration as one of the most significant stressors influencing coral growth rates. However, there is increasing recognition of problems of scale since a coral's growth response to an environmental stressor may be conditional on the scale of description. This research will investigate the following research questions: (1) How has seawater temperature on reef ecosystems (Florida Keys Reef Tract, USA; Belize Barrier Reef System, Belize; and Bocas Del Toro Reef Complex, Panama), reef communities (inshore and offshore reefs), reef populations (individual reefs), and near reef colonies (individual colonies), varied in the past? (2) How has seawater temperature influenced rates of coral growth and how does the seawater temperature-coral growth relationship vary across these four ecological spatial scales? (3) Does the seawater temperature-coral growth relationship forecast rates of coral growth under predicted end-of-century ocean warming at the four ecological spatial scales? Long term sea surface temperature records and small-scale high-resolution in situ seawater temperature measurements will be compared with growth chronologies for the reef building corals Siderastrea siderea and Orbicella faveolata, two keystone species ubiquitously distributed throughout the Caribbean Sea. Nutrients and irradiance will be quantified via satellite-derived observations, in situ measurements, and established colorimetric protocols. Field and laboratory experiments will be combined to examine seawater temperature-coral growth relationships under recent and predicted end-of-century ocean warming at four ecologically relevant spatial scales. The findings of this study will help us bridge the temperature-coral growth response gap across ecologically relevant spatial scales and thus improve our understanding of how corals have responded to recent warming. This will lead to more meaningful predictions about future coral growth response to climate change.";
    String projects_0_end_date "2018-02";
    String projects_0_geolocation "Western Caribbean";
    String projects_0_name "Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales";
    String projects_0_project_nid "635863";
    String projects_0_project_website "http://www.unc.edu/~kdcastil/research.html";
    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)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset contains sea surface temperature data obtained from daily 1-km horizontal resolution SST estimates acquired from the Jet Propulsion Laboratory\\u2019s Multi-Scale High Resolution SST (JPL MUR SST) records via the Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the NASA JPL, Pasadena, CA (https://podaac.jpl.nasa.gov).\\r\\n\\r\\nNOTE: Data from 2012 are given twice at each site; only the first set, along with the 2003-2011 data,  was used in the original analysis in Baumann et al (2016). The 2012-2015 data were only available following revision in the peer review process. It became useful for making comparisons between the in-situ data and satellite data.\\r\\n\\r\\nThese data were used in a coral study in: Baumann JH, Townsend JE, Courtney TA, Aichelman HE, Davies SW, Lima FP, et al. (2016) Temperature Regimes Impact Coral Assemblages along Environmental Gradients on Lagoonal Reefs in Belize. PLoS ONE 11(9): e0162098. https://doi.org/10.1371/journal.pone.0162098.";
    String title "[MBRS SST 2003-2015: MUR] - Sea surface temperature JPL MUR data, Belize Mesoamerican Barrier Reef System (MBRS), 2003-2015 (Investigating the influence of thermal history on coral growth response to recent and predicted end-of-century ocean warming across a cascade of ecological scales)";
    String version "1";
    Float64 Westernmost_Easting -88.629;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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