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Dataset Title:	[Edmunds et al. MarBio 2019a: Transmission data] - Light data (transmission) from surveys conducted in St. John, US Virgin Islands in 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_793561)
Range:	time = 2017-08-17T14:02Z to 2017-11-30T17:02Z
Information:	Summary \| License \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Underwater_Date_Local {
    String bcodmo_name "date_local";
    String description "Local date (AST,UTC-4) in ISO format yyyy-mm-dd";
    String long_name "Underwater Date Local";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  Underwater_Time_Local {
    String bcodmo_name "time_local";
    String description "Local time (AST,UTC-4) in ISO format HH:MM";
    String long_name "Underwater Time Local";
    String units "unitless";
  }
  Underwater_Light {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 512;
    String bcodmo_name "PAR";
    String description "Underwater PAR";
    String long_name "Underwater Light";
    String units "micromoles per square meter per second (µmol quanta/m2/s)";
  }
  Surface_DateTime_Local {
    String bcodmo_name "DateTime";
    String description "Local date and time (AST,UTC-4) at the surface in ISO format yyyy-mm-dd HH:MM";
    String long_name "Surface Date Time Local";
    String source_name "Surface_DateTime_Local";
    String time_precision "1970-01-01T00:00Z";
    String units "unitless";
  }
  Surface_Light {
    Int16 _FillValue 32767;
    Int16 actual_range 24, 2516;
    String bcodmo_name "PAR";
    String description "Surface PAR";
    String long_name "Surface Light";
    String units "micromoles per square meter per second (µmol quanta/m2/s)";
  }
  Transmition_Percent {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 35.1;
    String bcodmo_name "transmission";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Mean light transmission percent to depth (two values per day)";
    String long_name "Transmition Percent";
    String units "percent";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.50297852e+9, 1.51206132e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date time (UTC) at the surface in ISO format yyyy-mm-ddTHH:MMZ";
    String ioos_category "Time";
    String long_name "Surface Date Time ISO 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";
    String acquisition_description 
"The following methodology applies to this dataset in addition to other
datasets published in Edmunds et al. (2019).
 
Methodology:  
 This study was completed on the coral reefs of St. John, which have been the
subjects of time-series analyses for 32 years. The measurements described
herein originated from a schedule of instrument deployments initiated in 2014
to quantify variation in underwater physical environmental conditions, and
ultimately, to facilitate testing for their role in driving changes in benthic
community structure. As part of this schedule, rainfall was recorded
throughout the year, and a light meter was placed in Great Lameshur Bay in
August 2017, with the objective of leaving it immersed for 6\\u201312 months.
Three weeks later, the first of two Category 5 hurricanes impacted the island,
with the second arriving 14 days later. The discovery in July 2018 that this
meter had survived the storms, and had remained upright and functional,
created the opportunity to describe underwater light during, and immediately
after, two major storms.
 
Rainfall was recorded on the north shore of St. John at Windswept Beach
(18\\u00b0 21\\u00b4 20.95N, 64\\u00b0 45\\u00b4 57.53W), where a 20.3 cm,
Standard Rain Gauge (NOAA, National Weather Service) was mounted on a roof,
1.5 m above the ground. This rain gauge was ~ 6.7 km from the underwater light
sensor, and was emptied and read on a daily basis.
 
Underwater light was recorded with a light meter (Compact LW, JFE Advantech
Co., Ltd, Japan) fitted with a cosine-corrected sensor recording
photosynthetically active radiation (PAR, 400-700 nm wavelength) as
photosynthetic photon flux density (PPFD). The meter was equipped with a
mechanical wiper that cleaned the sensor before every measurement, and it was
mounted with the sensor at 19.1-m depth on the eastern side of Great Lameshur
Bay (18\\u00b0 18\\u00b4 37.04N, 64\\u00b0 43\\u00b4 23.17W. The instrument was
operated in burst mode during which 10 measurements were recorded every 180
minutes, with 30 seconds separating measurements within a burst. This sampling
regime ensured that the battery would support a deployment of one year. The
Compact LW meter is designed for oceanographic applications to 200-m depth, is
fitted with a photodiode sensor, and has an accuracy of \\u00b1 4% (over
0\\u20132,000 \\u00b5mol photons m-2 s-1) and resolution of 0.1 \\u00b5mol
photons m-2 s-1. The sensors are calibrated by the manufacturer, with the
calibration stable for at least 1 year. When the meter was deployed in August
2017, it had been used underwater for ~ 16 mo in previous deployments, and
initial records of PPFD were similar to those previously recorded at the same
depth and time of year in St. John, which suggested that the calibration had
not appreciably drifted.
 
PPFD also was measured on the surface, using two cosine-corrected sensors
(S-LIA-M003, Onset Computer Corporation) mounted ~ 4 m above sea level on the
roof of the lab, ~ 0.875 km from the underwater sensor. The surface sensors
were attached to weather stations (Micro Station Data Logger H21-002, Onset
Computer Corporation) that recorded light every 5 minutes. The two sensors
were calibrated by the manufacturers, and were operated in a paired mode to
detect spurious records and sensor drift, and to guard against equipment
malfunction.";
    String awards_0_award_nid "722162";
    String awards_0_award_number "OCE-1801335";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1801335";
    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 "Daniel Thornhill";
    String awards_0_program_manager_nid "722161";
    String cdm_data_type "Other";
    String comment 
"Edmunds et al. MarBio 2019a: Transmission data 
  PI: Peter J. Edmunds 
  Data Version 1: 2020-02-17";
    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 "2020-02-17T17:29:54Z";
    String date_modified "2020-02-18T17:54:32Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.793561.1";
    String history 
"2024-11-08T06:05:03Z (local files)
2024-11-08T06:05:03Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_793561.das";
    String infoUrl "https://www.bco-dmo.org/dataset/793561";
    String institution "BCO-DMO";
    String instruments_0_acronym "AWS";
    String instruments_0_dataset_instrument_description "A Standard Rain Gauge (NOAA, National Weather Service) was mounted on a roof 1.5 m above the ground.";
    String instruments_0_dataset_instrument_nid "793569";
    String instruments_0_description "Land-based AWS systems are designed to record meteorological information.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/102/";
    String instruments_0_instrument_name "Automated Weather Station";
    String instruments_0_instrument_nid "407";
    String instruments_0_supplied_name "Standard Rain Gauge";
    String instruments_1_acronym "Light Meter";
    String instruments_1_dataset_instrument_description "Underwater light was recorded with a light meter (Compact LW, JFE Advantech Co., Ltd, Japan) fitted with a cosine-corrected sensor recording photosynthetically active radiation (PAR, 400-700 nm wavelength) as photosynthetic photon flux density (PPFD).";
    String instruments_1_dataset_instrument_nid "793568";
    String instruments_1_description "Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)";
    String instruments_1_instrument_name "Light Meter";
    String instruments_1_instrument_nid "703";
    String instruments_1_supplied_name "Compact LW";
    String instruments_2_acronym "Light Meter";
    String instruments_2_dataset_instrument_description "PPFD was measured on the surface, using two cosine-corrected sensors (S-LIA-M003, Onset Computer Corporation)";
    String instruments_2_dataset_instrument_nid "793570";
    String instruments_2_description "Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)";
    String instruments_2_instrument_name "Light Meter";
    String instruments_2_instrument_nid "703";
    String instruments_2_supplied_name "S-LIA-M003, Onset Computer Corporation";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, dmo, erddap, iso, light, local, management, oceanography, office, percent, preliminary, surface, Surface_DateTime_ISO_UTC, Surface_Light, time, transmition, Transmition_Percent, underwater, Underwater_Date_Local, Underwater_Light, Underwater_Time_Local";
    String license "https://www.bco-dmo.org/dataset/793561/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/793561";
    String param_mapping "{'793561': {'Surface_DateTime_ISO_UTC': 'master - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/793561/parameters";
    String people_0_affiliation "California State University Northridge";
    String people_0_affiliation_acronym "CSU-Northridge";
    String people_0_person_name "Peter J. Edmunds";
    String people_0_person_nid "51536";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Dr Georgios Tsounis";
    String people_1_person_nid "565353";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Laboratoire d'Écogéochimie des Environnements Benthiques";
    String people_2_affiliation_acronym "LECOB";
    String people_2_person_name "Dr Lorenzo Bramanti";
    String people_2_person_nid "562094";
    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 "Amber D. York";
    String people_3_person_nid "643627";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Hurricane Irma and St. John Reefs";
    String projects_0_acronym "Hurricane Irma and St. John Reefs";
    String projects_0_description 
"Coral reefs have long been recognized for their diversity, and unique functional roles, but these features have been undermined by decades of disturbances that cast doubt on their ability to survive. Against this backdrop, 2017 brought two hurricanes of unprecedented magnitude to the Caribbean, both of which damaged coral reefs that already were degraded compared to those of a few decades ago. While the impacts of these storms on some of the few coral reefs protected within the US National Park and National Monument systems is particularly unfortunate, it also creates unique opportunities to understand the impacts on coral reefs that have been studied in detail for decades. This project builds on these opportunities by leveraging 31 years of coral reef monitoring research, much of which has been supported by NSF, to describe the impacts of Hurricanes Irma and Maria on coral reefs in St. John, US Virgin Islands. That the analyses will reveal severe destruction is a forgone conclusion, but what remains unknown is how present-day reefs will respond to severe versions of a well-known disturbance (hurricanes), and how these effects will impact their long-term survival. Post-storm surveys and new analyses will be used to determine whether ongoing declines in coral abundance have influenced the way coral reefs respond to storms, notably to enhance post-storm mortality, and reduce the capacity to recover from such event. To achieve these outcomes, a team of researchers from California State University, Northridge, will use a cruise on the R/V Walton Smith to survey the reefs of St. John using photography and in-water counts to generate data that will be analyzed throughout 2018. The benefits of this research will extend beyond scientific discoveries to include leveraged support for other scientists participating in the cruise, evaluation of the status of natural resources in the VI National Park, the delivery of relief supplies from Miami to St. John, and the creation of unique research and training opportunities for graduate students who will participate in all phases of the project.
Coral reefs have undergone dramatic changes in community structure since they were first described in the 1950's, and the current onslaught of threats from rising temperature, declining seawater pH, storms, and numerous other events has cast doubt on their persistence in the Athropocene. With such profound changes underway, time-series analyses of community structure are on the cutting edge of contemporary studies of coral reefs. In the Caribbean, the impact of two category 5 hurricanes underscores why time-series are important, as they are the only means to describe the impact of such events, and critically, create the context for testing hypotheses regarding impacts and consequences of disturbances. This project addresses the impacts of Hurricanes Irma and Maria on the coral reefs of St. John, US Virgin Islands, which have been studied since the 1950's, and for the last 31 years largely with NSF LTREB support. This support provides descriptions of the population dynamics of the important coral, Orbicella annularis, and the coral community dynamics in adjacent habitats. Any study of the effects of these storms will demonstrate that large waves kill corals, but here intellectual merit is acquired through testing of general hypotheses: (1) storm impacts on O. annularis will be colony-density dependent, (2) delayed coral mortality will be accentuated compared to previous storms, (3) the resilience of coral communities to physical disturbances has declined since 1989, and (4) evolutionary rescue will mediate reef recovery for select corals through large initial population sizes, density-dependent population growth, and recruitment. These hypotheses will be tested using a 14 day cruise on the R/V Walton Smith to collect critical time-sensitive data, followed by a year of analysis of new and legacy photographic data.";
    String projects_0_end_date "2018-10";
    String projects_0_geolocation "St. John, US Virgin Islands";
    String projects_0_name "RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience";
    String projects_0_project_nid "722163";
    String projects_0_project_website "http://coralreefs.csun.edu";
    String projects_0_start_date "2017-11";
    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 "Light data (transmission) from surveys conducted in Great Lameshur Bay, St. John, US Virgin Islands in 2017. These data were used in Edmunds et al. (2019) in Figure 2.";
    String time_coverage_end "2017-11-30T17:02Z";
    String time_coverage_start "2017-08-17T14:02Z";
    String title "[Edmunds et al. MarBio 2019a: Transmission data] - Light data (transmission) from surveys conducted in St. John, US Virgin Islands in 2017 (RAPID: Hurricane Irma: Effects of repeated severe storms on shallow Caribbean reefs and their changing ecological resilience)";
    String version "1";
    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.

(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.