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Dataset Title:  [Carbonate_Chemistry_2017-2018] - Carbonate chemistry effects from Hurricane
Harvey in San Antonio Bay and Mission Aransas Estuary from 2017-02-22 to 2018-
11-15 (CAREER: The Impact of Hydrologic State on CO2 Flux and Acidification in
Subtropical Estuaries)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_784673)
Range: longitude = -97.200836 to -96.6843°E, latitude = 27.838057 to 28.39354°N, depth = 0.0 to 6.2m
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 {
  Station {
    String bcodmo_name "station";
    String description "station name";
    String long_name "Station";
    String units "unitless";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -97.200833, -96.6843;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude with negative values indicating West";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 27.838056, 28.39354;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude with negative values indicating South";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  DATE {
    String bcodmo_name "date";
    String description "sample date in dd-mmm-yy format";
    String long_name "DATE";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 6.2;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "sample depth";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  TEMP {
    Float32 _FillValue NaN;
    Float32 actual_range 10.0, 32.5;
    String bcodmo_name "temperature";
    String description "Temperature";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "degrees C";
  }
  SAL {
    Float32 _FillValue NaN;
    Float32 actual_range 0.19, 37.17;
    String bcodmo_name "sal";
    String description "Salinity";
    String long_name "SAL";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "psu";
  }
  DIC {
    Float32 _FillValue NaN;
    Float32 actual_range 1361.0, 3471.6;
    String bcodmo_name "DIC";
    String description "total dissolved inorganic carbon";
    String long_name "DIC";
    String units "micromole per kilogram (umol/kg)";
  }
  TA {
    Float32 _FillValue NaN;
    Float32 actual_range 1245.4, 3674.2;
    String bcodmo_name "TALK";
    String description "Total titration alkalinity";
    String long_name "TA";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MDMAP014/";
    String units "micromole per kilogram (umol/kg)";
  }
  Calcium {
    Float32 _FillValue NaN;
    Float32 actual_range 0.51, 10.76;
    String bcodmo_name "Ca";
    String description "Calcium";
    String long_name "Calcium";
    String units "milimole per kilogram (mmol/kg)";
  }
  pH {
    Float32 _FillValue NaN;
    Float32 actual_range 7.1422, 8.7109;
    String bcodmo_name "pH";
    Float64 colorBarMaximum 9.0;
    Float64 colorBarMinimum 7.0;
    String description "pH at 25C";
    String long_name "Sea Water Ph Reported On Total Scale";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHXXZZXX/";
    String units "unitless";
  }
  pH_Label {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 4;
    String bcodmo_name "unknown";
    String description "1-spectophotometric method; 4-potentiometric method";
    String long_name "P H Label";
    String units "unitless";
  }
  ISO_Date {
    String bcodmo_name "date";
    String description "Date in ISO format following yyyy-mm-dd format";
    String long_name "ISO Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "ISO_Date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description "\"\"";
    String awards_0_award_nid "751076";
    String awards_0_award_number "OCE-1654232";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1654232";
    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 "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String awards_1_award_nid "783255";
    String awards_1_award_number "OCE-1760006";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1760006";
    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 "Henrietta N Edmonds";
    String awards_1_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Effects of Hurricane Harvey in San Antonio Bay and Mission Aransas Estuary carbonate chemistry from 2017-02-22 to 2018-11-15 
  PI: Xinping Hu 
  Version: 2019-12-19";
    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 "2019-12-18T20:55:40Z";
    String date_modified "2019-12-19T17:12:42Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.784673.1";
    Float64 Easternmost_Easting -96.6843;
    Float64 geospatial_lat_max 28.39354;
    Float64 geospatial_lat_min 27.838056;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -96.6843;
    Float64 geospatial_lon_min -97.200833;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 6.2;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-08T05:49:58Z (local files)
2024-11-08T05:49:58Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_784673.das";
    String infoUrl "https://www.bco-dmo.org/dataset/784673";
    String institution "BCO-DMO";
    String instruments_0_acronym "YSI Sonde 6-Series";
    String instruments_0_dataset_instrument_description "Water physical measurements - YSI 6920 multisonde, YSI";
    String instruments_0_dataset_instrument_nid "784740";
    String instruments_0_description "YSI 6-Series water quality sondes and sensors are instruments for environmental monitoring and long-term deployments. YSI datasondes accept multiple water quality sensors (i.e., they are multiparameter sondes). Sondes can measure temperature, conductivity, dissolved oxygen, depth, turbidity, and other water quality parameters. The 6-Series includes several models. More from YSI.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0737/";
    String instruments_0_instrument_name "YSI Sonde 6-Series";
    String instruments_0_instrument_nid "663";
    String instruments_0_supplied_name "YSI 6920 multisonde";
    String instruments_1_acronym "Spectrophotometer";
    String instruments_1_dataset_instrument_description "pH - 8453 UV-Vis spectrophotometer, Agilent";
    String instruments_1_dataset_instrument_nid "784742";
    String instruments_1_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_1_instrument_name "Spectrophotometer";
    String instruments_1_instrument_nid "707";
    String instruments_1_supplied_name "8453 UV-Vis spectrophotometer";
    String instruments_2_acronym "Salinity Sensor";
    String instruments_2_dataset_instrument_description "Salinity - Orion Star™ A12, Thermo Scientific";
    String instruments_2_dataset_instrument_nid "784741";
    String instruments_2_description "Category of instrument that simultaneously measures electrical conductivity and temperature in the water column to provide temperature and salinity data.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/350/";
    String instruments_2_instrument_name "Salinity Sensor";
    String instruments_2_instrument_nid "710";
    String instruments_2_supplied_name "Orion Star A12";
    String instruments_3_dataset_instrument_description "Van Dorn Beta™ Horizontal Bottle, Aquatic Biotechnology";
    String instruments_3_dataset_instrument_nid "784739";
    String instruments_3_description "A free-flushing water sample bottle comprising a cylinder (polycarbonate, acrylic or PVC) with a stopper at each end. The bottle is closed by means of a messenger from the surface releasing the tension on a latex band and thus pulling the two stoppers firmly into place. A thermometer can be mounted inside the bottle. One or more bottles can be lowered on a line to allow sampling at a single or multiple depth levels. Van Dorn samplers are suitable for for physical (temperature), chemical and biological sampling in shallow to very deep water. Bottles are typically lowered vertically through the water column although a horizontal version is available for sampling near the seabed or at thermoclines or chemoclines. Because of the lack of metal parts the bottles are suitable for trace metal sampling, although the blue polyurethane seal used in the Alpha version may leach mercury. The Beta version uses white ASA plastic seals that do not leach mercury but are less durable.";
    String instruments_3_instrument_name "Van Dorn water sampler";
    String instruments_3_instrument_nid "755357";
    String instruments_3_supplied_name "Van Dorn Beta Horizontal Bottle";
    String keywords "altimetry, bco, bco-dmo, biological, calcium, chemical, chemistry, data, dataset, date, depth, dic, dmo, earth, Earth Science > Oceans > Ocean Chemistry > pH, erddap, iso, label, laboratory, latitude, longitude, management, ocean, oceanography, oceans, office, pH_Label, preliminary, reported, sal, satellite, scale, science, sea, sea_water_ph_reported_on_total_scale, seawater, station, TEMP, temperature, time, total, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/784673/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/784673";
    Float64 Northernmost_Northing 28.39354;
    String param_mapping "{'784673': {'Latitude': 'flag - latitude', 'DEPTH': 'flag - depth', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/784673/parameters";
    String people_0_affiliation "Texas A&M, Corpus Christi";
    String people_0_affiliation_acronym "TAMU-CC";
    String people_0_person_name "Xinping Hu";
    String people_0_person_nid "751079";
    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 BCO-DMO";
    String people_1_person_name "Mathew Biddle";
    String people_1_person_nid "708682";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "CO2 Flux and Acidification in Subtropical Estuaries,Hurricane Harvey Texas Lagoons";
    String projects_0_acronym "CO2 Flux and Acidification in Subtropical Estuaries";
    String projects_0_description 
"NSF Award Abstract:
This project is a CAREER award to Xinping Hu at Texas A&M University-Corpus Christi. Hu proposes to integrate research and education in an investigation of carbon cycling and ocean acidification in the Mission-Aransas Estuary in South Texas. This coastal system is strongly affected by changes in river flow between seasons and from year to year. The relationship of changing river flows to carbon cycling in estuaries is not well understood. This lack of understanding in turn contributes to uncertainty in estimating global estuarine carbon budgets. In addition, climate change and other human activities heavily influence riverine input into estuaries and the coastal ocean, which then affect biogeochemistry and metabolism in these environments. Despite the need for this information, long-term records that can help to address the change in the strength and directions of CO2 fluxes in these ecosystems are very rare. Using high-intensity field sampling and analysis of historical data, this project aims to improve understanding of carbon cycling in this estuary and in the coastal ocean in general. The results obtained from this study will also provide key information about the biogeochemical response of estuaries to changing hydrologic conditions, as the southwestern U.S. grows drier with overall declining precipitation.
The research objectives of this project include 1) investigating the relationship between hydrologic state and estuarine CO2 partial pressure (pCO2) in a case study of the Mission-Aransas Estuary, a subtropical semiarid estuary, 2) understanding the extent of CO2 flux and its hydrologic control in one of the world's largest lagoonal estuarine systems along the northwestern Gulf of Mexico, and 3) elucidating the mechanisms that lead to estuarine acidification and its feedback to CO2 fluxes. Intensive field campaigns for high-temporal resolution pCO2 and water carbonate chemistry sampling as well as sediment incubation will be carried out; analysis of multidecadal carbonate chemistry parameters that have been collected by Texas Commission on Environmental Quality will be used to obtain temporal trends of estuarine water pCO2 against the backdrop of increasing freshwater scarcity in this region. The education component of this CAREER award includes 1) creating an ocean and estuarine acidification research course and redesigning two existing courses for both undergraduate and graduate students, 2) collaborating with Foy Moody High School on their Aquatic Science education to engage high school students predominantly from underrepresented and economically challenged backgrounds in field and lab experiences. The ultimate educational goal is to encourage high school students to follow a STEM path for their college education, and undergraduate STEM students to pursue graduate degrees. This will be a part of the concerted effort to enhance diversity in the future workforce by increasing the number of underrepresented graduates with bachelor's or higher degrees in the STEM fields. This project will train one Ph.D. student. High school students and undergraduate interns from underrepresented and economically challenged backgrounds will also be supported to participate in summer research. Broader dissemination of the project findings will include undergraduate student presentations at symposiums organized by both TAMU-CC and the Texas A&M University System, public seminars by both the graduate students and the principal investigator at various meetings organized by regional estuarine programs, presentations at national and international meetings, and publications in peer-reviewed journals.";
    String projects_0_end_date "2022-04";
    String projects_0_geolocation "Gulf of Mexico";
    String projects_0_name "CAREER: The Impact of Hydrologic State on CO2 Flux and Acidification in Subtropical Estuaries";
    String projects_0_project_nid "751077";
    String projects_0_project_website "http://hulab.tamucc.edu/research.htm";
    String projects_0_start_date "2017-05";
    String projects_1_acronym "Hurricane Harvey Texas Lagoons";
    String projects_1_description 
"NSF Award Abstract:
Hurricane Harvey made landfall Friday 25 August 2017 about 30 miles northeast of Corpus Christi, Texas as a Category 4 hurricane with winds up to 130 mph. This is the strongest hurricane to hit the middle Texas coast since Carla in 1961. After the wind storm and storm surge, coastal flooding occurred due to the storm lingering over Texas for four more days, dumping as much as 50 inches of rain near Houston. This will produce one of the largest floods ever to hit the Texas coast, and it is estimated that the flood will be a one in a thousand year event. The Texas coast is characterized by lagoons behind barrier islands, and their ecology and biogeochemistry are strongly influenced by coastal hydrology. Because this coastline is dominated by open water systems and productivity is driven by the amount of freshwater inflow, Hurricane Harvey represents a massive inflow event that will likely cause tremendous changes to the coastal environments. Therefore, questions arise regarding how biogeochemical cycles of carbon, nutrients, and oxygen will be altered, whether massive phytoplankton blooms will occur, whether estuarine species will die when these systems turn into lakes, and how long recovery will take? The investigators are uniquely situated to mount this study not only because of their location, just south of the path of the storm, but most importantly because the lead investigator has conducted sampling of these bays regularly for the past thirty years, providing a tremendous context in which to interpret the new data gathered. The knowledge gained from this study will provide a broader understanding of the effects of similar high intensity rainfall events, which are expected to increase in frequency and/or intensity in the future.
The primary research hypothesis is that: Increased inflows to estuaries will cause increased loads of inorganic and organic matter, which will in turn drive primary production and biological responses, and at the same time significantly enhance respiration of coastal blue carbon. A secondary hypothesis is that: The large change in salinity and dissolved oxygen deficits will kill or stress many estuarine and marine organisms. To test these hypotheses it is necessary to measure the temporal change in key indicators of biogeochemical processes, and biodiversity shifts. Thus, changes to the carbon, nitrogen and oxygen cycles, and the diversity of benthic organisms will be measured and compared to existing baselines. The PIs propose to sample the Lavaca-Colorado, Guadalupe, Nueces, and Laguna Madre estuaries as follows: 1) continuous sampling (via autonomous instruments) of salinity, temperature, pH, dissolved oxygen, and depth (i.e. tidal elevation); 2) bi-weekly to monthly sampling for dissolved and total organic carbon and organic nitrogen, carbonate system parameters, nutrients, and phytoplankton community composition; 3) quarterly measurements of sediment characteristics and benthic infauna. The project will support two graduate students. The PIs will communicate results to the public and to state agencies through existing collaborations.";
    String projects_1_end_date "2019-08";
    String projects_1_geolocation "Northwest Gulf of Mexico estuaries on Texas Coast";
    String projects_1_name "RAPID: Capturing the Signature of Hurricane Harvey on Texas Coastal Lagoons";
    String projects_1_project_nid "783256";
    String projects_1_start_date "2017-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 27.838056;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "A calibrated YSI 6920 multisonde was used to obtain in-situ temperature at both the surface (~0.5 m) and the bottom (within 0.5 m from the sediment-water interface) of the water column, and a Van Dorn water sampler was used to take water samples from both the surface and bottom of the water column.";
    String title "[Carbonate_Chemistry_2017-2018] - Carbonate chemistry effects from Hurricane Harvey in San Antonio Bay and Mission Aransas Estuary from 2017-02-22 to 2018-11-15 (CAREER: The Impact of Hydrologic State on CO2 Flux and Acidification in Subtropical Estuaries)";
    String version "1";
    Float64 Westernmost_Easting -97.200833;
    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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