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Dataset Title:  HF radar daily averaged surface currents from the MOOSE MEDTLN sites (Toulon
area) over the May 2012 to September 2014 period.
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Institution:  MIO UMR7294 CNRS / OSU Pytheas   (Dataset ID: hfradar_1b42_be47_cf37)
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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.3358736e+9, 1.4120784e+9;
    String axis "T";
    String calendar "GREGORIAN";
    String ioos_category "Time";
    String lon_name "Center time of the averaging window UTC";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 42.45000076293945, 43.04408645629883;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String point_spacing "uneven";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 5.699999809265137, 6.707389831542969;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    Float64 modulo 360.0;
    String point_spacing "uneven";
    String standard_name "longitude";
    String units "degrees_east";
  }
  EWCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Currents";
    String long_name "Daily averaged surface eastward sea water velocity";
    Float64 missing_value -1.0e+34;
    String standard_name "eastward_sea_water_velocity";
    String units "m/s";
  }
  NSCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Currents";
    String long_name "Daily averaged surface northward sea water velocity";
    Float64 missing_value -1.0e+34;
    String standard_name "northward_sea_water_velocity";
    String units "m/s";
  }
  EWCS {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Statistics";
    String long_name "Daily standard deviation of EWCT";
    Float64 missing_value -1.0e+34;
    String units "m/s";
  }
  NSCS {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Statistics";
    String long_name "Daily standard deviation of NSCT";
    Float64 missing_value -1.0e+34;
    String units "m/s";
  }
  QC_EWCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 300.0;
    Float64 colorBarMinimum 0.0;
    String flag_meanings "0: bad or missing, < 1.5 possibly RFI biased values, 1.5-3: probably good data, 3-4: good data";
    String flag_values "0 to 4 (daily mean of hourly values)";
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Quality";
    String long_name "Daily averaged QC for EWCT";
    Float64 missing_value -1.0e+34;
  }
  QC_NSCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 300.0;
    Float64 colorBarMinimum 0.0;
    String flag_meanings "0: bad or missing, < 1.5 possibly RFI biased values, 1.5-3: probably good data, 3-4 : good data";
    String flag_values "0 to 4 (daily mean of hourly values)";
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Quality";
    String long_name "Daily averaged QC for NSCT";
    Float64 missing_value -1.0e+34;
  }
  N_EWCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Statistics";
    String long_name "Number of hourly EWCT values over the 25h centered time averaging window";
    Float64 missing_value -1.0e+34;
  }
  N_NSCT {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String history "From ../current_L3_LIar_L1_1fcleaned_2012-2014.nc";
    String ioos_category "Statistics";
    String long_name "Number of hourly NSCT values over the 25h centered time averaging window";
    Float64 missing_value -1.0e+34;
  }
  NC_GLOBAL {
    String aknowledgement "The MOOSE HFradar network was set up and is currently maintained with support from CNRS/INSU, Toulon University, ALLENVI, the EU MED Program TOSCA and H2020-INFRAIA JERICO-next project, the PACA Regional Council and Var Department. Thanks also to the radar site hosting partners: Port-Cros National Park, Conservatoire du littoral, CETMEF and Association Syndicale Autorisée du Cap Bénat";
    String area "Northwest Mediterranean Sea";
    String cdm_data_type "Grid";
    String citation " Zakardjian B., Quentin C.,  (2018). MOOSE HF radar daily averaged surface currents from MEDTLN site (Toulon NW Med). SEANOE, http://doi.org/10.17882/56500. A user should also acknowledge use of the HFradar MOOSE data in all publications and products where such data are used, preferably with the following standard sentence : The MOOSE HFradar network was set up and is currently maintained with support from CNRS/INSU, Toulon University, ALLENVI, the H2020-INFRAIA JERICO-next project, the PACA Regional Council and Var Department.";
    String comment "The daily averaged currents in this dataset are computed from hourly total velocity data of level L3B (velocity threshold and GDOP threshold tests passed) for which additional RFI outliers elimination are made using a one inertial period (17h at 43°N) statistical method (B. Zakardjian May-June 2015) based on the number of L3B valid data, variance and mean over the 17h period by reference to the long term (full dataset) statistics. The associated quality control (QC) indexes for the hourly data range from 0 (missing or bad values) to 4 (best confidence values). Details of the method available on the MOOSE HFradar website. Velocity and QC values in this file are those averaged on a lunar daily basis (25 hours average) centered at noon of each day.";
    String contributor_name "Barbin Y., Bellomo L., Bernardet K., Forget P., Gagelli J., Grosdidier S., Guerin C.-A., Marmain J., Molcard A., Quentin C., Zakardjian B.";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "Mediterranean Institute of Oceanography - UMR7294/UM110 AMU/UTLN/CNRS/IRD http://mio.pytheas.univ-amu.fr/";
    String creator_type "institution";
    String data_mode "D";
    String date_created "2018-08-23T10:00:00Z";
    Float64 Easternmost_Easting 6.707389831542969;
    String format_version "Delayed_Time_v1.0";
    Float64 geospatial_lat_max 43.04408645629883;
    Float64 geospatial_lat_min 42.45000076293945;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 6.707389831542969;
    Float64 geospatial_lon_min 5.699999809265137;
    String geospatial_lon_units "degrees_east";
    String history 
"FERRET V6.93    6-Sep-18
2020-10-21T07:33:50Z (local files)
2020-10-21T07:33:50Z http://erddap.osupytheas.fr/griddap/hfradar_1b42_be47_cf37.das";
    String id "MOOSE_HFradar_MEDTLN_DT_v1";
    String infoUrl "???";
    String institution "MIO UMR7294 CNRS / OSU Pytheas";
    String keywords "25h, amu, amu.fr, area, averaged, averaging, centered, circulation, cnrs, control, currents, daily, data, day, deviation, earth, Earth Science > Oceans > Ocean Circulation > Ocean Currents, eastward, eastward_sea_water_velocity, EWCS, ewct, frequency, HF, hf radar, hfradar, high, hour, hourly, institute, ird, LATITUDE, LONGITUDE, mediterranean, medtln, mio.pytheas.univ, mio.pytheas.univ-amu.fr, moose, N_EWCT, N_NSCT, northward, northward_sea_water_velocity, NSCS, nsct, number, ocean, ocean currents, oceanography, oceans, over, period, QC_EWCT, QC_NSCT, quality, radar, science, scr-hf, sea, seawater, sites, standard, statistics, surface, surface water, time, toulon, um110, umr7294, utln, values, velocity, water, window";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "The MOOSE HFradar dataset is licensed under a Creative Commons Attribution 4.0 International license type CC-BY-NC https://creativecommons.org/licenses/by-nc/4.0/";
    String naming_authority "mio.pytheas.univ-amu.fr";
    String netcdf_format "netcdf4_classic";
    String netcdf_version "4.3.1.1";
    String network "MOOSE_HFradar_MEDTLN";
    Float64 Northernmost_Northing 43.04408645629883;
    String platform_code "MEDTLN";
    String processing_level "4";
    String project "SNO/SOERE MOOSE and H2020-INFRAIA JERICO-next";
    String publisher_email "Bruno.Zakardjian@mio.osupytheas.fr - Celine.Quentin@mio.osupytheas.fr";
    String publisher_name "Bruno Zakardjian/Céline Quentin";
    String publisher_url "mio.pytheas.univ-amu.fr - http://hfradar.univ-tln.fr";
    String sensor_type "WERA  (Wellen  Radar - Helzel Messtechnik GmbH) operated at 16.1-16.2 MHz - 50 kHz bandwidth (3km range resolution) - 8 receiving antennas and MUSIC Direction Finding (2° azimuthal resolution) in monostatic (Peyras site) and bistatic (Benat-Porquerolles site) configuration. Vector component gridded on a 2km X 2km Cartesian regular grid. More details of the intallation and acquisition protocols can be found on the real-time dedicated web site http://hfradar.univ-tln.fr/ and in Quentin et al. 2014. 7th EuroGOOS Conference, Oct 2014, Lisboa, Portugal <hal-01131489>.";
    String source "coastal structure";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 42.45000076293945;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "The dataset consists of daily averaged surface currents computed from High Frequency (HF) radar hourly total velocity (Quality Control (QC) level L3b) with additional QC tests as described in the comment attribute below.";
    String time_coverage_end "2014-09-30T12:00:00Z";
    String time_coverage_resolution "P1D";
    String time_coverage_start "2012-05-01T12:00:00Z";
    String title "HF radar daily averaged surface currents from the MOOSE MEDTLN sites (Toulon area) over the May 2012 to September 2014 period.";
    String update_interval "void";
    Float64 Westernmost_Easting 5.699999809265137;
  }
}

 

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its projection 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.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.


 
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