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ERDDAP > griddap > Make A Graph ?

Dataset Title:  Data from a local source. Subscribe RSS
Institution:  ???   (Dataset ID: PMEL_FORECAST)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
time (UTC) ?     specify just 1 value →
    << -
< <
depth (m) ?     specify just 1 value →
    << -
< <
latitude (degrees_north) ?
    +
    -
< slider >
longitude (degrees_east) ?
    +
    -
< slider >
 
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   Ascending: 
 
(Please be patient. It may take a while to get the data.)
 
Optional:
Then set the File Type: (File Type information)
and
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
Zoom:
[The graph you specified. Please be patient.]

 

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 1.382184e+9, 1.4070672e+9;
    String axis "T";
    String calendar "gregorian";
    String ioos_category "Time";
    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";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 actual_range 0.0, 300.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String point_spacing "uneven";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 50.0, 66.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String point_spacing "even";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 160.0, 210.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    Float64 modulo 360.0;
    String point_spacing "even";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sea_water_temperature {
    Float64 _FillValue -1.0e+34;
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String field "temperature, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Temperature";
    String long_name "time-averaged potential temperature";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "sea_water_temperature";
    String time "ocean_time";
    String units "degree_Celsius";
  }
  small_phytoplankton_concentration {
    Float64 _FillValue -1.0e+34;
    String field "small phytoplankton, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Phytoplankton Species";
    String long_name "time-averaged small phytoplankton concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "small_phytoplankton_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  large_phytoplankton_concentration {
    Float64 _FillValue -1.0e+34;
    String field "large phytoplankton, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Phytoplankton Species";
    String long_name "time-averaged large phytoplankton concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "large_phytoplankton_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  large_microzooplankton_concentration {
    Float64 _FillValue -1.0e+34;
    String field "large microzooplankton, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Zooplankton Abundance";
    String long_name "time-averaged large microzooplankton concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "large_microzooplankton_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  small_coastal_copepod_concentration {
    Float64 _FillValue -1.0e+34;
    String field "copepod, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Time";
    String long_name "time-averaged small coastal copepod concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "small_coastal_copepod_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  neocalanus_concentration {
    Float64 _FillValue -1.0e+34;
    String field "neocalanus, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Taxonomy";
    String long_name "time-averaged neocalanus spp. concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "neocalanus_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  offshore_neocalanus_concentration {
    Float64 _FillValue -1.0e+34;
    String field "neocalanus, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Taxonomy";
    String long_name "time-averaged Offshore neocalanus spp. concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "offshore_neocalanus_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  euphausiids_concentration {
    Float64 _FillValue -1.0e+34;
    String field "euphausiid, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Time";
    String long_name "time-averaged euphausiid concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "euphausiids_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  detritus_concentration {
    Float64 _FillValue -1.0e+34;
    String field "detritus, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Time";
    String long_name "time-averaged detritus concentration";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "detritus_concentration";
    String time "ocean_time";
    String units "milligram carbon meter-3";
  }
  u_current {
    Float64 _FillValue -1.0e+34;
    String field "u-velocity, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Currents";
    String long_name "Zonal Current";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "eastward_current_velocity";
    String time "ocean_time";
    String units "m.s-1";
  }
  v_current {
    Float64 _FillValue -1.0e+34;
    String field "v-velocity, scalar, series";
    String history "From forecast_fast_avg.mc";
    String ioos_category "Currents";
    String long_name "Meridional Current";
    String long_name_mod "Z=-2.5:325, L=40";
    String standard_name "northward_current_velocity";
    String time "ocean_time";
    String units "m.s-1";
  }
  NC_GLOBAL {
    String _CoordSysBuilder "ucar.nc2.dataset.conv.CF1Convention";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, Unidata Dataset Discovery v1.0";
    Float64 Easternmost_Easting 210.0;
    Float64 geospatial_lat_max 66.0;
    Float64 geospatial_lat_min 50.0;
    Float64 geospatial_lat_resolution 0.1;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 210.0;
    Float64 geospatial_lon_min 160.0;
    Float64 geospatial_lon_resolution 0.2;
    String geospatial_lon_units "degrees_east";
    String history 
"FERRET V6.82    7-Nov-13
2018-05-25T09:16:46Z (local files)
2018-05-25T09:16:46Z http://erddap.axiomdatascience.com/griddap/PMEL_FORECAST.das";
    String infoUrl "???";
    String institution "???";
    String keywords "abundance, averaged, coastal, concentration, copepod, current, currents, data, detritus, detritus_concentration, Earth Science > Oceans > Ocean Temperature > Water Temperature, eastward, eastward_current_velocity, euphausiid, euphausiids, euphausiids_concentration, large, large_microzooplankton_concentration, large_phytoplankton_concentration, local, meridional, microzooplankton, neocalanus, neocalanus_concentration, northward, northward_current_velocity, ocean, oceans, offshore, offshore_neocalanus_concentration, phytoplankton, phytoplankton species, potential, sea, sea_water_temperature, seawater, small, small_coastal_copepod_concentration, small_phytoplankton_concentration, source, species, spp, taxonomy, temperature, time, time-averaged, velocity, water, zonal, zooplankton, zooplankton abundance";
    String keywords_vocabulary "GCMD Science Keywords";
    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 Metadata_Conventions "CF-1.6, COARDS, Unidata Dataset Discovery v1.0";
    Float64 Northernmost_Northing 66.0;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 50.0;
    String standard_name_vocabulary "CF-12";
    String summary "Data from a local source.";
    String time_coverage_end "2014-08-03T12:00:00Z";
    String time_coverage_start "2013-10-19T12:00:00Z";
    String title "Data from a local source.";
    Float64 Westernmost_Easting 160.0;
  }
}

 

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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