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ERDDAP > griddap > Make A Graph ?

Dataset Title:  X-Experimental POC from NOAA S-NPP VIIRS Source Data Subscribe RSS
Institution:  STAR   (Dataset ID: noaa_snpp_poc)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
 
Dimensions ?    Start ?    Stop ?
time (UTC) ?     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:   
 
(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:
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    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 1.3570704e+9, 1.6409808e+9;
    String axis "T";
    String calendar "gregorian";
    String ioos_category "Time";
    String long_name "Centered 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 -89.75625, 89.75625;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
    Float64 valid_max 90.0;
    Float64 valid_min -90.0;
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -179.98125, 179.98125;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
    Float64 valid_max 180.0;
    Float64 valid_min -180.0;
  }
  poc {
    Float32 _FillValue -999.0;
    Float32 colorBarMaximum 5000.0;
    Float32 colorBarMinimum 5.0;
    String colorBarScale "Log";
    String grid_mapping "coord_ref";
    String ioos_category "Other";
    String long_name "Particulate Organic Carbon, D. Stramski, 2022";
    String standard_name "mass_concentration_of_particulate_organic_carbon_in_sea_water";
    String units "mg m^-3";
  }
  Rrs_443 {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 0.02;
    Float64 colorBarMinimum 0.0;
    String grid_mapping "coord_ref";
    String ioos_category "Other";
    String long_name "Remote Sensing Reflectance at 443 nm";
    Float32 solar_irradiance 190.2609;
    String solar_irradiance_units "mW cm^-2 um^-1";
    String standard_name "surface_ratio_of_upwelling_radiance_emerging_from_sea_water_to_downwelling_radiative_flux_in_air";
    String units "sr^-1";
  }
  Rrs_486 {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 0.02;
    Float64 colorBarMinimum 0.0;
    String grid_mapping "coord_ref";
    String ioos_category "Other";
    String long_name "Remote Sensing Reflectance at 486 nm";
    Float32 solar_irradiance 198.8655;
    String solar_irradiance_units "mW cm^-2 um^-1";
    String standard_name "surface_ratio_of_upwelling_radiance_emerging_from_sea_water_to_downwelling_radiative_flux_in_air";
    String units "sr^-1";
  }
  Rrs_551 {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 0.02;
    Float64 colorBarMinimum 0.0;
    String grid_mapping "coord_ref";
    String ioos_category "Other";
    String long_name "Remote Sensing Reflectance at 551 nm";
    Float32 solar_irradiance 184.2347;
    String solar_irradiance_units "mW cm^-2 um^-1";
    String standard_name "surface_ratio_of_upwelling_radiance_emerging_from_sea_water_to_downwelling_radiative_flux_in_air";
    String units "W m^-2 um^-1 sr^-1";
  }
  Rrs_510v {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 0.02;
    Float64 colorBarMinimum 0.0;
    String grid_mapping "coord_ref";
    String ioos_category "Other";
    String long_name "Virtual Remote Sensing Reflectance at 510 nm";
    Float32 solar_irradiance 184.2347;
    String solar_irradiance_units "mW cm^-2 um^-1";
    String standard_name "surface_ratio_of_upwelling_radiance_emerging_from_sea_water_to_downwelling_radiative_flux_in_air";
    String units "W m^-2 um^-1 sr^-1";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.7.3,hdf5=1.12.0,";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6 ACDD-1.3, COARDS";
    String creator_email "coastwatch.info@noaa.gov";
    String creator_name "NOAA CoastWatch West Coast";
    String creator_type "institution";
    String creator_url "https://coastwatch.noaa.gov";
    Float64 Easternmost_Easting 179.98125;
    Float64 geospatial_lat_max 89.75625;
    Float64 geospatial_lat_min -89.75625;
    Float64 geospatial_lat_resolution 0.0375;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.98125;
    Float64 geospatial_lon_min -179.98125;
    Float64 geospatial_lon_resolution 0.0375;
    String geospatial_lon_units "degrees_east";
    String history 
"Daily L3 global fields of Rrs_443, Rrs_490, and 'Rrs_510' from NOAA VIIRS SNPP were applied to the VIIRS POC algorithm of Stramski et at, 2022.
2024-04-19T17:08:23Z (local files)
2024-04-19T17:08:23Z https://polarwatch.noaa.gov/griddap/noaa_snpp_poc.das";
    String id "L3/2km/infile_2km_G.nc";
    String infoUrl "https://coastwatch.noaa.gov";
    String institution "STAR";
    String instrument "VIIRS";
    String keywords "air, atmosphere, atmospheric, carbon, coast, coastwatch, color, concentration, data, deviation, downwelling, earth, Earth Science > Atmosphere > Atmospheric Radiation > Radiative Flux, Earth Science > Oceans > Ocean Optics > Radiance, emerging, experimental, field, field-of-view, flux, image, imager, imager/radiometer, imaging, infrared, latitude, level, level-3, longitude, mapped, mass, mass_concentration_of_particulate_organic_carbon_in_sea_water, national, noaa, node, npp, number, observations, ocean, ocean color, oceans, optics, orbiting, organic, particulate, partnership, poc, polar, polar-orbiting, radiance, radiation, radiative, radiometer, ratio, reflectance, remote, Rrs_443, Rrs_486, Rrs_510v, Rrs_551, s-npp, science, sea, sea-wide, seawater, seawifs, sensing, sensor, smi, source, standard, star, stramski, suite, surface, surface_ratio_of_upwelling_radiance_emerging_from_sea_water_to_downwelling_radiative_flux_in_air, time, upwelling, view, viirs, virtual, visible, water, wide, x-experimental";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "These data may be redistributed and used without restriction.";
    String map_projection "geographic";
    String naming_authority "gov.noaa.coastwatch";
    Float64 Northernmost_Northing 89.75625;
    String platform "Suomi-NPP";
    String processing_level "L3 Mapped";
    String proj4_string "+proj=eqc +lat_ts=0 +lat_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +lon_0=0.000000";
    String project "POC from NOAA VIIRS nLw";
    String publisher_email "coastwatch.info@noaa.gov";
    String publisher_name "NOAA CoastWatch";
    String publisher_type "institution";
    String publisher_url "https://coastwatch.noaa.gov";
    String references "Stramski, D., et al. Ocean color algorithms to estimate the concentration of particulate organic carbon in surface waters of the global ocean in support of a long-term data record from multiple satellite missions. Remote Sensing of Environment Vol. 269 (2022). https://doi.org/10.1016/j.rse.2021.112776.";
    String Satellite "Suomi-NPP";
    String Sensor "VIIRS";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.75625;
    String spatialResolution "4.17 km";
    String standard_name_vocabulary "CF Standard Name Table v36";
    String summary "Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022";
    String time_coverage_end "2021-12-31T20:00:00Z";
    String time_coverage_start "2013-01-01T20:00:00Z";
    String title "X-Experimental POC from NOAA S-NPP VIIRS Source Data";
    Float64 Westernmost_Easting -179.98125;
  }
}

 

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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