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Dataset Title:  Kd490, NOAA S-NPP VIIRS, Science Quality, U.S. East Coast 750m, Level 3, 2012-
present, Seasonal
Institution:  NOAA NESDIS CoastWatch East Coast Node   (Dataset ID: noaacwecnNPPVIIRSSQkd490EastCoastSeasonal)
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 →
    |< - >|
< <
level (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:   
(Please be patient. It may take a while to get the data.)
Then set the File Type: (File Type information)
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
[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 1.32938628391e+9, 1.715879932084e+9;
    String axis "T";
    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";
  level {
    Float64 actual_range 0.0, 0.0;
    String ioos_category "Location";
    String long_name "Altitude";
    String positive "up";
    String standard_name "altitude";
    String units "m";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 22.107128596152897, 46.0659239654323;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -85.07597103632074, -59.95131255561142;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  kd_490 {
    UInt32 _ChunkSizes 1, 1, 512, 512;
    Float32 _FillValue NaN;
    String cell_methods "area: mean";
    Float64 colorBarMaximum 6.0;
    Float64 colorBarMinimum 0.02;
    String colorBarPalette "Rainbow";
    String colorBarScale "Log";
    String grid_mapping "coord_ref";
    String ioos_category "Optical Properties";
    String long_name "Diffuse Attenuation Coefficient at 490 nm";
    Float32 missing_value NaN;
    String source "noaa_mecb_kd_490_algorithm noaa_mecb_bmw_atmospheric_correction";
    String standard_name "diffuse_attenuation_coefficient_of_downwelling_radiative_flux_in_sea_water";
    String units "m^-1";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "ronald.vogel at";
    String creator_name "NOAA CoastWatch East Coast Node";
    String creator_type "institution";
    String creator_url "";
    Float64 Easternmost_Easting -59.95131255561142;
    Float64 geospatial_lat_max 46.0659239654323;
    Float64 geospatial_lat_min 22.107128596152897;
    Float64 geospatial_lat_resolution 0.006168587891163594;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -59.95131255561142;
    Float64 geospatial_lon_min -85.07597103632074;
    Float64 geospatial_lon_resolution 0.006168587891163593;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-07-18T23:35:40Z (local files)
    String infoUrl "";
    String institution "NOAA NESDIS CoastWatch East Coast Node";
    String instrument "Visible Infrared Imaging Radiometer Suite (VIIRS)";
    String keywords "color, data, diffuse attenuation coefficient at 490nm, downwelling radiative flux, downwelling spectral irradiance, Earth Science > Oceans > Ocean Optics > Attenuation/Transmission, Earth Science > Oceans > Ocean Optics > Extinction Coefficients, Earth Science > Oceans > Ocean Optics > Ocean Color, Earth Science > Oceans > Ocean Optics > Turbidity, Earth Science > Oceans > Water Quality, image, imager, imager/radiometer, Kd-490, Kd490, kd490, kd_490, L3, level 3, level-3, light attenuation, mapped, ocean, ocean color, oceans, optical, polar-orbiting, radiance, radiometer, remote sensing, s-npp, satellite, sea, seasonal, seawater, snpp, VIIRS, viirs, visible, water, water quality";
    String keywords_vocabulary "NASA Global Change Master Directory (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, CoastWatch, NOAA, nor the US Government, nor any of their employees or contractors, make 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.";
    Float64 Northernmost_Northing 46.0659239654323;
    String satellite "Suomi National Polar-orbiting Partnership (S-NPP)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 22.107128596152897;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Seasonal average diffuse attenuation coefficient at 490nm (Kd490) for the U.S. East Coast, from the VIIRS instrument aboard the S-NPP satellite, 2012-present, is produced using the Wang et al. (2009) algorithm, in which separate algorithms for clear open ocean and turbid coastal waters are weighted into a combined product. This approach improves accuracy across ocean conditions. Atmospheric correction uses the near-infrared (NIR) approach of Jiang and Wang (2014), referred to as the BMW atmospheric correction. The individual overpasses are composited into daily mean grids (~840m), then the daily mean grids are averaged into seasonal gridded chlorophyll-a. Data in the last year of the series represent near real-time data and are of lesser accuracy than the science-quality data of the years before the last year. Seasons represent the periods January to March, April to June, July to September, and October to December. More info:";
    String time_coverage_end "2024-05-16T17:18:52Z";
    String time_coverage_start "2012-02-16T09:58:03Z";
    String title "Kd490, NOAA S-NPP VIIRS, Science Quality, U.S. East Coast 750m, Level 3, 2012-present, Seasonal";
    Float64 Westernmost_Easting -85.07597103632074;


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{?query}
For example,[(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.


ERDDAP, Version 2.23

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