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Dataset Title:  Global 9km Chlorophyll a Anomalies. Subscribe RSS
Institution:  USF IMaRS   (Dataset ID: anom_9km_2b83_52f7_ef91)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      191    30 days 10h 29m 3s (uneven)
  < slider >
 latitude (degrees_north) ?      2160    -0.08337193 (even)
  < slider >
 longitude (degrees_east) ?      4320    0.08335263 (even)
  < slider >
Grid Variables (which always also download all of the dimension variables)
 mean ?
 anomaly ?
 z_score (Z-score) ?

File type: (more info)

(Documentation / Bypass this form) ?
(Please be patient. It may take a while to get the data.)


The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.033344e+9, 1.5329952e+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";
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range -90.0, 90.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -180.0, 180.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  mean {
    String ioos_category "Statistics";
    String long_name "Mean";
  anomaly {
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum -10.0;
    String ioos_category "Unknown";
    String long_name "Anomaly";
  z_score {
    String ioos_category "Location";
    String long_name "Z-score";
    String cdm_data_type "Grid";
    String Composite_end_date "07/31/2018";
    String Composite_start_date "07/01/2018";
    String contact "Dan Otis -";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String CreationDate "10/23/2018 18:52:28";
    String creator_email "";
    String creator_name "DOTIS";
    String creator_type "institution";
    Float64 Easternmost_Easting 180.0;
    Float64 geospatial_lat_max 90.0;
    Float64 geospatial_lat_min -90.0;
    Float64 geospatial_lat_resolution 0.08337193144974525;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 180.0;
    Float64 geospatial_lon_min -180.0;
    Float64 geospatial_lon_resolution 0.08335262792313035;
    String geospatial_lon_units "degrees_east";
    String history 
"2020-07-05T04:09:47Z (local files)
    String infoUrl "???";
    String institution "USF IMaRS";
    String keywords "anomaly, data, florida, latitude, local, longitude, mail.usf, mean, score, source, south, statistics, university, usf, z-score";
    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.";
    Float64 Northernmost_Northing 90.0;
    String Original_Image_Format "Level-3(NetCDF)";
    String Original_Image_Source "NASA OBPG";
    String Processing_and_binning "USF IMaRS";
    String Product "chlor_a";
    String project "SDG14";
    String Region "Global (GLOB)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -90.0;
    String Spatial_resolution "9km";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Global 9km Chlorophyll a Anomalies.";
    String time_coverage_end "2018-07-31T00:00:00Z";
    String time_coverage_start "2002-09-30T00:00:00Z";
    String title "Global 9km Chlorophyll a Anomalies.";
    Float64 Westernmost_Easting -180.0;


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{?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.

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