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Dataset Title:  EXPERIMENTAL - Median Phytoplankton Size, North Pacific. Monthly, 1998-2022 Subscribe RSS
Institution:  NOAA PIFSC   (Dataset ID: md50_exp)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background | Make a graph
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      300    30 days 10h 26m 5s (uneven)
  < slider >
 latitude (degrees_north) ?      901    0.05 (even)
  < slider >
 longitude (degrees_east) ?      2401    0.05 (even)
  < slider >
Grid Variables (which always also download all of the dimension variables) 
 MD50 (2.138*(MB50^0.355)) ?

File type: (more information)

(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 8.836128e+8, 1.6698528e+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";
    Float64 actual_range 0.0, 45.0;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String point_spacing "even";
    String source_name "AX009";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 120.0, 240.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String point_spacing "even";
    String source_name "AX008";
    String standard_name "longitude";
    String units "degrees_east";
  MD50 {
    Float64 _FillValue NaN;
    String ioos_category "Unknown";
    String long_name "2.138*(MB50^0.355)";
    Float64 missing_value NaN;
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    Float64 Easternmost_Easting 240.0;
    Float64 geospatial_lat_max 45.0;
    Float64 geospatial_lat_min 0.0;
    Float64 geospatial_lat_resolution 0.05;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 240.0;
    Float64 geospatial_lon_min 120.0;
    Float64 geospatial_lon_resolution 0.05;
    String geospatial_lon_units "degrees_east";
    String history 
"FERRET V7.6  19-Jul-23
2023-10-02T21:31:13Z (local files)
    String infoUrl "";
    String institution "NOAA PIFSC";
    String license "Experimental product.\\n License terms for CoralTemp: The data produced by Coral Reef Watch are available for use without restriction, but Coral Reef Watch relies on the ethics and integrity of the user to ensure that the source of the data and products is appropriately cited and credited. When using these data and products, credit and courtesy should be given to NOAA Coral Reef Watch. Please include the appropriate DOI associated with this dataset in the citation. For more information, visit the NOAA Coral Reef Watch website: Recommendations for citing and providing credit are provided at Users are referred to the footer section of the Coral Reef Watch website ( for disclaimers, policies, notices pertaining to the use of the data.\\n License terms for ESA OC-CCI: ESA CCI Data Policy: free and open access. When referencing, please use: Ocean Colour Climate Change Initiative dataset, Version Number, European Space Agency, available online at We would also appreciate being notified of publications so that we can list them on the project website at";
    Float64 Northernmost_Northing 45.0;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 0.0;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "Experimental product derived from NOAA CoralReefWatch CoralTemp SST and ESA OC-CCI chlorophyll a concentration using algorithm from Carolyn Barnes, Xabier Irigoien, José A. A. De Oliveira, David Maxwell, Simon Jennings, Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables, Journal of Plankton Research, Volume 33, Issue 1, January 2011, Pages 13-24,";
    String time_coverage_end "2022-12-01T00:00:00Z";
    String time_coverage_start "1998-01-01T00:00:00Z";
    String title "EXPERIMENTAL - Median Phytoplankton Size, North Pacific. Monthly, 1998-2022";
    Float64 Westernmost_Easting 120.0;


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,[(2015-06-09T09:00:00Z)][(-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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