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Dataset Title:  Average Alexandrium catenella occurrence risk (25-48h) Subscribe RSS
Institution:  DFO-MPO   (Dataset ID: mpoAlguesToxiquesPred25-48)
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 →
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latitude (degrees_north) ?
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< slider >
longitude (degrees_east) ?
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< slider >
 
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
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Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
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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 1.6771356e+9, 1.6796592e+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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 43.007623748779295, 54.297623748779294;
    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 -78.17900573730469, -37.719005737304684;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Risk {
    Float32 _FillValue -3.4e+38;
    String grid_mapping "crs";
    String long_name "A.catenella occurrence risk (0-100)";
    Float64 max 2.736972489693706;
    Float64 min 0.0037976342549134153;
    String proj4 "+proj=longlat +datum=NAD83 +no_defs";
  }
  NC_GLOBAL {
    String Algae_model "HARM v1";
    String cdm_data_type "Grid";
    String Climate_model "CIOPS-E v1.2";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String created_by "R, packages ncdf4 and raster (version 3.5-15)";
    String creator_name "DFO-MPO";
    String creator_type "institution";
    String date "2023-03-24 21:04:06";
    String Description "Daily forecast of Alexandrium catenella occurrence risk (0-100 scale) in the Estuary and Gulf of St. Lawrence averaged between 25-48h after forecast time";
    Float64 Easternmost_Easting -37.719005737304684;
    String Forecast_time "2023-03-24 08:00:00";
    Float64 geospatial_lat_max 54.297623748779294;
    Float64 geospatial_lat_min 43.007623748779295;
    Float64 geospatial_lat_resolution 0.009999999999999998;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -37.719005737304684;
    Float64 geospatial_lon_min -78.17900573730469;
    Float64 geospatial_lon_resolution 0.010000000000000002;
    String geospatial_lon_units "degrees_east";
    String history 
"2023-03-25T04:08:12Z (local files)
2023-03-25T04:08:12Z https://erddap.ogsl.ca/griddap/mpoAlguesToxiquesPred25-48.das";
    String infoUrl "???";
    String Institution "DFO-MPO";
    String institution "DFO-MPO";
    String keywords "0-100, 25-48h, 48h, a.catenella, alexandrium, average, catenella, data, department, dfo, dfo-mpo, fisheries, latitude, longitude, mpo, occurrence, ocean, oceans, risk, time";
    String license "Open Government Licence - Canada, Licence du gouvernement ouvert - Canada";
    Float64 Northernmost_Northing 54.297623748779294;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 43.007623748779295;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "Daily forecast of Alexandrium catenella occurrence risk (0-100 scale) in the Estuary and Gulf of St. Lawrence averaged between 25-48h after forecast time";
    String testOutOfDate "now-19days";
    String time_coverage_end "2023-03-24T12:00:00Z";
    String time_coverage_start "2023-02-23T07:00:00Z";
    String Timelapse_covered "25-48h average from Forecast time";
    String title "Average Alexandrium catenella occurrence risk (25-48h)";
    Float64 Westernmost_Easting -78.17900573730469;
  }
}

 

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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