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Dataset Title:	Soil moisture Early Runs 0-5cm 0.1 x 0.1 degrees / 3 h, from Pellarin et al 2022 algorithm with SMOS-L3SM-RE07 and IMERG Early assimilation (Particle Filter)
Institution:	IGE (Institut des Geosciences de l'Environnement, Grenoble, FRANCE (Dataset ID: soil_moisture_cc4b_afb4_cc10)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

time (UTC)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

Graph Settings
Color Bar: Continuity: Scale:
Min: Max: N Sections:
Draw the land mask:
Y Axis Minimum: Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: and

or view the URL:
(Documentation / Bypass this form

) (File Type information)

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:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.7308512e+9, 1.7311968e+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 -35.85, 38.15;
    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 -19.15, 51.85;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  soil_moisture {
    Float32 _FillValue 9.96921e+36;
    Float64 colorBarMaximum 5.0;
    Float64 colorBarMinimum 0.0;
    String long_name "Soil Moisture Content";
    String standard_name "soil_moisture_content";
    String units "m3/m3";
  }
  soil_moisture_max {
    Float32 _FillValue 9.96921e+36;
    String long_name "Soil Moisture Max";
    String standard_name "soil_moisture_max";
    String units "m3/m3";
  }
  soil_moisture_min {
    Float32 _FillValue 9.96921e+36;
    String long_name "Soil Moisture Min";
    String standard_name "soil_moisture_min";
    String units "m3/m3";
  }
  NC_GLOBAL {
    String assimilation_date "2024-05-02 10:07:15.913684";
    String cdm_data_type "Grid";
    String Configuration1 "CDF-Matching coefficients (2 parameters) obtained on 2014 (IMERG-FR)";
    String Configuration2 
"Initial precipitation product : IMERG-Early (0.1deg / 3h, NASA),
https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHHE_06/summary";
    String Configuration3 "Initial soil moisture product : SMOS-L3SM-RE07 (CATDS/CNES)";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "IGE (Institut des Geosciences de l'Environnement, Grenoble, FRANCE";
    String creator_type "institution";
    Float64 Easternmost_Easting 51.85;
    Float64 geospatial_lat_max 38.15;
    Float64 geospatial_lat_min -35.85;
    Float64 geospatial_lat_resolution 0.1;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 51.85;
    Float64 geospatial_lon_min -19.15;
    Float64 geospatial_lon_resolution 0.1;
    String geospatial_lon_units "degrees_east";
    String history 
"Tue Nov 19 07:02:36 2024: ncks -4 --cnk_map=nc4
/homelocal5/home/pellarit/prism_oper/daily_oper/imerg_smos_l3sm_africa/early_runs_tmp/soil_moisture/PrISM_SM_0-5cm_SMOS-L3SM_20241110_3h_010d_Africa.nc.8ny78lse.tmp
-O /homelocal5/home/pellarit/prism_oper/daily_oper/imerg_smos_l3sm_africa/early_runs_tmp/soil_moisture/PrISM_SM_0-5cm_SMOS-L3SM_20241110_3h_010d_Africa.nc.yzomi3mu.tmp
2024-11-19T12:23:49Z (local files)
2024-11-19T12:23:49Z http://osug-smos-rea.osug.fr:8081/griddap/soil_moisture_cc4b_afb4_cc10.das";
    String infoUrl "???";
    String institution "IGE (Institut des Geosciences de l'Environnement, Grenoble, FRANCE";
    String keywords 
"0-5cm, 5cm, agriculture,
Agriculture > Soils > Soil Moisture/Water Content,
algorithm, assimilation, content, data, degrees, des, early, environnement,
filter, france, geosciences, grenoble, ige, imerg, institut, l3sm, land,
Land Surface > Soils > Soil Moisture/Water Content,
latitude, longitude, max, min, moisture, particle, pellarin, re07, runs,
smos, smos-l3sm-re07, soil, soil_moisture, soil_moisture_content,
soil_moisture_max, soil_moisture_min, soils, surface, time, water, with";
    String keywords_vocabulary "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, 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.";
    String NCO 
"netCDF Operators version 5.2.4 (Homepage = http://nco.sf.net, Code =
http://github.com/nco/nco, Citation = 10.1016/j.envsoft.2008.03.004)";
    Float64 Northernmost_Northing 38.15;
    String references "Pellarin et al. 2022 (Remote Sensing)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -35.85;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary 
"Soil moisture Early Runs 0-5cm 0.1 x 0.1 degrees / 3 h, from Pellarin et al
2022 algorithm with SMOS-L3SM-RE07 and IMERG Early assimilation (Particle
Filter)";
    String time_coverage_end "2024-11-10T00:00:00Z";
    String time_coverage_start "2024-11-06T00:00:00Z";
    String title 
"Soil moisture Early Runs 0-5cm 0.1 x 0.1 degrees / 3 h, from Pellarin et al
2022 algorithm with SMOS-L3SM-RE07 and IMERG Early assimilation (Particle
Filter)";
    Float64 Westernmost_Easting -19.15;
  }
}

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.

(easy) You can get data by using the dataset's Data Access Form. It makes the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by
hand or with a computer program or script.

griddap request URLs must be in the form
http://osug-smos-rea.osug.fr:8081/erddap/griddap/datasetID.fileType{?query}
For example,
http://osug-smos-rea.osug.fr:8081/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2015-06-09T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a variable name (e.g., analysed_sst),
followed by a set of [] for each of the variable's dimensions
(for example, [time][latitude][longitude]),
with your desired (start):stride:(stop) values within each [].

For details, see the griddap Documentation.

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