ERDDAP > griddap > Data Access Form

Dataset Title:	EMODPACE - Absolute sea level trend (1993 - 2019) - derived from CMEMS- DUACS (DT-2018) satellite altimetry
Institution:	CMCC   (Dataset ID: EMODPACE_SLEV_TREND)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Files | Make a graph

 

Dimensions	Start	Stride	Stop	Size	Spacing
time (UTC)				1	(just one value)
latitude (degrees_north)				208	0.25 (even)
longitude (degrees_east)				400	0.25 (even)

Grid Variables (which always also download all of the dimension variables)

sla (Sea level anomaly, mm/yr)

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriAscii - Download an ISO-8859-1 ESRI ASCII file (latitude longitude data only; longitude must be all below or all above 180). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .graph - View a Make A Graph web page. .help - View a web page with a description of griddap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each axis variable and each data variable becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncml - View the dataset's structure and metadata as a UTF-8 NCML .xml file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download time,latitude,longitude,otherVariables as an ODV Generic Spreadsheet File (.txt). .timeGaps - View a UTF-8 list of gaps in the time values which are larger than the median gap. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .geotif - View a grayscale GeoTIFF .tif file (for latitude longitude data; longitude must be all below or all above 180). .kml - View a Google Earth .kml file (for latitude, longitude data only). .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

(Documentation / Bypass this form)
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    UInt32 _ChunkSizes 512;
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.5764544e+9, 1.5764544e+9;
    String axis "T";
    String bounds "time_bnds";
    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";
    Float32 actual_range -6.875, 44.875;
    String axis "Y";
    String bounds "latitude_bnds";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 30.125, 129.875;
    String axis "X";
    String bounds "longitude_bnds";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  sla {
    UInt32 _ChunkSizes 1, 1, 400;
    Float64 _FillValue -214748.3647;
    String cell_methods "time: mean";
    String comment "The sea level anomaly is the sea surface height above mean sea surface; it is referenced to the [1993, 2012] period; see the product user manual for details";
    String grid_mapping "crs";
    String long_name "Sea level anomaly";
    Float64 missing_value -214748.3647;
    String standard_name "sea_surface_height_above_sea_level";
    String units "mm/yr";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.7.4,hdf5=1.10.6";
    String cdm_data_type "Grid";
    String creator_name "CLS, CNES";
    Float64 Easternmost_Easting 129.875;
    Float64 geospatial_lat_max 44.875;
    Float64 geospatial_lat_min -6.875;
    Float64 geospatial_lat_resolution 0.25;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 129.875;
    Float64 geospatial_lon_min 30.125;
    Float64 geospatial_lon_resolution 0.25;
    String geospatial_lon_units "degrees_east";
    String history 
"Wed Oct 27 15:01:58 2021: C:\\ETT\\nco\\ncks.exe -d latitude,-7.0,+45.0 -d longitude,+30.0,+130.0 dt_global_twosat_phy_l4_trend_199301_201912_vDT2018.nc -O EMODNET_PACE_SEA_LEVEL_199301_201812_TREND.nc
Thu Dec 17 19:13:46 2020: ncatted -a ,global,d,, /Users/rlecci/Documents/EMOD_PACE/tmp/data/trend/dt_global_twosat_phy_l4_trend_199301_201912_vDT2018.nc
2024-12-03T18:01:14Z (local files)
2024-12-03T18:01:14Z http://erddap.emodnet-physics.eu/erddap/griddap/EMODPACE_SLEV_TREND.das";
    String infoUrl "http://climate.copernicus.eu";
    String institution "CMCC";
    String keywords "above, altimeter, altimeters, anomalies, anomaly, based, centre, cls, cnes, collecte, constellation, data, delayed, delayed-time, derived, dt-2018, duacs, earth, Earth Science > Oceans > Ocean Topography > Sea Surface Height, Earth Science > Oceans > Sea Surface Topography > Sea Surface Height, emodnet, emodnet_pace, etudes, global, gridded, height, L4, latitude, level, localisation, longitude, maps, merged, national, number, ocean, oceans, pace, product, regional, satellite, satellites, science, sea, sea_surface_height_above_sea_level, sla, spatiales, ssalto, ssh, stable, surface, time, topography, trends, two, version";
    String license "Creative Commons Attribution Share-Alike http://www.opendefinition.org/licenses/cc-by-sa";
    String NCO "\"4.6.3\"";
    Float64 Northernmost_Northing 44.875;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -6.875;
    String summary "EMODPACE - Absolute sea level trend (1993 - 2019) - derived from CMEMS-DUACS (DT-2018) satellite altimetry";
    String time_coverage_end "2019-12-16T00:00:00Z";
    String time_coverage_start "2019-12-16T00:00:00Z";
    String title "EMODPACE - Absolute sea level trend (1993 - 2019) - derived from CMEMS-DUACS (DT-2018) satellite altimetry";
    Float64 Westernmost_Easting 30.125;
  }
}

 

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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 Data Access Protocol (DAP) and its projection constraints.

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
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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