Data Access Form

Dataset Title:	Global Ocean, Gridded In Situ reprocessed carbon observations, SOCATv2024 (monthly)
Institution:	PMEL, NOAA (Dataset ID: SOCATv2024_tracks_gridded_monthly)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Files \| Make a graph

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Dimensions	Size	Spacing
time (TMNTH, UTC)	648	30 days 10h 27m 38s (uneven)

latitude (degrees_north)	180	1.0 (even)

longitude (degrees_east)	360	1.0 (even)

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 {
    UInt32 _ChunkSizes 512;
    String _CoordinateAxisType "Time";
    Float64 actual_range 1339200.0, 1.702728e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "TMNTH";
    String source_name "tmnth";
    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 -89.5, 89.5;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String point_spacing "even";
    String source_name "ylat";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -179.5, 179.5;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    Float64 modulo 360.0;
    String point_spacing "even";
    String source_name "xlon";
    String standard_name "longitude";
    String units "degrees_east";
  }
  count_ncruise {
    UInt32 _ChunkSizes 1, 180, 360;
    Int32 _FillValue -9999;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Number of cruises";
    Int32 missing_value -9999;
    String summary "Number of datasets containing observations in the grid cell";
    String units "count";
  }
  fco2_count_nobs {
    UInt32 _ChunkSizes 1, 180, 360;
    Int32 _FillValue -9999;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Number of fco2 obs";
    Int32 missing_value -9999;
    String summary "Total number of observations in the grid cell.";
    String units "count";
  }
  fco2_ave_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 mean - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String summary "Mean of fco2 recomputed computed by calculating the arithmetic mean value for each cruise passing through the cell and then averaging these datasets.";
    String units "uatm";
  }
  fco2_ave_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 mean - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String summary "Arithmetic mean of all fco2 recomputed values found in the grid cell.";
    String units "uatm";
  }
  fco2_min_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 min";
    Float32 missing_value -1.0e+34;
    String summary "Minimum value of fco2 recomputed observed in the grid cell.";
    String units "uatm";
  }
  fco2_max_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 max";
    Float32 missing_value -1.0e+34;
    String units "uatm";
  }
  fco2_std_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 std dev - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String summary 
"A weighted standard deviation of fco2 recomputed computed to account for the differing 
variance estimates for each cruise passing through the cell. The statistical technique is 
described at See http://wapedia.mobi/en/Weighted_mean#7.";
    String units "uatm";
  }
  fco2_std_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "fCO2 std dev - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String summary "The standard deviation of fco2 recomputed computed from the unweighted mean.";
    String units "uatm";
  }
  sst_count_nobs {
    UInt32 _ChunkSizes 1, 180, 360;
    Int32 _FillValue -9999;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Number of valid sst obs";
    Int32 missing_value -9999;
    String summary "Total number of observations in the grid cell.";
    String units "count";
  }
  sst_ave_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST mean - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String summary "Mean of sst computed by calculating the arithmetic mean value for each cruise passing through the cell and then averaging these datasets.";
    String units "degree_C";
  }
  sst_ave_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST mean - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String summary "Arithmetic mean of all sst values found in the grid cell.";
    String units "degree_C";
  }
  sst_min_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST min";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String summary "Minimum value of sst observed in the grid cell.";
    String units "degree_C";
  }
  sst_max_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST max";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String units "degree_C";
  }
  sst_std_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST std dev - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String summary 
"A weighted standard deviation of sst computed to account for the differing 
variance estimates for each cruise passing through the cell. The statistical technique is 
described at See http://wapedia.mobi/en/Weighted_mean#7.";
    String units "degree_C";
  }
  sst_std_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "SST std dev - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_surface_temperature";
    String summary "The standard deviation of sst computed from the unweighted mean.";
    String units "degree_C";
  }
  salinity_count_nobs {
    UInt32 _ChunkSizes 1, 180, 360;
    Int32 _FillValue -9999;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Number of valid salinity obs";
    Int32 missing_value -9999;
    String summary "Total number of observations in the grid cell.";
    String units "count";
  }
  salinity_ave_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity mean - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String summary "Mean of salinity computed by calculating the arithmetic mean value for each cruise passing through the cell and then averaging these datasets.";
    String units "PSU";
  }
  salinity_ave_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity mean - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String summary "Arithmetic mean of all salinity values found in the grid cell.";
    String units "PSU";
  }
  salinity_min_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity min";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String summary "Minimum value of salinity observed in the grid cell.";
    String units "PSU";
  }
  salinity_max_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity max";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String units "PSU";
  }
  salinity_std_weighted {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity std dev - per cruise weighted";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String summary 
"A weighted standard deviation of salinity computed to account for the differing 
variance estimates for each cruise passing through the cell. The statistical technique is 
described at See http://wapedia.mobi/en/Weighted_mean#7.";
    String units "PSU";
  }
  salinity_std_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Salinity std dev - unweighted all obs";
    Float32 missing_value -1.0e+34;
    String standard_name "sea_water_practical_salinity";
    String summary "The standard deviation of salinity computed from the unweighted mean.";
    String units "PSU";
  }
  lat_offset_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Latitude average offset from cell center";
    Float32 missing_value -1.0e+34;
    String summary 
"The arithmetic average of latitude offsets from the grid cell center for all observations in 
the grid cell. The value of this offset can vary from -0.5 to 0.5. A value of zero indicates 
that the computed fco2 mean values are representative of the grid cell center position.";
    String units "Deg N";
  }
  lon_offset_unwtd {
    UInt32 _ChunkSizes 1, 180, 360;
    Float32 _FillValue -1.0e+34;
    String history "From SOCAT_ABCD_data_for_gridding";
    String long_name "Longitude average offset from cell center";
    Float32 missing_value -1.0e+34;
    String summary 
"The arithmetic average of longitude offsets from the grid cell center for all observations in 
the grid cell. The value of this offset can vary from -0.5 to 0.5. A value of zero indicates 
that the computed fco2 mean values are representative of the grid cell center position.";
    String units "Deg E";
  }
  NC_GLOBAL {
    String _NCProperties "version=2,netcdf=4.8.1,hdf5=1.12.2";
    String caution 
"NO INTERPOLATION WAS PERFORMED. SIGNIFICANT BIASES ARE PRESENT IN THESE GRIDDED RESULTS DUE TO THE 
ARBITRARY AND SPARSE LOCATIONS OF DATA VALUES IN BOTH SPACE AND TIME.";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6";
    Float64 Easternmost_Easting 179.5;
    Float64 geospatial_lat_max 89.5;
    Float64 geospatial_lat_min -89.5;
    Float64 geospatial_lat_resolution 1.0;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.5;
    Float64 geospatial_lon_min -179.5;
    Float64 geospatial_lon_resolution 1.0;
    String geospatial_lon_units "degrees_east";
    String history 
"PyFerret V7.63 (optimized) 29-Apr-24
2024-11-21T13:02:52Z (local files)
2024-11-21T13:02:52Z http://erddap.emodnet-physics.eu/erddap/griddap/SOCATv2024_tracks_gridded_monthly.das";
    String infoUrl "https://www.socat.info/";
    String institution "PMEL, NOAA";
    String keywords "all, average, carbon, cell, center, circulation, control, count_ncruise, cruise, cruises, data, density, depth, dev, earth, Earth Science > Oceans > Ocean Temperature > Sea Surface Temperature, Earth Science > Oceans > Salinity/Density > Salinity, environmental, experiment, fco2, fco2_ave_unwtd, fco2_ave_weighted, fco2_count_nobs, fco2_max_unwtd, fco2_min_unwtd, fco2_std_unwtd, fco2_std_weighted, global, gridded, laboratory, lat_offset_unwtd, latitude, lon_offset_unwtd, longitude, marine, max, mean, min, noaa, number, obs, observations, ocean, oceans, offset, pacific, per, pmel, practical, profiler, quality, reprocessed, salinity, salinity-temperature-depth, salinity_ave_unwtd, salinity_ave_weighted, salinity_count_nobs, salinity_max_unwtd, salinity_min_unwtd, salinity_std_unwtd, salinity_std_weighted, science, sea, sea_surface_temperature, sea_water_practical_salinity, seawater, situ, socatv2019, sst, sst_ave_unwtd, sst_ave_weighted, sst_count_nobs, sst_max_unwtd, sst_min_unwtd, sst_std_unwtd, sst_std_weighted, std, surface, temperature, tmnth, unweighted, valid, water, weighted, woce, world, xlon, ylat";
    String keywords_vocabulary "GCMD Science Keywords";
    String license 
"The Surface Ocean CO2 Atlas (SOCAT) is an international effort, endorsed by the
International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean
Lower Atmosphere Study (SOLAS) and the Integrated Marine Biosphere Research
(IMBeR) program, to deliver a uniformly quality-controlled surface ocean CO2
database. The many researchers and funding agencies responsible for the collection
of data and quality control are thanked for their contributions to SOCAT.";
    Float64 Northernmost_Northing 89.5;
    String references "http://www.socat.info/";
    String SOCAT_Notes "SOCAT gridded v2024 29-Apr-2024";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.5;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Global Ocean - Gridded In Situ reprocessed carbon observations - SOCATv2024. Surface Ocean Carbon Atlas (SOCAT) Gridded (binned) SOCAT observations, with a spatial grid of 1x1 degree and yearly in time. The gridded fields are computed from the monthly 1-degree gridded data, which uses only SOCAT datasets with Quality Control (QC) flags of A through D and SOCAT data points flagged with World Ocean Circulation Experiment (WOCE) flag values of 2. This yearly data is computed using data from the start to the end of each year as described in the summary attribute of each variable.";
    String time_coverage_end "2023-12-16T12:00:00Z";
    String time_coverage_start "1970-01-16T12:00:00Z";
    String title "Global Ocean, Gridded In Situ reprocessed carbon observations, SOCATv2024 (monthly)";
    Float64 Westernmost_Easting -179.5;
  }
}

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
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)]
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