Make A Graph

Dataset Title:	TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, SSP370, ACCESS-ESM1-5
Institution:	Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia (Dataset ID: access-esm1-5_4d_ssp370)
Information:	Summary \| License \| 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 →

depth (m)

specify just 1 value →

j (1)

i (1)

Graph Settings
Color Bar:	Continuity:	Scale:
Minimum:	Maximum:	N Sections:
Y Axis Minimum:	Maximum:

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Optional:
Then set the File Type: (File Type information)
and

or view the URL:
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[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 1.4214096e+9, 4.1326416e+9;
    String axis "T";
    String calendar "proleptic_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";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 actual_range 5.0, 5831.29443359375;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String source_name "lev";
    String standard_name "depth";
    String units "m";
  }
  j {
    Int32 actual_range 0, 299;
    String axis "Y";
    String ioos_category "Location";
    String long_name "j";
    String source_name "j";
    String standard_name "cell index along second dimension";
    String units "1";
  }
  i {
    Int32 actual_range 0, 359;
    String axis "X";
    String ioos_category "Location";
    String long_name "i";
    String source_name "i";
    String standard_name "cell index along first dimension";
    String units "1";
  }
  thetao {
    Float32 _FillValue NaN;
    String cell_measures "area: areacello volume: volcello";
    String cell_methods "area: mean where sea time: mean";
    Float64 colorBarMaximum 32.0;
    Float64 colorBarMinimum 0.0;
    String comment "Diagnostic should be contributed even for models using conservative temperature as prognostic field.";
    String history "2019-11-15T09:33:14Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20).";
    String ioos_category "Temperature";
    String long_name "Sea Water Potential Temperature";
    Float32 missing_value NaN;
    String standard_name "sea_water_potential_temperature";
    String units "degree_C";
  }
  o2 {
    Float32 _FillValue NaN;
    String cell_measures "area: areacello volume: volcello";
    String cell_methods "area: mean where sea time: mean";
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum 0.0;
    String comment "'Mole concentration' means number of moles per unit volume, also called 'molarity', and is used in the construction mole_concentration_of_X_in_Y, where X is a material constituent of Y.  A chemical or biological species denoted by X may be described by a single term such as 'nitrogen' or a phrase such as 'nox_expressed_as_nitrogen'.";
    String history "2019-11-15T09:58:38Z altered by CMOR: Converted units from 'mmol m-3' to 'mol m-3'. 2019-11-15T09:58:38Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20).";
    String ioos_category "Dissolved O2";
    String long_name "Dissolved Oxygen Concentration";
    Float32 missing_value NaN;
    String standard_name "mole_concentration_of_dissolved_molecular_oxygen_in_sea_water";
    String units "mol m-3";
  }
  chl {
    Float32 _FillValue NaN;
    String cell_measures "area: areacello volume: volcello";
    String cell_methods "area: mean where sea time: mean";
    Float64 colorBarMaximum 3.0e-5;
    Float64 colorBarMinimum 3.0e-8;
    String colorBarScale "Log";
    String comment "Sum of chlorophyll from all phytoplankton group concentrations.  In most models this is equal to chldiat+chlmisc, that is the sum of Diatom Chlorophyll Mass Concentration and Other Phytoplankton Chlorophyll Mass Concentration";
    String history "2019-11-15T10:03:45Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20). 2019-11-15T10:03:51Z altered by CMOR: Converted type from 'd' to 'f'.";
    String ioos_category "Ocean Color";
    String long_name "Mass Concentration of Total Phytoplankton Expressed as Chlorophyll in Sea Water";
    Float32 missing_value NaN;
    String standard_name "mass_concentration_of_phytoplankton_expressed_as_chlorophyll_in_sea_water";
    String units "kg m-3";
  }
  zooc {
    Float32 _FillValue NaN;
    String cell_measures "area: areacello volume: volcello";
    String cell_methods "area: mean where sea time: mean";
    Float64 colorBarMaximum 0.02;
    Float64 colorBarMinimum 1.0e-5;
    String colorBarScale "Log";
    String comment "sum of zooplankton carbon component concentrations";
    String history "2021-05-25T05:34:14Z altered by CMOR: Converted units from 'mmol m-3' to 'mol m-3'. 2021-05-25T05:34:14Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20).";
    String ioos_category "Zooplankton Abundance";
    String long_name "Zooplankton Carbon Concentration";
    Float32 missing_value NaN;
    String standard_name "mole_concentration_of_zooplankton_expressed_as_carbon_in_sea_water";
    String units "mol m-3";
  }
  uo {
    Float32 _FillValue NaN;
    String cell_methods "time: mean";
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String comment "Prognostic x-ward velocity component resolved by the model.";
    String history "2019-11-15T09:44:44Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20).";
    String ioos_category "Currents";
    String long_name "Sea Water X Velocity";
    Float32 missing_value NaN;
    String standard_name "sea_water_x_velocity";
    String units "m s-1";
  }
  vo {
    Float32 _FillValue NaN;
    String cell_methods "time: mean";
    Float64 colorBarMaximum 0.5;
    Float64 colorBarMinimum -0.5;
    String comment "Prognostic y-ward velocity component resolved by the model.";
    String history "2019-11-15T09:38:18Z altered by CMOR: replaced missing value flag (-1e+20) with standard missing value (1e+20).";
    String ioos_category "Currents";
    String long_name "Sea Water Y Velocity";
    Float32 missing_value NaN;
    String standard_name "sea_water_y_velocity";
    String units "m s-1";
  }
  NC_GLOBAL {
    String activity_id "ScenarioMIP AerChemMIP";
    String branch_method "standard";
    Float64 branch_time_in_child 60265.0;
    Float64 branch_time_in_parent 60265.0;
    String cdm_data_type "Grid";
    String cmor_version "3.4.0";
    String Conventions "CF-1.7 CMIP-6.2, COARDS, ACDD-1.3";
    String creation_date "2019-11-15T09:33:17Z";
    String creator_name "Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia";
    String data_specs_version "01.00.30";
    String defaultGraphQuery "thetao[last][0][0:last][0:last]&.draw=surface";
    String experiment "gap-filling scenario reaching 7.0 based on SSP3";
    String experiment_id "ssp370";
    String external_variables "areacello volcello";
    Int32 forcing_index 1;
    String frequency "mon";
    String further_info_url "https://furtherinfo.es-doc.org/CMIP6.CSIRO.ACCESS-ESM1-5.ssp370.none.r1i1p1f1";
    String grid "native atmosphere N96 grid (145x192 latxlon)";
    String grid_label "gn";
    String history 
"2019-11-15T09:33:17Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.
2024-04-28T14:56:07Z (local files)
2024-04-28T14:56:07Z https://oceanwatch.pifsc.noaa.gov/griddap/access-esm1-5_4d_ssp370.das";
    String infoUrl "???";
    Int32 initialization_index 1;
    String institution "Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia";
    String institution_id "CSIRO";
    String keywords "access, access-esm1-5, aspendale, australia, climate, cmip6, commonwealth, data, earth, Earth Science > Oceans > Ocean Temperature > Potential Temperature, esm1, industrial, intercomparison, lev, model, ocean, oceans, organisation, output, potential, prepared, project, research, science, scientific, sea, sea_water_potential_temperature, seawater, temperature, thetao, time, victoria, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "CMIP6 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/).  Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment.  Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file).  The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.";
    String mip_era "CMIP6";
    String nominal_resolution "250 km";
    String notes "Exp: ESM-ssp370; Local ID: SSP-370-05; Variable: thetao (['pot_temp'])";
    String parent_activity_id "CMIP";
    String parent_experiment_id "historical";
    String parent_mip_era "CMIP6";
    String parent_source_id "ACCESS-ESM1-5";
    String parent_time_units "days since 1850-1-1";
    String parent_variant_label "r1i1p1f1";
    Int32 physics_index 1;
    String product "model-output";
    Int32 realization_index 1;
    String realm "ocean";
    String run_variant "forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)";
    String source 
"ACCESS-ESM1.5 (2019): 
aerosol: CLASSIC (v1.0)
atmos: HadGAM2 (r1.1, N96; 192 x 145 longitude/latitude; 38 levels; top level 39255 m)
atmosChem: none
land: CABLE2.4
landIce: none
ocean: ACCESS-OM2 (MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m)
ocnBgchem: WOMBAT (same grid as ocean)
seaIce: CICE4.1 (same grid as ocean)";
    String source_id "ACCESS-ESM1-5";
    String source_type "AOGCM";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "ACCESS-ESM1-5 output prepared for Climate Model Intercomparison Project 6 (CMIP6)";
    String table_id "Omon";
    String table_info "Creation Date:(30 April 2019) MD5:e14f55f257cceafb2523e41244962371";
    String time_coverage_end "2100-12-16T12:00:00Z";
    String time_coverage_start "2015-01-16T12:00:00Z";
    String title "TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, SSP370, ACCESS-ESM1-5";
    String tracking_id "hdl:21.14100/cf19bf5d-1988-4923-8483-7df926700112";
    String variable_id "thetao";
    String variant_label "r1i1p1f1";
    String version "v20191115";
  }
}

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[(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.