Easier access to scientific data
| ?    
Brought to you by NOAA NMFS SWFSC ERD    

ERDDAP > griddap > Make A Graph ?

Dataset Title:  X-experimental - Particulate Organic Carbon in Ocean Surface Water, SeaWiFS,
9km, NASA SMI, Stramski 2022
Subscribe RSS
Institution:  CoastWatch West Coast Node   (Dataset ID: seawifs_month_poc2022)
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 →
    |< - >|
< <
latitude (degrees_north) ?
< slider >
longitude (degrees_east) ?
< slider >
Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   
(Please be patient. It may take a while to get the data.)
Then set the File Type: (File Type information)
or view the URL:
(Documentation / Bypass this form ? )
    Click on the map to specify a new center point. ?
[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 8.743932e+8, 1.2924864e+9;
    String axis "T";
    String calendar "gregorian";
    String ioos_category "Time";
    String long_name "Centered 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 -89.95834, 89.95834;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
    Float32 valid_max 90.0;
    Float32 valid_min -90.0;
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -179.9583, 179.9583;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
    Float32 valid_max 180.0;
    Float32 valid_min -180.0;
  poc {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 5000.0;
    Float64 colorBarMinimum 5.0;
    String colorBarScale "Log";
    String ioos_category "Ocean Color";
    String long_name "Particulate Organic Carbon, D. Stramski, 2022";
    String standard_name "mass_concentration_of_particulate_organic_carbon_in_sea_water";
    String units "mg m^-3";
  poc_stdev {
    Float32 _FillValue -999.0;
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "Standard Deviation for Particulate Organic Carbon";
    String units "mg m^-3";
  poc_var {
    Float32 _FillValue -999.0;
    String ioos_category "Statistics";
    String long_name "Variance for Particulate Organic Carbon";
    String units "mg m^-3";
  poc_nobs {
    Int16 _FillValue -999;
    String ioos_category "Statistics";
    String long_name "Number Particulate Organic Carbon of Observations";
    String units "count";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6 ACDD-1.3, COARDS";
    String creator_email "";
    String creator_name "NOAA/NESDIS/CoastWatch/West Coast";
    String creator_type "institution";
    String creator_url "";
    String date_created "2022-06-28T16:10:42.000Z";
    Float64 Easternmost_Easting 179.9583;
    Float64 geospatial_lat_max 89.95834;
    Float64 geospatial_lat_min -89.95834;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.9583;
    Float64 geospatial_lon_min -179.9583;
    String geospatial_lon_units "degrees_east";
    String history 
"Generate SMI fileds for each L2 file. From each file, load data from Rrs_443, Rrs_490, 'Rrs_510', Rrs_555. Generate MBR and MBRDI algorithms to produce the ensemble POC fields. Bin L2 files into monthly composites
2024-07-21T13:13:44Z (local files)
    String id "L3//cwdata1/poc2/bin_month/sw/2002/";
    String infoUrl "";
    String institution "CoastWatch West Coast Node";
    String instrument "SeaWiFS";
    String keywords "carbon, coast, coastwatch, color, concentration, data, deviation, field, field-of-view, image, latitude, level, level-3, longitude, mapped, mass, mass_concentration_of_particulate_organic_carbon_in_sea_water, nasa, noaa, node, number, observations, ocean, ocean color, organic, particulate, poc, poc_nobs, poc_stdev, poc_var, sea, sea-wide, seawater, seawifs, sensor, smi, standard, statistics, stramski, surface, time, variance, view, water, west, wide";
    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 map_projection "Equidistant Cylindrical";
    String measure "Mean, Variance, Standard Deviation, Number of Observations";
    String naming_authority "gov.nasa.gsfc.sci.oceandata";
    Float64 Northernmost_Northing 89.95834;
    String platform "Orbview-2";
    String processing_level "L3 Mapped";
    String project "POC algorithm Stramski 2022";
    String publisher_name "NOAA/NESDIS/CoastWatch/West Coast";
    String publisher_type "institution";
    String publisher_url "";
    String references "Stramski, D., et al. Ocean color algorithms to estimate the concentration of particulate organic carbon in surface waters of the global ocean in support of a long-term data record from multiple satellite missions. Remote Sensing of Environment Vol. 269 (2022).";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -89.95834;
    String spatialResolution "4.64 km";
    String standard_name_vocabulary "CF Standard Name Table v36";
    String summary "Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022";
    String time_coverage_end "2010-12-16T08:00:00Z";
    String time_coverage_start "1997-09-16T07:00:00Z";
    String title "X-experimental - Particulate Organic Carbon in Ocean Surface Water, SeaWiFS, 9km, NASA SMI, Stramski 2022";
    Float64 Westernmost_Easting -179.9583;


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{?query}
For example,[(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.

ERDDAP, Version 2.24
Disclaimers | Privacy Policy | Contact