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Dataset Title:	Baltic Sea, Gulf of Riga, DIVAnd 4D seasonal analysis of Water body chlorophyll-a 1999/2022 v2025 [observations]
Institution:	Swedish Meteorological and Hydrological Institute (Dataset ID: oceanbrowser_opendap_03cf_f204_4e8c)
Information:	Summary \| License \| Metadata \| Background \| Data Access Form

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

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observations (count)

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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 {
  observations {
    Int32 actual_range 0, 30606;
    String long_name "Observations";
    String units "count";
  }
  obslon {
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String long_name "longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  obslat {
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String long_name "latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  obstime {
    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";
  }
  obsdepth {
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String long_name "depth below sea level";
    String positive "down";
    String standard_name "depth";
    String units "meters";
  }
  NC_GLOBAL {
    String area_keywords "Gulf of Riga";
    String area_keywords_urn "SDN:C19::2_5";
    String cdm_data_type "Grid";
    String Conventions "CF-1.8, COARDS, ACDD-1.3";
    String creator_name "Swedish Meteorological and Hydrological Institute";
    String creator_url "https://doi.org/10.13120/fa5c704a-a5ea-4f60-91b5-2bf6a7aded45";
    String data_access "https://emodnet.ec.europa.eu/geoviewer";
    String date "2025-09-29T17:32:27";
    String documentation "https://doi.org/10.13120/fa5c704a-a5ea-4f60-91b5-2bf6a7aded45";
    String doi "https://doi.org/10.13120/1233ec72-0460-40b4-94a4-4fb6ec4c962f";
    String file_name "Coastal_areas/Baltic_Sea_-_Gulf_of_Riga/Water_body_chlorophyll-a.nc";
    String history 
"2026-03-13T23:57:56Z http://opendap.oceanbrowser.net/thredds/dodsC/data/emodnet-projects/v2025/Coastal_areas-water_body/Baltic_Sea_-_Gulf_of_Riga/Water_body_chlorophyll-a.nc
2026-03-13T23:57:56Z https://erddap.emodnet.eu/griddap/oceanbrowser_opendap_03cf_f204_4e8c.das";
    String id "DatasetScan/emodnet-projects/v2025/Coastal_areas-water_body/Baltic_Sea_-_Gulf_of_Riga/Water_body_chlorophyll-a.nc";
    String infoUrl "https://doi.org/10.13120/fa5c704a-a5ea-4f60-91b5-2bf6a7aded45";
    String institution "Swedish Meteorological and Hydrological Institute";
    String institution_urn "SDN:EDMO::545";
    String keywords "analysis, baltic, below, body, chla, chlorophyll, chlorophyll-a, data, depth, divand, gulf, hydrological, institute, latitude, level, longitude, meteorological, obsdepth, observations, obslat, obslon, obstime, riga, sea, seasonal, seawater, swedish, time, v2025, water";
    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 parameter_keyword "Water body chlorophyll-a";
    String parameter_keyword_urn "SDN:P35::EPC00105";
    String product_code "Gulf of Riga-Water_body_chlorophyll-a-v2025-ANA";
    String product_id "1233ec72-0460-40b4-94a4-4fb6ec4c962f";
    String product_version "v2025";
    String project "EMODnet Chemistry - Phase 5";
    String search_keywords "Chlorophyll pigment concentrations in water bodies";
    String search_keywords_urn "SDN:P02::CPWC";
    String sourceUrl "http://opendap.oceanbrowser.net/thredds/dodsC/data/emodnet-projects/v2025/Coastal_areas-water_body/Baltic_Sea_-_Gulf_of_Riga/Water_body_chlorophyll-a.nc";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "Baltic Sea - Gulf of Riga - DIVAnd 4D seasonal analysis of Water body chlorophyll-a 1999/2022 v2025 (Baltic Sea - Gulf of Riga, Water body chlorophyll-a)";
    String title "Baltic Sea, Gulf of Riga, DIVAnd 4D seasonal analysis of Water body chlorophyll-a 1999/2022 v2025 [observations]";
    String WEB_visualisation "https://emodnet.ec.europa.eu/geoviewer";
  }
}

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)]
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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