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Dataset Title:  SS-DBEM fish projections under climate and fishing scenarios Subscribe RSS
Institution:  BRTA   (Dataset ID: biology_9114_ss-dbem-fish126c_87bc_96d6)
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 →
    |< - >|
< <
aphiaid (1) ?     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.)
 
Optional:
Then set the File Type: (File Type information)
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or view the URL:
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    Click on the map to specify a new center point. ?
Zoom:
[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 1.893456e+9, 4.1024448e+9;
    String axis "T";
    String calendar "standard";
    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";
  }
  aphiaid {
    Int32 actual_range 126417, 127089;
    String long_name "Life Science Identifier - World Register of Marine Species";
    String units "1";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 0.25, 79.75;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -79.75, 14.75;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Biomass_relative {
    Float64 _FillValue NaN;
    String comments "%percentage of change";
    String long_name "Biomass relative change";
    String units "1";
  }
  NC_GLOBAL {
    String acknowledgement "European Marine Observation Data Network (EMODnet) Biology project CINEA/EMFAF/2022/3.5.2/SI2.895681, funded by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund";
    String cdm_data_type "Grid";
    String citation "Anabitarte, A., Granado, I., Valle, M., Erauskin-Extramiana, M., & Fernandes-Salvador, J. A. (2026). SS-DBEM ensemble projections of 18 North Atlantic fish species under IPCC AR6 RCP 8.5 climate and MSY fishing scenario";
    String comment "Uses attributes recommended by https://cfconventions.org";
    String Conventions "CF-1.9, COARDS, ACDD-1.3";
    String creator_email "aanabitarte@azti.es";
    String creator_institution "AZTI, Marine research, Basque Research and Technology Alliance (BRTA)";
    String creator_name "Asier Anabitarte";
    String creator_type "person";
    String creator_url "www.azti.es";
    String date_created "2026-07-28";
    Float64 Easternmost_Easting 14.75;
    Float64 geospatial_lat_max 79.75;
    Float64 geospatial_lat_min 0.25;
    Float64 geospatial_lat_resolution 0.5;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 14.75;
    Float64 geospatial_lon_min -79.75;
    Float64 geospatial_lon_resolution 0.5;
    String geospatial_lon_units "degrees_east";
    String history 
"2026-05-27 07:10:00Z: Created initial biomass dataset in R.
2026-05-28 09:22:00Z: Calculated moving average of biomass using data.table::frollmean().
2026-05-28 09:30:00Z: Computed relative change of biomass based on the moving average.
2026-05-28 09:42:00Z: Added derived variables 'biomass_ma' (moving average) and 'biomass_rel_change' (relative change).
2026-05-28 10:05:00Z: Updated metadata to comply with CF-1.9 conventions.
2026-05-28 10:30:00Z: Saved final NetCDF using R (ncdf4) and validated with NASA PODAAC MCC checker.
2026-08-11T10:07:27Z (local files)
2026-08-11T10:07:27Z https://erddap.emodnet.eu/griddap/biology_9114_ss-dbem-fish126c_87bc_96d6.das";
    String infoUrl "www.azti.es";
    String institution "BRTA";
    String keywords "aphiaid, biomass, Biomass_relative, brta, change, climate, data, dbem, fish, fishing, projections, relative, scenarios, ss-dbem, time, under";
    String license "CC-BY";
    String naming_authority "emodnet-biology.eu";
    Float64 Northernmost_Northing 79.75;
    String project "CINEA/EMFAF/2022/3.5.2/SI2.895681";
    String publisher_email "bio@emodnet.eu";
    String publisher_institution "Flanders Marine Institute (VLIZ)";
    String publisher_name "EMODnet Biology Data Management Team";
    String publisher_type "group";
    String publisher_url "https://emodnet.ec.europa.eu/en/biology";
    String references "Fernandes, J. A., Cheung, W. W., Jennings, S., Butenschön, M., de Mora, L., Frölicher, T. L., ... & Grant, A. (2013). Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model. Global change biology, 19(8), 2596-2607";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 0.25;
    String standard_name_vocabulary "CF Standard Name Table v90";
    String summary "SS-DBEM projections for eighteen species under RCP8.5, biogeochemical ensemble model and FMSY (Fishing Maximum Sustainable Yield). Ensemble change fields were winsorized to limit extreme outliers and transformed using a signed log (log1p) to accommodate negative and zero values. Spatial patterns were then smoothed using a 15x15 cell moving average (terra::focal) to reduce grid-scale noise while preserving large-scale trends";
    String time_coverage_end "2100-01-01T00:00:00Z";
    String time_coverage_start "2030-01-01T00:00:00Z";
    String title "SS-DBEM fish projections under climate and fishing scenarios";
    Float64 Westernmost_Easting -79.75;
  }
}

 

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
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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