Easier access to scientific data
log in    
Brought to you by NOAA NMFS SWFSC ERD    

ERDDAP > griddap > Data Access Form ?

Dataset Title:  SST smoothed frontal gradients, Lon0360 Subscribe RSS
Institution:  NOAA/NMFS/SWFSC   (Dataset ID: FRD_SSTgradsmo_Lon0360)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      252    30 days 10h 25m 20s (uneven)
  < slider >
 latitude (degrees_north) ?      986    0.04167629 (even)
  < slider >
 longitude (degrees_east) ?      1705    0.0416715 (even)
  < slider >
Grid Variables (which always also download all of the dimension variables)
 SSTgrad (SST Edge-Gradient monthly, degrees C / km) ?

File type: (more info)

(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 {
    Int32 _ChunkSizes 524288;
    String _CoordinateAxisType "Time";
    Float64 actual_range 6.638976e+8, 1.3239072e+9;
    String axis "T";
    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";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 18.98355803907279, 60.03469886505636;
    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 180.0416683159196, 251.0498961407799;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  SSTgrad {
    Int32 _ChunkSizes 1, 493, 853;
    Float32 _FillValue 255.0;
    String ioos_category "Temperature";
    String long_name "SST Edge-Gradient monthly";
    String units "degrees C / km";
    String cdm_data_type "Grid";
    String Conventions "COARDS, CF-1.4, Unidata Dataset Discovery v1.0";
    String creator_email "";
    String defaultGraphQuery "SSTgrad[(1992-08-15)][(18.98355803907279):(60.03469886505636)][(-180.00000317928277):(-108.95010385922009)]&.draw=surface&.vars=longitude|latitude|SSTgrad&.colorBar=BlueWhiteRed|||||3";
    Float64 Easternmost_Easting 251.0498961407799;
    Float64 geospatial_lat_max 60.03469886505636;
    Float64 geospatial_lat_min 18.98355803907279;
    Float64 geospatial_lat_resolution 0.041676285102521395;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 251.0498961407799;
    Float64 geospatial_lon_min 180.0416683159196;
    Float64 geospatial_lon_resolution 0.041671495202382815;
    String geospatial_lon_units "degrees_east";
    String history 
"2021-09-23T05:57:11Z (local files)
    String infoUrl "";
    String institution "NOAA/NMFS/SWFSC";
    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 Metadata_Conventions "COARDS, CF-1.4, Unidata Dataset Discovery v1.0";
    Float64 Northernmost_Northing 60.03469886505636;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 18.98355803907279;
    String standard_name_vocabulary "CF-12";
    String summary 
"An improved automatic detection of mesoscale fronts, derived from Cayula, J. F., & Cornillon, P. (1992) and Cayula, J. F., & Cornillon, P. (1995), using the new method described by Nieto et al. (2012)

Nieto, Karen, Demarcq, H. and McClatchie, S. \"Mesoscale frontal structures in the Canary Upwelling System: new front and filament detection algorithms applied to spatial and temporal patterns\". Remote Sensing of the Environment 123, 2012 (pp.339-346)\"

Cayula, J. F., & Cornillon, P. (1992). Edge detection algorithm for SST images. Journal of Atmospheric and Oceanic Technology, 9, 67-80.

Cayula, J. F., & Cornillon, P. (1995). Multi-image edge detection for SST images. Journal of Atmospheric and Oceanic Technology, 12, 821-829.";
    String time_coverage_end "2011-12-15T00:00:00Z";
    String time_coverage_start "1991-01-15T00:00:00Z";
    String title "SST smoothed frontal gradients, Lon0360";
    Float64 Westernmost_Easting 180.0416683159196;


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 2.14
Disclaimers | Privacy Policy | Contact