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Dataset Title:  Navy Operational Global Atmospheric Prediction System (NOGAPS), 1 degree, 2013-
2013, Pressure MSL, Lon+/-180
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Institution:  FNMOC   (Dataset ID: erdNogaps1DPres_LonPM180)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
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 1.3569984e+9, 1.3607352e+9;
    String axis "T";
    String calendar "proleptic_gregorian";
    String comment "Uninitialized analysis / image product / forecast product valid for RT + P1";
    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";
    Float32 actual_range -90.00001, 89.99999;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -180.0, 179.0;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  pres_reduced_msl {
    Float64 colorBarMaximum 1050.0;
    Float64 colorBarMinimum 950.0;
    String comment "The conversion of an observed pressure value to the value it would theortically have at mean sea level @ Mean sea level";
    String coordinates "reftime time lat lon";
    String description "The conversion of an observed pressure value to the value it would theortically have at mean sea level";
    Int32 Grib1_Center 58;
    String Grib1_Interval_Name "Unknown Time Range Indicator -1";
    Int32 Grib1_Interval_Type -1;
    String Grib1_Level_Desc "Mean sea level";
    Int32 Grib1_Level_Type 102;
    Int32 Grib1_Parameter 2;
    String Grib1_Parameter_Name "pres_reduced";
    Int32 Grib1_Subcenter 0;
    Int32 Grib1_TableVersion 2;
    String Grib_Variable_Id "VAR_58-0-2-2_L102";
    String grid_mapping "LatLon_Projection";
    String ioos_category "Pressure";
    String long_name "Pressure (adjusted to Mean Sea Level)";
    Float32 missing_value NaN;
    String units "hPa";
    String _CoordSysBuilder "ucar.nc2.dataset.conv.CF1Convention";
    String cdm_data_type "Grid";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_name "FNMOC";
    String creator_type "institution";
    String creator_url "";
    Float64 Easternmost_Easting 179.0;
    String Generating_process_or_model "Naval Oceanographic Global Atmospheric Prediction System";
    Float64 geospatial_lat_max 89.99999;
    Float64 geospatial_lat_min -90.00001;
    Float64 geospatial_lat_resolution 1.0;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.0;
    Float64 geospatial_lon_min -180.0;
    Float64 geospatial_lon_resolution 1.0;
    String geospatial_lon_units "degrees_east";
    String GRIB_table_version "0,2";
    String history 
"Read using CDM IOSP GribCollection v3
    String infoUrl "";
    String institution "FNMOC";
    String keywords "conversion, data, fnmoc, level, mean, navgem, nogaps, observed, pressure, sea, theortically, value";
    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.";
    Float64 Northernmost_Northing 89.99999;
    String Originating_or_generating_Center "Fleet Numerical Meteorology and Oceanography Center, Monterey, CA, United States";
    String Originating_or_generating_Subcenter "0";
    String sourceUrl "";
    Float64 Southernmost_Northing -90.00001;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "The Navy Operational Global Atmospheric Prediction System (NOGAPS) is a global numerical weather prediction computer model run by the United States Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). It is run four times a day to produce weather forecasts.  NOGAPS was replaced by the NAVGEM in February 2013.[Wikipedia]";
    String time_coverage_end "2013-02-13T06:00:00Z";
    String time_coverage_start "2013-01-01T00:00:00Z";
    String title "Navy Operational Global Atmospheric Prediction System (NOGAPS), 1 degree, 2013-2013, Pressure MSL, Lon+/-180";
    Float64 Westernmost_Easting -180.0;


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.

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