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Dataset Title:  GPCP Version 2.3 Combined Precipitation Dataset (Final) (precip.mon.1981-2010.
ltm), 2.5°, 0001
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Institution:  NOAA ESRL   (Dataset ID: noaa_esrl_1330_4ff1_435e)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form
Graph Type:  ?
X Axis:  ?
Y Axis:  ?
Color:  ?
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time (UTC) ?     specify just 1 value →
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latitude (degrees_north) ?
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longitude (degrees_east) ?
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Graph Settings
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Draw land mask: 
Y Axis Minimum:   Maximum:   Ascending: 
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[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 -6.21357696e+10, -6.2106912e+10;
    String avg_period "0030-00-00 00:00:00";
    String axis "T";
    String climatology "climatology_bounds";
    String climo_period "1981/01/01 - 2010/12/31";
    String delta_t "0000-01-00 00:00:00";
    String interpreted_actual_range "0001/01/01 00:00:00 - 0001/12/01 00:00:00";
    String ioos_category "Time";
    String long_name "Time";
    Float64 ltm_range 66109.0, 77035.0;
    String prev_avg_period "0000-01-00 00:00:00";
    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 -88.75, 88.75;
    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 1.25, 358.75;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  precip {
    Float32 actual_range 5.604419e-4, 30.16107;
    Float64 colorBarMaximum 1.0e-4;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Meteorology";
    Int16 least_significant_digit 2;
    String level_desc "Surface";
    String long_name "Long Term Mean Average Monthly Rate of Precipitation";
    Float32 missing_value -9.96921e+36;
    String parent_stat "Mean";
    Int16 precision 32767;
    String standard_name "lwe_precipitation_rate";
    String statistic "Long Term Mean";
    String units "mm/day";
    Float32 valid_range 0.0, 100.0;
    String var_desc "Precipitation";
  valid_yr_count {
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Statistics";
    String long_name "count of non-missing values used in mean";
    Int16 missing_value 32767;
    String cdm_data_type "Grid";
    String citation 
"Adler, R.F., G.J. Huffman, A. Chang, R. Ferraro, P. Xie, J. Janowiak, B. 
Rudolf, U. Schneider, S. Curtis, D. Bolvin, A. Gruber, J. Susskind, P. 
Arkin, 2003: The Version 2 Global Precipitation Climatology Project 
(GPCP) Monthly Precipitation Analysis (1979 - Present). J. Hydrometeor., 
4(6), 1147-1167.";
    String contributor_name 
"Robert Adler    University of Maryland 
George Huffman  NASA Goddard Space Flight Center 
David Bolvin    NASA Goddard Space Flight Center/SSAI 
Eric Nelkin     NASA Goddard Space Flight Center/SSAI 
Udo Schneider   GPCC, Deutscher Wetterdienst 
Andreas Becker  GPCC, Deutscher Wetterdienst 
Long Chiu       George Mason University 
Mathew Sapiano  University of Maryland 
Pingping Xie    Climate Prediction Center, NWS, NOAA 
Ralph Ferraro   NESDIS, NOAA 
Jian-Jian Wang  University of Maryland 
Guojun Gu       University of Maryland";
    String Conventions "CF-1.6, COARDS, ACDD-1.3";
    String creator_email "";
    String creator_name "NOAA ESRL PSD";
    String creator_type "institution";
    String creator_url "";
    String curator 
"Dr. Jian-Jian Wang
ESSIC, University of Maryland College Park
College Park, MD  20742  USA
Phone: +1 301-405-4887";
    String dataset_title "Global Precipitation Climatology Project (GPCP) Monthly Analysis Product";
    String description "";
    String documentation "";
    Float64 Easternmost_Easting 358.75;
    Float64 geospatial_lat_max 88.75;
    Float64 geospatial_lat_min -88.75;
    Float64 geospatial_lat_resolution 2.5;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 358.75;
    Float64 geospatial_lon_min 1.25;
    Float64 geospatial_lon_resolution 2.5;
    String geospatial_lon_units "degrees_east";
    String history 
"Created 2016/11/08 by doMonthLTM
    String id "Datasets/gpcp/precip.mon.1981-2010.ltm.nc";
    String infoUrl "";
    String institution "NOAA ESRL";
    String keywords "2010.ltm, atmosphere, average, climatology, combined, count, data, dataset, earth, Earth Science > Atmosphere > Precipitation > Liquid Water Equivalent, Earth Science > Atmosphere > Precipitation > Precipitation Rate, equivalent, esrl, final, global, gpcp, laboratory, latitude, liquid, long, longitude, lwe, lwe_precipitation_rate, mean, meteorology, missing, month, monthly, noaa, non, non-missing, precip.mon.1981, precip.mon.1981-2010.ltm, precipitation, project, rain, rainfall, rate, research, science, statistics, system, term, time, used, valid_yr_count, values, version, water";
    String keywords_vocabulary "GCMD Science Keywords";
    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 88.75;
    String not_missing_threshold_percent "minimum 3% values input to have non-missing output value";
    String platform "NOAA POES (Polar Orbiting Environmental Satellites)";
    String references "";
    String source "";
    String source_documentation "";
    String source_obs 
"CDR RSS SSMI/SSMIS Tbs over ocean 
CDR SSMI/SSMIS rainrates over land (Ferraro) 
Geo-IR (Xie) calibrated by SSMI/SSMIS rainrates for sampling 
TOVS/AIRS empirical precipitation estimates at higher latitudes 
(ocean and land) 
GPCC gauge analysis to bias correct satellite estimates over land and 
merge with satellite based on sampling 
OLR Precipitation Index (OPI) (Xie) used for period before 1988";
    String sourceUrl "";
    Float64 Southernmost_Northing -88.75;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "";
    String time_coverage_end "0001-12-01T00:00:00Z";
    String time_coverage_start "0001-01-01T00:00:00Z";
    String title "GPCP Version 2.3 Combined Precipitation Dataset (Final) (precip.mon.1981-2010.ltm), 2.5°, 0001";
    String version "V2.3";
    Float64 Westernmost_Easting 1.25;


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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