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Dataset Title:  Top Dataset, dai pdsi, pdsi.mon.mean.selfcalibrated, 2.5°, 1850-2014 Subscribe RSS
Institution:  NOAA ESRL   (Dataset ID: noaa_esrl_c5c7_1493_8698)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      1980    30 days 10h 28m 41s (uneven)
  < slider >
 latitude (degrees_north) ?      55    2.5 (even)
  < slider >
 longitude (degrees_east) ?      144    2.5 (even)
  < slider >
 
Grid Variables (which always also download all of the dimension variables)
 pdsi (Standardized Units of Relative Dry and Wet) ?

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 {
    String _CoordinateAxisType "Time";
    Float64 actual_range -3.7868256e+9, 1.417392e+9;
    String avg_period "0000-01-00 00:00:00";
    String axis "T";
    String delta_t "0000-01-00 00:00:00";
    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 -58.75, 76.25;
    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 -178.75, 178.75;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  pdsi {
    Float32 actual_range -8.1602, 8.160143;
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum -10.0;
    String ioos_category "Time";
    Int16 least_significant_digit 2;
    String level_desc "Surface";
    String long_name "Monthly Self-calibrated Palmer Drought Severity Index using Penman-Monteith PE";
    Float32 missing_value -99999.0;
    String statistic "Mean";
    String units "Standardized Units of Relative Dry and Wet";
    Float32 valid_range -100.0, 100.0;
    String var_desc "Palmer Drought Severity Index";
  }
  NC_GLOBAL {
    String cdm_data_type "Grid";
    String comment "original creation date: Thu Oct 25 15:25:40 MDT 2012 at NCAR. Updated at PSD Oct 2016 with corrected NCAR data";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "esrl.psd.data@noaa.gov";
    String creator_name "NOAA ESRL PSD";
    String creator_type "institution";
    String creator_url "https://www.esrl.noaa.gov/psd/";
    String dataset_title "Palmer Drought Severity Index";
    String description 
"Monthly Self-calibrated Palmer Drought Severity Index (scPDSI)     
calculated using observed surface air temperature (HadCRUT4 from   
https://www.cru.uea.ac.uk/cru/data/temperature/ ) and               
precipitation (from Dai et al. (1997, J.Clim: for 1870-1947) +     
Chen et al. (2002, J. Hydromet.: for 1948-1978 + GPCP v2.2 for     
1979-present. The Dai and Chen P data were adjusted to have the    
same mean as the GPCP data over the 1979-1996 period).             
Calibration (or reference) period is 1950-1979.                    
Wind speed and air pressure data were from 20CR v2. Other data     
were based on CRU TS3.22. Documention:  	                   
Dai, A., 2011a: Characteristics and trends in various forms of the 
Palmer Drought Severity Index (PDSI) during 1900-2008. J. Geophys. 
Res., 116, D12115, doi:10.1029/2010JD015541.			   
Dai, A., K. E. Trenberth, and T. Qian, 2004: A global data set of  
Palmer Drought Severity Index for 1870-2002: Relationship with soil
moisture and effects of surface warming. J. Hydrometeorology, 5,   
1117-1130. Data source: Dr. A. Dai/NCAR (adai@ucar.edu). See       
https://www.cgd.ucar.edu/cas/catalog/climind/pdsi.html for updates. 
WARNING: PDSI and scPDSI over the higher latitudes (e.g., >50deg.) 
may not be a good proxy of soil moisutre content. Also, PDSI and   
scPDSI are highly autocorrelated indices not good at resolving     
sub-seasonal variations.  Please use with caution!                 
This is a normalized version so that every grid box has the same   
s.d. as that in the central U.S. during the calibr. period (1950-79)";
    String details "see ncar for more detials and updates";
    Float64 Easternmost_Easting 178.75;
    Float64 geospatial_lat_max 76.25;
    Float64 geospatial_lat_min -58.75;
    Float64 geospatial_lat_resolution 2.5;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 178.75;
    Float64 geospatial_lon_min -178.75;
    Float64 geospatial_lon_resolution 2.5;
    String geospatial_lon_units "degrees_east";
    String history 
"created Apr 2013 from data at NCAR webpage:updated Nov 2015 from new dataset version
2018-07-22T09:06:00Z https://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/dai_pdsi/pdsi.mon.mean.selfcalibrated.nc
2018-07-22T09:06:00Z http://upwell.pfeg.noaa.gov/erddap/griddap/noaa_esrl_c5c7_1493_8698.das";
    String id "Datasets/dai_pdsi/pdsi.mon.mean.selfcalibrated.nchttps://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/dai_pdsi/pdsi.mon.mean.selfcalibrated.nc";
    String infoUrl "https://www.esrl.noaa.gov/psd/data/gridded/data.pdsi.html";
    String institution "NOAA ESRL";
    String keywords "atmospheric, calibrated, center, climatic, climatology, cru, dai, data, dataset, drought, earth, esrl, global, gpcp, index, laboratory, latitude, longitude, monteith, month, monthly, national, ncar, noaa, palmer, pdsi, pdsi.mon.mean.selfcalibrated, penman, penman-monteith, precipitation, project, rain, rainfall, research, scpdsi, self, self-calibrated, severity, system, time, top, unit, using";
    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 76.25;
    String original_source "NCAR/UCAR: A Dai https://www.cgd.ucar.edu/cas/catalog/climind/pdsi.html.";
    String references "https://www.esrl.noaa.gov/psd/data/gridded/data.pdsi.html";
    String sourceUrl "https://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/dai_pdsi/pdsi.mon.mean.selfcalibrated.nc";
    Float64 Southernmost_Northing -58.75;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary 
"Global Monthly Dai Palmer Drought Severity Index. Monthly Self-calibrated Palmer Drought Severity Index (scPDSI)     
calculated using observed surface air temperature (HadCRUT4 from   
https://www.cru.uea.ac.uk/cru/data/temperature/ ) and               
precipitation (from Dai et al. (1997, J.Clim: for 1870-1947) +     
Chen et al. (2002, J. Hydromet.: for 1948-1978 + Global Precipitation Climatology Project (GPCP) v2.2 for     
1979-present. The Dai and Chen P data were adjusted to have the    
same mean as the GPCP data over the 1979-1996 period).             
Calibration (or reference) period is 1950-1979.                    
Wind speed and air pressure data were from 20CR v2. Other data     
were based on Climatic Research Unit (CRU) TS3.22. Documention:  	                   
Dai, A., 2011a: Characteristics and trends in various forms of the 
Palmer Drought Severity Index (PDSI) during 1900-2008. J. Geophys. 
Res., 116, D12115, doi:10.1029/2010JD015541.			   
Dai, A., K. E. Trenberth, and T. Qian, 2004: A global data set of  
Palmer Drought Severity Index for 1870-2002: Relationship with soil
moisture and effects of surface warming. J. Hydrometeorology, 5,   
1117-1130. Data source: Dr. A. Dai/National Center for Atmospheric Research (NCAR) (adai@ucar.edu). See       
https://www.cgd.ucar.edu/cas/catalog/climind/pdsi.html for updates. 
WARNING: PDSI and scPDSI over the higher latitudes (e.g., >50deg.) 
may not be a good proxy of soil moisutre content. Also, PDSI and   
scPDSI are highly autocorrelated indices not good at resolving     
sub-seasonal variations.  Please use with caution!                 
This is a normalized version so that every grid box has the same   
s.d. as that in the central U.S. during the calibr. period (1950-79)";
    String time_coverage_end "2014-12-01T00:00:00Z";
    String time_coverage_start "1850-01-01T00:00:00Z";
    String title "Top Dataset, dai pdsi, pdsi.mon.mean.selfcalibrated, 2.5°, 1850-2014";
    Float64 Westernmost_Easting -178.75;
  }
}

 

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://upwell.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://upwell.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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