Dai Global Palmer Drought Severity Index (PDSI)
d299000
This dataset consists of monthly Palmer Drought Severity Index (PDSI) over global land areas on a 2.5 degree grid computed using observed monthly surface air temperature and precipitation, plus other surface meteorological forcing data for the self calibrating PDSI Penman Monteith (sc_PDSI_pm) case. Additionally, ensemble mean monthly sc_PDSI_pm data on a 2.5 degree grid has been calculated from 1900-2099 (for CMIP5) and 1900-2100 (for CMIP6) based on one historical and future (under RCP4.5 for CMIP5), and SSP2-4.5 (similar to RCP4.5) and SSP5-8.5 (similar to RCP8.5 for CMIP5) simulation by each of the 14 CMIP5 models and 25 CMIP6 models. These sc_PDSI_pm data from individual runs were simply averaged to produce the multiple model ensemble mean. The PDSI can be used as a measure of surface aridity anomalies and changes on seasonal to longer time scales. It is correlated with observed soil moisture and water storage variations over land.
dataset
https://rda.ucar.edu/datasets/d299000/
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https://rda.ucar.edu/datasets/d299000/dataaccess/
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climatologyMeteorologyAtmosphere
dataset
revision
2014-10-16
GROUND-BASED OBSERVATIONS > GROUND-BASED OBSERVATIONS
revision
2024-07-23
EARTH SCIENCE > CLIMATE INDICATORS > LAND SURFACE/AGRICULTURE INDICATORS > DROUGHT INDICES > PALMER DROUGHT SEVERITY INDEX
revision
2024-07-24
-180
180
77.5
-60
1850-01-01T00:00:00Z
2018-12-31T23:00:00Z
publication
2017-05-01
irregular
Creative Commons Attribution 4.0 International License
None
UCAR/NCAR - Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
(303)-497-1216
303-497-1291
pointOfContact
NCAR Research Data Archive
National Center for Atmospheric Research
CISL/DECS
P.O. Box 3000
Boulder
80307
U.S.A.
303-497-1291
name: NCAR Research Data Archive
description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.
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pointOfContact
2024-08-04T02:10:54Z