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RAPID: Self-calibrating Palmer Drought Severity Index (scPDSI) data from Europe and America

Update Frequency: As Needed
Latest Data Update: 2009-11-13
Status: Completed
Online Status: ONLINE
Publication State: Published
Publication Date: 2014-09-21
Download Stats: last 12 months
Dataset Size: 4 Files | 24MB


"The Quantitative applications of high-resolution late Holocene proxy data sets: estimating climate sensitivity and thermohaline circulation influences" project, part of the Natural Environment Research Council (NERC) RAPID Climate Change Research Programme, was led by Prof Keith Briffa of the University of East Anglia and co-investigators at the University of East Anglia (Round 1 - NER/T/S/2002/00440 - Duration 1 Jul 2003 - 30 Jun 2008).

This dataset contains self-calibrating Palmer Drought Severity Index data.

Citable as:  NCAS British Atmospheric Data Centre (2014): RAPID: Self-calibrating Palmer Drought Severity Index (scPDSI) data from Europe and America. Briffa, date of citation.
Abbreviation: Not defined
Keywords: RAPID, Climate change, Drought


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Data lineage:

Data provided by Tim Osborn at UEA.

Data Quality:
Not known.
File Format:
Data are ASCII formatted

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Process overview

This dataset was generated by the computation detailed below.

Palmer drought index


The Palmer drought index, sometimes called the Palmer drought severity index and often abbreviated PDSI, is a measurement of dryness based on recent precipitation and temperature. It was developed by meteorologist Wayne Palmer, who first published his method in the 1965 paper Meteorological Drought for the Office of Climatology of the U.S. Weather Bureau.

The Palmer Drought Index is based on a supply-and-demand model of soil moisture. Supply is comparatively straightforward to calculate, but demand is more complicated as it depends on many factors, not just temperature and the amount of moisture in the soil but also hard-to-calibrate factors including evapotranspiration and recharge rates. Palmer tried to overcome these difficulties by developing an algorithm that approximated them based on the most readily available data, precipitation and temperature.

The index has proven most effective in determining long-term drought, a matter of several months, but it is not as good with conditions over a matter of weeks. It uses a 0 as normal, and drought is shown in terms of negative numbers; for example, negative 2 is moderate drought, negative 3 is severe drought, and negative 4 is extreme drought. Palmer's algorithm also is used to describe wet spells, using corresponding positive numbers. Palmer also developed a formula for standardizing drought calculations for each individual location based on the variability of precipitation and temperature at that location. The Palmer index can therefore be applied to any site for which sufficient precipitation and temperature data is available.

Input Description


Output Description


Software Reference


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