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Theoretical and Applied Climatology

, Volume 120, Issue 1–2, pp 41–54 | Cite as

Quantifying the impact of climate change on drought regimes using the Standardised Precipitation Index

Original Paper

Abstract

The study presents a methodology to characterise short- or long-term drought events, designed to aid understanding of how climate change may affect future risk. An indicator of drought magnitude, combining parameters of duration, spatial extent and intensity, is presented based on the Standardised Precipitation Index (SPI). The SPI is applied to observed (1955–2003) and projected (2003–2050) precipitation data from the Community Integrated Assessment System (CIAS). Potential consequences of climate change on drought regimes in Australia, Brazil, China, Ethiopia, India, Spain, Portugal and the USA are quantified. Uncertainty is assessed by emulating a range of global circulation models to project climate change. Further uncertainty is addressed through the use of a high-emission scenario and a low-stabilisation scenario representing a stringent mitigation policy. Climate change was shown to have a larger effect on the duration and magnitude of long-term droughts, and Australia, Brazil, Spain, Portugal and the USA were highlighted as being particularly vulnerable to multi-year drought events, with the potential for drought magnitude to exceed historical experience. The study highlights the characteristics of drought which may be more sensitive under climate change. For example, on average, short-term droughts in the USA do not become more intense but are projected to increase in duration. Importantly, the stringent mitigation scenario had limited effect on drought regimes in the first half of the twenty-first century, showing that adaptation to drought risk will be vital in these regions.

Keywords

Standardise Precipitation Index Drought Event Drought Frequency Agricultural Drought Hydrological Drought 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

704_2014_1143_MOESM1_ESM.doc (348 kb)
ESM 1 (DOC 348 kb)

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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  1. 1.Cambridge Centre for Climate Change Mitigation Research (4CMR), Department Land EconomyUniversity of CambridgeCambridgeUK
  2. 2.Tyndall Centre, School of Environmental SciencesUniversity of East AngliaNorwichUK
  3. 3.Environmental Change Institute, School of Geography and the EnvironmentUniversity of OxfordOxfordUK

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