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Climatic Change

, Volume 126, Issue 3–4, pp 469–483 | Cite as

Dissecting indices of aridity for assessing the impacts of global climate change

  • Evan H. Girvetz
  • Chris Zganjar
Article

Abstract

There is great interest in understanding how climate change will impact aridity through the interaction of precipitation changes with rising temperatures. The Aridity Index (AI), Climatic Moisture Deficit (CMD), and Climatic Moisture Surplus (CMS) are metrics commonly used to quantify and map patterns in aridity and water cycling. Here we show that these metrics have different patterns of change under future climate—based on an ensemble of nine general circulation climate models—and the different metrics are appropriate for different purposes. Based on these differences between the metrics, we propose that aridity can be dissected into three different types—hydrological (CMS), agricultural (CMD), and meteorological. In doing this, we propose a novel modified version of the Aridity Index, called AI+, that can be useful for assessing changes in meteorological aridity. The AI + is based on the same ratio between precipitation and evapotranspiration as the traditional AI, but unlike the traditional AI, the AI + only accounts for changes to precipitation during months when precipitation is less than reference/potential evapotranspiration (i.e. there is a deficit). Moreover, we show that the traditional AI provides a better estimate of change in moisture surplus driven by changes to precipitation during the wet season, rather than changes in deficit that occur during the drier seasons. These results show that it is important to select the most appropriate metric for assessing climate driven changes in aridity.

Keywords

General Circulation Model Aridity Index Reference Evapotranspiration Global Land Area Hargreaves Method 
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.

Notes

Acknowledgments

We thank Peter Kareiva, Michelle Marvier, Craig Groves, and two anonymous reviewers for providing helpful comments on the manuscript, analysis and presentation of results.

Supplementary material

10584_2014_1218_Fig8_ESM.gif (124 kb)
Supplemental Fig. 1

Historic average (1961–1990) and future projected (2081–2100) change in temperature (average of minimum and maximum) and precipitation for the ensemble median of nine GCMs. Only areas below 60° north are shown (GIF 123 kb)

10584_2014_1218_MOESM1_ESM.tif (1.5 mb)
High resolution image (TIFF 1581 kb)
10584_2014_1218_Fig9_ESM.gif (84 kb)
Supplemental Fig. 2

Histograms showing the distribution of historical average (left column) and future change for 2081–2100 under the SRES A2 emissions scenario (right column) for the four aridity metrics based on the 538 randomly selected points globally (separated by at least 2.0° in distance from one another) (GIF 84 kb)

10584_2014_1218_MOESM2_ESM.tif (700 kb)
High resolution image (TIFF 700 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.International Center for Tropical AgricultureNairobiKenya
  2. 2.University of Washington School of Environmental and Forest SciencesSeattleUSA
  3. 3.The Nature Conservancy Central Science ProgramArlingtonUSA

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