Climatic Change

, Volume 135, Issue 3–4, pp 655–668 | Cite as

Evaluation and projections of extreme precipitation over southern Africa from two CORDEX models

  • Izidine Pinto
  • Christopher Lennard
  • Mark Tadross
  • Bruce Hewitson
  • Alessandro Dosio
  • Grigory Nikulin
  • Hans-Juergen Panitz
  • Mxolisi E. Shongwe


The study focuses on the analysis of extreme precipitation events of the present and future climate over southern Africa. Parametric and non-parametric approaches are used to identify and analyse these extreme events in data from the Coordinated Regional Climate Downscaling Experiment (CORDEX) models. The performance of the global climate model (GCM) forced regional climate model (RCM) simulations shows that the models are able to capture the observed climatological spatial patterns of the extreme precipitation. It is also shown that the downscaling of the present climate are able to add value to the performance of GCMs over some areas depending on the metric used. The added value over GCMs justifies the additional computational effort of RCM simulation for the generation of relevant climate information for regional application. In the climate projections for the end of twenty-first Century (2069–2098) relative to the reference period (1976–2005), annual total precipitation is projected to decrease while the maximum number of consecutive dry days increases. Maximum 5-day precipitation amounts and 95th percentile of precipitation are also projected to increase significantly in the tropical and sub-tropical regions of southern Africa and decrease in the extra-tropical region. There are indications that rainfall intensity is likely to increase. This does not equate to an increase in total rainfall, but suggests that when it does rain, the intensity is likely to be greater. These changes are magnified under the RCP8.5 when compared with the RCP4.5 and are consistent with previous studies based on GCMs over the region.


Regional Climate Model Extreme Precipitation Global Climate Model Generalize Extreme Value Extreme Precipitation Event 
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.



We are grateful to the Water Research Commission financial support from the Project K5-2240. We would like to thank the regional downscaling groups for producing and making available their model data. We also thank two anonymous reviewers for their helpful comments.

Supplementary material

10584_2015_1573_MOESM1_ESM.pdf (3 mb)
ESM 1 (PDF 3075 kb)
10584_2015_1573_MOESM2_ESM.tex (9 kb)
ESM 2 (TEX 9 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Izidine Pinto
    • 1
  • Christopher Lennard
    • 1
  • Mark Tadross
    • 1
    • 2
  • Bruce Hewitson
    • 1
  • Alessandro Dosio
    • 3
  • Grigory Nikulin
    • 4
  • Hans-Juergen Panitz
    • 5
  • Mxolisi E. Shongwe
    • 6
  1. 1.Climate System Analysis GroupUniversity of Cape Town (UCT)RondeboschSouth Africa
  2. 2.United Nations Development Programme (UNDP-GEF)Energy and Environment GroupNew YorkUSA
  3. 3.European Commission Joint Research Centre (JRC)Institute for Environment and Sustainability (IES)IspraItaly
  4. 4.Rossby CentreSwedish Meteorological and Hydrological InstituteNorrköpingSweden
  5. 5.Karlsruhe Institute of TechnologyInstitute of Meteorology and Climate Research - Tropopshere ResearchKarlsruheGermany
  6. 6.South African Weather Service and University of PretoriaPretoriaSouth Africa

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