Climate Dynamics

, Volume 44, Issue 5–6, pp 1595–1609 | Cite as

Drought regimes in Southern Africa and how well GCMs simulate them

  • Eva L. Ujeneza
  • Babatunde J. AbiodunEmail author


This paper presents the spatial and temporal structures of drought regimes in Southern Africa and evaluates the capability of ten global climate models (GCMs) in simulating the regimes. The study uses a multi-scaled standardized index (called standardized precipitation evapo-transpiration index, SPEI) in characterizing droughts over Southern Africa at 3- and 12-month scales. The spatial patterns of the drought regimes are identified using the rotated principal component analysis (PCA) on the SPEI, while the temporal characteristics of the drought regimes are studied using wavelet analysis. The relationship between each drought regime and global SSTs (and climate indices) is quantified using correlation analysis and wavelet coherence analysis. The study also quantifies the capability of the GCMs in simulating the drought regimes. The PCA results show four main drought regimes that jointly explain about 50 % SPEI variance over South Africa. The drought regimes (hereafter PF1, PF2, PF3 and PF4) centre over the south-western part of Southern Africa (i.e. South Africa, Botswana and Namibia common border), Zimbabwe, Tanzania, and Angola, respectively. PF1, PF2 and PF4 are strongly correlated with SST over the South Atlantic, Tropical Pacific and Indian Oceans, while PF3 is strongly correlated with the SST over the Tropical Pacific, Atlantic and Indian Oceans. The drought regimes (except PF4) have significant coherence with some atmospheric teleconnection, but the strength, duration, and phase of the coherence vary with time. All the GCMs simulate the drought regimes better at a 3-month scale than at a 12-month scale. At a 3-month scale, 70 % of the GCMs simulate all the drought regimes with a high correlation coefficient (r > 0.6), but at a 12-month scale only 60 % of the models simulate at least three of the drought regimes with a high correlation coefficient (r > 0.6). The results of this study have applications in using GCMs to study the underlying atmospheric dynamics that control droughts and to understand the impacts of global warming on droughts.


Droughts Southern Africa Climate indices Global climate models 



The project was supported with grants from the Water Research Commission (WRC, South Africa) and the National Research Foundation (NRF, South Africa). Computations facility was provided by the Centre for High Performance Computing (CHPC, South Africa). We thank the two anonymous reviewers, whose comments improved the quality of this manuscript.


  1. Beguería S, Vicente-Serrano SM (2013) Package “SPEI”. doi: 10.1175/2009JCLI2909.1.http
  2. Blamey R, Reason CJC (2007) Relationships between Antarctic sea-ice and South African winter rainfall. Clim Res 33:183–193CrossRefGoogle Scholar
  3. Calow RC, Macdonald AM, Nicol AL, Robins NS (2010) Ground water security and drought in Africa: linking availability, access, and demand. Gr Water 48(2):246–256. doi: 10.1111/j.1745-6584.2009.00558.x CrossRefGoogle Scholar
  4. Dai Aiguo (2011) Drought under global warming: a review. Wiley Interdiscip Rev Clim Change 2(1):45–65. doi: 10.1002/wcc.81 CrossRefGoogle Scholar
  5. Dai Aiguo, Trenberth EK, Qian T (2004) A global dataset of Palmer drought severity index for 1870–2002: relationship with soil moisture and effects of surface warming. J Hydrometeorol 5:1117–1130CrossRefGoogle Scholar
  6. Farge M (1992) Wavelet transforms and their applications to turbulence. Annu Rev Fluids Mech 24:395–457 (Holschneider 1991)CrossRefGoogle Scholar
  7. Fauchereau N, Trzaska S, Rouault M, Richard Y (2003) Rainfall variability and changes in Southern Africa during the 20th century in the Global Warming context. Nat Hazards 29:139–154CrossRefGoogle Scholar
  8. Giannini A, Biasutti M, Held IM, Sobel AH (2008) A global perspective on African climate. Clim Change 90:359–383. doi: 10.1007/s10584-008-9396-y CrossRefGoogle Scholar
  9. Hayes MJ, Svodoba MD, Wilhite DA, Vanyarko OV (1999) Monitoring the 1996 drought using the standardized precipitation index. Bull Am Meteorol Soc 80:429–438CrossRefGoogle Scholar
  10. Heddinghaus TR, Sahol P (1991). A review of the Palmer Drought Severity Index and Where do we go from here? In Proceedings of the seventh conference on applied climatology. american meteorological society, Boston, pp 242–246Google Scholar
  11. Ideião SMA, Santos CAG (2005) Analysis of precipitation time series using the wavelet transform. Sociedade Natureza (Special Issue) 736–745.
  12. IPCC (2007) The physical science basis. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miler HL (eds) Contribution of working group I to the fourth assessment report of the International Panel on Climate Change Program. Cambridge University Press, Cambridge, p 996Google Scholar
  13. Jolliffe IT (1995) Rotation of principal components: choice of normalization constraints. J Appl Stat 22:29–35CrossRefGoogle Scholar
  14. Jolliffe I, Trendafilov NT, Uddin M (2003) A modified principal component technique based on the lasso. J Comput Graph Stat 12(3):531–547CrossRefGoogle Scholar
  15. Jury Mark R (2002) Economic impacts of climate variability in South Africa and development of resource prediction models. J Appl Meteorol 41(1):46–55. doi: 10.1175/1520-0450(2002)041<0046:EIOCVI>2.0.CO;2 CrossRefGoogle Scholar
  16. Jury MR, Enfield DB (2002). Tropical monsoons around Africa : Stability of El Nino—Southern Oscillation associations and links with continental climate 107 doi: 10.1029/2000JC000507
  17. Jury MR, Mwafulirwa ND (2002) Climate variability in Malawi, part 1: dry summers, statistical associations and predictability. Int J Climatol 22(11):1289–1302. doi: 10.1002/joc.771 CrossRefGoogle Scholar
  18. Karl TR (1986) Sensitivity of the palmer drought Severity index and Palmer’s Z-index to their calibration coefficients including potential evapotranspiration. J Clim Appl Meteorol 25:77–86CrossRefGoogle Scholar
  19. Labat D (2005) Recent advances in wavelet analyses: Part 1. Rev concepts 314:275–288. doi: 10.1016/j.jhydrol.2005.04.003 Google Scholar
  20. Makarau A, Jury MR (1997) Predictability of Zimbabwe summer rainfall. Int J Climatol 17:1421–1432CrossRefGoogle Scholar
  21. Manatsa D, Matarira CH (2009) Changing dependence of Zimbabwean rainfall variability on ENSO and the Indian Ocean dipole/zonal mode. Theoret Appl Climatol 98(3–4):375–396. doi: 10.1007/s00704-009-0114-0 CrossRefGoogle Scholar
  22. Manatsa D, Chingombe W, Matsikwa H, Matarira CH (2008) The superior influence of Darwin Sea level pressure anomalies over ENSO as a simple drought predictor for Southern Africa. doi: 10.1007/s00704-007-0315-3
  23. Manatsa Desmond, Reason CJC, Mukwada G (2012) On the decoupling of the IODZM from southern Africa summer rainfall variability. Int J Climatol 32(5):727–746. doi: 10.1002/joc.2306 CrossRefGoogle Scholar
  24. Mason SJ (2001) El Nino, Climate change and Southern African Climate. Environmetrics 12:327–345CrossRefGoogle Scholar
  25. Mason SJ, Jury MR (1997) Climatic variability and change over southern Africa: a reflection on underlying processes. Prog Phys Geogr 21(1):23–50. doi: 10.1177/030913339702100103 CrossRefGoogle Scholar
  26. McKee TB, Doesken NJ, Kleist J. (1993). The relationship of drought frequency and duration to time Scales. Preprints, 8th conference on applied climatology, January 17–22 Anaheim, CA, 179–184Google Scholar
  27. Meehl GA, Stocker TF, Collins WD, Friedlinstein P, Gaye A, Gregory JM, Kitoh A et al (2007) Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. In: Solomon S, Quirion D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M (eds) Global climate projections. Cambridge University Press, Cambridge, pp 747–846Google Scholar
  28. Meque A, Abiodun BJ (2014) Simulating the link between ENSO and summer drought in Southern Africa using regional climate models. Clim Dyn. doi: 10.1007/s00382-014-2143-3
  29. Mishra AK, Singh VP (2010) Review paper a review of drought concepts. J Hydrol 391(1–2):202–216. doi: 10.1016/j.jhydrol.2010.07.012 CrossRefGoogle Scholar
  30. Misra V (2003) The influence of Pacific SST variability on the precipitation over Southern Africa. J Clim 16:2408–2418Google Scholar
  31. Mitchell TD, Carter TR, Jones PD, Hulme M, New M (2004). A comprehensive set of high-resolution grids of monthly climate for Europe and the globe : the observed record (1901–2000) and 16 scenarios (2001–2100). Geography, 55(July), 30.
  32. Nash DJ, Endfield GH (2002) A 19th century climate chronology for the Kalahari region of central southern Africa derived from missionary correspondence. Int J Climatol 22(7):821–841. doi: 10.1002/joc.753 CrossRefGoogle Scholar
  33. Nicholson SE, Leposo D, Grist J (2001) The relationship between El nino and drought over Botswana. J Clim 14:323–335CrossRefGoogle Scholar
  34. Ntale HK, Gan TYEW (2003) Drought indices and their application to east Africa. Int J Climatol 23:1335–1357. doi: 10.1002/joc.931 CrossRefGoogle Scholar
  35. Palmer CW (1965) Meteorological drought. US Weather Bureau, WashingtonGoogle Scholar
  36. Palmer WC (1968) Keeping track of crop moisture conditions, nationwide: the new Crop Moisture Index. Weatherwise 21:156–161CrossRefGoogle Scholar
  37. Philippon N, Rouault M, Richard Y, Favre A (2011) The influence of ENSO on winter rainfall in South Africa. Int J Clim. doi: 10.1002/joc.3403 Google Scholar
  38. Rao SA, Behera SK, Masumoto Y, Yamagata T (2002) Interannual subsurface variability in the tropical Indian Ocean with a special emphasis on the Indian Ocean Dipole. Deep Sea Res Part II 49(7–8):1549–1572. doi: 10.1016/S0967-0645(01)00158-8 CrossRefGoogle Scholar
  39. Reason CJC, Rouault M (2005) Links between theAntartic Ocean and winter rainfall over western South Africa. Geophys Res Lett 32:L077057Google Scholar
  40. Reason CJC, Rouault M, Melice J-L, Jagadheesha D (2002) Interannual winter rainfall variability in SW South Africa and large scale ocean-atmosphere interaction. Meteorol Atmos Phys 80:19–29CrossRefGoogle Scholar
  41. Richard Y, Poccard I (1998) A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa. Int Rem Sens 19(15):2907–2920CrossRefGoogle Scholar
  42. Richard Y, Fauchereau N, Poccard I, Rouault M, Trzaska S (2001) 20th century droughts in southern Africa: spatial and temporal variability, teleconnections with oceanic and atmospheric conditions. Int J Climatol 21(7):873–885. doi: 10.1002/joc.656 CrossRefGoogle Scholar
  43. Richman MB (1986) Rotation of principal components. J Climatol 6:293–335CrossRefGoogle Scholar
  44. Rouault M, Richard Y (2003) Intensity and spatial extension of drought in South Africa at different time scales. WaterSA 29(4):489–500Google Scholar
  45. Rouault M, Richard Y (2005) Intensity and spatial extent of droughts in southern Africa, 32(April) 2–51. doi: 10.1029/2005GL022436
  46. Sheffield J, Wood EF (2008) Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Clim Dyn 31(1):79–105. doi: 10.1007/s00382-007-0340-z CrossRefGoogle Scholar
  47. Sivakumar MVK, Motha PR, Wilhite AD, Woods AD (2011) Agriculture Al Drought indices. In: Proceedings of the WMO/UNISDR expert group meeting on agricultural drought indices. World Meteorological OrganizationGoogle Scholar
  48. Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical Merged Land-Ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296CrossRefGoogle Scholar
  49. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93(4):485–498 doi: 10.1175/BAMS-D-11-00094.1.
  50. Thomson MC, Abayomi K, Barnston AG, Levy M, Dilley M (2003) El Niño and drought in Southern Africa. The Lancet 361:437–438CrossRefGoogle Scholar
  51. Torrence C, Webster PJ (1999) Interdecadal Changes in the ENSO—Monsoon System. J Clim 12:2679–2690CrossRefGoogle Scholar
  52. Usman MT, Reason CJC (2004) Dry spell frequencies and their variability over southern Africa. Clim Res 26:199–211CrossRefGoogle Scholar
  53. Vicente-Serrano SM, López-Moreno JI (2005) Hydrological response to different time scales of climatological drought: an evaluation of the standardized precipitation index in a mountainous Mediterranean basin. Hydrol Earth Syst Sci 9:523–533CrossRefGoogle Scholar
  54. Vicente-Serrano SM, Beguería S, López-Moreno JI, Angulo M, El Kenawy A (2010a) A new global 0.5° gridded dataset (1901–2006) of a multiscalar drought index: comparison with current drought index datasets based on the Palmer drought severity index. J Hydrometeorol 11(4):1033–1043. doi: 10.1175/2010JHM1224.1 CrossRefGoogle Scholar
  55. Vicente-Serrano SM, Beguería S, López-Moreno JI (2010b) A multiscalar drought index sensitive to Global Warming: the Standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718. doi: 10.1175/2009JCLI2909.1 CrossRefGoogle Scholar
  56. Vicente-Serrano SM, López-moreno JI, Drumond A, Gimeno L, Nieto R, Morán-Tejeda E, Lorenzo-Lacruz J et al (2011) Effects of warming processes on droughts and water resources in the NW Iberian Peninsula (1930–2006). Clim Res 48:203–212. doi: 10.3354/cr01002 CrossRefGoogle Scholar
  57. Washington R, Downing TE (1999) Seasonal Forecasting of African rainfall  prediction, responses and household food security. Geograph J 165(3):255–274.
  58. Washington R, Preston A (2006) Extreme wet years over southern Africa : role of Indian Ocean sea surface temperatures. J Geophys Res Atmos 111:1–15. doi: 10.1029/2005JD006724 Google Scholar
  59. Wells N, Goddard S, Hayes MJ (2004) A self-calibrating palmer drought severity index. J Clim 17:2335–2351CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Climate Systems Analysis Group, Department of Environmental and Geographical ScienceUniversity of Cape TownCape TownSouth Africa

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