Skip to main content

Advertisement

Log in

Towards bridging the gap between climate change projections and maize producers in South Africa

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral mid-summer maximum temperature simulations for southern Africa. The statistical model uses atmospheric thickness fields from a high-resolution (0.5° × 0.5°) reanalysis-forced simulation as predictors in order to develop a linear recalibration model which represents the relationship between atmospheric thickness fields and gridded maximum temperatures across the region. The regional climate model, the conformal-cubic atmospheric model (CCAM), projects maximum temperatures increases over southern Africa to be in the order of 4 °C under low mitigation towards the end of the century or even higher. The statistical recalibration model is able to replicate these increasing temperatures, and the atmospheric thickness–maximum temperature relationship is shown to be stable under future climate conditions. Since dry land crop yields are not explicitly simulated by climate models but are sensitive to maximum temperature extremes, the effect of projected maximum temperature change on dry land crops of the Witbank maize production district of South Africa, assuming other factors remain unchanged, is then assessed by employing a statistical approach similar to the one used for maximum temperature projections.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Barnett TP, Preisendorfer RW (1987) Origins and levels of monthly and seasonal forecast skill for United States air temperature determined by canonical correlation analysis. Mon Weather Rev 115:1825–1850

    Article  Google Scholar 

  • Cai W, Borlace S, Lengaigne M, van Rensch P, Collins M, Vecchi G, Timmermann A, Santoso A, McPhaden MJ, Wu L, England MH, Wang G, Guilyardi A, Jin F-F (2014) Increasing frequency of extreme El Niño events due to greenhouse warming. Nat Clim Chang. doi:10.1038/NCLIMATE2100

  • Cai W, Wang G, Santoso A, McPhaden MJ, Wu L, Jin F-F, Timmermann A, Collins M, Vecchi G, Lengaigne M, England MH, Dommenget D, Takahashi K, Guilyardi E (2015) Increased frequency of extreme La Niña events under greenhouse warming. Nat Clim Chang. doi:10.1038/NCLIMATE2492

  • Challinor A, Wheeler T, Garforth C, Craufurd P, Kassam A (2007) Assessing the vulnerability of food crop systems in Africa to climate change. Clim Chang 83:381–399. doi:10.1007/s10584-007-9249-0

    Article  Google Scholar 

  • Engelbrecht CJ, Engelbrecht FA (2015) Shifts in Köppen-Geiger climate zones over southern Africa in relation to key global temperature goals. Theor Appl Climatol. doi:10.1007/s00704-014-1354-1

  • Engelbrecht FA, McGregor JL, Engelbrecht CJ (2009) Dynamics of the conformal-cubic atmospheric model projected climate-change signal over southern Africa. Int J Climatol 29:1013–1033

    Article  Google Scholar 

  • Engelbrecht FA, Landman WA, Engelbrecht CJ, Landman S, Bopape MM, Roux B, McGregor JL, Thatcher M (2011) Multi-scale climate modelling over southern Africa using a variable-resolution global model. Water SA 37:647–658

    Article  Google Scholar 

  • Engelbrecht F, Adegoke J, Bopape MM, Naidoo M, Garland R, Thatcher M, McGregor J, Katzfey J, Werner M, Ichoku C, Gatebe C (2015) Projections of rapidly rising surface temperatures over Africa under low mitigation. Environ Res Lett. doi:10.1088/1748-9326/10/8/085004

  • Greene AM, Goddard L, Lall U (2006) Probabilistic multimodel regional temperature change projections. J Clim 19:4326–4343

    Article  Google Scholar 

  • Hewitson BC, Crane RG (2006) Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa. Int J Climatol 26:1315–1337

    Article  Google Scholar 

  • Hewitson BC, Daron J, Crane RG, Zermoglio MF, Jack C (2013) Interrogating empirical-statistical downscaling. Clim Chang 122:539–554. doi:10.1007/s10584-013-1021-z

    Article  Google Scholar 

  • Holton JR, Hakim GJ (2013) An introduction to dynamic meteorology, 5th edn. Academic Press, New York, 532 pp

  • IPCC (2014) Summary for policymakers. In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Climate change 2014: impacts, adaptation, and vulnerability. Part a: global and sectoral aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 1–32

    Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–472

    Article  Google Scholar 

  • Katzfey KK, McGregor JL, Nguyen K, Thatcher M (2009) Dynamical downscaling techniques: impacts on regional climate change signals 18th World IMACS/MODSIM Congress. Cairns, Australia, 2009

  • Kim J, Waliser DE, Mattmann CA, Goodale CE, Hart AF, Zimdars PA, Crichton DJ, Jones C, Nikulin G, Hewitson B, Jack C, Lennard C, Favre A (2014) Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors. Clim Dyn 42:1189–1202. doi:10.1007/s00382-013-1751-7

    Article  Google Scholar 

  • Kruger AC, Sekele SS (2013) Trends in extreme temperature indices in South Africa: 1962–2009. Int J Climatol 33:661–676. doi:10.1002/joc.3455

    Article  Google Scholar 

  • Landman WA, Beraki A (2012) Multi-model forecast skill for mid-summer rainfall over southern Africa. Int J Climatol 32:303–314. doi:10.1002/joc.2273

    Article  Google Scholar 

  • Landman WA, Goddard L (2002) Statistical recalibration of GCM forecasts over southern Africa using model output statistics. J Clim 15:2038–2055

    Article  Google Scholar 

  • Landman WA, Beraki A, DeWitt D, Lötter D (2014) SST prediction methodologies and verification considerations for dynamical mid-summer rainfall forecasts for South Africa. Water SA 40(4):615–622. doi:10.4314/wsa.v40i4.6

    Article  Google Scholar 

  • Lazenby M, Landman WA, Garland R, DeWitt D (2014) Seasonal temperature prediction skill over southern Africa and human health. Meteorol Appl 21:963–974. doi:10.1002/met.1449

    Article  Google Scholar 

  • Malherbe J, Landman WA, Olivier C, Sakuma H, Luo J-J (2014) Seasonal forecasts of the SINTEX-F coupled model applied to maize yield and streamflow estimates over north-eastern South Africa. Meteorol Appl 21:733–742. doi:10.1002/met.1402

    Article  Google Scholar 

  • Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, Brienen S, Rust HW, Sauter T, Themeßl M, Venema VKC, Chun KP, Goodess CM, Jones RG, Onof C, Vrac M, Thiele-Eich I (2010) Precipitation downscaling under climate change. Recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48:RG3003. doi:10.1029/2009RG000314

    Article  Google Scholar 

  • Mason SJ, Tippett MK (2016) Climate predictability tool version 15.3. Columbia University Academic Commons, New York. doi:10.7916/D8NS0TQ6

    Google Scholar 

  • McGregor JL (2005) C-CAM: geometric aspects and dynamical formulation. CSIRO Atmospheric Research Technical Paper, No 70, 41.

  • McGregor JL (2015) Recent developments in variable-resolution global climate modelling. Clim Chang 129:369–380

    Article  Google Scholar 

  • McGregor JL, Dix MR (2001) The CSIRO conformal-cubic atmospheric GCM. In: Hodnett PF (ed) Proc. IUTAM Symposium on Advances in Mathematical Modelling of Atmosphere and Ocean Dynamics. Kluwer, Dordrecht, pp 197–202

    Chapter  Google Scholar 

  • McGregor JL, Dix MR (2008) An updated description of the conformal-cubic atmospheric model. In: Hamilton K, Ohfuchi W (eds) High resolution simulation of the atmosphere and ocean. Springer Verlag, Berlin, pp 51–76

    Google Scholar 

  • Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multi-model dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394

    Article  Google Scholar 

  • Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712. doi:10.1002/joc.1181

    Article  Google Scholar 

  • Mjelde JW, Thompson TN, Nixon CJ, Lamb PJ (1997) Utilising a farm-level decision model to help prioritise future climate prediction research needs. Meteorol Appl 4:161–170

    Article  Google Scholar 

  • Nguyen KC, Katzfey JJ, McGregor JL (2012) Global 60 km simulations with CCAM: evaluation over the tropics. Clim Dyn 39:637–654

    Article  Google Scholar 

  • Reynolds RW (1988) A real-time global sea surface temperature analysis. J Clim 1:75–86

  • Riphagen HA, Bruyère CL, Jordaan W, Poolman ER, Gertenbach JD (2002) Experiments with the NCEP regional eta model at the South African Weather Bureau, with emphasis on terrain representation and its effect on precipitation predictions. Mon Weather Rev 130:1246–1263

    Article  Google Scholar 

  • Rummukainen M (2010) State-of-the-art with regional climate models. WIRES Clim Change 1:82–96. doi:10.1002/wcc.8

    Article  Google Scholar 

  • Schmidt F (1977) Variable fine mesh in spectral global model. Beitr Phys Atmos 50:211–217

    Google Scholar 

  • Thatcher M, McGregor JL (2009) Using a scale-selective filter for dynamical downscaling with the conformal cubic atmospheric model. Mon Weather Rev 137:1742–1752

    Article  Google Scholar 

  • Thatcher M, McGregor JL (2010) A technique for dynamically downscaling daily-averaged GCM datasets over Australia using the conformal cubic atmospheric model. Mon Weather Rev 139:79–95

    Article  Google Scholar 

  • Thornton PK, Jones PG, Ericksen PJ, Challinor AJ (2011) Agriculture and food systems in sub-Saharan Africa in a 4°C+ world. Phil Trans R Soc A 369:117–136. doi:10.1098/rsta.2010.0246

    Article  Google Scholar 

  • Weaver SJ, Kumar A, Chen M (2014) Recent increases in extreme temperature occurrence over land. Geophys Res Lett 41. doi:10.1002/2014GL060300

Download references

Acknowledgments

This material is based upon work partly supported financially by the National Research Foundation of South Africa and by the Applied Centre for Climate and Earth System Science.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Willem A. Landman.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Landman, W.A., Engelbrecht, F., Hewitson, B. et al. Towards bridging the gap between climate change projections and maize producers in South Africa. Theor Appl Climatol 132, 1153–1163 (2018). https://doi.org/10.1007/s00704-017-2168-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-017-2168-8

Navigation