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.
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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
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
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
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
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
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
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
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
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
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
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
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
Landman WA, Goddard L (2002) Statistical recalibration of GCM forecasts over southern Africa using model output statistics. J Clim 15:2038–2055
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
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
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
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
Mason SJ, Tippett MK (2016) Climate predictability tool version 15.3. Columbia University Academic Commons, New York. doi:10.7916/D8NS0TQ6
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
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
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
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
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
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
Nguyen KC, Katzfey JJ, McGregor JL (2012) Global 60 km simulations with CCAM: evaluation over the tropics. Clim Dyn 39:637–654
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
Rummukainen M (2010) State-of-the-art with regional climate models. WIRES Clim Change 1:82–96. doi:10.1002/wcc.8
Schmidt F (1977) Variable fine mesh in spectral global model. Beitr Phys Atmos 50:211–217
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
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
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
Weaver SJ, Kumar A, Chen M (2014) Recent increases in extreme temperature occurrence over land. Geophys Res Lett 41. doi:10.1002/2014GL060300
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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.
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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
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DOI: https://doi.org/10.1007/s00704-017-2168-8