http://dx.doi.org/10.4314/wsa.v40i3.9 Available on website http://www.wrc.org.za ISSN 0378-4738 (Print) = Water SA Vol. 40 No. 3 July 2014 ISSN 1816-7950 (On-line) = Water SA Vol. 40 No. 3 July 2014 461 * To whom all correspondence should be addressed.  +27 83 785-7115; e-mail: shephido@yahoo.com Received 24 October 2013; accepted in revised form 20 June 2014. Seasonal rainfall predictability over the Lake Kariba catchment area Shepherd Muchuru 1 *, Willem A Landman 1,2 , David DeWitt 3 and Daleen Lötter 2 1 Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa 2 Council for Scientifc and Industrial Research, Natural Resources and the Environment, Pretoria, South Africa 3 International Research Institute for Climate and Society, Columbia University, Palisades, New York ABSTRACT Te Lake Kariba catchment area in southern Africa has one of the most variable climates of any major river basin, with an extreme range of conditions across the catchment and through time. Marked seasonal and interannual fuctuations in rainfall are a signifcant aspect of the catchment. To determine the predictability of seasonal rainfall totals over the Lake Kariba catchment area, this study used the low-level atmospheric circulation (850 hPa geopotential height felds) of a coupled ocean-atmosphere general circulation model (CGCM) over southern Africa, statistically downscaled to gridded seasonal rainfall totals over the catchment. Tis downscaling confguration was used to retroactively forecast the 3-month rainfall seasons of September-October-November through February-March-April, over a 14-year independent test period extending from 1994. Retroactive forecasts are produced for lead times of up to 5 months and probabilistic forecast performances evaluated for extreme rainfall thresholds of the 25 th and 75 th percentile values of the climatological record. Te verifcation of the retroactive forecasts shows that rainfall over the catchment is predictable at extended lead-times, but that predictability is primarily found for austral mid-summer rainfall. Tis season is also associated with the highest potential economic value that can be derived from seasonal forecasts. A forecast case study of a recent extreme rainfall season (2010/11) that lies outside of the verifcation period is presented as evidence of the statistical downscaling system’s operational capability. Keywords: Lake Kariba catchment, coupled ocean-atmosphere model, statistical downscaling, seasonal forecasting, economic value INTRODUCTION Southern Africa is a region of signifcant rainfall variability at a range of temporal and spatial scales and is prone to serious drought and food events (e.g. Tyson, 1986); Nicholson et al., 1987; Lindesay, 1998; Reason et al., 2000). Te region is also sensitive to precipitation shifs and variability (IPCC, 2007; Reason et al., 2006). Despite the diverse climatic zones, rainfall in southern Africa is mainly observed during the austral sum- mer between October and May. Te future spatial and temporal rainfall distribution and variability is uncertain (Gordon et al., 2000; Hachingonta et al., 2007). Te region’s summer climate is mainly driven by oscillations of the inter-tropical conver- gence zone (ITCZ) (Beilfuss, 2012). Te temporal and spatial distribution of convection is associated with evaporative losses that strain food and water resources (Jury et al., 1999; Lyon B, 2009). Te South Atlantic and Indian Oceans, being the major sources of moisture for southern Africa, play a major role in determining the spatio-temporal variations of rainfall in the region (Matarira and Jury, 1992; Levey and Jury, 1996; Jury et al., 1999). Te aforementioned studies have provided ample evidence for regional forcing features of composite wet and dry spells caused by the atmospheric circulation. Harrison (1986), Harangozo, (1989) and Barclay et al. (1993) have found that the seasonal cycle of convective spells over southern Africa and the surrounding oceanic basins during the austral summer are characterised by equatorial extratropical temperature gradi- ents. Tis is caused by diferential solar heating between the equator and the mid-latitudes. A more recent study has deter- mined how the external forcing of major wet spells over south- ern Africa varies through the summer (Fauchereau et al., 2009). Te wet spells occur at intervals of approximately 20 to 35 d (Levey and Jury, 1996), and half of all of the wet spells appear quasi-stationery from November to March. Southern Africa is a predominantly semi-arid region with a high degree of interan- nual rainfall variability. Although much of the recent climate research has focused on the causes of drought events, the region has also experienced extremes of above-average rainfall (Washington and Preston, 2006), the most recent examples being the major fooding episodes that devastated Mozambique during 2010 and 2011 when many people were killed and nearly 200 000 people made homeless. Tere is increasing change in high rainfall events in some parts of the southern Africa region (Reason et al., 2014). Te variability of such rainfall can have detrimental consequences for water resources, population and property. Tis variabil- ity can afect the sustainability of major dams and reservoirs due to food risks to the population and properties on the foodplain. Te region’s water resources, agriculture and rural communities are impacted considerably due to high rain- fall variability (Cook et al., 2004). Te remote infuence of El-Niño–Southern Oscillation (ENSO) events has been seen to be contributing to major foods and drought events in southern Africa (Mason and Jury, 1997; Cook, 2000 Reason and Rouault, 2002). Southern African precipitation shows high variability at all timescales (Mason and Jury, 1997). Te proximity of the Agulhas, Benguela, and Antarctic circumpolar currents leads