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Abstract
The 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 fluctuations in rainfall are a significant 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 fields) of a coupled ocean-atmosphere general circulation model (CGCM) over southern Africa, statistically downscaled to gridded seasonal rainfall totals over the catchment. This downscaling configuration 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 25th and 75th percentile values of the climatological record. The verification 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. This 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 verification 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
Highlights
Southern Africa is a region of significant rainfall variability at a range of temporal and spatial scales and is prone to serious drought and flood events (e.g. Tyson, 1986); Nicholson et al, 1987; Lindesay, 1998; Reason et al, 2000)
This study focuses on the Lake Kariba catchment since rainfall over this area is directly responsible for the water levels in the lake
The archived data of the general circulation model and gridded rainfall data We investigated the predictability of 3-month seasonal rainfall totals over the Kariba catchment during the rainy season from September through April, by statistically downscaling the archived output of a state-of-the-art coupled ocean-atmosphere general circulation model (CGCM)
Summary
Southern Africa is a region of significant rainfall variability at a range of temporal and spatial scales and is prone to serious drought and flood events (e.g. Tyson, 1986); Nicholson et al, 1987; Lindesay, 1998; Reason et al, 2000). Despite the diverse climatic zones, rainfall in southern Africa is mainly observed during the austral summer between October and May. The future spatial and temporal rainfall distribution and variability is uncertain (Gordon et al, 2000; Hachingonta et al, 2007). 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 gradients. This is caused by differential solar heating between the equator and the mid-latitudes. Much of the recent climate research has focused on the causes of drought events, the region has experienced extremes of above-average rainfall (Washington and Preston, 2006), the most recent examples being the major flooding episodes that devastated Mozambique during 2010 and 2011 when many people were killed and nearly 200 000 people made homeless
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