Seasonal rainfall predictability over the Lake Kariba catchment area

Authors

  • Shepherd Muchuru Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa
  • Willem A Landman 1. Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa; 2. Council for Scientific and Industrial Research, Natural Resources and the Environment, Pretoria, South Africa
  • David DeWitt International Research Institute for Climate and Society, Columbia University, Palisades, New York, USA
  • Daleen Lötter Council for Scientific and Industrial Research, Natural Resources and the Environment, Pretoria, South Africa

DOI:

https://doi.org/10.4314/wsa.v40i3.9

Keywords:

Lake Kariba catchment, coupled ocean-atmosphere model, statistical downscaling, seasonal forecasting, economic value

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. 

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Published

2025-03-30

Issue

Section

Research paper

How to Cite

Shepherd Muchuru (2025) “Seasonal rainfall predictability over the Lake Kariba catchment area”, Water SA, 40(3 July). doi:10.4314/wsa.v40i3.9.