Abstract:
Seasonal-to-interannual variations of rainfall over southern Africa, key to predicting
extreme climatic events, are predictable over certain regions and during specific periods
of the year. This predictability had been established by testing seasonal forecasts from
models of varying complexity against official station rainfall records typically managed
by weather services, as well as against gridded data sets compiled through a range of
efforts. Members of the general public, including farmers, additionally have extended
records of rainfall data, often as daily values spanning several decades, which are
recorded and updated regularly at their farms and properties. In this paper, we show
how seasonal forecast modelers may use site recorded farm rainfall records for the
development of skillful forecast systems specific to the farm. Although the uptake of
seasonal forecasts in areas with modest predictability such as southern Africa may
be challenging, we will show that there is potential for financial gain and improved
disaster risk farm management by co-developing with farmers forecast systems based
on a combination of state-of-the-art climate models and farm rainfall data. This study
investigates the predictability of seasonal rainfall extremes at five commercial farms in
southern Africa, four of which are in the austral summer rainfall areas, while one is
located in the winter rainfall area of the southwestern Cape. We furthermore calculate a
measure of cumulative profits at each farm, assuming a “fair odds” return on investments
made according to forecast probabilities. The farmers are presented with hindcasts
(re-forecasts) at their farms, and potential financial implications if the hindcasts were used
in decision-making. They subsequently described how they would use forecasts for their
farm, based on their own data.
