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Application of seasonal forecasts in agriculture has significant potential and realized utility. Other sectors that may also benefit from using seasonal forecasts include (but are not limited to) health, hydrology, water, and energy. This paper shows that seasonal forecast model data, satellite Pour l'Observation de la Terre (SPOT), dry matter productivity (DMP) data (proxy of grass biomass) along with other sets of data are effectively used to estimate grazing capacity (GC) over a 12-year test period (1998/1999–2009/2010) in Limpopo Province. GC comprises a vital consideration in agricultural activities, particularly for a province in South Africa like Limpopo, due to its varying climate. The Limpopo Province capitalizes on subsistence farming, including livestock and crop production. Grazing should thus be regulated in order to conserve grass, shrubs, and trees, thereby ensuring sustainability of rangelands. In a statistical downscaling model, the predictor is the 850 geopotential height fields of a coupled ocean–atmosphere general circulation (CGCM) over Southern Africa to predict seasonal DMP values. This model shows that the mid-summer rainfall totals are important predictors for the November through April (NDJFMA) DMP (as well as grazing capacity) growing season. Forecast verification is conducted using the relative operating characteristics (ROC) and reliability diagrams. The CGCM model shows skill in discriminating high and low DMP (GC) seasons in the Limpopo Province, as well as reliability in the probabilistic forecasts. This paper demonstrates the development of a tailored forecast, an avenue that should be explored in enhancing relevance of forecasts in agricultural production. [ABSTRACT FROM AUTHOR]

During strong El Niño events, below-average rainfall is expected in large parts of southern Africa. The 1992 El Niño season was associated with one of the worst drought episodes in large parts of South Africa. Using reanalysis data set from NCEP-NCAR, this study examined circulation types (CTs) in Africa south of the equator that are statistically related to the El Niño signal in the southwest Indian Ocean and the implication of this relationship during the 1992 drought episode in South Africa. A statistically significant correlation was found between the above-average Nino 3.4 index and a CT that features widespread cyclonic activity in the tropical southwest Indian Ocean, coupled with a weaker state of the south Indian Ocean high-pressure. During the analysis period, it was found that the El Niño signal enhanced the amplitude of the aforementioned CT. The impacts of the El Niño signal on CTs in southern Africa, which could have contributed to the 1992 severe drought episode in South Africa, were reflected in (i) robust decrease in the frequency of occurrence of the austral summer climatology pattern of atmospheric circulation that favors southeasterly moisture fluxes, advected by the South Indian Ocean high-pressure; (ii) modulation of easterly moisture fluxes, advected by the South Atlantic Ocean high-pressure, ridging south of South Africa; (iii) and enhancement of the amplitude of CTs that both enhances subsidence over South Africa, and associated with the dominance of westerlies across the Agulhas current. Under the ssp585 scenario, the analyzed climate models suggested that the impact of radiative heating on the CT significantly related to El Niño might result in an anomalous increase in surface pressure at the eastern parts of South Africa. [ABSTRACT FROM AUTHOR]