The impact of ENSO on South Africa
Although the southern part of Africa generally receives below-normal rainfall during El Nino years and La Nina usually brings normal or above-normal rainfall, it cannot be accepted as a rule. Southern Africa can be divided into numerous rainfall regions, each region having a different correlation with ENSO. Also, ENSO explains only approximately 30% of the rainfall variability, which means that other factors should also be taken into account when predicting seasonal rainfall. For example: The 1997-98 El Nino was the strongest on record, but not all of South Africa received below-normal rainfall. Some regions had an abundance of rain because of moist air that was imported from the Indian Ocean. One should be careful not to make a general rule for rainfall and temperature changes in ENSO years over southern Africa.
Does El Nino always cause drought in South Africa?
No. Although most El Nino years have been associated with below-normal rainfall, the impact of El Nino is often reduced by the sufficient groundwater and soil moisture content carried over from previous seasons.
Can ENSO be forecast?
Yes. SSTs are used to measure the state of the ocean (and ENSO) and can be forecast up to 9 months ahead with good skill. Computer models are used for this and the first indication of ENSO influencing the October-to-March (summer) rainfall season can be forecast as early as the preceding May. IMPORTANT: An El Nino/La Nina forecast is NOT a rainfall forecast.
If you would like to know more about ENSO please follow these links to other ENSO sites:
Anomaly: The deviation from the mean. To calculate SST anomalies, the long-term mean for a specific point in the ocean is subtracted from the current value. A negative value indicates that the current value is cooler (smaller) than usual, while a positive value indicates that the current value is warmer (larger) than usual.
For example: The Nino 3.4 value for December 2003 is 26.9 °C. The long-term mean for the Nino 3.4 region is 26.5 °C
Anomaly = current value – mean
Anomaly = 26.9 °C - 26.5 °C = 0.4 °C