Over the last decade the advance in seasonal forecast product skill has been minimal when considered from the perspective of the user and decision making communities. In response to that, our project seeks to address fundamental questions about the seasonal forecasting of meteorological variables important to society, such as:

  • what are the limits of skill in seasonal forecasting?
  • what are the priority constraints on advancing skill that are not being addressed?
  • which alternative avenues can be developed to address user’s information needs?

Within such defined framework, the project aims to:

  • identify the signal to noise ratio over southern Africa using observations and GCM datasets in response to the forcing of global modes of variability,
  • identify the spatial and temporal time scales of robust regional response to global modes of variability,
    determine how integration of regional responses within hydrological system constrains predictability in the “downstream” direction,
  • understand the theoretical limits to predictability from seasonal forecast models, utilizing ensemble-based prediction techniques in the perfect model scenario,
  • test emergent understanding of how models may be developed to improve forecasts.


Time frames: Research commenced in June 2013 and was finalized in the beginning of 2017.

Funder: Water Research Commission

Partners: UKZN

For further details: Contact Bruce Hewitson