The project showed that translating relatively recent ENSO knowledge into useful information for managing risks and opportunities associated with climate variability is a challenge for traditional agricultural research and extension. Researchers improved the skill and value of forecasting, increased the lead time for prediction, identified the key decisions and practices in the farming cycle to which forecast information may be applied, and communicated information in a risk-management context.
The project made important contributions to increasing the understanding of ENSO in Indonesia, where the impact is as great as anywhere in the world. A key finding was that the changing seasonal pattern of spatial coherence of rainfall correlated with predictions. Badan Meteorologi dan Geofisika (the Indonesian Bureau of Meteorology) has added this knowledge to its program for compiling seasonal forecasts.
A publication 'Will it rain?' was produced in Indonesian and is an important means of communicating the state of the science. Decision-support tools developed for Lombok, Indonesia will assist analysis of stream flows and optimise water allocation decisions.
The development of an international RAINMAN version led to excellent progress in assembling a global database of monthly rainfall and some other data sets. Outputs for India and Zimbabwe have significantly increased understanding, particularly through use of simulation models to show amplified impacts on agricultural systems compared with ENSO impacts on seasonal rainfall.
A highlight was the successful calibration and validation of the GRASP pasture simulation model for Zimbabwe pastures. And in Tamil Nadu, India, scientists have assessed seasonal climate forecasts through farm surveys and workshops, and undertaken analyses using crop simulation models.
The project outcomes should lead to changes in farm management decisions, to better adapt farming to climate variability, and to prepare for climate change.