Agricultural production in Indonesia is strongly influenced by the annual cycle of precipitation and the year-to-year variations in the annual cycle of precipitation caused by El Nino-Southern Oscillation (ENSO) dynamics. The combined forces of ENSO and global warming are likely to have dramatic, and currently unforeseen, effects on agriculture production and food security in Indonesia and other tropical countries.

This project uses a combination of general circulation model (GCM) experiments and empirical downscaling models (EDMs) to assess the influence of global warming on the annual cycle of precipitation, and on ENSO-induced changes in precipitation and agricultural production in Indonesia. We then apply a risk assessment framework to evaluate how climate-related uncertainty and probable agricultural outcomes derived from the downscaling model can be used in policy decision-making processes. The models will focus on rice, the country's primary food staple.

The intellectual merit of this project is based on its interdisciplinary and integrated design. To date, climate models have been developed with little knowledge of agricultural system dynamics, and agricultural policy analysis has been conducted with little knowledge of climate dynamics. The integration proposed here will permit an assessment of climate-related uncertainty associated with global warming and ENSO dynamics. It will also demonstrate how the treatment of uncertainty affects the choice and consequences of agricultural policies.

The innovative and integrated set of models developed here will have broad impacts both on interdisciplinary educational programs and on policy formulation. Existing institutional arrangements in Indonesia will facilitate the use of these tools in short- and long- run decision-making processes. Once developed, these tools can be applied in other countries where ENSO affects regional climate, and where regional vulnerabilities contribute to national economic instability.