Agricultural Decision-Making in Indonesia with ENSO Variability: Integrating Climate Science, Risk Assessment, and Policy Analysis

 


Our Team

David Battisti, University of Washington

Rosamond Naylor, Stanford University

Dan Vimont, University of Wisconsin

Walter Falcon, Stanford University


Our project is funded by the Human and Social Dimensions Program at NSF.


 

Overview of the Project

 

In this project, we are show how climate science can be used to inform agricultural decision-making at the policy level. We are focusing on Indonesia, where agricultural production is strongly influenced by the annual cycle of precipitation and by year-to-year variations in the annual cycle caused by El Nino-Southern Oscillation (ENSO) dynamics, and where the combined forces of ENSO and global warming are likely to have dramatic effects on agricultural production and food security.

 

The two main goals of the research are: 1) to project the impacts of global warming on Indonesian agriculture by estimating changes in mean climate and climate variability (i.e., ENSO); and 2) to analyze how these projections (including relevant bands of uncertainty) can be used to inform agricultural decision-making processes. To accomplish the first goal, we developed a set of regional climate scenarios for Indonesia in the mid-21st century. These scenarios are developed using (i) the large-scale climate changes projected from the collection of climate models used in the IPCC process, (ii) select experiments with an atmospheric general circulation model, and (iii) a newly developed downscaling model that links the large-scale circulation to the regional scale climate. These scenarios are then used to assess the influence of global warming on the annual climate cycle and on ENSO-induced changes in precipitation and agricultural production in Indonesia. (The link between projected crop production and climate is established from our previous work). The second goal is accomplished by developing a risk assessment framework that links the probabilities of climate change to its potential consequences on agriculture, taking into account various adaptation measures, such as the development of drought tolerant crop varieties and irrigation investment.

 

The model template we have designed and used in Indonesia for informing the decision making process under conditions of climate uncertainty can be applied to other tropical agricultural countries.