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

这一人类和社会动力优先领域项目涉及一种跨学科研究方法，以便在面临与气候有关的不确定性的情况下为农业决策提供信息。研究将侧重于印度尼西亚，那里的农业生产受到年度降水周期和厄尔尼诺-南方涛动(ENSO)动态引起的年度周期年际变化的强烈影响。该项目将结合大气环流模式实验和缩小尺度模式来评估全球变暖对印度尼西亚年度气候循环以及ENSO引起的降水和农业生产变化的影响。这些模型实验将为印度尼西亚在21世纪中叶产生一套区域气候情景，用于决策分析。预计的作物产量和产量不确定性将通过回归分析从气候情景中得出。然后将制定一个风险评估框架，将气候变化的可能性与其潜在后果联系起来，并展示适应措施，如开发耐旱作物品种和灌溉投资，如何改变潜在损害的程度。这项研究的两个主要目标是：i)通过平均气候和气候变率(即ENSO)的变化来预测全球变暖对印度尼西亚农业的影响；以及ii)分析如何利用这些预测(包括相关的不确定性范围)为农业决策过程提供信息。该项目的智力优势是基于其跨学科和综合设计：迄今为止，气候模型的开发几乎不了解农业系统动力学，农业政策分析也几乎不了解气候动力学。该项目的教育价值是基于对所有参与大学的跨学科和学科研究生项目的学生的培训和教学模式的发展。该项目的实际价值源于这样一个事实，即ENSO和全球变暖的合力很可能对印度尼西亚和其他热带国家的农业生产和粮食安全产生巨大的、目前无法预见的影响。一旦模型模板在印度尼西亚设计、验证和使用，它就可以应用于其他热带农业国家。

This Human and Social Dynamics Priority Area project involves an interdisciplinary research approach to informing agricultural decision-making in the face of climate-related uncertainty. The research will focus 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. The project will use a combination of general circulation model experiments and downscaling models to assess the influence of global warming on the annual climate cycle and on ENSO-induced changes in precipitation and agricultural production in Indonesia. These model experiments will result in a set of regional climate scenarios for Indonesia in the mid-21st century that will be used for decision analysis. Projected crop production and production uncertainty will be derived from the climate scenarios using regression analysis. A risk assessment framework will then be developed to link the probabilities of climate change to its potential consequences, and to show how adaptation measures, such as the development of drought tolerant crop varieties and irrigation investment, could alter the magnitude of potential damages.The two main goals of the research are: i) to project the impacts of global warming on Indonesian agriculture by means of changes in mean climate and climate variability (i.e., ENSO); and ii) to analyze how these projections (including relevant bands of uncertainty) can be used to inform agricultural decision-making processes. 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 educational merit of the project is based on the training of students from interdisciplinary and disciplinary graduate programs at all of the participating universities and the development of teaching models. The practical merit of the project stems from the fact that the combined forces of ENSO and global warming are likely to have dramatic, and currently unforeseen, effects on agricultural production and food security in Indonesia and other tropical countries. Once the model template is designed, validated, and used in Indonesia, it can be applied to other tropical agricultural countries.