U.S.-Australian Cooperative Research: Climate Prediction Design for Agricultural Production

该奖项将支持博士之间的合作研究。 伊利诺伊大学/州水资源调查局的Peter Lamb 司和澳大利亚卫生局的内维尔·尼科尔斯博士 气象学研究中心。这项研究是为了扩大和 扩大伊利诺伊大学/州立水资源调查研究 与生长季节气候设计有关的程序 对中西部农业的预测在这个合作社 项目，美国的努力将扩大到解决 高粱生产气候预测设计问题 在澳大利亚东北部。这项新研究将提高 开发的广泛的经济建模能力， 美国中西部工作它还将试图利用 气候预测技术，即 厄尔尼诺现象的强烈控制所固有的， 振荡（ENSO）现象对澳大利亚东北部产生影响 降雨该项目将提供一个关于成果的视角 到达美国中西部（那里的生长季节 气候更难预测），提供更好的理解 目前可实现的气候预测的价值 技能，为设计和评估 澳大利亚其他部门的气候预测系统 农业，以及发展中国家， 季节性降水受ENSO强烈控制。 该项目代表了出色的合作， 澳大利亚大气科学家的专业知识和澳大利亚 基于南方涛动（SO）的季节性降雨数据 凭借广泛的经济建模能力， 美国研究团队。这是一项重要的基础工作， 气候预测设计研究，以及 提高农业生产力的潜力。

This award will support collaborative research between Dr. Peter Lamb of the University of Illinois/State Water Survey Division and Dr. Neville Nicholls of the Australian Bureau of Meterorology Research Centre. This research is to extend and broaden a University of Illinois/State Water Survey research program concerned with the design of growing season climate predictions for midwestern agriculture. In this cooperative project, the U.S. effort will be extended to address the climate prediction design issue for grain sorghum production in northeastern Australia. This new research will enhance the extensive economic modeling capabilities developed by the U.S. midwestern work. It will also attempt to exploit the substantial growing season climate prediction skill that is inherent in the strong control that the El Nino-Southern Oscillation (ENSO) phenomenon exerts on northeastern Australian rainfall. The project will provide a perspective on results reached for the U.S. Midwest (where the growing season climate is less predictable), furnish a better understanding of the value of currently achievable climate prediction skill, provide a modus operandi for designing and valuing climate prediction systems for other sectors of Australian agriculture, as well as for developing nations whose growing season rainfall is strongly controlled by ENSO. The project represents excellent collaboration in combining Australian atmospheric scientist expertise and Australian data on Southern Oscillation (SO)-based seasonal rainfall with the extensive economic modeling capabilities of the U.S.research team. This is important fundamental work on climate prediction design research, as well as having potential for improving agricultural productivity.