Collaborative Proposal: FRG: Statistical Analysis of Uncertainty in Climate Change

提案ID：DMS - 0204232; DMS - 0139948; DMS -0139903 PI：L。作者声明：Richard A.放大图片作者：Christopher K. WikleTitle：联邦德国：气候变化不确定性的统计分析摘要尽管科学界承认在气候变化的形式、水平和影响方面存在很大的不确定性，但科学家们越来越一致地认为，由于人类的影响，我们星球的气候正在发生变化。量化这些不确定性需要新的统计研究提供气候科学的信息。气候变化问题的有效解决办法将依赖于以量化管理不确定性的方式将模型和数据的信息内容结合起来的新方法。研究团队将广泛依赖贝叶斯分层建模和分析策略。具体项目包括：（1）在广泛的气候模拟基础上开发新的概率气候变化评估;（2）结合不同气候模式进行气候预测的统计程序;（3）评估全球气候行为对区域和地方的影响。描述地球气候并预测其对人类影响的反应是科学和公共政策中的关键问题。来自国家大气研究中心的统计学家和气候建模专家组成的研究小组将开发新的统计策略，将联合收割机观测结果与气候系统计算机模型中的信息结合起来，同时管理两者中隐含的不确定性。评估气候变化对环境和人类活动的潜在影响也充满了不确定性。该研究小组将制定综合方法，预测气候对区域和地方现象的影响。这些方法将用于预测厄尔尼诺-南方涛动和美国中部龙卷风发生的特性。

Proposal Ids: DMS - 0204232; DMS - 0139948; DMS - 0139903PIs: L. Mark Berliner; Richard A. Levine; Christopher K. WikleTitle: FRG: Statistical Analysis of Uncertainty in Climate ChangeABSTRACTThere is a growing consensus among scientists that aspects of our planet's climate are changing due to human influences, though the scientific community acknowledges that substantial uncertainty exists regarding the forms, levels, and impacts of change. Quantifying these uncertainties requires new statistical research informed by climate science. Effective solutions to climate change problems will rely on new methods for combining the information content of models and data in a fashion that quantitatively manages uncertainty. The research team will rely extensively on Bayesian hierarchical modeling and analysis strategies. Specific projects will include (1) developing new probabilistic climate change assessments based on an extensive suite of climate simulations; (2) statistical procedures for combining different climate models to produce climate projections; and (3) assessing regional and local impacts of global climate behavior.Describing the Earth's climate and predicting its responses to human influences are critical problems in science and public policy. The research team of statisticians and climate modeling experts from the National Center for Atmospheric Research will develop new statistical strategies that combine observations with the information present in computer models for the climate system, while managing the uncertainties implicit in both. Assessing potential impacts of climate change on the environment and human activities is also fraught with uncertainty. The research team will develop integrated methods for predicting climate impacts on regional and local phenomena. These methods will be applied in predicting the El Nino-Southern Oscillation and properties of tornado occurrence in the Central United States.