Collaborative Research: RNMS: Statistical Methods for Atmospheric and Oceanic Sciences

合作研究：RNMS：大气和海洋科学统计方法

• 批准号: 1106974
• 负责人: Michael Stein
• 金额: $ 111.86万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1106974&HistoricalAwards=false
• 关键词: Collaborative; Research; RNMS; Statistical; Methods

STATMOS (STatistical methods for ATMospheric and Oceanic Sciences)This award supports a Research Network in the Mathematical Sciences. Recent events in climate science have highlighted the need for increased participation of statisticians. While mathematics plays an important role in modeling fluid dynamics, statistics specializes in quantifying uncertainty. The objective of this project is to build a network of statisticians with interest in atmospheric and ocean science. The hubs of the network (and some nodes) have personnel both in statistics and in atmospheric and ocean science; the National Center for Atmospheric Research is a common node connected to each of the nodes. The network will also connect with similar networks in the Pacific Northwest and in Europe, and will provide the research necessary for decision makers to make informed decisions, based on accurate assessment of uncertainty. Scientifically, the exchanges between the nodes of the network will help foster a cadre of young researchers, including both undergraduate and graduate students, able to work across disciplines, developing relevant methodologies and applying them to important scientific problems. Students at early stages in their careers will get effectively integrated in the statistical and scientific community. This will help them to build a network in the community of statisticians working on multidisciplinary problems. The research topics of this project cover broad areas, with a common theme being multivariate nonstationary non-Gaussian spatio-temporal models, which are needed to describe a changing world. Network researchers will study extreme events in space and time, will develop methods to compare models to data, will make uncertainty assessments for scenario-based climate projections, and will produce computationally efficient ways to deal with large amounts of data from observations and numerical models. The particular combination of research and teaching carried out by the network will ensure that the knowledge generated by the group will immediately be transmitted to graduate students.STATMOS Research Network home page: http://www.nrcse.washington.edu/statmos/

STATMO（大气和海洋科学的统计方法）该奖项支持数学科学中的研究网络。 气候科学的最新事件强调了统计学家参与的必要性。虽然数学在建模流体动力学中起着重要作用，但统计数据专门量化不确定性。 该项目的目的是建立一个对大气和海洋科学兴趣的统计学家网络。网络的枢纽（以及一些节点）都有统计和大气和海洋科学领域的人员；国家大气研究中心是连接到每个节点的通用节点。该网络还将与太平洋西北和欧洲的类似网络联系，并根据对不确定性的准确评估，为决策者提供了必要的研究，以做出明智的决策。从科学上讲，网络节点之间的交流将有助于培养包括本科和研究生在内的年轻研究人员的干部，能够跨学科工作，开发相关方法论并将其应用于重要的科学问题。在职业生涯的早期阶段的学生将有效地融入统计和科学界。这将帮助他们在从事多学科问题的统计学家社区中建立网络。该项目的研究主题涵盖了广泛的领域，一个共同的主题是多元非组织的非高斯时空模型，这些模型是描述不断变化的世界所需的。网络研究人员将研究时空中的极端事件，将开发将模型与数据进行比较的方法，将对基于场景的气候预测进行不确定性评估，并将产生计算上有效的方法来处理来自观察和数值模型的大量数据。网络进行的研究和教学的特殊组合将确保小组产生的知识会立即传输给研究生。STATMOS研究网络主页：http：//www.nrcse.washing.washington.edu/statmos/