Collaborative Research: RNMS Statistical methods for atmospheric and oceanic sciences

STATMOS（大气与海洋科学统计方法）该奖项支持一个数学科学研究网络。气候科学领域最近发生的事件突出表明，需要增加统计学家的参与。数学在流体动力学建模中起着重要的作用，而统计学专门用于量化不确定性。该项目的目标是建立一个对大气和海洋科学感兴趣的统计学家网络。网络的中心（和一些节点）既有统计人员，也有大气和海洋科学人员；国家大气研究中心是一个与每个节点相连的公共节点。该网络还将与太平洋西北地区和欧洲的类似网络连接，并将为决策者提供必要的研究，以便根据对不确定性的准确评估作出明智的决定。在科学上，网络节点之间的交流将有助于培养一批年轻的研究人员，包括本科生和研究生，他们能够跨学科工作，开发相关的方法并将其应用于重要的科学问题。处于职业生涯早期阶段的学生将有效地融入统计和科学界。这将有助于他们在研究多学科问题的统计学家社区中建立一个网络。本项目的研究课题涉及面广，一个共同的主题是描述变化世界所需的多元非平稳非高斯时空模型。网络研究人员将研究空间和时间上的极端事件，将开发将模型与数据进行比较的方法，将对基于情景的气候预测进行不确定性评估，并将产生有效的计算方法来处理来自观测和数值模型的大量数据。网络进行的研究和教学的特殊结合将确保小组产生的知识将立即传递给研究生。STATMOS研究网络主页：http://www.nrcse.washington.edu/statmos/

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/