Collaborative Research: CMG: Ocean Circulation Climatology and Dynamics Using Bayesian Hierarchical Methods

这个项目是一个应用现代贝叶斯分层统计分析方法的问题，海洋状态估计。 目标是利用这种统计技术，结合联合收割机水文数据、动力学约束以及关于观测和动力学假设中的不确定性的知识，得出：（a）北大西洋选定等密度线上海洋特性场的缓慢变化图，（B）与现有数据一致的北大西洋环流可能状态的概率分布函数估计。 该项目将统计学家和海洋科学家联合起来，为一名研究生和两名博士后研究人员提供跨学科研究方面的培训。

This project is an application of modern Bayesian hierarchical methods of statistical analysis to the problem of ocean state estimation. The goal is to use this statistical technique to combine hydrographic data, dynamical constraints, and knowledge about the uncertainties in both observations and dynamical assumptions, to arrive at: (a) slowly varying maps of oceanic property fields on a selection of isopycnals in the North Atlantic, (b) an estimate of the probability distribution function for possible states of the North Atlantic circulation consistent with the available data. The project unites statisticians and ocean scientists and provides training in interdisciplinary research for a graduate student and two post-doctoral researchers.