A Random Field Framework for Boundary Conditions in Numerical Models of Coastal and Ocean Circulation

沿海和海洋环流数值模型中边界条件的随机场框架

• 批准号: 0136700
• 负责人: Toshio Chin
• 金额: $ 36.24万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0136700&HistoricalAwards=false
• 关键词: Random; Field; Framework; Boundary; Conditions

0136700/ChinThis project introduces a novel approach to representing boundary conditions in ocean models. The idea is, absent the ability to follow small-scale physical processes in detail, to represent the influence of these small-scale processes on the larger-scale dynamics resolved by the model by a stochastic process. The project will try several different auto-regressive representations of the boundary conditions and examine how the large-scale structure of the flow reacts to these. The model results will be compared with data from observations near the Florida Current made with HF radar. Using inverse techniques, based on a Markov random field approach, the values of parameters in the stochastic models of boundary conditions will be estimated. The sensitivity of these inversions will also be determined. In larger domains, dynamically similar to the North Atlantic, the question of whether stochastic boundary conditions along the eastern boundary can lead to internal jets (beta plumes) will be studied. Initially, the numerical circulation model will be a reduced-gravity, quasigeostrophic model in idealized geometries. The most effective approaches to stochastic boundary conditions will then be transferred to a primitive-equation OGCM.

0136700/Chin 该项目引入了一种表示海洋模型中边界条件的新颖方法。 这个想法是，在缺乏详细跟踪小规模物理过程的能力的情况下，表示这些小规模过程对模型通过随机过程解决的更大规模动态的影响。 该项目将尝试几种不同的边界条件自回归表示，并研究流动的大规模结构如何对这些表示做出反应。 该模型结果将与高频雷达在佛罗里达海流附近观测到的数据进行比较。 使用基于马尔可夫随机场方法的逆向技术，将估计边界条件随机模型中的参数值。 这些反转的敏感性也将被确定。 在与北大西洋动态相似的较大区域中，将研究沿东部边界的随机边界条件是否会导致内部喷流（β羽流）的问题。 最初，数值环流模型将是理想几何形状的减重准地转模型。 然后，处理随机边界条件的最有效方法将转移到原始方程 OGCM。