Data Assimilation in a Strongly Nonlinear Ocean Model

提案编号：0137169PI：R.Miller，OSU将使用正压和斜压准地转模式解的动力系统分析来研究控制黑潮许多路径的物理。动力系统工具将用于确定黑潮在日本海岸外路径的模型模拟的定性性质。斜压准地转区模式及其伴随模式将与以往模式研究中已有的解进行比较。预计正压和斜压系统的分叉图将是相似的，但解将表现出显着的斜压效应。斜压准地转模式的伴随将被用来研究模式对不同类型扰动的敏感性，并确定在不同的小曲折和大曲折情况下观测同化对模式预报的影响。数据同化研究还将有助于确定哪些观测预测了从一个状态到另一个状态的转变。此外，研究的这一部分将有助于区分不同物理在不同模型中代表系统自然可变性的充分性。这项研究将有助于更好地了解日本近海的黑潮系统，以及产生黑潮双峰性的不同物理机制，并有可能为捕捉该系统行为的关键观测集提供指导。

Proposal Number: 0137169PI: R. Miller, OSUThe physics governing the many paths of the Kuroshio will be investigated using dynamical systems analysis of barotropic and baroclinic quasigeostrophic model solutions. The dynamical systems tools will be used to determine the qualitative nature of model simulations of the Kuroshio's path off the coast of Japan. A baroclinic quasigeostrophic regional model and its adjoint will be used comparatively with existing solutions from previous model studies. It is expected that the bifurcation diagram will be similar between the barotropic and baroclinic systems but that the solutions will exhibit significant baroclinic effects. The adjoint of the baroclinic quasigeostrophic model will be used to investigate the sensitivity of the model to different types of perturbations and to determine the influence of assimilation of observations on the model predictions in each different small and large meander case. The data assimilation study will also help determine which observations predict the transition from one state to another. In addition, this portion of the study will help discriminate between the adequacies of different physics in different models for representing the natural variability of the system. This study will lead to a better understanding of the Kuroshio system off Japan, the different physical mechanisms that generate bimodality of the Kuroshio, and it has the potential to yield guidance towards the critical set of observations that capture the behavior of the system.