Collaborative Research: A Pilot Study of Simultaneous Parameter and State Estimation in Coupled Ocean-Atmosphere General Circulation Models Using the Ensemble Kalman Filter

合作研究：使用集合卡尔曼滤波器同时估计海洋-大气环流耦合模型参数和状态的初步研究

• 批准号: 0968383
• 负责人: Zhengyu Liu
• 金额: $ 50.99万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968383&HistoricalAwards=false
• 关键词: Collaborative; Research; Pilot; Study; Simultaneous

Ocean Atmosphere General Circulation Models (OAGCM) exhibit significant model biases, e.g., the tropical bias in the Intertropical Convergence Zone cold tongue complex. A significant part of such biases is due to uncertainties in the model parameters. Thus far, however, parameter tuning in OAGCMs remains rudimentary. This collaborative project will develop a novel strategy for systematic parameter optimization in OAGCMs, using an ensemble based data assimilation strategy, focusing on the outstanding tropical bias problem. Building on an existing coupled data assimilation system, an adaptive coupled ensemble Kalman Filter system (AcEnKF) for a simultaneous estimation of model parameter and state, will be developed. Different assimilation techniques to search for an effective method of parameter optimization in OAGCMs will be studied, as also coupled dynamics relevant to parameter optimization in the tropical climate system for both the climatology and climate variability. The work is expected to give the first comprehensive evaluation of the ensemble based strategy for parameter optimization in OAGCMs. The study will also shed light on the mechanism of the coupled dynamics of the tropical climate system and its sensitivity to model parameters. In spite of potential difficulties, this pilot study represents a significant step forward in the improvement of OAGCMs. This activity has significant broader impacts: it will lay a foundation for a systematic improvement of OAGCMs and, more generally, future coupled earth system models.

海洋大气环流模型（OAGCM）表现出显着的模型偏差，例如热带辐合带冷舌复合体中的热带偏差。这种偏差的很大一部分是由于模型参数的不确定性造成的。然而到目前为止，OAGCM 中的参数调整仍然处于初级阶段。该合作项目将使用基于集合的数据同化策略，开发一种新的 OAGCM 系统参数优化策略，重点关注突出的热带偏差问题。在现有耦合数据同化系统的基础上，将开发用于同时估计模型参数和状态的自适应耦合集成卡尔曼滤波器系统（AcEnKF）。将研究用于寻找 OAGCM 参数优化的有效方法的不同同化技术，以及与热带气候系统中气候学和气候变率参数优化相关的耦合动力学。这项工作预计将对 OAGCM 中基于集成的参数优化策略进行首次全面评估。该研究还将揭示热带气候系统耦合动力学机制及其对模型参数的敏感性。尽管存在潜在的困难，这项试点研究代表着 OAGCM 改进方面向前迈出了重要一步。这项活动具有更广泛的影响：它将为 OAGCM 的系统改进以及更广泛的未来耦合地球系统模型奠定基础。