Impact of Instantaneous Parameter Sensitivity on Ensemble-Based Parameter Estimation: Simulation With an Intermediate Coupled Model

IF 4.4 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Advances in Modeling Earth Systems Pub Date : 2024-08-28 DOI:10.1029/2024MS004253
Lige Cao, Guijun Han, Wei Li, Haowen Wu, Xiaobo Wu, Gongfu Zhou, Qingyu Zheng
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Abstract

On ensemble-based coupled data assimilation, cross-component parameter estimation (CPE), has not been as extensively developed and applied as weakly coupled state and parameter estimation along with cross-component state estimation. This discrepancy is partially attributed to the lack of emphasis on the instantaneous response of coupled model states with respect to parameters across different components. We define so-called response as the instantaneous parameter sensitivity (IPS). Under the framework of sequential assimilation, the prior information heavily relies on the IPS of coupled states with different time scales. Based on the IPS analysis for an intermediate coupled model, a series of twin experiments of state and parameter estimation are conducted, in which an IPS-inspired adaptive inflation scheme for parameter ensemble is introduced. Results show that the success of a parameter estimation strategy is closely tied to the significant IPS of the observed state to the parameter targeted for optimization, as it maintains a high signal-to-noise ratio in the error covariance between parameter and prior state, thereby enhancing parameter estimation. An interesting finding in the context of IPS-based CPE is: an atmospheric parameter can be successfully estimated by assimilating observations from slow-varying oceanic component, but not vice versa. In comparison with cross-component state estimation, successful CPE significantly enhances the estimation accuracy of coupled states by mitigating model bias.

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瞬时参数敏感性对基于集合的参数估计的影响:中间耦合模型模拟
在基于集合的耦合数据同化方面,跨分量参数估计(CPE)并没有像弱耦合状态和参数估计以及跨分量状态估计那样得到广泛的发展和应用。造成这种差异的部分原因是没有重视耦合模式状态对不同成分参数的瞬时响应。我们将所谓的响应定义为瞬时参数灵敏度(IPS)。在序列同化框架下,先验信息主要依赖于不同时间尺度耦合状态的 IPS。在对中间耦合模型进行 IPS 分析的基础上,进行了一系列状态和参数估计的孪生实验,其中引入了一种受 IPS 启发的参数集合自适应膨胀方案。结果表明,参数估计策略的成功与观测状态与优化目标参数的显著 IPS 密切相关,因为它能保持参数与先验状态之间误差协方差的高信噪比,从而增强参数估计。基于 IPS 的 CPE 的一个有趣发现是:通过同化变化缓慢的海洋分量的观测数据,可以成功地估算出大气参数,但反之亦然。与跨分量状态估计相比,成功的 CPE 可通过减轻模型偏差来显著提高耦合状态的估计精度。
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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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