数据同化频率和观测位置对沿海热排放模拟的影响

IF 2.9 3区 地球科学 Q2 ASTRONOMY & ASTROPHYSICS
N. Alsulaiman, M. van Reeuwijk, M. D. Piggott
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引用次数: 0

摘要

本研究探讨了使用集合卡尔曼滤波(EnKF)的数据同化(DA)的应用,以解决与发电厂和海水淡化厂排放到浅水潮汐湾的热废水建模相关的不确定性。利用Delft3D柔性网格套件,开发了科威特Sulaibikhat湾(SB)的二维流体动力学模型,模拟了在主要的半日潮作用下热羽流的传输和扩散。利用OpenDA工具箱进行了一系列观测系统仿真实验,确定了最佳观测位置和数据采集频率。使用EnKF进行状态估计可以显著降低温度预测误差。最佳数据分析频率的特点是能够在保持计算效率的同时保留系统中的分析调整。相对于SB的动态,最佳频率为每小时。发现过大的DA率会引起滤波偏差,由于集合方差的减小,预报误差被错误地低估了。这导致过滤器忽略观测提供的信息。相反,发现DA的稀疏率导致模型恢复到其同化前状态。利用基于集合的目标观测方法,根据其最大限度地减小分析误差方差的能力,确定了最优站点位置。最优位置归因于与其他状态元素表现出强协方差与经历超过规定观测误差方差的局部方差之间的平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of Data Assimilation Frequency and Observation Location in Thermal Effluent Modeling for Coastal Waters

Impact of Data Assimilation Frequency and Observation Location in Thermal Effluent Modeling for Coastal Waters

This study investigates the application of data assimilation (DA) using the Ensemble Kalman Filter (EnKF) to address the uncertainties associated with modeling the thermal effluents discharged from power and desalination plants into a shallow, tidal bay. A two-dimensional hydrodynamic model of Sulaibikhat Bay (SB), Kuwait, was developed using the Delft3D Flexible Mesh Suite to simulate the transport and dispersion of a thermal plume under the forces of predominantly semidiurnal tides. A series of observing system simulation experiments were conducted using the OpenDA toolbox to identify the optimal observation location and DA frequency. Significant reductions in temperature prediction errors were achieved using the EnKF for state estimation. The optimal DA frequency was characterized by its ability to retain the analysis adjustments in the system while maintaining computational efficiency. Relative to the dynamics of SB, the optimal frequency was found to be hourly. An excessive rate of DA was found to cause filter divergence, where forecast error is falsely underestimated due to diminishing ensemble variance. This leads the filter to ignore the information provided by the observations. In contrast, a sparse rate of DA was found to cause the model to revert to its pre-assimilative state. The optimal station locations were identified using the ensemble-based targeted observation method, based on their ability to maximize the reduction of the analysis error variance. The optimal locations were attributed to having a balance between exhibiting strong covariances with the other state elements while experiencing local variance exceeding that of the prescribed observation error variance.

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来源期刊
Earth and Space Science
Earth and Space Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
5.50
自引率
3.20%
发文量
285
审稿时长
19 weeks
期刊介绍: Marking AGU’s second new open access journal in the last 12 months, Earth and Space Science is the only journal that reflects the expansive range of science represented by AGU’s 62,000 members, including all of the Earth, planetary, and space sciences, and related fields in environmental science, geoengineering, space engineering, and biogeochemistry.
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