用集合卡尔曼滤波估计爪哇岛南部海岸的潮高

Shaffiani Nurul Fajar, E. Apriliani, E. Y. Handoko
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引用次数: 0

摘要

潮汐是值得讨论的重要问题,尤其是对印度尼西亚这样的海洋国家。潮汐观测的主要目的是确定海岸的潮汐高度。本文将数据同化方法——集合卡尔曼滤波(Ensemble Kalman Filter, EnKF)应用于潮汐估计。本研究地点位于爪哇岛南部海岸,位于Cilacap潮汐站和Pacitan潮汐站之间。通过确定具体网格,可以得到另一个潮站的潮高值。在估计过程中,测量数据用于校正步骤。模拟结果表明,在100个集合下,EnKF与潮站实测数据的平均误差为2,4535 cm,约为0,2113%。由于模拟结果误差值较小,因此可以得到潮汐站另一点的潮高值。因此,可以得到的信息是,波浪的最高高度和最低高度不是发生在回历的月初、月末和月中。但是在那个时候发生的波幅很大。因此,在振幅较大的情况下,可以同时产生高、低波。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tide Height Estimation on Southern Coast of Java Island by Ensemble Kalman Filter
Tide is important things to discuss, especially for maritime countries such as Indonesia. The main purpose of tide observations is to determine the tide height on coast. In this study, data assimilation method, Ensemble Kalman Filter (EnKF), is applied to tide estimation. The location of this study is on the southern coast of Java Island which is located between Cilacap's tide station and Pacitan's tide station. The value of tide height on another tide station can be obtained with determination specific grid. In the estimation process, measurement data is used in correction step. Based on the results of simulation, the average error between EnKF and the measurement data from tide stations is 2,4535 cm or about 0,2113% with 100 ensemble. Because the simulation results show small error value, the value of tide height at the other point of tide station can be obtained. Therefore, it can be obtained information that not the highest or lowest height of the wave that occurred at the beginning, the end and the middle of the month in Hijri calendar. But the large amplitude of wave that happened at that time. So with a large amplitude, high and low waves can be generated at once.
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