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Generation of Hudson River Tidal Datums Using a Hybrid Data Assimilation Method

机译:使用混合数据同化方法生成哈德逊河潮汐基准

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摘要

A hybrid data assimilation (H-DA) method is introduced and applied to the calculation of tidal datums for the tidal Hudson River. The hybrid method is a combination of Newtonian Relaxation (nudging), integrated into the physics of a numerical hydrodynamic code, and error interpolation. It takes better advantage of available observed water level data along the Hudson River compared to previous methods that have been applied to the area.;Observed water level data at 4 observation stations along the Hudson River were used for data assimilation. Errors at the observation stations were interpolated to synthetic stations at multiple intermediate locations without observed water level data in order to more effectively nudge a high-resolution barotropic two-dimensional hydrodynamic model. Multiple configurations were tested and compared with free model results (without H-DA) to quantify improvements in the simulated water level time series after H-DA against independent observation records.;The H-DA model results were then used to calculate tidal datum maps over the entire tidal Hudson River. The new datums were verified against tidal datums calculated using historical water level data at 12 observation stations. Compared to the free model, the model with data assimilation greatly improved the tidal datum result. RMS Error for MSL, MHHW, MHW, MLW and MLLW decreased by 65-75%, while RMSE for DTL and MTL decreased by 28% and 50%, respectively.;Compared to preexisting and spatially more limited Hudson River datums (NOAA VDatum), H-DA resulted in improved RMSE for MSL, MHHW, MHW, DTL and MTL over VDatum's domain. RMSE for MLW and MLLW did not improve but where within 1cm of the corresponding VDatum. Finally, compared to our previous study in which a three-dimensional diagnostic rendition of the same numerical model was applied to the Hudson River to improve VDatum results, the faster two-dimensional model with H-DA improved all calculated tidal datums except for MLLW, for which RMSE was greater by 0.7cm.
机译:介绍了一种混合数据同化(H-DA)方法,并将其应用于潮汐哈德逊河的潮汐基准。混合方法是将牛顿松弛(微分),数字流体力学代码的物理特性和误差插值结合在一起的方法。与该地区以前的方法相比,它更好地利用了沿哈德逊河沿岸的可用观测水位数据。;将沿哈德逊河沿岸4个观测站的观测水位数据用于数据同化。观测站的误差被内插到多个中间位置的合成站,而没有观测到的水位数据,以便更有效地推算高分辨率正压二维水动力模型。测试了多种配置,并与自由模型结果(无H-DA)进行了比较,以量化H-DA对独立观察记录后模拟水位时间序列的改进;然后将H-DA模型结果用于计算潮汐基准图在整个哈德逊河上。对照在12个观测站使用历史水位数据计算出的潮汐数据验证了新数据。与自由模型相比,具有数据同化的模型大大改善了潮汐基准结果。 MSL,MHHW,MHW,MLW和MLLW的RMS误差分别降低了65-75%,而DTL和MTL的RMSE分别降低了28%和50%。 ,H-DA改善了VDatum范围内MSL,MHHW,MHW,DTL和MTL的RMSE。 MLW和MLLW的RMSE并未提高,但在相应VDatum的1cm之内。最后,与我们以前的研究(在该研究中,将相同数值模型的三维诊断表示法应用于哈得逊河以改善VDatum结果)相比,采用H-DA的快速二维模型改善了除MLLW之外的所有计算潮汐数据, RMSE增大0.7厘米。

著录项

  • 作者

    Wen, Bin.;

  • 作者单位

    Stevens Institute of Technology.;

  • 授予单位 Stevens Institute of Technology.;
  • 学科 Ocean engineering.;Engineering.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 146 p.
  • 总页数 146
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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