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Synergistic applications of autonomous underwater vehicles and regional ocean modeling system in coastal ocean forecasting

机译:自主水下航行器与区域海洋建模系统在沿海海洋预报中的协同应用

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摘要

The potential for using synergistic combinations of measurements from autonomous underwater vehicles (AUVs) and output from three-dimensional numerical models for studying the central California coastal region is demonstrated. Two case studies are used to illustrate the approach. In the first, propeller-driven AUV observations revealed a subsurface salinity minimum in northern Monterey Bay. A Regional Ocean Modeling System (ROMS) reanalysis of the three-dimensional flow in the region suggested an offshore source for this water and particular propagation pathways from the south and west into the bay. In the second case study, the effectiveness of assimilating observations in improving the ROMS reanalysis fields is investigated. A significant improvement, especially in the salinity fields, is demonstrated through a single glider deployed outside the intensive observational domain. These results suggest that investigation of more sophisticated techniques for using data and models together is warranted. Such techniques include increasing model resolution in areas of interest identified by observing platforms and using model-based \u22targeted observing\u22 techniques to identify areas of uncertainty in the flow to guide placement of observational assets.
机译:展示了使用自动水下航行器(AUV)的测量结果和三维数值模型输出的协同组合来研究加利福尼亚中部沿海地区的潜力。使用两个案例研究来说明该方法。首先,由螺旋桨驱动的AUV观测揭示了蒙特利湾北部的地下盐度最小值。对该区域三维流动的区域海洋建模系统(ROMS)的重新分析表明,该水的海上来源以及从南部和西部到海湾的特定传播路径。在第二个案例研究中,研究了同化观察在改善ROMS重新分析领域中的有效性。通过在集约化观测域外部署一架滑翔机,证明了特别是在盐度领域的显着改善。这些结果表明,有必要对将数据和模型一起使用的更复杂的技术进行研究。此类技术包括在由观测平台识别的感兴趣区域中提高模型分辨率,以及使用基于模型的目标观测技术来识别流量不确定性区域,以指导观测资产的放置。

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