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Multi-model ensemble forecasting and glider path planning in the Mid-Atlantic Bight

机译:大西洋中部海岸线的多模型集合预报和滑翔机路径规划

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摘要

During the first two weeks of November 2009, a field experiment was conducted in the Mid-Atlantic Bight region to demonstrate a coastal ocean observatory that can collect observations from heterogeneous platforms and forecast fields from four different ocean models, provide multi-model ensemble forecasts based on either an equal weighting (EQ) or objective weighting (OBJ) method, and use model forecasts in a path planning system to relocate autonomous gliders. This experiment is a prototype for the command and control component of cyberinfrastructure of the Ocean Observatories Initiative funded by the National Science Foundation. The four individual models use different forcing fields, boundary conditions and data assimilation techniques, and have resolutions varying from 2. km to 15. km. Our results indicate that for sea surface temperature and surface currents, the OBJ ensemble outperforms the four individual models, while the EQ ensemble can also provide an effective way to improve individual model forecasts. In terms of glider path planning, the OBJ ensemble has a performance similar to the best individual model, which has the finest horizontal resolution. This field experiment demonstrates the first-ever use of ensemble current forecasts to guide glider path planning in the context of real-time data collection and ocean model forecasting.
机译:在2009年11月的前两周,在大西洋中部地区进行了野外实验,展示了一个沿海海洋天文台,该天文台可以收集来自非均质平台的观测值并预测来自四个不同海洋模型的场,并提供基于多模型集合的预报均等加权(EQ)或客观加权(OBJ)方法,并在路径规划系统中使用模型预测来重新定位自主滑翔机。该实验是由美国国家科学基金会资助的“海洋观测计划”网络基础设施的指挥和控制部分的原型。这四个单独的模型使用不同的作用场,边界条件和数据同化技术,并且分辨率从2. km到15 km不等。我们的结果表明,在海表温度和地表洋流方面,OBJ集合的性能优于四个单独的模型,而EQ集合也可以提供一种改进单个模型预测的有效方法。在滑翔机路径规划方面,OBJ集合的性能类似于最佳个人模型,后者具有最佳水平分辨率。这项现场实验演示了在实时数据收集和海洋模型预测的背景下,首次使用整体当前预报来指导滑翔机路径规划。

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