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首页> 外文期刊>Nonlinear processes in geophysics >The impact of initial spread calibration on the RELO ensemble and its application to Lagrangian dynamics
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The impact of initial spread calibration on the RELO ensemble and its application to Lagrangian dynamics

机译：初始扩展校准对RELO集合的影响及其在拉格朗日动力学中的应用

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A number of real-time ocean model forecasts were carried out successfully at Naval Research Laboratory (NRL) to provide modeling support and numerical guidance to the CARTHE GLAD at-sea experiment during summer 2012. Two RELO ensembles and three single models using NCOM and HYCOM with different resolutions were carried out. A calibrated ensemble system with enhanced spread and reliability was developed to better support this experiment. The calibrated ensemble is found to outperform the un-calibrated ensemble in forecasting accuracy, skill, and reliability for all the variables and observation spaces evaluated. The metrics used in this paper include RMS error, anomaly correlation, PECA, Brier score, spread reliability, and Talagrand rank histogram. It is also found that even the un-calibrated ensemble outperforms the single forecast from the model with the same resolution. brbr The advantages of the ensembles are further extended to the Lagrangian framework. In contrast to a single model forecast, the RELO ensemble provides not only the most likely Lagrangian trajectory for a particle in the ocean, but also an uncertainty estimate that directly reflects the complicated ocean dynamics, which is valuable for decision makers. The examples show that the calibrated ensemble with more reliability can capture trajectories in different, even opposite, directions, which would be missed by the un-calibrated ensemble. The ensembles are applied to compute the repelling and attracting Lagrangian coherent structures (LCSs), and the uncertainties of the LCSs, which are hard to obtain from a single model forecast, are estimated. It is found that the spatial scales of the LCSs depend on the model resolution. The model with the highest resolution produces the finest, small-scale, LCS structures, while the model with lowest resolution generates only large-scale LCSs. The repelling and attracting LCSs are found to intersect at many locations and create complex mesoscale eddies. The fluid particles and drifters in the middle of these tangles are subject to attraction and repulsion simultaneously from these two kinds of LCSs. As a result, the movements of particles near the Deepwater Horizon (DWH) location are severely limited. This is also confirmed by the Lagrangian trajectories predicted by the ensembles.
机译：在海军研究实验室（NRL）上成功进行了许多实时海洋模型预测，从而为CARTHE GLAD海上实验在2012年夏季提供了建模支持和数值指导。使用NCOM和HYCOM的两个RELO集合和三个单个模型以不同的分辨率进行。开发了具有增强的扩展性和可靠性的经过校准的集成系统，以更好地支持该实验。发现在评估的所有变量和观察空间的预测准确性，技巧和可靠性方面，校准后的集合都优于未校准后的集合。本文使用的指标包括RMS误差，异常相关性，PECA，Brier分数，传播可靠性和Talagrand等级直方图。还发现，即使是未校准的集合也要比具有相同分辨率的模型的单个预测要好。 合奏的优势进一步扩展到了拉格朗日框架。与单一模型预测相反，RELO集合不仅提供了海洋中粒子最可能的拉格朗日轨迹，而且还提供了直接反映复杂海洋动态的不确定性估计，这对于决策者而言非常有价值。这些示例表明，具有更高可靠性的已校准合奏可以捕获不同甚至相反方向的轨迹，而未校准合奏会丢失这些轨迹。将该集合用于计算排斥和吸引拉格朗日相干结构（LCS），并估计了难以从单个模型预测中获得的LCS的不确定性。发现LCS的空间尺度取决于模型分辨率。分辨率最高的模型将生成最精细的小型LCS结构，而分辨率最低的模型将仅生成大型LCS。发现排斥和吸引的LCS在许多位置相交并产生复杂的中尺度涡流。这些缠结中间的流体颗粒和漂移物同时受到这两种LCS的吸引和排斥。结果，深水地平线（DWH）位置附近的粒子运动受到严重限制。合奏预测的拉格朗日轨迹也证实了这一点。

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