Comparing Eddy-Permitting Ocean Model Parameterizations via Lagrangian Particle Statistics in a Quasigeostrophic Setting
Comparing Eddy-Permitting Ocean Model Parameterizations via Lagrangian Particle Statistics in a Quasigeostrophic Setting
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DOI：
10.1029/2018jc014182
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发表时间：
2018-08-01
影响因子：
3.6
通讯作者：
Grooms, Ian
中科院分区：
文献类型：
--
作者：
Chen, Amy;Barham, William;Grooms, Ian
本文利用拉格朗日统计的绝对弥散、对弥散和粒子预报对理想中尺度海洋动力学的四种涡动允许模式进行了比较。基线模式使用动量的尺度选择性双调和阻尼来保持速度场在网格尺度上的平滑，而不过度涂抹部分分辨的涡流。第二个模型使用空间和时间变化的非线性Leith粘性来吸收网格尺度附近的拟能，而不消耗太多的能量。后两种模型使用动量的强双调和阻尼来保持速度场在网格尺度上的平滑；这会耗散不切实际的大量动能，并且这两种模型添加了确定性或随机性的强迫来在更大的尺度上重新注入这种能量。这些模型被称为Jansen，并以Jansen和Hold(2014)的名字持有模型。所有四个模型都正确地模拟了粒子在超过几周的时间尺度上的扩散传输，这是通过拉格朗日绝对弥散来衡量的，表明所有模型都正确地再现了大尺度的相干涡流。在速度场中，拉格朗日相对色散(或对色散)对小尺度的结构更为敏感。Leith模型的相对离散度最不准确，而Jansen和Hold两个模型的相对离散度最高。在初始化预报实验中，模型之间的性能差异很小。
This paper uses Lagrangian statisticsabsolute dispersion, pair dispersion, and particle forecastingto compare four eddy-permitting models of idealized mesoscale ocean dynamics. The baseline model uses scale-selective biharmonic damping of momentum to keep the velocity field smooth at the grid scale without overly smearing the partially resolved eddies. The second model uses a nonlinear space- and time-varying Leith viscosity to absorb enstrophy near the grid scale without dissipating too much energy. The last two models use a strong biharmonic damping of momentum to keep the velocity field smooth at the grid scale; this dissipates an unrealistically large amount of kinetic energy, and the models add either deterministic or stochastic forcing to reinject this energy at larger scales. These models are called Jansen and Held models after Jansen and Held (2014, ). All four models correctly model the diffusive transport of particles over time scales more than a few weeks, as measured by the Lagrangian absolute dispersion, showing that all models correctly reproduce the large scales of coherent eddies. The Lagrangian relative dispersion (or pair dispersion) is more sensitive to structure at smaller scales in the velocity field. The Leith model has the least-accurate relative dispersion, while the two Jansen and Held models have the most accurate. In initialized forecast experiments, there is very little difference in performance between the models.