A Gaussian-product stochastic Gent–McWilliams parameterization
A Gaussian-product stochastic Gent–McWilliams parameterization
复制标题
高斯积随机 Gent–McWilliams 参数化
DOI：
10.1016/j.ocemod.2016.09.005
复制
发表时间：
2016
期刊：
影响因子：
3.2
通讯作者：
I. Grooms
中科院分区：
文献类型：
--
作者：
I. Grooms
中尺度涡流的局部平均水平浮力通量是根据海洋中尺度涡动力学的涡旋解析准地转模拟计算得出的。该通量具有非常非高斯分布，峰值为零，而不是平均值。这种非高斯通量分布的出现是因为通量是零均值随机变量的乘积：涡流速度和浮力。提出了随机 Gent-McWilliams (GM) 参数化的框架。开发了亚网格尺度速度和浮力的高斯随机场模型。这些高斯随机场的乘积用于构造水平亚网格尺度密度通量的非高斯随机参数化，从而产生非高斯随机 GM 参数化。这种新的非高斯随机 GM 参数化在理想化的盒子海洋模型中进行了测试，并与简单地将确定性 GM 参数化乘以高斯随机场的高斯方法进行了比较。非高斯方法对模拟的平均值和变异性都有显着影响，比高斯方法影响更大；例如，非高斯模拟比可比的高斯模拟具有更大的净动能和更强的翻转环流。讨论了随机 GM 参数化的未来发展方向和高斯积方法的扩展。
The locally-averaged horizontal buoyancy flux by mesoscale eddies is computed from eddy-resolving quasigeostrophic simulations of ocean-mesoscale eddy dynamics. This flux has a very non-Gaussian distribution peaked at zero, not at the mean value. This non-Gaussian flux distribution arises because the flux is a product of zero-mean random variables: the eddy velocity and buoyancy.A framework for stochastic Gent–McWilliams (GM) parameterization is presented. Gaussian random field models for subgrid-scale velocity and buoyancy are developed. The product of these Gaussian random fields is used to construct a non-Gaussian stochastic parameterization of the horizontal subgrid-scale density flux, which leads to a non-Gaussian stochastic GM parameterization. This new non-Gaussian stochastic GM parameterization is tested in an idealized box ocean model, and compared to a Gaussian approach that simply multiplies the deterministic GM parameterization by a Gaussian random field. The non-Gaussian approach has a significant impact on both the mean and variability of the simulations, more so than the Gaussian approach; for example, the non-Gaussian simulation has a much larger net kinetic energy and a stronger overturning circulation than a comparable Gaussian simulation. Future directions for development of the stochastic GM parameterization and extensions of the Gaussian-product approach are discussed.