Stochastic superparameterization in a quasigeostrophic model of the Antarctic Circumpolar Current
Stochastic superparameterization in a quasigeostrophic model of the Antarctic Circumpolar Current
复制标题
南极绕极流准地转模型中的随机超参数化
DOI：
10.1016/j.ocemod.2014.10.001
复制
发表时间：
2015
期刊：
影响因子：
3.2
通讯作者：
K. Shafer Smith
中科院分区：
文献类型：
--
作者：
I. Grooms;A. Majda;K. Shafer Smith
随机超参数化是一种基于多尺度形式的随机参数化框架，用于粗分辨率海洋模式中的中尺度涡动参数化。随机superparameterization的框架进行了审查和几种配置的实施和测试在准地转通道模型-南极绕极流的理想化表示。五个版本的Gent-McWilliams（GM）参数化也实施和测试进行比较。技能的测量分别使用时间平均值和时间变异性，并结合使用单点统计中的相对熵。在所有模型中，具有更准确的平均状态的模型具有更低的准确性变异性，反之亦然。随机超参数化的结果在改善气候保真度相比，GM参数化的相对熵。特别是，配置的随机超参数化，包括随机雷诺应力项在粗糙的模型方程，对应于动能后向散射，执行比模型，只包括等密高度平滑。
Stochastic superparameterization, a stochastic parameterization framework based on a multiscale formalism, is developed for mesoscale eddy parameterization in coarse-resolution ocean modeling. The framework of stochastic superparameterization is reviewed and several configurations are implemented and tested in a quasigeostrophic channel model – an idealized representation of the Antarctic Circumpolar Current. Five versions of the Gent–McWilliams (GM) parameterization are also implemented and tested for comparison. Skill is measured using the time-mean and temporal variability separately, and in combination using the relative entropy in the single-point statistics. Among all the models, those with the more accurate mean state have the less accurate variability, and vice versa. Stochastic superparameterization results in improved climate fidelity in comparison with GM parameterizations as measured by the relative entropy. In particular, configurations of stochastic superparameterization that include stochastic Reynolds stress terms in the coarse model equations, corresponding to kinetic energy backscatter, perform better than models that only include isopycnal height smoothing.
在三维大气环流海洋模型中实现线性稳定性分析的扩散性
影响因子：
3.2
作者：
通讯作者：
--
影响因子：
3.5
作者：
Marshall, David P.;Maddison, James R.;Berloff, Pavel S.
通讯作者：
Berloff, Pavel S.