Stochastic parametrization of subgrid‐scale processes in coupled ocean–atmosphere systems: benefits and limitations of response theory
Stochastic parametrization of subgrid‐scale processes in coupled ocean–atmosphere systems: benefits and limitations of response theory
复制标题
海洋-大气耦合系统中次网格尺度过程的随机参数化：响应理论的优点和局限性
DOI：
10.1002/qj.2973
复制
发表时间：
2016
影响因子：
8.9
通讯作者：
S. Vannitsem
中科院分区：
文献类型：
--
作者：
J. Demaeyer;S. Vannitsem
Wouters 和 Lucarini 提出的基于 Ruelle 响应理论的随机次网格尺度参数化在低阶耦合海洋-大气模型的背景下进行了测试，该模型的一部分大气模式被认为是未解析的。将相空间自然分离成不变集及其补集，允许对参数化中涉及的不同项（即平均值、波动和长记忆项）进行分析推导。在这种情况下，波动项由加性随机噪声组成。其在低阶系统中的应用表明，只要耦合足够弱，就可以获得沿着不变子集的低频变异性的相当大的校正。这种新的尺度分离方法为用于气候预测的多尺度系统中的亚网格尺度参数化开辟了新途径。
A stochastic subgrid‐scale parametrization based on the Ruelle's response theory and proposed by Wouters and Lucarini is tested in the context of a low‐order coupled ocean–atmosphere model for which a part of the atmospheric modes is considered as unresolved. A natural separation of phase‐space into an invariant set and its complement allows for an analytical derivation of the different terms involved in the parametrization, namely the average, fluctuation and long memory terms. In this case, the fluctuation term consists of additive stochastic noise. Its application to the low‐order system reveals that a considerable correction of the low‐frequency variability along the invariant subset can be obtained, provided that the coupling is sufficiently weak. This new approach of scale separation opens new avenues of subgrid‐scale parametrizations in multiscale systems used for climate forecasts.