当前位置: X-MOL 学术Clim. Dyn. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
On the use of near-neutral Backward Lyapunov Vectors to get reliable ensemble forecasts in coupled ocean–atmosphere systems
Climate Dynamics ( IF 4.6 ) Pub Date : 2020-06-02 , DOI: 10.1007/s00382-020-05313-3
Stéphane Vannitsem , Wansuo Duan

The use of coupled Backward Lyapunov Vectors (BLV) for ensemble forecast is demonstrated in a coupled ocean–atmosphere system of reduced order, the Modular Arbitrary Order Ocean–Atmosphere Model (MAOOAM). It is found that overall the most suitable BLVs to initialize a (multiscale) coupled ocean–atmosphere forecasting system are the ones associated with near-neutral and slightly negative Lyapunov exponents. This unexpected result is related to the fact that these BLVs display larger projections on the ocean variables than the others, leading to an appropriate spread for the ocean, and at the same time a rapid transfer of these errors toward the most unstable BLVs affecting predominantly the atmosphere is experienced. The latter dynamics is a natural property of any generic perturbation in nonlinear chaotic dynamical systems, allowing for a reliable spread with the atmosphere too. Furthermore, this specific choice becomes even more crucial when the goal is the forecasting of low-frequency variability at annual and decadal time scales. The implications of these results for operational ensemble forecasts in coupled ocean–atmosphere systems are briefly discussed.



中文翻译:

利用近中性后向Lyapunov向量获得海洋-大气耦合系统中的可靠整体预报

在降序的海洋-大气耦合系统,模块化任意阶海洋-大气模型(MAOOAM)中,证明了使用耦合后向李雅普诺夫向量(BLV)进行整体预报。发现总体上最适合初始化(多尺度)海洋-大气耦合预报系统的BLV是与近中性和略带负Lyapunov指数相关的BLV。这种出乎意料的结果与以下事实有关:这些BLV在海洋变量上显示的投影比其他变量大,从而导致海洋有适当的扩散,同时这些错误迅速转移到最不稳定的BLV上,这些BLV主要影响到气氛很丰富。后一种动力学是非线性混沌动力学系统中任何一般扰动的自然属性,也可以在大气中可靠传播。此外,当目标是在年度和十年时间尺度上预测低频变化时,这一特定选择就变得尤为重要。简要讨论了这些结果对海洋-大气耦合系统中的业务集合预报的影响。

更新日期:2020-06-02
down
wechat
bug