A Note on the Role of the Initial Error Structure in the Tropics on the Seasonal-to-Decadal Forecasting Skill in the Extratropics

Abstract

The predictability of a coupled system composed of a coupled reduced-order extratropical ocean–atmosphere model forced by a low-order three-variable tropical recharge–discharge model is explored with emphasis on its long-term forecasting capabilities. Highly idealized ensemble forecasts are produced taking into account the uncertainties in the initial states of the system, with specific attention to the structure of the initial errors in the tropical model. Three main types of experiments are explored: with random perturbations along the three Lyapunov vectors of the tropical model; along the two dominant Lyapunov vectors; and along the first Lyapunov vector only. When perturbations are introduced along all vectors, forecasting biases develop even if in a perfect model framework and with known initial uncertainty properties. Theses biases are considerably reduced only when the perturbations are introduced along the dominant Lyapunov vector. Furthermore, this perturbation strategy allows a reduced mean square error to be obtained at long lead times of a few years, as well as reliable ensemble forecasts across the whole time range. These very counterintuitive findings further underline the importance of appropriately controlling the initial error structure in the tropics through data assimilation.

摘 要

本文探讨了由低阶三变量热带充放电模型驱动的降阶热带外海气耦合模式的可预报性, 重点研究其长期预测能力。 高度理想化的集合预报方法考虑了系统初始状态的不确定性, 并特别关注热带模型中初始误差的结构。 本文主要开展了三类实验: 分别为在热带模型的三个 Lyapunov 向量方向上引入随机扰动; 在两个主导 Lyapunov 向量方向上引入扰动; 以及仅在第一个 Lyapunov 向量方向上引入扰动。 当在所有向量方向上引入扰动时, 即使在完美模型的框架下且初始不确定性特征已知, 预报偏差仍会增长。 只有仅在主导 Lyapunov 向量方向引入扰动时, 这些偏差才会大幅减小。 此外, 这种扰动策略能够在数年的长预报时效内获得减小的均方误差, 并在整个时间范围内获得可靠的集合预报。 这些非常“反常规”的发现进一步强调了通过数据同化适当控制热带地区初始误差结构的重要性。