The backward nonlinear local Lyapunov exponent method (BNLLE) is applied to quantify the predictability of warm and cold events in the Lorenz model. Results show that the maximum prediction lead times of warm and cold events present obvious layered structures in phase space. The maximum prediction lead times of each warm (cold) event on individual circles concentric with the distribution of warm (cold) regime events are roughly the same, whereas the maximum prediction lead time of events on other circles are different. Statistical results show that warm events are more predictable than cold events.

中文翻译：

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使用后向非线性局部 Lyapunov 指数方法定量比较冷暖事件的可预测性

后向非线性局部李雅普诺夫指数法（BNLLE）用于量化洛伦兹模型中冷暖事件的可预测性。结果表明，冷暖事件的最大预测提前期在相空间上呈现明显的层状结构。与暖（冷）区事件分布同心的单个圈上每个暖（冷）事件的最大预测提前期大致相同，而其他圈上事件的最大预测提前期不同。统计结果表明，暖事件比冷事件更容易预测。