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The backward nonlinear local Lyapunov exponent and its application to quantifying the local predictability of extreme high-temperature events
Climate Dynamics ( IF 4.6 ) Pub Date : 2022-09-01 , DOI: 10.1007/s00382-022-06469-w
Xuan Li , Ruiqiang Ding

The backward nonlinear local Lyapunov exponent (BNLLE) was developed based on the NLLE method to quantitatively investigate the local predictability of extreme events. By studying the dynamical characteristics of error growth preceding extreme events, the local predictability limits of these events can be determined. In this study, the BNLLE method is used to quantify the local predictability limits of two extreme high-temperature events (EHTEs) that occurred in Europe during the summer of 2019. The results show that the error dynamics are dependent on the geographical location. During the early forecast period, positive error-growth rates are mainly located in southern regions, whereas negative error-growth rates are mainly located in northern regions. However, the variations in the error growth rates exhibit regional differences with the forecast time. As such, the relative growth of initial errors (RGIEs) also depends on the geographical location. From the RGIEs, the local predictability limits of the two EHTEs are determined to be 11 and 9 days, respectively. By measuring the forecast skill, the local predictability limits (11 and 9 days) are verified to be reasonable and realistic. Therefore, the BNLLE method can quantify the local predictability of EHTEs, and is an effective technique for studying the predictability of future extreme weather and climate events.



中文翻译:

后向非线性局部李雅普诺夫指数及其在量化极端高温事件局部可预报性中的应用

后向非线性局部李雅普诺夫指数(BNLLE)是在NLLE方法的基础上发展起来的,用于定量研究极端事件的局部可预测性。通过研究极端事件前误差增长的动力学特征,可以确定这些事件的局部可预测性极限。在这项研究中,BNLLE 方法用于量化 2019 年夏季在欧洲发生的两次极端高温事件 (EHTE) 的局部可预测性限制。结果表明,误差动态取决于地理位置。预测前期,正误差增长率主要分布在南方地区,负误差增长率主要分布在北部地区。然而,误差增长率的变化表现出与预测时间的区域差异。因此,初始误差 (RGIE) 的相对增长也取决于地理位置。根据 RGIE,两个 EHTE 的局部可预测性限制分别确定为 11 天和 9 天。通过衡量预报技巧,验证了局部可预测性限制(11 天和 9 天)的合理性和现实性。因此,BNLLE方法可以量化EHTE的局部可预报性,是研究未来极端天气气候事件可预报性的有效技术。通过衡量预报技巧,验证了局部可预测性限制(11 天和 9 天)的合理性和现实性。因此,BNLLE方法可以量化EHTE的局部可预报性,是研究未来极端天气气候事件可预报性的有效技术。通过衡量预报技巧,验证了局部可预测性限制(11 天和 9 天)的合理性和现实性。因此,BNLLE方法可以量化EHTE的局部可预报性,是研究未来极端天气气候事件可预报性的有效技术。

更新日期:2022-09-01
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