Abstract. Climate change is expressed as a climate system transiting from the initial state to a new state in a short time. The period between the initial state and the new state is defined as the transition process, which is the key part for connecting the two states. By using a piece-wise function, the transition process is stated approximately (Mudelsee, 2000). However, the dynamic processes are not included in the piece-wise function. Thus, we proposed a method (Yan et al., 2015, 2016) to fit the transition process by using a continuous function. In this paper, this method is further developed for predicting the uncompleted transition process based on the dynamic characteristics of the continuous function. We introduce this prediction method in detail and apply it to three ideal time sequences and the Pacific Decadal Oscillation (PDO). The PDO is a long-lasting El Nino-like pattern of Pacific climate variability (Barnett et al., 1999; Newman et al., 2016). A new quantitative relationship during the transition process has been revealed, and it explores a nonlinear relationship between the linear trend and the amplitude (difference) between the initial state and the end state. As the transition process begins, the initial state and the linear trend are estimated. Then, according to the relationship, the end state and end moment of the uncompleted transition process are predicted.

中文翻译：

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一种预测未完成气候转变过程的方法

摘要。气候变化表现为气候系统在短时间内从初始状态过渡到新状态。初始状态和新状态之间的时间段被定义为过渡过程，这是连接两个状态的关键部分。通过使用分段函数，可以近似地说明过渡过程（Mudelsee，2000）。但是，动态过程不包括在分段函数中。因此，我们提出了一种方法 (Yan et al., 2015, 2016) 通过使用连续函数来拟合过渡过程。在本文中，该方法进一步发展用于基于连续函数的动态特性预测未完成过渡过程。我们详细介绍了这种预测方法，并将其应用于三个理想时间序列和太平洋年代际振荡（PDO）。PDO 是一种持久的类似厄尔尼诺现象的太平洋气候变化模式（Barnett 等，1999；Newman 等，2016）。揭示了过渡过程中的一种新的定量关系，它探索了线性趋势与初始状态和最终状态之间的幅度（差值）之间的非线性关系。当转换过程开始时，初始状态和线性趋势被估计。然后，根据该关系，预测未完成过渡过程的结束状态和结束时刻。它探讨了线性趋势与初始状态和结束状态之间的幅度（差值）之间的非线性关系。当转换过程开始时，初始状态和线性趋势被估计。然后，根据该关系，预测未完成过渡过程的结束状态和结束时刻。它探讨了线性趋势与初始状态和结束状态之间的幅度（差值）之间的非线性关系。当转换过程开始时，初始状态和线性趋势被估计。然后，根据该关系，预测未完成过渡过程的结束状态和结束时刻。