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基于有序划分网络方法揭示海洋对巴西东北部极端干旱事件的阶段性影响

Uncovering episodic influence of oceans on extreme drought events in Northeast Brazil by ordinal partition network approaches.

机构信息

School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China.

Instituto Nacional de Pesquisas Espaciais, São José dos Campos 12246-021, São Paulo, Brazil.

出版信息

Chaos. 2020 May;30(5):053104. doi: 10.1063/5.0004348.

Abstract

Since 2012, the semiarid region of Northeast Brazil (NEB) has been experiencing a continuous dry condition imposing significant social impacts and economic losses. Characterizing the recent extreme drought events and uncovering the influence from the surrounding oceans remain to be big challenges. The physical mechanisms of extreme drought events in the NEB are due to varying interacting time scales from the surrounding tropical oceans (Pacific and Atlantic). From time series observations, we propose a three-step strategy to establish the episodic coupling directions on intraseasonal time scales from the ocean to the precipitation patterns in the NEB, focusing on the distinctive roles of the oceans during the recent extreme drought events of 2012-2013 and 2015-2016. Our algorithm involves the following: (i) computing drought period length from daily precipitation anomalies to capture extreme drought events; (ii) characterizing the episodic coupling delays from the surrounding oceans to the precipitation by applying the Kullback-Leibler divergence (KLD) of complexity measure, which is based on ordinal partition transition network representation of time series; and (iii) calculating the ratio of high temperature in the ocean during the extreme drought events with proper time lags that are identified by KLD measures. From the viewpoint of climatology, our analysis provides data-based evidence of showing significant influence from the North Atlantic in 2012-2013 to the NEB, but in 2015-2016, the Pacific played a dominant role than that of the Atlantic. The episodic intraseasonal time scale properties are potential for monitoring and forecasting droughts in the NEB in order to propose strategies for drought impacts reduction.

摘要

自 2012 年以来,巴西东北部(NEB)的半干旱地区一直持续干旱,这给当地带来了严重的社会影响和经济损失。准确刻画近期极端干旱事件并揭示其与周边海洋的相互作用机制仍然是一个巨大的挑战。NEB 极端干旱事件的物理机制是由于其与周边热带海洋(太平洋和大西洋)之间相互作用的时间尺度不同。基于时间序列观测,我们提出了一种三步策略,以建立海洋与 NEB 降水模式之间的季节内时间尺度上的偶发性耦合方向,重点研究海洋在 2012-2013 年和 2015-2016 年最近的极端干旱事件中的独特作用。我们的算法包括以下三个步骤:(i)通过计算日降水异常的干旱期长度来捕捉极端干旱事件;(ii)通过应用复杂度测度的 Kullback-Leibler 散度(KLD)来刻画海洋到降水的偶发性耦合延迟,该复杂度测度基于时间序列的有序分区转移网络表示;(iii)计算在极端干旱事件期间海洋中高温的比值,其中适当的时间滞后是通过 KLD 测量确定的。从气候学的角度来看,我们的分析提供了基于数据的证据,表明 2012-2013 年期间北大西洋对 NEB 有显著影响,但在 2015-2016 年期间,太平洋的影响比大西洋更为显著。季节内时间尺度的偶发性特征为监测和预测 NEB 的干旱提供了可能,有助于提出减少干旱影响的策略。

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