Wang Bin, Chen Guosen, Liu Fei
Earth System Modeling Center, Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Department of Atmospheric Sciences and Atmosphere-Ocean Research Center, University of Hawaii at Manoa, Honolulu, HI 96822, USA.
Sci Adv. 2019 Jul 31;5(7):eaax0220. doi: 10.1126/sciadv.aax0220. eCollection 2019 Jul.
Madden-Julian Oscillation (MJO) is the dominant mode of atmospheric intraseasonal variability and the cornerstone for subseasonal prediction of extreme weather events. Climate modeling and prediction of MJO remain a big challenge, partially due to lack of understanding the MJO diversity. Here, we delineate observed MJO diversity by cluster analysis of propagation patterns of MJO events, which reveals four archetypes: standing, jumping, slow eastward propagation, and fast eastward propagation. Each type exhibits distinctive east-west asymmetric circulation and thermodynamic structures. Tight coupling between the Kelvin wave response and major convection is unique for the propagating events, while the strength and length of Kelvin wave response distinguish slow and fast propagations. The Pacific sea surface temperature anomalies can affect MJO diversity by modifying the Kelvin wave response and its coupling to MJO convection. The results shed light on the mechanisms responsible for MJO diversity and provide potential precursors for foreseeing MJO propagation.
马登-朱利安振荡(MJO)是大气季节内变率的主要模态,也是极端天气事件次季节预测的基石。MJO的气候模拟和预测仍然是一个巨大的挑战,部分原因是对MJO的多样性缺乏了解。在这里,我们通过对MJO事件传播模式的聚类分析来描绘观测到的MJO多样性,结果揭示了四种原型:静止型、跳跃型、缓慢东传型和快速东传型。每种类型都表现出独特的东西向不对称环流和热力结构。对于传播型事件,开尔文波响应与主要对流之间的紧密耦合是其独特之处,而开尔文波响应的强度和长度则区分了缓慢传播和快速传播。太平洋海表面温度异常可以通过改变开尔文波响应及其与MJO对流的耦合来影响MJO多样性。这些结果揭示了造成MJO多样性的机制,并为预测MJO传播提供了潜在的先兆。