Further Studies of El Niño-Southern Oscillation (ENSO) Dynamics

厄尔尼诺-南方涛动（ENSO）现象是造成全球气候变化的主要原因。ENSO对整个热带和美洲的人类健康、安全和食品生产产生重大影响。它在许多不同的时间尺度上表现出丰富的变化谱。根据该奖项，PI将解决ENSO动力学的基本问题：ENSO的稳定性如何在不同的模式中变化；随着气候变化，它将如何变化？ENSO不同周期性的来源是什么？ENSO和变率在更短时间尺度上的相互作用会影响ENSO的稳定性吗？这些问题将使用PI在他之前的奖项下开发的大气-海洋稳定指数来解决。该指数将应用于表现出不同ENSO行为的各种大气-海洋耦合气候模式，并评估不同气候条件下ENSO的稳定性。将研究慢速ENSO模式和快变率之间的尺度相互作用，并确定这些尺度相互作用对耦合ENSO模式稳定性的影响。PI将探索导致类似ENSO的多个独立耦合模式可能共存的物理机制，并将确定它们与所观察到的行为的相关性。将使用耦合模型的层次结构。这项研究将有助于更好地了解ENSO的动态和可预测性。这项研究的更广泛的影响是它对改进ENSO预测和评估ENSO将如何随着全球气候变化而变化的潜在贡献。

The El Nino - Southern Oscillation (ENSO) phenomenon is responsible for nearly global variations in climate. ENSO has major effects on human health, safety, and food production throughout the tropics and the Americas. It exhibits a rich spectrum of variations on many different timescales. Under this award the PI will address fundamental questions about the dynamics of ENSO: How does the stability of ENSO vary among different models; how will it change as climate changes? What are the sources of the different periodicities of ENSO? Do interactions between ENSO and variability on much shorter timescales influence the stability of ENSO? These questions will be addressed using an atmosphere-ocean stability index developed by the PI under his previous award. The index will be applied to various coupled atmosphere-ocean climate models, which exhibit different ENSO behavior, and to assess the stability of ENSO under different climate conditions. Scale-interactions between slow ENSO modes and fast variability will be investigated and the impact of these scale interactions on the stability of the coupled ENSO modes will be determined. The PI will explore the physical mechanisms leading to the possible co-existence of multiple independent coupled modes that resemble ENSO and will determine their relevance to its observed behavior. A hierarchy of coupled models will be used. The study will lead to a better understanding of the dynamics and predictability of ENSO. Broader impacts of this research are its potential contributions to improved predictions of ENSO and to assessments of how ENSO will change as the global climate changes.