Collaborative Research: The Nature and Predictability of The Madden and Julian Oscillation in the Coupled Ocean- Atmosphere System

这项资助是为加州大学圣巴巴拉分校的Charles Jones博士和纽约州立大学石溪分校的Duane Waliser博士之间的合作项目提供支持的两个奖项之一（编号为ATM-9712483）。主要研究人员试图提高我们对一种被称为麦登-朱利安涛动（MJO）的热带季节性内现象的理解，并最终提高我们的预测能力。Madden-Julian涛动是热带季节内变率的重要模态之一，它通过与西风爆发的密切联系，可能对温带地区的中至大范围天气预报、亚洲-澳大利亚季风活动甚至赤道太平洋温跃层结构的变率产生重要影响。越来越多的证据，包括主要研究人员最近获得的模拟结果表明，海气相互作用过程，特别是海表温度变化对表面通量的影响，可能对MJO的维持很重要。主要研究人员将继续进行研究，包括：(1)利用海洋-大气耦合模式进一步探讨海温和地面过程在决定MJO强度和维持MJO的作用；(2)评估MJO的表现/预报对可操作的中期天气预报模式整体扩展范围预报技能的影响。这项研究将涉及使用诊断和统计分析以及数值模拟。pi将在他们的研究中使用几种不同的模型。该研究对改进季节内和季节时间尺度的动态扩展范围预测具有重要意义。因此，气候动力学和大尺度气象学项目都将分享这一合作项目的支持。

9712855 Jones This grant represents one of the two awards that provide support for a collaborative project between Dr. Charles Jones of UC - Santa Barbara and Dr. Duane Waliser at SUNY - Stony Brook (under ATM-9712483). The principal investigators seek to improve our understanding of, and ultimately our capability to forecast, a tropical intraseasonal phenomenon known as the Madden-Julian Oscillation (MJO). The Madden-Julian Oscillation is one of the most important modes of tropical intraseasonal variability that may have important influences on medium- to extended-range weather forecasting in the extratropics, the Asian-Australian monsoon activity, and even the variability of the equatorial Pacific Ocean thermocline structure via its close association with westerly wind bursts. A growing body of evidence, including recent modeling results obtained by the principal investigators, suggests that air-sea interaction processes, particularly the influence of sea-surface temperature (SST) variations on surface fluxes, may be important in the maintenance of the MJO. The principal investigators will continue their investigation by (1) further exploring the role of SST and surface processes in determining the strength of and maintaining the MJO using coupled ocean-atmosphere models and (2) assessing the impact of the representation/forecast of the MJO on the overall extended range forecast skill in an operational medium-range weather forecast model. The research will involve the use of diagnostic and statistical analyses as well as numerical simulations. The PIs will employ several different models in their study. This research has important implications for improving dynamical extended range forecasting at both intraseasonal and seasonal time scales. Therefore, both the Climate Dynamics and Large-scale Meteorology Programs will share in the support of this collaborative project.