Tropical Ocean-Atmosphere Interaction

本研究旨在了解热带海气相互作用的机制及其产生的现象。已经开发的方法和模型将应用于三个主要领域：1)继续开展年际变化方面的工作，强调分析和数值方法。2)开始研究气候学中的耦合反馈效应。耦合环流模式(GCM)中的热带气候特征对涉及三维动力相互作用的耦合反馈十分敏感。目前关于热带气候中海洋-大气相互作用的大部分讨论都集中在一维的垂直柱观点上。提出了一种补充方法，旨在加深对水平上非局部相互作用的理解。3)热带大气模式。目前用于耦合的简单大气模型对于这类研究有许多不足之处。建议进一步发展介于这些和大气GCM之间的复杂性模型；特别是，由于Betts(1986)对流方案的性质，在简化情况下可以得到近似解析形式的模型。本课程将探讨热带大气对地表边界条件和季节内变化的反应机制，如马登-朱利安振荡。这项研究之所以重要，是因为它将有助于确定对海洋-大气耦合系统进行建模的可行性，以便预测其在几个月至几年的时间尺度上的变化，这是气候变异性中的一个令人关切的问题。

This research is aimed at understanding the mechanisms of ocean-atmosphere interaction in the tropics and the phenomena that these produce. The methods and models already developed will be applied to three main areas: 1) Contined work on interannual variability, emphasizing analytical as well as numerical approaches. 2) Initiation of work on the effects of coupled feedbacks in the climatology. Tropical climate features in coupled general circulation models (GCMs) appear to be quite sensitive to coupled feedbacks involving three-dimensional dynamical interactions. Much of the current discussion of ocean- atmosphere interaction in tropical climate centers on a one- dimensional, vertical column point of view. A complementary approach is proposed, aimed at developing understanding of the interactions which are nonlocal in the horizontal. 3) Tropcial atmosphere modeling. Current simple atmospheric models used in coupling have a number of deficiencies for this type of study. Further development of a model of complexity intermediate between these and atmospheric GCMs is proposed; in particular one for which near-analytic versions can be obtained in simplifying cases, thanks to the properties of the Betts (1986) convection scheme. The mechanisms driving both the tropical atmospheric response to surface boundary conditions and intraseasonal variability, such as the Madden- Julian oscillation, will be examined. This research is important because it is one of the studies which will help determine the feasibility of modeling the coupled ocean-atmosphere system for the purpose of predicting its variations on time scales of months to years, an issue of concern in climate variability.