Multiple Equilibria and Self-aggregation of Deep Tropical Convection

在没有任何明显外部影响的情况下，热带深层对流聚集的趋势是大气科学中一个重要的未解决问题。自聚集可能是气旋形成的前兆，因此可能对一些飓风的早期阶段很重要。马登-朱利安振荡在预测方面是一个突出但难以捉摸的问题，它也可能是对流自聚集的一种表现。本研究的目的是利用云解析模式来研究热带对流中的自聚集现象。研究人员将利用一种新的策略，利用大域的自聚集和有限域模拟中的多重平衡之间的类比。了解控制自聚集的潜在机制将是一项重大成就，并将极大地提高大尺度模式表征对流和大尺度热带气流之间相互作用过程的能力。因此，这一努力具有显著的更广泛的影响。除了对本科生和研究生进行培训外，还有一项工作计划，通过该计划，PI将帮助对K-12教师进行气候相关问题的教育。

The tendency for deep tropical convection to aggregate in the absence of any obvious external influences represents an important unsolved problem in the atmospheric sciences. Self-aggregation may serve as a precursor to cyclogenesis, and therefore may be important to the early stages of some hurricanes. The Madden-Julian Oscillation, which represents a prominent but elusive problem in terms of prediction, may also be a manifestation of convective self-aggregation. The goal of the proposed research is to utilize a cloud resolving model to investigate the phenomenon of self-aggregation in tropical convection. The investigators will utilize a novel strategy which exploits the analogy between self-aggregation in large domains and multiple equilibria in limited domain simulations. Understanding the underlying mechanisms which control self-aggregation would constitute a major achievement and could greatly improve the ability of large scale models to represent interaction processes between convection and large-scale tropical flows. Thus this effort has significant broader impacts. In addition to undergraduate and graduate student training, there is a work plan through which the PI will help educate K-12 teachers on climate-related issues.