Collaborative Research: The Interaction of Anticyclonic Eddies with Deep Convection
Collaborative Research: The Interaction of Anticyclonic Eddies with Deep Convection
批准号:
0525929
负责人:
Fiammetta Straneo
金额:
$57.18万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-09-01 至 2010-08-31
中文摘要
现在越来越多的观测证据表明,强烈的、往往是长期存在的非气旋性涡旋是世界海洋深对流区域的突出动力学特征之一。 然而,根据过去有限的观测资料,模拟研究往往集中在相反的情况下,气旋性涡旋在受到强烈的表面冷却时迅速解体。 反气旋涡旋可以通过多种方式与深对流相互作用,但它们对对流水团转化的净影响并不明显。 因此,它们的影响必须被认为是全球温盐环流的一个重要的未解决因素,并推而广之,是一个重大的社会关注的研究问题。本文提出用数值模拟和资料分析相结合的方法研究反气旋涡旋与对流的相互作用。 将在很宽的参数空间范围内研究强表面浮力损失下反气旋涡旋的详细行为。 借助新开发的数学和统计技术,我们将使用各种高质量的数据集系统地识别和描述几个关键对流区域的相干涡旋。 最终的结果应该是一个重要的一步,更完整的了解深对流在现实的设置。这一面向过程的工作将有可能改进大尺度模式中对流的参数化,从而更准确地预测气候变化。
英文摘要
An increasing amount of observational evidence now points to intense, often long-lived, aticyclonic eddies as one of the outstanding dynamical features in the deeply convecting regions of the world ocean. Yet modeling studies, informed by the more limited observations available in the past, have tended to focus on precisely the opposite case, cyclonic eddies that rapidly disintegrate when subjected to strong surface cooling. Anticyclonic eddies could interact with deep convection in a variety of ways, but their net effect on convective water mass transformation is far from obvious. Their influence must therefore be considered an important unresolved element of the global thermohaline circulation, and by extension, a research problem of substantial societal concern. It is proposed to investigate the interaction between anticyclonic eddies and convection using a combined modeling and data analysis approach. The detailed behavior of anticyclonic eddies subject to strong surface buoyancy loss will be examined throughout a broad range of parameter space. With the aid of newly developed mathematical and statistical techniques, we will systematically identify and describe coherent eddies in several key convection areas using a variety of high-quality datasets. The net result should be a significant step towards a more complete understanding of deep convection in a realistic setting. This process-oriented work will make possible improved parameterizations of convection in large-scale models, and thus more accurate predictions of climate variability.
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