Submesoscale Instabilities and Turbulence Across Oceans: Connecting Theory and Observations

海洋流动的尺度相对较大，通常超过几十英里，由于地球的自转，大部分都局限在水平面上。在较小的亚中尺度，这种限制大大减少，允许更剧烈的垂直运动，这在调节上层海洋热含量和海气交换中起着至关重要的作用。因此，在数值模式中改进这些过程的表现对于准确预测从ENSO到热带季风再到北极海冰融化速度等一系列与社会直接相关的现象非常重要。由于亚中尺度的横向尺度短（公里数量级）和时间尺度快（惯性周期数量级或更快），在海洋中很难直接观测到亚中尺度的流动。另一方面，数值和分析研究在描述理想化的亚中尺度流动动力学方面取得了实质性进展。已经为不同的亚中尺度不稳定的开始制定了标准。已经进行了参数化，以解释全球海洋模式中这些尚未解决的不稳定性。然而，从这些研究中获得的知识很少得到观察结果的证实或与观察结果进行比较，这使得我们很难满怀信心地向前迈进。该项目将通过将综合线性稳定性模型的开发和应用与对现有几个重要海洋学数据集的分析相结合来解决这一差距。该项目主要由一位早期职业科学家撰写并将为其提供资金。这个模型是由早期职业科学家开发的，它是新颖的，因为它是由观察到的密度和速度的分布所强迫的，不像过去使用的许多理想化的平均状态。初步的工作表明，它有能力重现大量类型的亚中尺度不稳定，从混合层斜压不稳定到对称不稳定，再到朗缪尔环流，以及介于两者之间的一切。与之前的线性稳定性模型不同，它可以从一个不稳定类别平滑地过渡到另一个不稳定类别；也就是说，它从单个平均流状态输入产生广泛的不稳定性。该模型将与最近几次海洋考察积累的数据集进行比较。其中两组数据显示了亚中尺度活动的有力证据，既有轶事例子，也有系统统计数据。将使用来自这些示例中的几个概要文件开发和测试模型技能。反过来，预计模型结果将有助于阐明观测中存在的动力不稳定性的性质；由于该模型是用真实的梯度剖面初始化的，并且允许对大范围的不稳定性进行完全复杂的叠加，因此它特别适合于处理宽带海洋中的复杂观测。将模式预测与跨越多个海洋盆地和多个季节的现有观测结果进行比较，将有助于加深对亚中尺度变率的广泛模式的理解，这些模式可用于验证新的全球参数化发展。

Ocean flows at relatively large scales, typically more than tens of miles, are mostly confined to horizontal plane due to the rotation of the Earth. At the smaller submesoscale, this constraint is much reduced, allowing more vigorous vertical motion, which plays a crucial role in mediating upper ocean heat content and air-sea exchange. Improving the representation of these processes in numerical models is therefore important for accurate forecasts of a wide range of directly societally relevant phenomena, from ENSO to tropical monsoons to the rate of Arctic sea ice melt. Due to their intrinsic short lateral scales (order of km) and fast time scales (order of inertial period or faster), submesoscale flows have been difficult to observe directly in the ocean. Numerical and analytical studies, on the other hand, have made substantial progress in describing the dynamics of idealized submesoscale flows. Criteria have been developed for the onset of different submesoscale instabilities. Parametrizations have been made to account for these instabilities in global ocean models where they are not resolved. Yet little of the knowledge gained from these studies has been confirmed by or compared with observations, which makes it difficult to move forward with confidence. This project will address this gap by combining development and application of a comprehensive linear stability model with analysis of several substantial oceanographic datasets already in hand. This project largely written by and will fund an early career scientist.The model, developed by the early career scientist, is novel in that it is forced by observed profiles of density and velocity, unlike many idealized mean states that have been used in the past. Preliminary work demonstrates its capacity to reproduce a vast range of types of submesoscale instabilities, from mixed layer baroclinic instability to symmetric instability to Langmuir circulation, and everything in between. Unlike linear stability models before, it can smoothly transition from one instability class to another; i.e. it produces a broad spectrum of instabilities from a single mean flow state input. The model will be forced by and then compared with amassed datasets from several recent oceanographic expeditions. Two of the data-sets have shown strong evidence of submesoscale activity, both with anecdotal examples and systematic statistics. Model skill will be developed and tested using profiles from several of these examples. In turn, it is anticipated that the model results will help illuminate the nature of the dynamical instabilities present in the observations; because the model is initialized with real gradient profiles and allows a fully complex superposition of a wide range of instabilities, it is uniquely suited for detangling complex observations in a broadband ocean. Comparison of model predictions with available observations that span multiple ocean basins and multiple seasons will help develop understanding of broad patterns of submesoscale variability, the sorts of patterns that can be used to validate new global parametrization development.