Deep-mixing and deep-cooling events in Lake Garda: Simulation and Mechanisms

Pub Date : 2021-06-21 DOI:10.5194/egusphere-egu21-8326
B. Biemond, Marina Amadori, M. Toffolon, S. Piccolroaz, H. van Haren, H. Dijkstra
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引用次数: 4

Abstract

A calibrated three-dimensional numerical model (Delft3D) and in-situ observations are used to study the relation between deep water temperature and mixing in Lake Garda (Italy). A model-observation comparison indicates that the model is able to adequately capture the production of turbulent kinetic energy in the surface layer and its vertical propagation during unstratified conditions. Here, the model is used as a support to identify the main processes causing deep water cooling and deep mixing in the lake. The analysis indicated that two processes cause mixing over the entire depth. The first process is thermocline tilting due to strong and persistent winds. This is found to generate a temporary disappearance of stratification followed by vertical mixing over the entire depth. The second process is turbulent cooling, which arises as a combination of negative-buoyancy produced by surface cooling and turbulence injection from strong winds. Turbulent cooling acts when vertical temperature gradients are absent over the whole depth and cools and mixes the lake over its entire vertical. The third identified process is associated to differential cooling between the shallow southern part and the deep northern trunk. This generates the advection of cold water from the southern, colder and well-mixed basin to the norther trunk along the sloping bottom of the lake. Such differential cooling is found to be a consequence of the turbulent cooling and is not associated with mixing over the entire depth in the northern trunk. Available observations indicate that the three processes identified from the model indeed occur in Lake Garda. Long- term simulations of deep water temperature and related deep mixing appear to be very sensitive to the atmospheric forcing, whose accurate reproduction is essential for the prediction of the future occurrence of deep mixing events.

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加尔达湖的深度混合和深度冷却事件:模拟和机制
利用校正后的三维数值模型(Delft3D)和现场观测资料,研究了意大利加尔达湖深水温度与混合的关系。模型与观测值的对比表明,该模型能够充分捕捉到非分层条件下表层湍流动能的产生及其垂直传播。本文以该模型为支撑,确定了引起湖泊深层水冷却和深层混合的主要过程。分析表明,两个过程导致了整个深度的混合。第一个过程是由于强劲和持续的风造成的温跃层倾斜。这被发现会产生一个暂时的分层消失,然后是整个深度的垂直混合。第二个过程是湍流冷却,它是由表面冷却产生的负浮力和强风注入的湍流相结合而产生的。当垂直温度梯度在整个深度上不存在时,湍流冷却就会发生,并在整个垂直方向上冷却和混合湖泊。第三个确定的过程与南部浅层和北部深层主干之间的差异冷却有关。这就产生了冷水的平流,从南部较冷且混合良好的盆地沿倾斜的湖底流向北部干流。这种差异冷却被发现是湍流冷却的结果,与北部主干整个深度的混合无关。现有的观测表明,从模式中确定的三个过程确实发生在加尔达湖。深水温度和相关的深海混合的长期模拟似乎对大气强迫非常敏感,其精确再现对于预测未来深海混合事件的发生至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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