【2h】

Stochastic models for convective momentum transport

机译:对流动量传输的随机模型

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摘要

The improved parameterization of unresolved features of tropical convection is a central challenge in current computer models for long-range ensemble forecasting of weather and short-term climate change. Observations, theory, and detailed smaller-scale numerical simulations suggest that convective momentum transport (CMT) from the unresolved scales to the resolved scales is one of the major deficiencies in contemporary computer models. Here, a combination of mathematical and physical reasoning is utilized to build simple stochastic models that capture the significant intermittent upscale transports of CMT on the large scales due to organized unresolved convection from squall lines. Properties of the stochastic model for CMT are developed below in a test column model environment for the large-scale variables. The effects of CMT from the stochastic model on a large-scale convectively coupled wave in an idealized setting are presented below as a nontrivial test problem. Here, the upscale transports from stochastic effects are significant and even generate a large-scale mean flow which can interact with the convectively coupled wave.
机译:对流的未解决特征的改进的参数化是当前用于天气预报和短期气候变化的长期总体预报的计算机模型的中心挑战。观察,理论和详细的小规模数值模拟表明,从未解决的尺度到已解决的尺度的对流动量输运(CMT)是当代计算机模型的主要缺陷之一。在这里,数学和物理推理的结合被用于建立简单的随机模型,该模型捕获了由于MT线的有组织的未解决的对流而导致的大规模连续大规模大规模大规模CMT传输。下面在测试列模型环境中针对大型变量开发CMT随机模型的属性。随机模型的CMT对理想条件下的大型对流耦合波的影响在下面作为非平凡的测试问题给出。在这里,来自随机效应的高层传输是显着的,甚至产生了可以与对流耦合波相互作用的大规模平均流。

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