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Reconstruction of an Intense Mesoscale Convective System in the Midwestern United States Using the Weather Research and Forecasting (WRF) Model in the Simulation Mode

机译:在仿真模式下使用天气研究和预测(WRF)模型在美国中西部的强烈介质对流系统重建

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Mesoscale convective systems (MCSs) are large clusters of thunderstorms that act as a single system generating localized extreme precipitation and causing disastrous flooding and destruction in the central United States. To enhance our modeling of such storm events, especially under future climate projections, this study focuses on modeling MCSs through the use of the weather research and forecasting (WRF) model running in the simulation mode, i.e., without any nudging or other data assimilation techniques. In this study, the WRF model is run using several combinations of the different model parameterization schemes and is used to reconstruct an intense historical MCS over the Midwestern United States. The simulation results are then compared to the observation. The model's performance is evaluated through the use of a few statistical tests as well as a visual comparison, and the best simulation is chosen based on the statistical tests as well as the location, intensity, and texture of the simulated storm event. From this exercise, we find that the WRF model, running in the simulation mode, has the capability of reproducing intense historical MCSs relatively well over the Midwestern United States under the appropriate model parameterization scheme combination.
机译:Mesoscale对流系统(MCS)是雷暴的大集群,充当一个系统的单一系统,产生局部极端降水并导致美国中部地区的灾难性洪水和破坏。为了提高我们对这种风暴事件的建模,特别是在未来的气候预测下,本研究侧重于使用在模拟模式下运行的天气研究和预测(WRF)模型来建模MCS,而无需任何亮度或其他数据同化技术。在这项研究中,WRF模型使用不同型号参数化方案的多种组合来运行,并且用于重建美国中西部的强烈历史MCS。然后将模拟结果与观察结果进行比较。模型的性能通过使用少数统计测试以及视觉比较来评估,并且基于统计测试的最佳模拟以及模拟风暴事件的位置,强度和纹理。从这个练习中,我们发现WRF模型,在仿真模式下运行,在适当的模型参数化方案组合下,在美国中西部地区的剧烈历史MCS的能力相对较好。

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