初始和边界条件对使用高分辨率WRF模式模拟恶劣天气事件的影响。2017年8月11日波兰derecho事件的案例研究

Mariusz Figurski, G. Nykiel, A. Jaczewski, Z. Baldysz, M. Wdowikowski
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引用次数: 5

摘要

在气候变化的时代,对恶劣天气事件的精确模拟是一项挑战。通过正确和准确地进行模拟,可以更好地研究和理解这些现象。在本文中,我们验证了不同的初始条件和边界条件如何影响使用天气研究与预报模式(WRF)进行的模拟质量。在我们的分析中,我们选择了2017年8月11日发生在波兰的derecho事件,这是近年来最强烈和最具破坏性的事件。高分辨率模拟在UTC时间00点和12点(2017年8月11日)进行初始化,使用来自四个全球模式的初始条件和边界条件:国家环境预报中心(NCEP)的全球预报系统(GFS)、欧洲中期天气预报中心(ECMWF)开发的综合预报系统(IFS)、全球数据同化系统(GDAS)和ERA5。最后,我们使用压力和模型水平的数据分别进行了计算。根据地面和雷达数据对结果进行了评估。我们发现使用GDAS和GFS模式在12 UTC的数据的模拟更准确,而ERA5给出了最差的预测。然而,所有模式在模拟极端降水和阵风时都具有低探测概率和高误报率的特点。
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The impact of initial and boundary conditions on severe weather event simulations using a high-resolution WRF model. Case study of the derecho event in Poland on 11 August 2017
Precise simulations of severe weather events are a challenge in the era of changing climate. By performing simulations correctly and accurately, these phenomena can be studied and better understood. In this paper, we have verified how different initial and boundary conditions affect the quality of simulations performed using the Weather Research and Forecasting Model (WRF). For our analysis, we chose a derecho event that occurred in Poland on 11 August 2017, the most intense and devastating event in recent years. High-resolution simulations were conducted with initialization at 00 and 12 UTC (11 August 2017) using initial and boundary conditions derived from the four global models: Global Forecast System (GFS) from the National Centers for Environmental Prediction (NCEP), Integrated Forecast System (IFS) developed by the European Center for Medium-Range Weather Forecasts (ECMWF), Global Data Assimilation System (GDAS) and ERA5. For the last, we made separate calculations using data at the pressure and model levels. The results were evaluated against surface and radar data. We found that the simulations that used data from the GDAS and GFS models at 12 UTC were the more accurate, while ERA5 gave the worst predictions. However, all models were characterized by a low probability of detection and a high number of false alarms for simulations of extreme precipitation and wind gusts.
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