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Evaluation of the WRF meteorological model results during a high ozone episode in SW Poland - the role of model initial conditions

机译:在波兰西南部发生高臭氧事件期间对WRF气象模型结果的评估-模型初始条件的作用

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摘要

In meteorological, as well as air quality, modelling, input data plays an important role in the accuracy of the results, next to the model configuration. There are many sources of meteorological data available, both global and regional, and they differ not only by spatial and temporal resolution, but also by the number of observations included in the reanalysis and method of data assimilation used. In this study, the performance of the weather research and forecasting (WRF) model with two global reanalyses (ERA-Interim and NCEP FNL) used as input datasets has been assessed for a period of high tropospheric ozone concentrations. Both WRF model runs are in good agreement with observations, with IOA statistic ranging from 0.78 for wind speed to 0.98 for surface pressure. The ERA-Interim simulation showed better results for surface pressure, temperature and wind speed, while the performance of both datasets for parameters related to atmospheric moisture (e.g., dew point temperature) was comparable.
机译:在气象以及空气质量建模中,除了模型配置外,输入数据在结果准确性中也起着重要作用。全球和地区都有许多可用的气象数据来源,它们不仅在空间和时间分辨率上不同,而且在重新分析和使用的数据同化方法中所包括的观测数量上也不同。在这项研究中,对流层臭氧浓度高的时期,已经评估了使用两个全球再分析(ERA-Interim和NCEP FNL)作为输入数据集的天气研究和预报(WRF)模型的性能。两种WRF模型运行都与观测结果非常吻合,IOA统计范围从风速的0.78到表面压力的0.98。 ERA-Interim模拟显示了更好的表面压力,温度和风速结果,而与大气湿度(例如露点温度)相关的两个数据集的性能均相当。

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