Abstract Recently, the mesoscale model GRAMM-SCI has been further developed to make use of the freely available global ERA5 reanalysis dataset issued by the ECMWF. In this study, first results are discussed for the federal state of Styria, which is situated in the eastern Alps of Austria. Additional simulations were made with the mesoscale model WRF, which serve as a benchmark in this work. The model runs covered one week in summer and another one in winter dominated by fair weather conditions. These were characterized by the development of complex mountain wind systems in the Alps, which play an important role for the dispersion of pollutants. Regarding the bias and the root mean square error both models perform very well in comparison with existing studies for Alpine areas and are able to capture the main features of observed surface flows such as valley-wind systems or katabatic flows at slopes. In addition, observed calm wind conditions at many stations during the winter period were reproduced by the models. However, the correct simulation of wind directions in these conditions was found to be extremely challenging. Existing model quality criteria for wind direction seem to be too strict for low-wind-speed conditions. Therefore, based on theoretical and empirical considerations, a new model evaluation benchmark for wind direction is proposed, which takes into account the random nature of horizontally meandering flows in stagnant weather situations.

中文翻译：

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使用 WRF 和 GRAMM-SCI 的东部高山地区中尺度流场模拟的比较研究

摘要 最近，中尺度模型 GRAMM-SCI 得到进一步发展，以利用 ECMWF 发布的免费全球 ERA5 再分析数据集。在这项研究中，讨论了位于奥地利东部阿尔卑斯山的施蒂里亚联邦州的第一个结果。使用中尺度模型 WRF 进行了额外的模拟，作为这项工作的基准。该模型在夏季运行一周，冬季运行一周，主要是晴朗的天气条件。这些特点是阿尔卑斯山复杂的山风系统的发展，对污染物的扩散起着重要的作用。关于偏差和均方根误差，与现有的高山地区研究相比，这两个模型都表现得非常好，并且能够捕捉观察到的地表流的主要特征，例如谷风系统或斜坡上的降波流。此外，这些模型还再现了冬季在许多站点观察到的平静风况。然而，发现在这些条件下正确模拟风向极具挑战性。现有的风向模型质量标准对于低风速条件似乎过于严格。因此，基于理论和经验的考虑，提出了一种新的风向模型评估基准，该基准考虑了停滞天气情况下水平蜿蜒流的随机性。