This paper presents a statistical analysis of the motion of hail-producing supercells in Germany based on data from a radar-based cell detection and tracking algorithm and a mesocyclone detection algorithm. The parameterization of supercell motion by Bunkers et al. (2000), originally developed using storm data from the United States, is evaluated regarding its applicability in Central Europe, where storm environments have other dynamic and thermodynamic characteristics owing to different geographical features. As a first step, the motion of 354 observed supercells in the warm season (April to September) 2013–2016 is compared to the motion obtained with the original parameterization. The cells are classified as right-moving or left-moving supercells due to their motion direction with regard to the vertical wind shear of the environment, which is calculated using high-resolution model analyses. Afterwards, the accuracy of the parameterization is checked for both motion classes, as well as for classifications according to the lifetime, track length, and severity proxies of the cells. Clear differences between observed and parameterized motion are obtained for all categories, calling for an adjustment of the parameterization in a second step. This adjusted parameterization improves the storm motion estimation for most of the storm categories. A better storm motion estimation improves the calculation of storm-relative helicity, enabling a more reliable nowcasting and forecasting of supercell potential.

中文翻译：

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评估德国地堡产生冰雹的超级单体的风暴运动及其风暴相对螺旋度

本文基于基于雷达的细胞检测和跟踪算法以及中气旋检测算法的数据，对德国产生冰雹的超级单体的运动进行了统计分析。Bunkers 等人的超胞运动参数化。（2000）最初使用美国的风暴数据开发，评估了其在中欧的适用性，其中由于不同的地理特征，风暴环境具有其他动态和热力学特征。第一步，将 2013-2016 年暖季（4 月至 9 月）观察到的 354 个超级单体的运动与通过原始参数化获得的运动进行比较。由于它们相对于环境的垂直风切变的运动方向，这些单元被分类为向右移动或向左移动的超级单元，这是使用高分辨率模型分析计算得出的。然后，检查两个运动类别的参数化准确性，以及根据单元的寿命、轨迹长度和严重性代理进行的分类。所有类别的观察运动和参数化运动之间存在明显差异，需要在第二步中调整参数化。这种调整后的参数化改进了大多数风暴类别的风暴运动估计。更好的风暴运动估计改进了风暴相对螺旋度的计算，从而实现了更可靠的超级单体潜力的临近预报和预测。以及根据细胞的寿命、轨迹长度和严重程度代理进行分类。所有类别的观察运动和参数化运动之间存在明显差异，需要在第二步中调整参数化。这种调整后的参数化改进了大多数风暴类别的风暴运动估计。更好的风暴运动估计改进了风暴相对螺旋度的计算，从而实现了更可靠的超级单体潜力的临近预报和预测。以及根据细胞的寿命、轨迹长度和严重程度代理进行分类。所有类别的观察运动和参数化运动之间存在明显差异，需要在第二步中调整参数化。这种调整后的参数化改进了大多数风暴类别的风暴运动估计。更好的风暴运动估计改进了风暴相对螺旋度的计算，从而实现了更可靠的超级单体潜力的临近预报和预测。