Abstract. Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, and they are as hazardous and fatal as many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study proposes a physically based definition of derechos that contains the key features of derechos described in the literature and allows their automated objective identification using either observations or model simulations. The automated detection is composed of three algorithms: the Flexible Object Tracker algorithm to track mesoscale convective systems (MCSs), a semantic segmentation convolutional neural network to identify bow echoes, and a comprehensive algorithm to classify MCSs as derechos or non-derecho events. Using the new approach, we develop a novel high-resolution (4 km and hourly) observational dataset of derechos over the United States east of the Rocky Mountains from 2004 to 2021. The dataset is analyzed to document the derecho climatology in the United States. Many more derechos (increased by ~50–400 %) are identified in the dataset (~31 events per year) than in previous estimations (~6–21 events per year), but the spatial distribution and seasonal variation patterns resemble earlier studies with a peak occurrence in the Great Plains and Midwest during the warm season. In addition, around 20 % of damaging gust (≥ 25.93 m s^-1) reports are produced by derechos during the dataset period over the United States east of the Rocky Mountains. The dataset is available at https://doi.org/10.5281/zenodo.10884046 (Li et al., 2024).

中文翻译：

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美国基于弓形回波机器学习识别的 derecho 气候学（2004-2021）


摘要。由于持续大范围的强风，德雷乔斯对人类安全和财产构成重大威胁，并且与许多龙卷风和飓风一样危险和致命。然而，由于缺乏时空连续观测以及定义该现象所采用的复杂标准，自动检测 derechos 仍然具有挑战性。这项研究提出了基于物理的 derechos 定义，其中包含文献中描述的 derechos 的关键特征，并允许使用观察或模型模拟对其进行自动客观识别。自动检测由三种算法组成：用于跟踪中尺度对流系统 (MCS) 的灵活对象跟踪器算法、用于识别弓形回波的语义分割卷积神经网络以及用于将 MCS 分类为 derechos 或非 derecho 事件的综合算法。使用新方法，我们开发了 2004 年至 2021 年美国落基山脉以东 derechos 的新型高分辨率（4 公里，每小时）观测数据集。分析该数据集以记录美国的 derecho 气候。数据集中识别出的 derechos（增加了约 50-400%）（每年约 31 起事件）比之前的估计（每年约 6-21 起事件）多得多，但空间分布和季节变化模式与早期研究相似在暖季期间，大平原和中西部地区出现高峰。此外，大约 20% 的破坏性阵风（≥ 25.93 m s ^-1 ）报告是在数据集期间美国落基山脉以东的 derechos 产生的。该数据集可在 https://doi.org/10.5281/zenodo.10884046 上获取（Li et al., 2024）。