Propagating in the lower troposphere, the trapped lee waves (TLWs) generate severe turbulence over a large area in the afternoon and thus have a significant impact on aviation safety and atmospheric environment. Due to the lack of high temporal and spatial resolution observations, the diurnal variation of the TLWs remains unknown. This study employed the U-Net deep learning model to identify 3,533 images with TLWs from over thirty thousand 500-m resolution Fengyun-4 satellite images at intervals of a few minutes during the cold season from 2020 to 2023. The results show that the wavelength increases in the afternoon (from 12:00 to 16:00 LST) with high low-level winds and low atmospheric stability while the amplitude and propagation area continually increase during the daytime (from 09:00 to 16:00 LST) as the boundary layer becomes turbulent. These findings explain environmental disasters related to severe turbulence in the afternoon over the mountainous region.

中文翻译：

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利用风云四号卫星图像和 U-Net 网络观测被困的李波


在对流层低层传播的被困背风波 （TLW） 在下午产生大面积的严重湍流，从而对航空安全和大气环境产生重大影响。由于缺乏高时间和空间分辨率的观测，TLWs 的日变化仍然未知。本研究采用 U-Net 深度学习模型，在 2020 年至 2023 年的寒冷季节，每隔几分钟从超过 3,000 m 分辨率的风云四号卫星图像中识别 3,533 张带有 TLW 的图像。结果表明，随着边界层变得湍流，下午（从 12：00 到 16：00 LST）波长增加，低层风和大气稳定性低，而振幅和传播面积在白天（从 09：00 到 16：00 LST）不断增加。这些发现解释了与山区下午严重湍流相关的环境灾害。