Abstract This study aimed to improve the estimation of blowing snow events for predicting expressway closures. The Japan Meteorological Agency mesoscale model analysis with a grid resolution of 5 km was dynamically downscaled to 1 km using the SCALE meteorological model in the domain including Hokkaido, Japan, in the period from 1 November 2017 to 28 February 2018. This study focused on the E5 expressway, run by East Nippon Expressway Co., Ltd., in Hokkaido, where closures frequently occur as a result of low visibility due to blowing snow in winter. The blowing snow potential was evaluated in terms of the minimum driver visibility estimated by an empirical relation among wind speed, air temperature, and snowfall intensity. Because the downscaling overestimated wind speed, a simple bias correction was applied. The downscaling produced small-scale snow cloud streaks that led to blowing snow, although snowfall spots were often mispositioned. In contrast, the mesoscale model analysis did not produce such small-scale phenomena, and thus the blowing snow potential matched closures only when the snowfall was caused by synoptic-scale disturbances.

中文翻译：

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预测高速公路因吹雪事件而关闭

摘要 本研究旨在改进吹雪事件的估计，以预测高速公路封闭。2017 年 11 月 1 日至 2018 年 2 月 28 日期间，日本气象厅使用 SCALE 气象模型将网格分辨率为 5 km 的中尺度模型分析动态缩小到 1 km。 E5高速公路，由东日本高速公路有限公司运营，位于北海道，由于冬季吹雪，能见度低，因此经常关闭。根据风速、气温和降雪强度之间的经验关系估计的最低驾驶员能见度来评估吹雪潜力。由于降尺度高估了风速，因此应用了简单的偏差校正。降尺度产生了小规模的雪云条纹，导致吹雪，尽管降雪点经常定位错误。相比之下，中尺度模型分析并没有产生这种小尺度现象，因此只有当降雪是由天气尺度扰动引起时，吹雪势才匹配闭合。