春夏季海表面温度冷斑对黄海海雾分布的影响
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1.中国海洋大学深海圈层与地球系统前沿科学中心;2.中国海洋大学海洋与大气学院;3.山东省气象防灾减灾重点实验室;4.山东省气象科学研究所

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P47

基金项目:

国家自然科学基金面上项目(42275071);国家自然科学基金联合(U2342214)


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Impact of spring-summer cold SST patches on the distribution of the Yellow Sea fog
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1.Frontiers Science Center for Deep Ocean Multispheres and Earth System,Ocean University of China;2.College of Oceanic and Atmospheric Sciences, Ocean University of China;3.Key Laboratory for Meteorological Disaster Prevention and Mitigation of Shandong;4.Shandong Institute of Meteorological Sciences

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    摘要:

    海雾是威胁黄海海域船舶航行与港口活动安全的重要灾害性天气。本研究使用多种观测资料结合WRF模式(Weather Research and Forecasting Model),研究春夏季海表面温度(Sea Surface Temperature, SST)冷斑对黄海海雾分布的影响。基于71年的船舶观测发现,在青岛、成山头、苏北浅滩附近海域等冷斑区,春夏季黄海海雾的发生频率较海盆平均雾频偏高约10%。对比不同分辨率的SST数据集与浮标观测发现,GHRSST(Group for High-Resolution Sea Surface Temperature)对冷斑强度低估最小。进而设计了一个冷斑去除方案,并分别以GHRSST和去除冷斑后的GHRSST作下边界条件开展控制实验和无冷斑试验,使用预报海雾效果较优的Lin微物理方案对2014—2016年4—7月的黄海海雾进行后报。两组试验对比结果表明:冷斑通过增大近海面气温与海温差,增强大气稳定度,形成有利于海雾生成与维持的稳定层结。冷斑上空相对湿度增加、风速减小,并且液态水含量显著偏高,多年平均雾频增加约15%。进一步对比两组后报试验发现,冷斑使黄海海雾的误报率显著升高,这说明仅通过提高下边界条件的SST分辨率、增强冷斑,无法显著改善黄海海雾的预报技巧。

    Abstract:

    Sea fog is a major hazardous weather phenomenon that threatens the safety of ship navigation and port operations in the Yellow Sea waters. In this study, we use multiple observational datasets and the Weather Research and Forecasting (WRF) model to investigate the impacts of spring and summer Sea Surface Temperature (SST) cold patches on the distribution of the Yellow Sea fog. Based on 71 years of shipboard observations, we find that the occurrence frequency of the Yellow Sea fog in cold patch areas, including the waters near Qingdao, Chengshantou and the Subei Shoal, is approximately 10% higher than the basin-averaged fog frequency in spring and summer. Comparison between SST datasets of different resolutions and buoy observations shows that the Group for High-Resolution Sea Surface Temperature (GHRSST) dataset has the smallest underestimation of cold patch intensity. We further develop a cold patch removal scheme, and conduct the control experiment and no-cold-patch experiment by taking the original GHRSST and the cold-patch-removed GHRSST as the lower boundary conditions, respectively. The Lin microphysics scheme, which delivers superior performance in sea fog forecasting, is adopted to perform hindcasts of the Yellow Sea fog from April to July during 2014 to 2016. Comparison results between the two experiments show that cold patches enhance atmospheric stability by increasing the air-sea temperature difference near the sea surface, thus forming a stable stratification conducive to the formation and maintenance of the Yellow Sea fog. Over the cold patches, relative humidity increases, wind speed decreases, and liquid water content is significantly higher, leading to an approximately 15% increase in the multi-year averaged fog frequency. Further comparison between the two sets of hindcast experiments reveals that cold patches cause a significant rise in the false alarm rate of the Yellow Sea fog. This indicates that merely improving the SST resolution of the lower boundary conditions and enhancing cold patches cannot significantly improve the forecast skill for the Yellow Sea fog.

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  • 收稿日期:2026-03-23
  • 最后修改日期:2026-05-06
  • 录用日期:2026-05-07
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