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2018年2月琼州海峡持续性海雾过程的数值模拟分析

王慧 林建 马占山 刘达 吴晓京

王慧, 林建, 马占山, 等. 2022. 2018年2月琼州海峡持续性海雾过程的数值模拟分析[J]. 大气科学, 46(5): 1267−1280 doi: 10.3878/j.issn.1006-9895.2203.21265
引用本文: 王慧, 林建, 马占山, 等. 2022. 2018年2月琼州海峡持续性海雾过程的数值模拟分析[J]. 大气科学, 46(5): 1267−1280 doi: 10.3878/j.issn.1006-9895.2203.21265
WANG Hui, LIN Jian, MA Zhanshan, et al. 2022. Numerical Simulation and Analysis of the Persistent Sea Fog in the Qiongzhou Strait in February 2018 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(5): 1267−1280 doi: 10.3878/j.issn.1006-9895.2203.21265
Citation: WANG Hui, LIN Jian, MA Zhanshan, et al. 2022. Numerical Simulation and Analysis of the Persistent Sea Fog in the Qiongzhou Strait in February 2018 [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(5): 1267−1280 doi: 10.3878/j.issn.1006-9895.2203.21265

2018年2月琼州海峡持续性海雾过程的数值模拟分析

doi: 10.3878/j.issn.1006-9895.2203.21265
基金项目: 国家重点研发计划项目2021YFC3090205、2019YFC1510104
详细信息
    作者简介:

    王慧,女,主要从事海洋天气预报和研究工作。E-mail: wangh1@cma.cn

    通讯作者:

    马占山,E-mail: mazs@cma.cn

  • 中图分类号: P47

Numerical Simulation and Analysis of the Persistent Sea Fog in the Qiongzhou Strait in February 2018

Funds: National Key R&D Program of China (Grants 2021YFC3090205, 2019YFC1510104)
  • 摘要: 2018年2月春节期间琼州海峡发生持续性大雾天气,造成大量船舶停航。本文结合葵花8号卫星反演海雾产品、琼州海峡沿岸站点能见度观测数据及美国国家环境预报中心NCEP(National Centers for Environmental Prediction) 提供的FNL(Final Analysis)客观分析资料,对2018年2月18~20日的大雾过程进行了天气学成因分析,并进一步利用CMA-MESO(Global and Regional Assimilation and Prediction System)高分辨率数值模式从边界层方案、模式垂直分层以及海雾能见度算法三个方面进行敏感性试验,以找出模拟效果更好的模式设置方案。研究结果表明:大雾期间华南近海海温较常年平均偏低,受地面冷高压南下补充的弱冷空气影响,偏东暖湿气流流经冷海面并快速凝结。而数值模拟对比试验显示,采用YSU(Yonsei University)边界层方案、边界层垂直层次加密及美国国家海洋大气局预报系统实验室(FSL/NOAA)的海雾诊断方案(简称FSL)对改进能见度预报效果显著:YSU边界层方案比MRF(Medium Range Forecast Model)边界层方案对该次大雾过程的分布范围和最低能见度出现的时间模拟效果更优;模式低层分层加密可更好体现出低能见度的演变过程;通过能见度算法与实况对比,基于模式预报性能较好的湿度和温度预报而来的FSL算法,其能见度预报与站点实况最为接近。
  • 图  1  CMA-MESO模式垂直分层加密前(红色线条)后(蓝色线条)高度对比:(a)加密前后所有层次对比;(b)加密后2 km以下垂直分层放大。黑色纵坐标为垂直高度(单位:km),红色纵坐标为原始模式垂直层次,蓝色纵坐标为加密后模式垂直层次

    Figure  1.  Height of the vertical levels in CMA-MESO model, where the red line represents the initial layers of the model, and the blue line represents the increased model layers: (a) Comparison of all levels before and after increased model layers; (b) vertical stratification amplification below 2 km after increased model layers. The black vertical level is the vertical height (units: km), the red vertical level is the original mode vertical level, and the blue vertical level is the increased mode vertical level

    图  8  基于TYM和加密模式的徐闻站(a)和海口站(b)的能见度算法对比,图中标值为均方根误差(单位:km)

    Figure  8.  Comparison of the visibility of (a) Xuwen station and (b) Haikou station using multiple algorithms of visibility based on TYM and increased model of vertical levels (units: km); the values in the figure are RMSE

    图  2  2018年2月17日02:00至20日20:00徐闻站(红色实线)和海口站(蓝色实线)能见度(单位:km)观测,图中绿色方框表示能见度低于1 km的大雾时段

    Figure  2.  Visibility observations (units: km) of Xuwen station (red line) and Haikou station (blue line) from 0200 BJT (Beijing time) 17 February to 2000 BJT 20 February in 2018. The period of dense fog with visibility less than 1 km is highlighted by the green box

    图  3  2018年2月18日02:00至20日11:00徐闻站(59754)观测的气压(黑色实线,单位:hPa)、2 m温度(红色实线,单位:°C)、2 m露点温度(蓝色实线,单位:°C)、10 m风(蓝色风向杆)、能见度(蓝色数字,单位:km)以及天气现象(蓝色天气符号)

    Figure  3.  Observed pressure (black line, units: hPa), 2 m temperature (red line, units: °C), 2 m dew-point temperature (blue line, units: °C), 10 m wind (blue wind barb, units: m s−1), visibility (blue numbers, units: km), and weather phenomena (blue symbols) of Xuwen station (No. 59754) from 0200 BJT 18 February to 1100 BJT 20 2018

    图  4  (a)2018年2月19日08:00海平面气压场(红色等值线,单位:hPa)、10 m风场(风向杆,单位:m s−1)及500 hPa高度场588 hPa等高线(蓝色等值线,单位:dagpm);(b)2月17日14:00至22日14:00琼州海峡单点(20°N,110°E)相对湿度(等值线和阴影)和风场(风向杆)时间—垂直剖面

    Figure  4.  (a) Sea level pressure (red contours, units: hPa), 10 m wind (wind barb, units: m s−1), and 500 hPa geopotential height 588 hPa contour lines (blue contours, units: dagpm) at 0800 BJT 19 February 2018; (b) vertical profiles of relative humidity (contour and shaded) and wind (wind bard, units: m s−1) of one point (20°N, 110°E) in Qiongzhou Strait from 1400 BJT 17 February to 1400 BJT 22 February

    图  5  2018年2月19日(a)海表温度距平(单位:°C)和(b)02:00气海温差(单位:°C)分布

    Figure  5.  Distributions of (a) sea surface temperature anomalies on February 19, 2018 and (b) distributions of air–sea temperature differences at 0200 BJT on February 19, 2018. Units: °C

    图  6  2018年2月18日20:00(左列)、19日02:00(中间列)和19日08:00(右列)的各模式能见度预报(单位:km)对比:(a–c)HW8卫星反演海雾(深灰色为海雾,灰色为疑似海雾);(d–f)TYM模式;(g–i)MESO_MRF模式;(j–l)MESO_MRF_HR模式;(m–o)MESO_YSU_HR模式

    Figure  6.  The predictions Predictions of visibility (units: km) at 2000 BJT 18 February (left column), 0200 BJT 19 February (middle column), and 0800 BJT February (right column) in 2018: (a–c) Himawari-8 (dark gray is for sea fog, gray is for suspected sea fog); (d–f) TYM model; (g–i) MESO_MRF model; (j–l) MESO_MRF_HR model; (m–o) MESO_YSU_HR model

    图  7  2018年2月18日14:00至20日08:00徐闻站各模式预报因子对比:(a)10 m风速(单位:m s−1);(b)10 m风向;(c)2 m相对湿度;(d)2 m温度(单位:°C);(e)2 m露点温度(单位:°C);(f)温度露点差(单位:°C)

    Figure  7.  Comparison of the predicting factors of the models from 1400 BJT 18 February to 0800 BJT 20 February 2018: (a) 10 m wind speed (units: m s−1), (b) 10 m wind direction, (c) 2 m relative humidity, (d) 2 m temperature (units: °C), (e) 2 m dew-point temperature (units: °C), and (f) dew-point depression (units: °C)

    图  9  图6,但为FSL算法的能见度预报(单位:km),去掉了TYM模式预报(第二行)

    Figure  9.  Same as Figure 6, but for predictions of visibility (units: km) using the FSL method except for the results of TYM (the second row in Figure 6)

    表  1  数值模拟方案对比

    Table  1.   1 Comparison of the numerical simulation scheme

    方案数值模式边界层方案垂直分层
    TYMCMA-TYMMRF50
    MESO_MRFCMA-MESOMRF50
    MESO_MRF_HRCMA-MESOMRF58
    MESO_YSU_HRCMA-MESOYSU58
    下载: 导出CSV

    表  2  各模式预报因子均方根误差对比

    Table  2.   Comparison for the RSME of models


    风速/ m s−1风向2 m相对湿度2 m温度/°C2 m露点温度/°C2米温度露点差/°C
    TYM3.6373.19°5.59%2.391.331.32
    MESO_MRF4.2467.52°6.81%1.891.101.28
    MESO_MRF_HR4.5466.16°6.75%1.711.111.26
    MESO_YSU_HR4.1160.52°5.00%1.230.920.90
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-12-31
  • 录用日期:  2022-06-14
  • 网络出版日期:  2022-06-15
  • 刊出日期:  2022-09-22

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