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不同边界层参数化方案对江苏地区一次平流雾过程的模拟影响

崔驰潇 包云轩 袁成松 周林义 焦圣明 宗晨

崔驰潇, 包云轩, 袁成松, 周林义, 焦圣明, 宗晨. 不同边界层参数化方案对江苏地区一次平流雾过程的模拟影响[J]. 大气科学, 2018, 42(6): 1344-1362. doi: 10.3878/j.issn.1006-9895.1801.17212
引用本文: 崔驰潇, 包云轩, 袁成松, 周林义, 焦圣明, 宗晨. 不同边界层参数化方案对江苏地区一次平流雾过程的模拟影响[J]. 大气科学, 2018, 42(6): 1344-1362. doi: 10.3878/j.issn.1006-9895.1801.17212
Chixiao CUI, Yunxuan BAO, Chengson YUAN, Linyi ZHOU, Shenming JIAO, Chen ZONG. Influence of Different Boundary Layer Parameterization Schemes on the Simulation of an Advection Fog Process in Jiangsu[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(6): 1344-1362. doi: 10.3878/j.issn.1006-9895.1801.17212
Citation: Chixiao CUI, Yunxuan BAO, Chengson YUAN, Linyi ZHOU, Shenming JIAO, Chen ZONG. Influence of Different Boundary Layer Parameterization Schemes on the Simulation of an Advection Fog Process in Jiangsu[J]. Chinese Journal of Atmospheric Sciences, 2018, 42(6): 1344-1362. doi: 10.3878/j.issn.1006-9895.1801.17212

不同边界层参数化方案对江苏地区一次平流雾过程的模拟影响

doi: 10.3878/j.issn.1006-9895.1801.17212
基金项目: 

国家公益性行业(气象)科研专项 GYHY201306043

江苏省科技支撑计划项目 BE2015732

江苏省气象局北极阁基金项目 BJG201404

详细信息
    作者简介:

    崔驰潇, 女, 1988年出生, 博士研究生, 主要从事交通气象、气象灾害监测与预警研究。E-mail:cuichixiao@163.com

    通讯作者:

    包云轩, E-mail:baoyunxuan@163.com

  • 中图分类号: P426.4

Influence of Different Boundary Layer Parameterization Schemes on the Simulation of an Advection Fog Process in Jiangsu

Funds: 

Special Research Fund for Meteorology in the Public Interest of China GYHY201306043

Science and Technology Support Program of Jiangsu Province BE2015732

Meteorological Bureau Foundation of Jiangsu BJG201404

  • 摘要: 边界层参数化方案的选取在平流雾的预报准确度上起着决定性的作用。本文利用WRF模式对2013年3月18~19日发生在江苏地区的一次平流雾过程进行数值模拟试验,对耦合不同闭合方式边界层参数化方案的试验结果与实测气象数据进行对比分析,评估了他们对此次平流雾的模拟效果,探讨了边界层高度对此次平流雾的生成和发展的影响。研究结果表明:(1)耦合不同边界层方案的WRF模式对地面气象要素的模拟结果均呈现气温偏低、湿度和风速偏大的特征。(2)QNSE方案对气温的模拟能力最强;ACM2方案对相对湿度的模拟性能最好;YSU方案对风速的模拟效果最佳。不同边界层方案的模拟结果在垂直方向上的差别主要表现在低空相对湿度上:QNSE方案预报的湿度更大。(3)综合TS(Threat Score)和BS(Bias Score)两个评分指标来看,ACM2方案对雾区分布的模拟效果最好。三个边界层方案对此次平流雾的模拟结果在江苏沿海站点的预报评分较高,在距海较远站点的预报评分表现较差。YSU方案对东南沿海地区的雾区预报评分较高;QNSE方案对长江沿江区域的雾区预报评分较高;ACM2方案对沿海地区、尤其对沿海北部地区的有较好的预报效果。(4)QNSE方案对此次平流雾的生成时间、出现地点预报比较准确。(5)平流雾的生成与发展阶段模拟雾区覆盖范围与边界层高度关系十分紧密,适当强度的湍流混合作用有助于平流雾在地面的生成与发展;但是过强的湍流混合作用会导致大雾过早的消散。
  • 图  1  2013年3月(a)18日20:00、(b)19日00:00、(c)19日07:00和(d)19日12:00江苏省地面能见度(阴影;单位:m)和相对湿度(等值线;单位:%)分布

    Figure  1.  Spatial distributions of ground visibility (shaded; units: m) and relative humidity (contours; units: %) in Jiangsu Province at (a) 2000 BT (Beijing time) 18, (b) 0000 BT 19, (c) 0700 BT 19, and (d) 1200 BT 19 March 2013

    图  2  2013年3月18日20:00(第一行)和19日08:00(第二行)天气形势图:(a、d)500 hPa;(b、e)925 hPa;(c、f)地面。黑色实线为位势高度场(单位:gpm),红线为温度场(单位:℃)

    Figure  2.  Synoptic weather patterns at 2000 BT 18 (first line) and 0800 BT 19 (second line) March 2013: (a, d) 500 hPa; (b, e) 925hPa; (c, f) the surface. Black solid lines are geopotential height (units: gpm), and red solid lines show temperature (units: ℃)

    图  3  (a)模拟区域设置与(b)D03地形高度

    Figure  3.  (a) Simulation domains and (b) terrain height in D03 of WRF model

    图  4  不同边界层方案模拟3月19日地面气象要素的泰勒图。参考点REF为实测场,预报场到原点的距离代表其相对于REF的标准差;预报场在图中方位角的余弦代表其余观测的相关系数;预报相对于REF的距离代表其与REF的均方根误差

    Figure  4.  Taylor diagram of various near-surface meteorological elements simulated by different PBL schemes compared to the observations. REF means observations. The distance between a given forecast element and the origin point represents the standard deviation of the forecasted element to REF. The cosine of the azimuth of a given forecast field stands for its correlation with REF; the distance between the value of a given forecast element and REF represents the root mean square error

    图  5  2013年3月18日20:00射阳站(第一行)、南京站(第二行)实测探空(a、d)温度(单位:℃)、(b、c)相对湿度和(c、f)风速(单位:m s-1)与模式模拟值的垂直变化对比

    Figure  5.  Vertical profiles of the observed (OBS) and simulated temperature (units: ℃), relative humidity, and wind speed (units: m s-1) at 2000 BT 18 March 2013 at Sheyang station (first line) and Nanjing station (second line)

    图  6  图 5,但为2013年3月19日08:00

    Figure  6.  Same as Fig. 5, but for 0800 BT 19 March 1 2013

    图  7  不同边界层方案模拟的TS(上)和BS(下)评分区域分布:(a、d)YSU方案;(b、e)QNSE方案;(c、f)ACM2方案

    Figure  7.  TS (Threat Score, first line) and BS (Bias Score, second line) distributions of fog area simulations based on different boundary layer parameterization schemes: (a, d) YSU scheme, (b, e) QNSE scheme, (c, f) ACM2 scheme

    图  8  2013年3月(a1–a3)18日20:00、(b1–b3)19日00:00和(c1–c3)19日07:00距离地面10 m高度液态水含量大于0.05 g kg−1的模拟区域与地面实测能见度的比较:YSU方案(左列);QNSE方案(中间列);ACM2方案(右列)。阴影为模拟液态水含量(单位:g kg−1),“•”代表测站能见度小于1 km,“×”代表测站能见度大于1 km.

    Figure  8.  Comparison between the simulated liquid water content at 10 m level above the surface that is greater than 0.05 g kg−1 and the distribution of the observed visibility at (a1–a3) 2000 BT 18 March, (b1–b3) 0000 BT 19 March, and (c1–c3) 0700 BT 19 March, 2013: YSU scheme (left column); QNSE scheme (middle column); ACM2 scheme (right column). Shaded areas denote the simulated liquid water content (units: g kg−1), "•" denotes the stations where the observed visibility is less than 1 km and "×" denotes the stations where the observed visibility is more than 1 km

    图  9  2013年3月(a)18日20:00沿33.5°N和19日(b)00:00、(c)07:00沿32.5°N的边界层高度的经度—高度剖面

    Figure  9.  Longitudevertical cross sections of the boundary layer height along (a) 33.5°N and (b, c) 32.5°N at (a) 2000 BT 18 March, (b) 0000 BT 19 March, and (c) 0700 BT 19 March, 2013

    图  10  图 4,但为3月28日

    Figure  10.  Same as Fig. 4, but for 28 March

    图  11  如皋站3月28日(a)实测能见度(Vis;单位:m)和相对湿度以及(b)YSU方案、(c)QNSE方案和(d)ACM2方案下模拟液态水含量(LWC;单位:g kg-1)、边界层高度(PBLH;单位:m)的时间变化曲线

    Figure  11.  a) Temporal evolutions of observed visibility (Vis; units : m) and relative humidity on March 28th of 2013 at Rugao station. Temporal evolutions of simulated liquid water content (LWC; units: g kg-1) and boundary layer height (PBLH; units: m) with (b) the YSU scheme, (c) the QNSE scheme, and (d) the ACM2 scheme on March 28th of 2013 at Rugao station

    表  1  各边界层参数化方案对地面气象要素模拟平均偏差值

    Table  1.   Mean biases of various near-surface meteorological elements with different PBL schemes

    平均偏差MB
    参数化方案 T2/℃ RH2 WS10/m s-1
    YSU -1.07 9.77% 0.74*
    QNSE -0.30* 13.02% 1.14
    ACM2 -0.65 8.41%* 1.06
    *表示该要素中模拟值与实测值最为接近的值。
    下载: 导出CSV
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  • 收稿日期:  2017-08-11
  • 网络出版日期:  2018-01-31
  • 刊出日期:  2018-11-15

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