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包含冻结过程的广义位温及位涡特征分析

周括 冉令坤 齐彦斌 高枞亭

周括, 冉令坤, 齐彦斌, 等. 2020. 包含冻结过程的广义位温及位涡特征分析[J]. 大气科学, 44(4): 816−834 doi:  10.3878/j.issn.1006-9895.1908.19154
引用本文: 周括, 冉令坤, 齐彦斌, 等. 2020. 包含冻结过程的广义位温及位涡特征分析[J]. 大气科学, 44(4): 816−834 doi:  10.3878/j.issn.1006-9895.1908.19154
ZHOU Kuo, RAN Lingkun, QI Yanbin, et al. 2020. Characteristic Analysis of Generalized Potential Temperature and Potential Vorticity during Freezing [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 816−834 doi:  10.3878/j.issn.1006-9895.1908.19154
Citation: ZHOU Kuo, RAN Lingkun, QI Yanbin, et al. 2020. Characteristic Analysis of Generalized Potential Temperature and Potential Vorticity during Freezing [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(4): 816−834 doi:  10.3878/j.issn.1006-9895.1908.19154

包含冻结过程的广义位温及位涡特征分析

doi: 10.3878/j.issn.1006-9895.1908.19154
基金项目: 中国科学院战略性先导科技专项XDA17010105,国家重点研发计划项目2018YFC1507104,国家自然科学基金项目41575065、41775140
详细信息
    作者简介:

    周括,1992年出生,男,博士研究生,主要从事中尺度动力学与数值模拟研究。E-mail: iap_zhouk@163.com

    通讯作者:

    冉令坤,E-mail: rlk@mail.iap.ac.cn

  • 中图分类号: P426

Characteristic Analysis of Generalized Potential Temperature and Potential Vorticity during Freezing

Funds: Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDA17010105), National Key Research and Development Program of China (Grant 2018YFC1507104), National Natural Science Foundation of China (Grants 41575065, 41775140)
  • 摘要: 为了对比分析降水过程中不同表达形式热力学变量和位涡时空分布特点,本文针对2017年7月13~14日吉林省强降水过程,利用模式输出资料对常规位温(θ)、相当位温(θe)、包含凝结概率函数的广义位温(θGao)、包含冻结概率函数的广义位温(θWang)和同时涵盖凝结过程与冻结过程(θGu)五种不同形式位温进行计算,并分析五种对应位涡[PV(θ)、PV(θe)、PV(θGao)、PV(θWang)、PV(θGu)]与降水的关系。结果表明,引入冻结概率函数的广义位温(θWang)和对应的广义湿位涡PV(θWang)与强降水的对应性更好。θWangθGao差异集中在降水区对流层中高层5~11 km,前者始终高于后者,最大差异达2.5 K,说明冻结概率函数的引入扩大了广义位温的适用范围,更适合描述降水区湿大气非均匀饱和热力状态。五种位涡的差异主要在降水区上空12 km以下,由θGaoθWang定义的位涡PV(θGao)和PV(θWang)的正负异常中心更为明显。相比于PV(θGao)和PV(θWang)异常值更大,差异可达±0.2 PVU,这主要是由于冻结概率函数的引入增大降水区上空广义位温,促使冻结区的湿位涡异常增强。
  • 图  1  2017年7月12日00:00(左列;协调世界时,下同)、06:00(右列)(a、b)200 hPa风场(箭矢,单位:m s−1)和大于30 m s−1风速(填色,单位:m s−1)分布以及(c、d)500 hPa、(e、f)850 hPa高度场(黑色等值线,单位:gpm)和风场(箭矢,单位:m s−1)分布。(e、f)中填色表示地形高度,单位:m

    Figure  1.  (a, b) Wind field (arrows, units: m s−1) and wind speed of more than 30 m s−1 (shaded, units: m s−1) at 200 hPa, and geopotential height (black contours, units: gpm) and wind field (arrows, units: m s−1) at (c, d) 500 hPa and (e, f) 850 hPa on 12 July, 2017: 0000 UTC (left column); 0600 UTC (right column). The shaded areas denote the topography height in (e, f)

    图  2  2017年7月13日实况(左列)与模拟(右列)的6 h累积降水量(单位:mm)分布:(a,b)06:00;(c,d)12:00;(e,f)18:00

    Figure  2.  Observed (left column) and simulated (right column) 6 h accumulated precipitation (units: mm) on 13 July, 2017: (a, b) 0600 UTC; (c, d) 1200 UTC; (e, f) 1800 UTC

    图  3  2017年7月13日12:00五种位温(填色,单位:K)和模拟1 h累积降水(黑色等值线,单位:mm)叠加分布:(a)θ;(b)θe;(c)θGao;(d)θWang;(e)θGu

    Figure  3.  Five composite types of potential temperature (shaded, units: K) and simulated 1 h accumulated precipitation (black contours, units: mm) at 1200 UTC on July 13, 2017: (a) θ, (b) θe, (c) θGao, (d) θWang, and (e) θGu

    图  4  2017年7月13日12:00五种位温(黑色等值线,单位:K)沿124.7°E剖面图:(a)θ;(b)θe;(c)θGao;(d)θWang;(e)θGu。绿色实线表示模拟1 h累积降水(右侧坐标轴,单位:mm),下同

    Figure  4.  Cross sections of five types of potential temperature (black contours, units: K) along 124.7°E at 1200 UTC on 13 July, 2017: (a) θ, (b) θe, (c) θGao, (d) θWang, and (e) θGu. The green solid line denotes the simulated 1 h accumulated precipitation (the right ordinate, units: mm), the same below.

    图  5  五种位温(黑色等值线,单位:K)在(42.8°N,126.4°E)点(强降水区中的一个点,下同)的时间演变:(a)θ;(b)θe;(c)θGao;(d)θWang;(e)θGu

    Figure  5.  Time series of five types of potential temperature (black contours, units: K) at (42.8°N, 126.4°E) in heavy rainfall area : (a) θ, (b) θe, (c) θGao, (d) θWang, and (e) θGu

    图  6  2017年7月13日(a)03:00和(b)12:00 θWangθGao之差(黑色等值线,单位:K)和雪水混合比(填色,单位:g kg−1)沿124.7°E垂直剖面

    Figure  6.  Cross section of differences between θWang and θGao (black contours, units: K) and snow mixing ratio (shaded, units: g kg−1) along 124.7°E on 13 July, 2017: (a) 0300 UTC and (b) 1200 UTC

    图  7  2013年7月13~14日θWangθGao之差(黑色等值线,单位:K)在(42.8°N,126.4°E)的时间演变

    Figure  7.  Time series of differences between θWang and θGao (black contours, units: K) at (42.8°N, 126.4°E) during July 13–14, 2017

    图  8  2017年7月13日(a,c)θ与(b,d)θWang*(黑色等值线,单位:K)沿124.7°E垂直剖面:(a,b)06:00;(c,d)18:00

    Figure  8.  Cross section of (a, c) θ and (b, d) θWang* (black contours, units: K) along 124.7°E on 13 July, 2017: (a, b) 0600 UTC and (c, d) 1800 UTC

    图  9  2017年7月13日12:00同化实况资料计算得出的五种位温(黑色等值线,单位:K)沿124.7°E垂直剖面:(a)θ;(b)θe;(c)θGao;(d)θWang;(e)θGu

    Figure  9.  Cross section of five types of potential temperature calculated by assimilating the observation data (black contours, units: K) along 124.7°E at 1200 UTC on 13 July, 2017: (a) θ, (b) θe, (c) θGao, (d) θWang, and (e) θGu

    图  10  2017年7月13日12:00五种位涡(填色,单位:PVU)和模拟1 h累积降水(等值线,单位:mm)叠加图:(a)PV(θ);(b)PV(θe);(c)PV(θGao);(d)PV(θWang);(e)PV(θGu)

    Figure  10.  Five composite types of potential vorticity (shaded, unit: PVU) and simulated 1 h accumulated precipitation (contours, unit: mm) at 12:00 UTC on 13 July 2017: (a) PV(θ), (b) PV(θe), (c) PV(θGao), (d) PV(θWang), and (e) PV(θGu)

    图  11  2017年7月13日12:00五种位涡(填色,单位:PVU)沿124.7°E垂直剖面:(a)PV(θ);(b)PV(θe);(c)PV(θGao);(d)PV(θWang);(e)PV(θGu)

    Figure  11.  Cross section of five types of potential vorticity (shaded, units: PVU) along 124.7°E at 1200 UTC on July13, 2017: (a) PV(θ), (b) PV(θe), (c) PV(θGao), (d) PV(θWang), and (e) PV(θGu)

    图  12  五种位涡(填色,单位:PVU)在(42.8°N,126.4°E)点的时间演变:(a)PV(θ);(b)PV(θe);(c)PV(θGao);(d)PV(θWang);(e)PV(θGu)

    Figure  12.  Time series of five types of potential vorticity (shaded, units: PVU) located at (42.8°N, 126.4°E): (a) PV(θ), (b) PV(θe), (c) PV(θGao), (d) PV(θWang), and (e) PV(θGu)

    图  13  PV(θWang)与PV(θGao)之差(填色,单位:PVU)在(42.8°N,126.4°E)点的时间演变

    Figure  13.  Time series of differences between PV(θWang) and PV(θGao) (shaded, units: PVU) at (42.8°N, 126.4°E)

    图  14  2017年7月13日12:00同化实况资料计算得出的五种位涡(填色,单位:PVU)沿124.7°E垂直剖面:(a)PV(θ);(b)PV(θe);(c)PV(θGao);(d)PV(θWang);(e)PV(θGu)

    Figure  14.  Cross section of five types of potential vorticity calculated by assimilating the observation data (shaded, units: PVU) along 124.7°E at 1200 UTC on July 13, 2017: (a) PV(θ), (b) PV(θe), (c) PV(θGao), (d) PV(θWang), and (e) PV(θGu)

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出版历程
  • 收稿日期:  2019-04-28
  • 网络出版日期:  2020-04-01
  • 刊出日期:  2020-07-25

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