| 对流涡度矢量在暴雨诊断分析中的应用研究 |
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| 引用本文： | 赵宇,高守亭.对流涡度矢量在暴雨诊断分析中的应用研究[J].大气科学,2008,32(3):444-456. |
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| 作者姓名： | 赵宇 高守亭 |
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| 作者单位： | 1.中国科学院大气物理研究所云降水物理与强风暴实验室, 北京,100029;山东省气象台, 济南,250031;中国科学院研究生院, 北京,100049 |
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| 基金项目： | 国家自然科学基金
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中国科学院引进国外杰出人才基金
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山东省气象局资助项目 |
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| 摘 要： | 位涡在诊断分析中是一个常用且有效的物理量, 但在深对流系统中由于湿等熵面的倾斜变得较弱。因此, 本文利用高守亭等(2004)提出的新矢量——对流涡度矢量(简称CVV)来研究深对流系统, 并用对流涡度矢量诊断华北一次大范围的大到暴雨天气过程。结果表明, CVV垂直分量在中纬度对流性暴雨中有很好的指示性, 它的高值区与云中水凝物和地面降水有较好的对应关系, 暴雨区位于CVV垂直分量高值区附近及其北侧的梯度大值区内。CVV垂直分量是与云相联系的参数, 暴雨区垂直积分和区域平均的CVV垂直分量和云中水凝物混合比的相关系数为0.92, 与降水率的相关系数为0.71, 比湿位涡与云中水凝物的相关系数高很多。CVV垂直分量反映了水平涡度和水平相当位温梯度的相互作用, 可以把中纬度深对流系统中的中尺度动力过程和热力过程与云微物理过程密切联系起来, 有助于理解环流和云相互作用促使对流发展的机制, 可以很好地追踪暴雨系统的发展和演变。
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| 关 键 词： | 位势涡度 对流涡度矢量 暴雨 深对流系统 |
| 文章编号： | 1006-9895(2008)03-0444-13 |
| 修稿时间： | 2007年1月19日 |
Application of the Convective Vorticity Vector to the Analysis of a Rainstorm |
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| ZHAO Yu and GAO Shou-Ting.Application of the Convective Vorticity Vector to the Analysis of a Rainstorm[J].Chinese Journal of Atmospheric Sciences,2008,32(3):444-456. |
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| Authors: | ZHAO Yu and GAO Shou-Ting |
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| Abstract: | Although potential vorticity is a common and useful physical quantity for meteorological analysis,it is a little weak in deep convective systems due to the apparent slant of moist isentropic surfaces.Therefore,convective vorticity vector(CVV) introduced by Gao et al.(2004) is used to study deep convective system.By using CVV,a heavy rainfall event that occurred in North China is investigated in this paper.The result shows that the vertical component of the CVV is a good indicator for convective rainstorm in the mid-latitudes and its high value region is highly correlated with cloud hydrometeors and rainfall.The rainstorm is located in the region where the vertical component of the CVV is large and to the north of its large gradient.The vertical component of the CVV is a cloud-linked parameter.Analysis of domain-averaged and mass-integrated quantities shows that the linear correlation coefficient between the vertical component of the CVV and the sum of mixing ratio of cloud hydrometeors is 0.92,which is larger than that between the moist potential vorticity and the sum of mixing ratio of cloud hydrometeors.The linear correlation coefficient between the vertical component of the CVV and precipitation rate is 0.71.The vertical component of the CVV represents the interaction between horizontal vorticity and horizontal equivalent potential temperature gradient,which can associate dynamic and thermodynamic processes with cloud microphysical processes.Thus it can help to understand the mechanism of convection development caused by the interaction between the circulation and clouds.Therefore,it can better trace the development and evolution of rainstorm systems. |
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| Keywords: | potential vorticity convective vorticity vector rainstorm deep convective system |
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