艾永智, 杨传荣, 金少华. 高分辨对流有效位能在云南一次强对流天气中的应用分析[J]. 云南大学学报(自然科学版), 2014, 36(S1): 77-85. doi: 10.7540/j.ynu.20130411
引用本文: 艾永智, 杨传荣, 金少华. 高分辨对流有效位能在云南一次强对流天气中的应用分析[J]. 云南大学学报(自然科学版), 2014, 36(S1): 77-85. doi: 10.7540/j.ynu.20130411
Application of high-resolution convective available potential energy in once severe convective weather process in Yunnan[J]. Journal of Yunnan University: Natural Sciences Edition, 2014, 36(S1): 77-85. DOI: 10.7540/j.ynu.20130411
Citation: Application of high-resolution convective available potential energy in once severe convective weather process in Yunnan[J]. Journal of Yunnan University: Natural Sciences Edition, 2014, 36(S1): 77-85. DOI: 10.7540/j.ynu.20130411

高分辨对流有效位能在云南一次强对流天气中的应用分析

Application of high-resolution convective available potential energy in once severe convective weather process in Yunnan

  • 摘要: 利用地面站点资料和T639数值模式预报资料相结合的方法,计算出云南省每个地面站点逐时的高分辨对流有效位能(CAPE),并用其对2012年8月5—6日发生在云南省的一次强对流天气作了应用分析.结果表明:在此次强对流天气过程发生前,云南大部有较强的对流不稳定能量存在,强对流天气主要发生在CAPE为2000J/kg以上的区域.CAPE高值区较强对流云体提前3~5h出现,对流云体在CAPE高值区生成后有向引导气流下风方移动的趋势.这一分析方法能够给出逐时的具有较高空间分辨率的不稳定能量分布,对强对流天气的短时预报有一定指示意义.

     

    Abstract: Based on the surface meteorological data and T639 numerical model forecast data,the high-resolution convective available potential energy was calculated.And it was used to analyses once severe convection weather case occurred in Yunnan province during August 5 and August 6,2012.The results show that there is strong convective instability energy distribution over most area of Yunnan before the severe convective weather occurred.Severe convective weather occurred mainly in the areas of the CAPE above 2000J/kg.the strong CAPE appears early than the strong convective clouds for 3—5 hour.After the strong convective clouds generated over the areas of the CAPE high value,it has a trend of flowing to the downwind direction of steering flow.This analysis method can give an unstable energy distribution with higher spatial resolution in each hour,and is of certain indicating significance for short-term forecasting of severe convective weather.

     

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