摘要
[目的]探明威宁县分类强对流环境参数本地指标,为当地强对流天气预报预警工作提供参考.[方法]利用威宁县2014-2022 年常规地面观测和L波段雷达探空观测等多源气象资料,统计分析冰雹和短时强降水2 类强对流天气的环境参数特征,并通过百分位法得出分类强对流的关键环境参数预报指标.[结果]大气可降水量(PWV)、近地面的温度露点差(T-Td)、近地面到500 hPa的温差(ΔTsur-500)、对流有效位能(CAPE)、0～6 km垂直风切变(VWS')等环境参数能够区分2类强对流天气.其中,冰雹的预报指标为:PWV≥18.6 kg·m-2、ΔTsur-500≥24℃、CAPE≥856 J·kg-1、VWS'≥5.7 m·s-1,短时强降水的预报指标为:PWV≥26.7 kg·m-2、地面T-Td≤4.7℃、ΔTsur-500≥22℃、CAPE≥1 280 J·kg-2.此外,冰雹的湿球温度0℃高度应为4 311～5 078 m,短时强降水的暖云层厚度≥4 356 m.[结论]通过对2021-2023 年强对流个例的检验,冰雹和短时强降水的预报准确率分别为63%、68%,预报指标有一定的指导意义.
Abstract
To explore the local indicators of classified severe convective ambient parameters in Weining County and to provide a reference for local severe convective weather forecasting and warning,the ambient parameter characteristics of hail and short-time severer rainfall weather are analyzed based on multi-source meteorological data such as conventional ground observations and L-band radar sounding observations in Weining County from 2014 to 2022.In the meantime,the classification indexes and criterion of severe convection weather are summarized by the percentile method.The results show that the two types of severe convective weather can be distinguished by ambient parameters such as atmospheric precipitable water(PWV),near-surface temperature dew point difference(T-Td),temperature difference between near-surface and 500 hPa(ΔTsur-500),convective effective potential energy(CAPE)and 0～6 km vertical wind shear(VWS').Among them,the forecast indicators of hail are:PWV≥18.6 kg·m-2,ΔTsur-500≥24℃,CAPE≥856 J·kg-1,and VWS'≥5.7 m·s-1;the forecast indicators of short-time severe precipitation are:PWV≥26.7 kg·m-2,near-surface(T-Td)≤4.7℃,ΔTsur-500≥22℃,and CAPE≥1 280 J·kg-1.In addition,the height of the wet bulb of hail at 0℃ layer should be within the range of 4 311～5 078 m,and the layer thickness of warm clouds with short-time severe rainfall should be greater than or equal to 4,356 m.Verification of individual cases of severe convection in 2021-2023 suggests that the forecast accuracies of hail and short-time heavy precipitation are 63％and 68％,respectively.These forecast indicators are instructive for the forecasting of the two types weather.
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