| 基于探空资料因子组合分析方法的冰雹预报 |
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| 引用本文： | 刘晓璐,刘建西,张世林,刘平.基于探空资料因子组合分析方法的冰雹预报[J].应用气象学报,2014,25(2):168-175. |
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| 作者姓名： | 刘晓璐 刘建西 张世林 刘平 |
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| 作者单位： | 四川省人工影响天气办公室，成都 610072 |
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| 基金项目： | 中国气象局气象新技术面上推广项目（CMATG2010M21） |
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| 摘 要： | 以1978—2007年四川省宜宾探空站200 km范围内共45例降雹事件与非降雹事件作为时间样本，将利用T-lnp探空资料计算表征热力、动力、水汽条件、温度、高度等物理参数作为预报因子，采用因子组合分析方法对3244个预报因子进行筛选，找出影响宜宾探空站附近降雹的预报因子，并计算得到它们的阈值及组合关系，建立了冰雹预报指标判别式。两个主要因子为400 hPa饱和湿静力温度与850 hPa湿静力温度之差 (Tσ400*-Tσ850) 和400 hPa与地面垂直气压梯度之差 (Gz400-Gzsurface)，两个条件因子为700 hPa水汽压与饱和水汽压之差 (e700-es700) 和700 hPa露点温度与饱和湿静力温度之差 (Td700-Tσ700*)。将2008年全年732例时次的T-lnp探空资料代入判别式进行试报，探测率为84%，空报率为67.7%，成功指数为30.4%，试报结果表明:基于探空资料因子组合分析方法得到的冰雹预报指标判别方法可行，具有一定准确性。
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| 关 键 词： | 因子组合分析方法 探空指标 冰雹预报 |
| 收稿时间： | 5/7/2013 12:00:00 AM |
Hail Forecast Based on Factor Combination Analysis Method and Sounding Data |
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| Liu Xiaolu,Liu Jianxi,Zhang Shilin and Liu Ping.Hail Forecast Based on Factor Combination Analysis Method and Sounding Data[J].Quarterly Journal of Applied Meteorology,2014,25(2):168-175. |
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| Authors: | Liu Xiaolu Liu Jianxi Zhang Shilin and Liu Ping |
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| Affiliation: | Sichuan Weather Modification Office, Chengdu 610072 |
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| Abstract: | The emergence of the small probability of severe weather events is attributed to specific factor combinations of some early meteorological elements. The nonlinear and complicated characteristics of factor combinations can be used to find the relationship between forecast object and forecast factors. Based on this method, the relationship between hail events in the south of Sichuan Basin and some meteorological elements calculated by the sounding data is investigated, and a hail forecast index discriminant is established. The discriminant is physically significant and applied in daily operation.Hailstorm is a meso-scale weather system with the temporal scale of several to dozens of hours, and the horizontal scale of several hundred kilometers. In real business, the T-lnp sounding data are observed at 0800 BT and 2000 BT every day, and the hail forecasting is carried out every 12 hours. A sample sets of 7 hail events and 38 non-hail events near Yibin Station is established. Using the T-lnp sounding data, 3422 meteorological elements are calculated as forecast factors, including temperature, height, moisture, saturation vapor pressure, potential pseudo-equivalent temperature, K index and so on. Based on factors combination analysis method, 2 main factors and 2 conditional factors are selected from 3422 meteorological elements and their critical values are calculated. The main factors are Tσ400*-Tσ850 and Gz400-Gzsurface, and the conditional factors are e700-es700 and Td700-Tσ700*, Tσ400* stands for saturated wet static temperature at 400 hPa, and Tσ850 stands for wet static temperature at 850 hPa; Gz400 and Gzsurface stand for vertical pressure gradient at 400 hPa and the surface level; e700 and es700 stand for vapour pressure and saturated vapour pressure at 700 hPa; Td700 and Tσ700* stand for dew point temperature and saturated wet static temperature at 700 hPa. The hail forecast indexes discriminant nearby Yibin Station is established using these data.The environmental state of hailstorm generation and the unstable mechanism of severe convective weather can be explained by the hail forecast indexes discriminant, which is evaluated using historical records of the year of 2008. Among 65 warnings, the real hail events never miss but the false alarm ratio reaches 67.7%, which should be further distinguished using radar observations. The overall probability of detection is 84%, and the critical success index is 30.4%. The result shows that factor combination analysis method is feasible to some extent. |
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| Keywords: | factor combination analysis method sounding index hail forecasting |
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