| 不同天气背景下京津冀降水临近外推预报 |
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| 引用本文： | 王玉虹,BicaBenedikt.不同天气背景下京津冀降水临近外推预报[J].应用气象学报,2022,33(3):270-281. |
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| 作者姓名： | 王玉虹 BicaBenedikt |
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| 作者单位： | 1.河北省气象台, 石家庄 050021 |
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| 摘 要： | 基于2019—2020年京津冀地区不同天气系统影响下的降水过程，采用交叉相关法和光流法对快速更新多尺度分析和预报综合集成系统（Rapid-refresh Multi-Scale Analysis and Prediction System-Integration，RMAPS_IN）的降水分析产品进行0~2 h临近外推预报的批量试验。结果表明:由交叉相关法和光流法计算的两种外推矢量在大小和方向上存在一定差异，直接差异与影响降水的天气系统位置有明显的对应关系，而方向差异受地理位置的影响更明显，台风类降水呈弧形带状分布，低槽冷锋类、低涡类、气旋类、暖切变线类等几类降水均呈西北大东南小的特点；预报效果方面，总体上交叉相关法优于光流法，尤其是预报时效超过30 min以后，各种降水类型的批量检验结果显示交叉相关法的预报评分优于光流法，且预报时效越长、优势越明显，但预报时效为10 min时，光流法在低涡类、台风类、暖切变线类的空报率上优于交叉相关法。此外，基于外推的临近预报方法对京津冀地区台风类降水的预报效果最好，其次为暖切变线类、低涡类、低槽冷锋类、气旋类。
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| 关 键 词： | 临近预报 交叉相关法 光流法 RMAPS_IN |
| 收稿时间： | 2021-12-01 |
Precipitation Extrapolation Nowcasting in Beijing-Tianjin-Hebei Under Different Weather Backgrounds |
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| Affiliation: | 1.Hebei Meteorological Observatory, Shijiazhuang 0500212.Central Institute for Meteorology and Geodynamics, Vienna 1190 |
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| Abstract: | Rapid-refresh Multi-Scale Analysis and Prediction System-Integration (RMAPS_IN) is an important tool for Beijing, Hebei and other meteorological departments to make rapid-updated and refined precipitation nowcasting. The precipitation analysis products of the system are based on automatic station observation and radar quantitative precipitation estimation data, while 0-2 h forecast products are obtained by extrapolation based on the analysis products. To study the applicability of different extrapolation methods in RMAPS_IN, the precipitation events of different weather systems from 2019 to 2020 are analyzed, using cross correlation method and optical flow method to conduct a 0-2 h extrapolation nowcasting test based on the RMAPS_IN precipitation analysis products. The cross correlation method uses classic optimal correlation coefficient calculation scheme, while the optical flow method employs the Farneback dense optical flow calculation scheme in the OpenCV function library. According to the characteristics of the regional weather systems, the precipitation events are divided into five types: Low trough cold front precipitation, low vortex precipitation, typhoon precipitation, cyclone precipitation, and warm shear line precipitation. The sample size of each precipitation type is 2108, 1448, 1058, 260, and 140, respectively. The batch test results show that the extrapolated vectors by the cross correlation method and optical flow method have a certain difference in magnitude and direction. The direct difference has a clear correspondence with the position of the weather system that affects precipitation, and is more obviously affected by the geographical location. For typhoon precipitation, the difference in direction is distributed in an arc band, while for other 4 types of precipitation, the difference is large in the northwest and small in the southeast. In terms of forecasting effect, the cross correlation method is generally better than the optical flow method, especially when the forecast time exceeds 30 minutes, and the longer the lead time is, the more obvious the advantage is. But when the forecast time is 10 min, the optical flow method is better in the false alarm rate of low vortex precipitation, typhoon precipitation and warm shear line precipitation. In addition, the nowcasting method based on extrapolation has the best prediction effects on typhoon precipitation in Beijing-Tianjin-Hebei region, followed by warm shear line precipitation, low vortex precipitation, low trough cold front precipitation, and cyclone precipitation. It should be noted that in Beijing-Tianjin-Hebei region, cyclone precipitation and warm shear line precipitation rarely occurred in recent years, and the sample size of these two types of precipitation is significantly smaller than that of other types, so the relevant results are less representative. |
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