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Precipitation Extrapolation Nowcasting in Beijing-Tianjin-Hebei Under Different Weather Backgrounds
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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。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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Key words:
- nowcasting;
- cross correlation;
- optical flow;
- RMAPS_IN
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图 1 站点分布
(黑色圆点为RMAPS_IN分析场所用站点，红色三角为检验预报效果所用站点，蓝色方框和箭头为计算移动矢量的矩形设计)
Fig. 1 Distribution of stations
(black dots are stations used for RMAPS_IN analyses, red triangles are stations for verification, blue boxes and arrow are the rectangular design when calculating motion vectors)
图 2 不同天气背景下两种外推矢量对比
Fig. 2 Euclidean distance and Cosine distance of two motion vectors derived by cross correlation and optical flow under different weather backgrounds
图 3 低槽冷锋类降水的TS评分(a)、空报率(b)、漏报率(c)
Fig. 3 TS(a), FAR(b), MR(c) for low trough cold front precipitation
图 4 2020年8月9日23：00低涡降水过程(填色为降水强度)
(a)起报时刻23：00的降水分析产品与移动矢量(红色箭头为交叉相关法移动矢量，黑色箭头为光流法移动矢量)，(b)8月10日00：00的降水分析产品，(c)交叉相关法外推未来60 min的预报，(d)光流法外推未来60 min的预报
Fig. 4 Low vortex precipitation case at 2300 BT 9 Aug 2020(the shaded denotes precipitation intensity)
(a)precipitation analysis and motion field based at 2300 BT 9 Aug 2020(the red vector denotes motion field derived by cross correlation, the black vector denotes motion field derived by optical flow), (b)precipitation analysis at 0000 BT 10 Aug, (c)forecast of cross correlation at 60 min from the base time, (d)forecast of optical flow at 60 min from the base time
图 5 2020年8月9日降水过程两种外推矢量的对比(a)欧氏距离，(b)余弦距离
Fig. 5 Euclidean distance(a) and Cosine distance(b) of two motion vectors derived by cross correlation and optical flow on 9 Aug 2020
图 6 2019年8月11日台风降水过程(填色为降水强度)
(a)起报时刻12：00的降水分析产品与移动矢量(红色箭头为交叉相关法移动矢量，黑色箭头为光流法移动矢量)，(b)13：00的降水分析产品，(c)交叉相关法外推未来60 min的预报，(d)光流法外推未来60 min的预报
Fig. 6 Typhoon precipitation case on 11 Aug 2019(the shaded denotes precipitation intensity)
(a)precipitation analysis and motion field based at 1200 BT(the red vector denotes motion field derived by cross correlation, the black vector denotes motion field derived by optical flow), (b)precipitation analysis at 1300 BT 11 Aug, (c)forecast of cross correlation at 60 min from the base time, (d)forecast of optical flow at 60 min from the base time
图 7 2019年8月11日降水过程两种外推矢量的对比(a)欧氏距离，(b)余弦距离
Fig. 7 Euclidean distance(a) and Cosine distance(b) of two motion vectors derived by cross correlation and optical flow on 11 Aug 2019
表 1 不同天气背景下降水过程的日期和样本量
Table 1 Dates and sample number of precipitation events under different weather backgrounds
降水类型 日期 样本量 低槽冷锋类 2019-05-17，2019-05-18，2019-07-05，2019-07-22，
2019-07-29，2019-08-04，2019-09-09，2019-10-03，
2020-05-30，2020-06-24，2020-07-04, 2020-07-05，
2020-07-17，2020-07-30，2020-08-18，2020-08-232108 低涡类 2019-07-06，2020-05-07，2020-05-21，2020-06-25，
2020-06-28，2020-06-29，2020-07-01，2020-07-08，
2020-07-26，2020-07-28，2020-08-01，2020-08-09，
2020-08-12，2020-09-141448 台风类 2019-07-28，2019-08-01，2019-08-09，2019-08-10，
2019-08-11，2019-08-15，2020-08-051058 气旋类 2019-05-25，2020-07-12 260 暖切变线类 2020-08-15，2020-08-16 140 
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表 2 不同天气背景下交叉相关法和光流法的预报评分一览表
Table 2 Scores of nowcastings with different lead-times forecasted by cross correlation and optical flow under different weather backgrounds
预报时效/min 降水类型 TS评分 空报率 漏报率 交叉相关法 光流法 交叉相关法 光流法 交叉相关法 光流法 10 低槽冷锋类 0.41* 0.41* 0.28* 0.28* 0.51* 0.51* 低涡类 0.49 0.48 0.27** 0.26** 0.42 0.43 台风类 0.53 0.52 0.28** 0.27** 0.34 0.35 气旋类 0.41* 0.41* 0.28* 0.28* 0.51* 0.51* 暖切变线类 0.51 0.50 0.28** 0.27** 0.36 0.38 30 低槽冷锋类 0.36 0.35 0.35 0.36 0.55 0.57 低涡类 0.44 0.42 0.32 0.33 0.46 0.49 台风类 0.47 0.45 0.34 0.35 0.38 0.41 气旋类 0.35 0.34 0.34 0.36 0.57 0.58 暖切变线类 0.46 0.44 0.35* 0.35* 0.41 0.43 60 低槽冷锋类 0.31 0.29 0.42 0.45 0.61 0.64 低涡类 0.38 0.35 0.40 0.42 0.52 0.56 台风类 0.39 0.35 0.43 0.45 0.45 0.51 气旋类 0.29 0.27 0.41 0.44 0.63 0.66 暖切变线类 0.39 0.37 0.42 0.43 0.46 0.49 90 低槽冷锋类 0.27 0.24 0.48 0.51 0.66 0.69 低涡类 0.33 0.30 0.45 0.48 0.56 0.62 台风类 0.33 0.30 0.50 0.52 0.51 0.57 气旋类 0.24 0.22 0.48 0.50 0.69 0.71 暖切变线类 0.35 0.31 0.47 0.50 0.49 0.54 120 低槽冷锋类 0.23 0.21 0.53 0.56 0.70 0.73 低涡类 0.30 0.26 0.50 0.53 0.61 0.66 台风类 0.29 0.25 0.55 0.57 0.55 0.63 气旋类 0.20 0.19 0.54 0.56 0.74 0.75 暖切变线类 0.32 0.28 0.52 0.56 0.52 0.58 注：*表示两种方法评分一致，**表示光流法评分更优，无*号表示交叉相关法评分更优。
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