Influence of Assimilating Surface Observations on a Squall Line with Different Ensembles
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摘要: 针对夏季黄淮地区一次飑线过程,利用WRF (Weather Research and Forecasting) 模式及其Hybrid ETKF-3DVAR同化系统,考察不同生成方案的样本对同化地面观测的影响。集合样本创建方式包括3类:扰动初始背景场的方案 (RCV)、使用不同的物理参数化方案 (PPMP) 以及前两者集成方案 (BLE)。基于增量场分析,同化地面观测主要调整850 hPa以下水平风和水汽混合比的空间结构,其中RCV方案侧重于改变水平风的空间分布,PPMP方案侧重于改变水汽混合比的空间结构,BLE方案兼具二者特征。同化地面观测可以间接改善6 h降水预报,其中PPMP试验的降水预报最好,尤其是对降水位置和强度的预报。对比雷达回波观测,RCV试验和BLE试验对弓状回波模拟得较好,BLE试验的模拟较多体现RCV特征。PPMP试验和RCV试验还可改变冷池的位置和强度,同时影响飑线出现和消亡时间,相对而言,PPMP试验影响更大。Abstract: The Weather Research and Forecasting (WRF) model with the hybrid ETKF-3DVAR (ensemble transform Kalman filter-three-dimensional variational data assimilation) data assimilation system is used to investigate the impact of different ensemble generation schemes on a squall line forecast in the Huanghe-Huaihe region in the summer by assimilating the surface observations. Ensembles are created in three different ways-by using the different initial ensemble samples (RCV), by using different model physical process schemes (PPMP), and by combining the first two ensembles (BLE). Based on the increments of model states, assimilating the surface observations mainly adjusts the spatial structures of wind and water vapor mixing ratio below the level of 850 hPa; the RCV scheme mainly updates the wind distribution, the PPMP scheme updates the water vapor mixing ratio, and the BLE scheme has the characteristics of both RCV and PPMP. Assimilating surface observations can also improve 6-h precipitation forecasts, and the PPMP scheme can give a relatively better performance compared to PPMP and BLE, especially for the prediction of rainfall location and intensity. RCV and BLE schemes present a better simulation for the bow echo, and the performance with BLE is similar to that with RCV. PPMP and RCV schemes can adjust the position and intensity of the cold pool, and also influence the times of appearance and disappearance of the squall line. Generally, PPMP scheme has a greater impact on the squall line than RCV and BLE.
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Key words:
- Ensemble generation scheme /
- Surface data /
- Hybrid data assimilation /
- Mesoscale model WRF /
- Squall line
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图 4 (a) RCV试验、(b) PPMP试验、(c) BLE试验对应的最底层的水汽混合比增量 (阴影,单位:g kg-1) 和不小于3 m s-1的水平风速增量 (箭头) 在D3区水平分布。黑线表示图 5中剖面位置
Figure 4. Analysis increments of water vapor mixing ratio (shaded, units: g kg-1) in (a) RCV (the different initial ensemble samples) experiment, (b) PPMP (the different model physical process schemes) experiment, and (c) BLE (combining the first two ensembles) experiment at the lowest model level in region D3. Arrows indicate horizontal wind speed increments larger than 3 m s-1, the black line represents the location of cross section in Fig. 5
图 5 (a) RCV试验、(b) PPMP试验、(c) BLE试验导出的水汽混合比 (阴影,单位:g kg-1) 和水平风速 (等值线,间隔:2 m s-1) 分析增量沿图 4黑线的剖面
Figure 5. Cross sections (along black lines in Fig. 4) of analysis increments of water vapor mixing ratio (shaded, units: g kg-1) and horizontal wind speed (contoured interval 2 m s-1) in (a) RCV experiment, (b) PPMP experiment, and (c) BLE experiment
图 11 6月5日18:00相当位温 (等值线,间隔2 K) 和水平风场 (箭头,单位:m s-1) 在D3区最底层的水平分布:(a) CTRL试验;(b) RCV试验;(c) PPMP试验。黑线为图 12中剖面位置
Figure 11. Equivalent potential temperature θ (contours, interval 2 K) and horizontal wind (arrows, units: m s-1) at 1800 BJT on 5 June from (a) CTRL experiment, (b) RCV experiment, and (c) PPMP experiment at the lowest level in region D3. The black lines represent the location of cross section in Fig. 12
图 12 6月5日17:30相当位温 (等值线,间隔3 K) 和垂直速度w (阴影,单位:m s-1) 沿图 11中黑线的剖面:(a) CTRL试验;(b) RCV试验;(c) PPMP试验
Figure 12. Cross sections (along black lines in Fig. 11) of equivalent potential temperature θ (contours, interval 3 K) and w (shaded, units: m s-1) at 1730 BJT 5 June: (a) CTRL experiment; (b) RCV experiment; (c) PPMP experiment
表 1 不同样本集合间的比较
Table 1. Comparison among different ensembles
同化试验名称 样本生成方案 6月5日14:00是否同化地面观测 集合样本数 RCV试验 Random_CV扰动方法 是 40 PPMP试验 不同物理参数化方案的组合 是 40 BLE试验 RCV试验成员+PPMP试验成员 是 80 表 2 6月5日18:00 3组试验在江苏省南部飑线中心处的垂直风切变
Table 2. Vertical wind shears near the squall line center in southern Jiangsu Province in CTRL, RCV, and PPMP experiments at 1800 BJT 5 June
气压范围/hPa 垂直风切变/s-1 CTRL试验 RCV试验 PPMP试验 地面~900 0.023 0.021 0.034 850~700 0.008 0.003 0.003 600~350 0.008 0.008 0.006 -
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