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Effects of Assimilating Radar Rainfall Rate Estimation on Torrential Rain Forecast
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摘要: 选取2009年3月28日广东省广州市大暴雨过程，考察了变分校准前后Z-I关系估算雷达降水率的区别。变分校准后的降水率资料具有较高的单点精度与合理的梯度分布。降水率资料能够反映大气动力特征和水汽分布等重要信息，是模拟中小尺度系统的关键因子。基于GRAPES (Global/Regional Analysis and Prediction System) 区域三维变分系统，将FSU (Florida State University) 对流参数化方案作为观测算子的同化试验指出，同化降水率资料后同时增强了低层大气的辐合和高层大气的辐散，从而使整层气柱的不稳定能量增加。沙氏指数和K指数诊断分析也表明，同化降水率资料后有利于触发强对流天气。此外，低空辐合有利于水汽垂直输送，维持对流发展，改进降水模拟。逐小时数值模拟结果表明：同化校准后的雷达估算降水率不仅可以改进降水分布，而且使中尺度对流系统的发展和消亡清晰地表现出来。Abstract: Meso-scale weather system, such as torrential rain, is neither easily detected nor effectively simulated. Main causes consist of the insufficient observation and the inaccurate initial filed, which are prepared for the routine weather prediction and the hazardous weather simulation. To solve these problems, high resolution rainfall rate data estimated by doppler radar Z-I relationship is calibrated with AWS data by variational method. The forecast experiment on a torrential rain case captured by the radar in Guangzhou indicates that the east center of precipitation omitted in the original Z-I estimation is forecasted after the calibration. Even though the minor amount of rainfall rate is inclined to be overestimated, relative errors of calibration significantly decline as the increase of rain rate value. As a result, high resolution datasets of calibration rain rate are demonstrated to possess a more accurate single point value than the estimation of Z-I relationship and a more reasonable gradient than AWS data. Meanwhile, according to the distribution of instantaneous precipitation, calibration rainfall rate datasets imply lots of information on the atmospheric dynamic and moisture, which are the major factors to arouse a convective rainstorm.To verify various advantages of mixed characteristics, a set of experiments are performed using FSU (Florida State University) cumulus parameterization scheme as the observational operator, based on GRAPES (Global/Regional Analysis and Prediction System) Regional Three Dimensional Variation System. Compared with NCEP (National Centers for Environmental Prediction) global analysis data, the convergence in lower level and the divergence in higher level after assimilation are conspicuously strengthened, which sequentially lead the unstable energy in atmosphere to be elevated. Showalter index and K index diagnose indicate a heavy rain in the dense data region as well. In addition, the vertical transportation of moisture forced by the convergence sustains a strong convection and ameliorates the cumulative precipitation. The storm path prediction is obviously improved. Results of simulation experiment express that not only the hourly distribution and center of precipitation are similar to the observation, also, the meso-scale convective system development and demise are impressively depicted.
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图 1 2009年3月28日10:00广州雷达估算降水率 (填色图) 与自动气象站降水率 (数字)(降水率单位：mm·h-1) (a) 变分校准前，(b) 变分校准后
Fig. 1 Guangzhou radar estimations of rainfall rate (the shaded) and automatic weather station rainfall rate (number)(unit:m·h-1) at 1000 UTC 28 May 2009(a) before variational calibration, (b) after variational calibration
图 2 2009年3月28日10:00雷达估算降水率与自动气象站降水率的相对误差 (a) 变分校准前, (b) 变分校准后
Fig. 2 Relative errors between radar estimation of rainfall rate and automatic weather station rainfall rate at 1000 UTC 28 Mar 2009 (a) before variational calibration, (b) after variational calibration
图 3 切线性观测算子相对于比湿和垂直速度的扰动程度
Fig. 3 Disturbance of linear observational operator with respect to specific humidity and vertical velocity
图 4 同化前后比湿 (阴影)、散度 (等值线，单位：10-5s-1) 以及风场 (矢量) 分布
(a) 背景场850 hPa水平风场和比湿分布，(b) 分析场850 hPa水平风场和比湿分布，(c)850 hPa散度和比湿增量水平分布，(d) 散度和比湿增量沿23°N垂直分布
Fig. 4 The distribution of specific humidity (the shaded), divergence (contour, unit:10-5s-1) and horizontal wind (vector) before and after assimilation
(a)850 hPa horizontal distribution of background wind and specific humidity, (b)850 hPa horizontal distribution of analysis wind and specific humidity, (c)850 hPa horizontal distribution of increment divergence and specific humidity, (d) vertical distribution of increment divergence and specific humidity along 23°N
图 5 同化前后850 hPa水汽平流 (填色，单位：10-6 m·s-2)、水汽通量散度 (填色，单位：10-6 g·cm-2·hPa·s) 以及流场 (流线) 分布
(a) ExpC水汽平流，(b) ExpA水汽平流，(c) ExpC水汽通量散度和流线，(d) ExpA水汽通量散度和流线
Fig. 5 The distribution of moisture advection (the shaded, unit: 10-6 m·s-2), moisture flux divergence (the shaded, unit: 10-6 g·cm-2·hPa·s) and flow field (streamline) at 850 hPa before and after assimilation
(a) moisture advection of ExpC, (b) moisture advection of ExpA, (c) moisture flux divergence and flow field of ExpC, (d) moisture flux divergence and flow field of ExpA
图 6 沙氏指数和K指数
(a) ExpC的沙氏指数, (b) ExpA的沙氏指数, (c) ExpC的K指数, (d) ExpA的K指数
Fig. 6 Showalter index and K index
(a) Showalter index of ExpC, (b) Showalter index of ExpA, (c)K index of ExpC, (d)K index of ExpA
图 7 2009年3月28日10：00—15：00累积降水量 (单位：mm)
(a) ExpC，(b) ExpA，(c) 观测，(d) 逐小时最大降水量
Fig. 7 Precipitation from 1000 UTC to 1500 UTC on 28 Mar 2009(unit:mm)
(a) ExpC, (b) ExpA, (c) observation, (d) hourly maximum precipitation
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