Improving Radar Rainfall Estimation by Accounting for Microphysical Processes Using a Micro Rain Radar in West Africa

This study evaluates the improvement of the radar Quantitative Precipitation Estimation (QPE) by involving microphysical processes in the determination of Z-R algorithms. Within the framework of the AMMA campaign, measurements of an X-band radar (Xport), a vertical pointing Micro Rain Radar (MRR) to investigate microphysical processes and a dense network of rain gauges deployed in Northern Benin (West Africa) in 2006 and 2007 were used as support to establish such estimators and evaluate their performance compared to other estimators in the literature. By carefully considering and correcting MRR attenuation and calibration issues, the Z-R estimator developed with the contribution of microphysical processes and non-linear least-squares adjustment proves to be more efficient for quantitative rainfall estimation and produces the best statistic scores than other optimal Z-R algorithms in the literature. We also find that it gives results comparable to some polarimetric algorithms including microphysical information through DSD integrated parameter retrievals.

Research on Rainfall Estimation Based on Improved Kalman Filter Algorithm

In order to solve the rainfall estimation error caused by various noise factors such as clutter,super refraction,and raindrops during the detection process of Doppler weather radar.This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter.After data preprocessing,the radar data should be classified according to the precipitation intensity.And then,they are respectively substituted into the improved filter for calibration.The state noise variance Q(k)and the measurement noise variance R(k)can be adaptively calculated and updated according to the input observation data during this process.Then the optimal parameter value of each type of precipitation intensity can be obtained.The state noise variance Q(k)and the measurement noise variance R(k)could be assigned optimal values when filtering the remaining data.This rainfall estimation based on semiadaptive Kalman filter calibration not only improves the accuracy of rainfall estimation,but also greatly reduces the amount of calculation.It avoids errors caused by repeated calculations,and improves the efficiency of the rainfall estimation at the same time.

同化雷达估算降水率对暴雨预报的影响

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。

雷达回波强度拼图的定量估测降水及其效果检验

为了得到精度更高的高时空分辨率格点定量估测降水量,需要将雷达资料和雨量计降水量资料进行有效的综合利用。利用广东6部多普勒雷达的回波强度拼图资料和稠密的自动雨量计降水强度观测资料,采用概率密度法建立Z-R关系进行雷达降水估计,并采用客观订正方法利用雨量计资料对雷达降水估计进行校准。交叉检验表明:利用雨量计对雷达降水估计进行客观方法订正可以取得比单纯用雨量计资料进行OI插值好的效果。OI雷达订正法较优。

不同校准方法检验雷达定量估测降水的效果对比

应用雷达低仰角基本反射率资料和地面加密自动站降水量资料,采用最优化方法,根据天津地区降水特点和不同降水类型,建立适用本地的雷达Z-I关系。经实际应用检验,积混降水类型Z-I关系具实用性。在天津本地化Z-I关系基础上,通过了对比分析6种不同校准方法在天津夏季降水估测中的检验效果。结果表明:Z-I关系校准法和最大集成法对降水的估测偏高,误差较大;最优插值法的估测精度最高,平均绝对误差和均方根误差最小;但计算不同校准方法与实况相关性表明,变分校准法的估测效果与雨量计降水量的相关性最好。同时,所有估测校准法对小雨量级的降水均出现了不同程度的偏高估测。

多普勒天气雷达估测降水及雨洪应用研究进展

多普勒天气雷达具有测量范围广、时空分辨率高等优点,可获得大面积定量降水数据,具有较好的时空代表性。基于国内外多普勒天气雷达数据资料的应用研究成果,从雷达数据质量控制、联合雨量计校正、耦合天气雷达的应用等方面,对应用研究进展与最新动态进行综述。结果表明,虽然当前雷达探测降雨的精度仍较低,应用深度也不够,但是随着应用研究的深入,雷达将不断实现其具有的强大优势。