Study of Methods for Three-Dimensional Multiple-Radar Re ectivity Mosaics

This paper investigated several approaches to remapping and combining multiple-radar reflectivity fields onto a unified 3D Cartesian grid with high spatial and temporal resolutions,and analyzed systematic observation differences among multiple radars. The remapping approaches were evaluated by inspecting the spatial consistency of the reflectivity fields on vertical and horizontal cross sections on the equidistant line of radars, and the intensity change of 1-h accumulated precipitation before and after interpolation. The combining approaches were evaluated by continuity examination. The results show that for remapping schemes,the vertical interpolation with nearest neighbor on the range-azimuth plane is the most reasonable scheme that provides consecutive reflectivity fields and retains the high-resolution structure comparable to that of the raw data; for multiple-radar data mosaics, the distance-exponential-weighted mean scheme provides spatially consistent reflectivity mosaics. The mosaics can mitigate various problems caused by the radar beam geometry such as the cone of silence.     

新一代天气雷达网资料的三维格点化及拼图方法研究

文中研究了几种把球坐标系下的雷达网反射率体扫资料插值到统一的笛卡尔坐标系下的经纬度网格上以及用多个雷达的反射率网格资料进行三维拼图的方法,并对多个雷达同步观测的反射率因子的空间一致性、系统误差以及雷达等距离线上回波的水平和垂直结构进行了分析。结果发现:在雷达资料格点化过程中,径向和方位上的最近邻居法和垂直方向的线性内插法的结合(NVI方法)是一种有效的雷达资料分析方法,它既能得到空间比较连续的反射率分析场,同时也较好地保留了体扫资料中原有的反射率结构特征;广州雷达和梅州雷达同步观测的空间一致性比较好;在多个雷达资料合成拼图的过程中,距离指数权重平均法能提供空间连续的三维反射率拼图数据,拼图也减轻了由雷达波束几何学引起的各种问题。     

多普勒雷达数据三维格点化的方法研究

天气雷达数据三维格点化是天气雷达组网拼图的基础,本文研究了几种把球坐标系下的分辨率不均匀的雷达反射率资料（dBZ）插值到统一的分辨率均匀的笛卡尔坐标系下的方法,并采用模拟的天气雷达回波数据对这几种方法进行了比较分析,主要对空间反射率强度值的连续性及是否保留了雷达资料中原始的反射率结构特征进行对比分析。      

Comparison of Precipitation Observations from a Prototype Space-based Cloud Radar and Ground-based Radars

A prototype space-based cloud radar has been developed and was installed on an airplane to observe a precipitation system over Tianjin,China in July 2010.Ground-based S-band and Ka-band radars were used to examine the observational capability of the prototype.A cross-comparison algorithm between different wavelengths,spatial resolutions and platform radars is presented.The reflectivity biases,correlation coefficients and standard deviations between the radars are analyzed.The equivalent reflectivity bias between the S-and Ka-band radars were simulated with a given raindrop size distribution.The results indicated that reflectivity bias between the S-and Ka-band radars due to scattering properties was less than 5 dB,and for weak precipitation the bias was negligible.The prototype space-based cloud radar was able to measure a reasonable vertical profile of reflectivity,but the reflectivity below an altitude of 1.5 km above ground level was obscured by ground clutter.The measured reflectivity by the prototype space-based cloud radar was approximately 10.9 dB stronger than that by the S-band Doppler radar(SA radar),and 13.7 dB stronger than that by the ground-based cloud radar.The reflectivity measured by the SA radar was 0.4 dB stronger than that by the ground-based cloud radar.This study could provide a method for the quantitative examination of the observation ability for space-based radars.     

基于TRMM/PR的长江下游地基雷达一致性订正

我国有近200部地基多普勒天气雷达,已经积累了近20年的观测数据,这些数据对雷达气候学研究非常重要。但由于不同雷达的标定误差不同,雷达之间存在观测值不一致性的现象（与美国的地基雷达类似）,有的反射率因子差异超过了3 dB。这种不一致影响了多雷达联合降水估计的精度和雷达组网临近预报的效果。为此,采用筛选比较法对地基雷达与TRMM/PR（Tropical Rainfall Measuring Mission/Precipitation Radar）进行空间匹配和异常数据剔除,以TRMM/PR为参照计算并订正地基雷达偏差。对2013年5—9月长江下游7部S波段雷达数据订正后,结果表明:订正后7部雷达之间的平均反射率因子差异从1.8 dB降至0.5 dB,任意两部雷达之间的差异均小于1.0 dB,多雷达的观测一致性和空间连续性有明显改善。与传统的几何匹配法比较,筛选比较法订正结果相对稳定,不存在过量订正的问题。     

垂直指向测雨雷达的误差模拟及相互校准

基于马歇尔—帕米尔(M-P)分布的雨滴谱和下落末速—降雨算法, 模拟了垂直气流和雷达垂直倾角对垂直指向测雨雷达雨强测量的影响。同时在外场, 与雨量计观测相结合, 比较了五部垂直指向测雨雷达之间的差异, 对其进行了校准。结果表明: 模拟的上升气流对雨强测量的影响大于下沉气流, 垂直气流速率越大雨强测量误差愈显著; 当雷达垂直倾角<1.5°, 或在低风速下 (水平风速<2 m/s) 且倾角<9°, 对雨强测量的影响均小于10%; 强对流性降雨过程中, 垂直气流对雨强测量的影响大于垂直倾角。另外, 通过挑选层状云降雨过程, 对比雷达与共置雨量计测量的降雨量、 对比雷达间测量的降雨量均可获取较合理的归一化斜率; 但对比雷达间测量的降雨量法更优, 利用该斜率可降低雷达间的仪器误差; 在限定雷达间反射率因子差值的条件下, 比较雷达间全部降雨过程的反射率因子也可反映仪器间的系统误差趋势。     

浙江沿海登陆台风结构特性的多普勒雷达资料分析

利用浙江省新一代多普勒雷达组网资料,选取在浙江东南沿海近乎同一地点登陆的3个台风进行研究。从登陆前6 h到登陆后7 h,对比分析3个台风在登陆前后的雷达回波和降水结构时空变化特征。利用单多普勒雷达四维变分风场反演技术,对温州多普勒雷达探测资料进行了风场反演。结合利用雷达回波强度资料,对3个台风登陆前后1 h在云岩、昌禅等地造成特大暴雨的中尺度对流系统的三维结构及其演变特征进行了详细分析。结果表明,台风强度与其螺旋云带中的对流单体密切相关。台风强度愈强,其中低层环状平均回波强度就愈强,对流活动也就愈旺盛,降水强度也愈大。台风登陆前,回波(雨带)从眼墙向外围传播。台风登陆后,随着台风外围回波(雨带)明显减弱,台风眼墙回波(雨带)则明显增强,台风眼区逐渐被强回波所取代,使台风登陆后眼墙的平均雨强比登陆前增大。台风登陆后1 h,由于低(高)层水平辐合(散)增强,强对流回波中倾斜的上升(下沉)气流明显增大,使对流运动更加活跃,造成登陆后1 h的降雨量显著增强。台风强度与登陆后1 h降雨量的增强幅度成正比。台风强度越强,垂直风切变就越大,垂直切变风速大值区与最大降雨区有较好的对应关系。台风登陆后1 h,垂直切变风速的明显增加对登陆台风螺旋雨带中的中小尺度对流的加强和维持起到了非常重要的作用。     

多部雷达联合估算淮河流域降水

以淮河流域内6部CINRAD雷达基数据资料以及高密度自动雨量站观测资料为源,在应用多种方法进行降水估算和校准,并采用主成分集成方法进行集成应用的基础上,采用"先估算降水再拼图"和"重叠区域选取最大值"的方法来进行整个流域的降水估算结果拼图,从而实现了整个淮河流域的降水估算。从2007年7月初降水过程应用结果来看,经过校准以后估算误差在45%以下,并且能够反映出缺少地面雨量观测站的区域的降水分布,是一种切实可行的淮河流域降水估算的方法。     

用多普勒雷达反射率调整模式大气的云微物理变量

一种简单云分析方案, 用于由多普勒天气雷达反射率反演中尺度大气模式初值分析中的云微物理变量（云水混合比和雨水混合比）和空气湿度变量（比湿），使模式积分初始场反映出观测空间的云微物理特征以及哪些空间位置上的大气处于饱和状态。应用于2002年6月梅雨期安徽省马鞍山市一次降水过程的临近数值预报试验结果表明，模式预报的大气综合反射率与雷达观测的回波图像相近，由云微物理变量变化表示的模式云系演变与雷达观测的回波图像一致, 伴随模拟的中小尺度云系, 模式大气能很快调整出合理的中小尺度流场辐散、辐合结构；它们明显好于模式初始场不引入雷达反射率时的结果，即这种方法对改进临近数值天气预报准确率是有效的。     

基于VDRAS的快速更新雷达四维变分分析系统

基于雷达资料快速更新四维变分同化 (RR4DVar) 技术和三维数值云模式,初步研发了一个针对对流尺度数值模拟的快速更新雷达四维变分分析系统。系统通过对京津冀6部多普勒天气雷达资料进行RR4DVar同化,并融合5 min自动气象站观测和中尺度数值模式结果,可快速分析得到12~18 min更新的低层大气三维动力、热力场的对流尺度结构特征。针对2009年7月22日发生在京津冀的一次强风暴个例,通过一系列敏感性试验,并利用局地加密资料进行检验对比,表明有效的雷达资料RR4DVar同化及自动气象站和中尺度模式资料融合方案、恰当的中尺度背景场设置和动力约束方法是获得合理结果的关键。研究也表明:恰当的系统配置能够模拟出与对流生消发展密切相关的近风暴环境特征,包括低层入流、垂直风切变、低层辐合上升和暖舌等,以及风暴自身形成的冷池、出流等与风暴演变密切相关的对流尺度结构。     

A model for retrieval of dual linear polarization radar fields from model simulation outputs

An algorithm for retrieving polarimetric variables from numerical model fields is developed. By using this technique, radar reflectivity at horizontal polarization~ differential reflectivity, specific differential phase shift and correlation coefficients between the horizontal and vertical polarization signals at zero lag can be derived from rain, snow and hail contents of numerical model outputs. Effects of environmental temperature and the melting process on polarimetric variables are considered in the algorithm. The algorithm is applied to the Advanced Regional Prediction System （ARPS） model simulation results for a hail storm. The spatial distributions of the derived parameters are reasonable when compared with observational knowledge. This work provides a forward model for assimilation of dual linear polarization radar data into a mesoscale model.     

面向资料同化的风廓线雷达风场特征分析及其质控方法

以美国国家环境预报中心全球预报系统（National Centers for Environmental Prediction/Global Forecast System,NCEP/GFS）0.5°×0.5°分析场作为数值预报背景场,结合地面降水资料,面向资料同化分析了2017年1～12月逐日00时、06时、12时、18时（协调世界时）福建12部L波段风廓线雷达（其中CFL-03系列3部、CFL-06系列9部）水平风产品质量特征,并初步探讨了不同质量控制方案的影响差异。结果表明:（1）CFL-06系列雷达在水平风的最大探测高度、有效数据获取率和低层水平风质量等方面明显优于CFL-03系列;（2）相同系列的不同风廓线雷达探测水平风的数据获取率、有效探测高度、标准差、相关系数及偏差的垂直分布特征等存在极大差异,该差异与风廓线雷达所处的地理位置（沿海或内陆）、海拔高度等并无直接关系;（3）各雷达站探测u风速相对背景场存在明显系统性负偏差,小于背景场,不满足资料同化对背景场的无偏需求,资料同化时需进行偏差订正;v风则相对较好;（4）降水对风廓线雷达探测影响较大,有降水时数据获取率在中低层有所减小,但在中高层则大幅提高;u、v风标准差在中低层有所增加,而在中高层v风标准差有所增加,u风标准差则大幅降低;（5）针对不同风廓线雷达,提出了不同高可信度区间和不同有效探测高度两种质量控制方案,并与固定有效探测高度方案进行了对比,结果表明,这两种质量控制方案皆具有明显优势。不同高可信度区间方案的质量控制效果更为显著,不同雷达站水平测风数据得到更加充分和有效识别,既减少了雷达资料不必要损失,又可将质量差的数据进一步剔除;该方案在有降水情形下也有较好效果。     

Comparison of the observation capability of an X-band phased-array radar with an X-band Doppler radar and S-band operational radar

An X-band phased-array meteorological radar （XPAR） was developed in China and will be installed in an airplane to observe precipitation systems for research purposes.In order to examine the observational capability of the XPAR and to test the operating mode and calibration before installation in the airplane,a mobile X-band Doppler radar （XDR） and XPAR were installed at the same site to observe convective precipitation events.Nearby S-band operational radar （SA） data were also collected to examine the reflectivity bias of XPAR.An algorithm for quantitative analysis of reflectivity and velocity differences and radar sensitivity of XPAR is presented.The reflectivity and velocity biases of XPAR are examined with SA and XDR.Reflectivity sensitivities,the horizontal and vertical structures of reflectivity by the three radars are compared and analyzed.The results indicated that while the XPRA with different operating modes can capture the main characteristic of 3D structures of precipitation,and the averaged reflectivity differences between XPAR and XDR,and XDR and SA,were 0.4 dB and 6.6 dB on 13 July and-4.5 dB and 5.1 dB on 2 August 2012,respectively.The minimum observed reflectivities at a range of 50 km for XPAR,XDR and SA were about 15.4 dBZ,13.5 dBZ and-3.5 dBZ,respectively.The bias of velocity between XPAR and XDR was negligible.This study provides a possible method for the quantitative comparison of the XPAR data,as well as the sensitivity of reflectivity,calibration,gain and bias introduced by pulse compression.     

用机载多普勒雷达资料进行三维风场解析反演 I. 多重解析多普勒方法在机载雷达情况下的推广及模拟验证

多重解析多普勒（MANDOP）方法是用解析表达式进行三维风场反演。它成功地应用于处理地基多普勒雷达资料，获取对流系统层状降水区域的风场结构。本文将MANDOP方法在机载雷达情况下的进行推广并通过模拟研究径向速度测量中信号噪声、雨滴降落速度估计误差、平流速度估计误差、尤其是由于机载特性的引入产生的雷达束定位误差等对方法的影响。模拟结果显示，在机载雷达的技术参数下，MANDOP方法能够提供误差可以接受的三维风场反演。这为利用MANDOP方法处理在CaPE实验中获取的历史上第一次机载双束多普勒雷达资料建立了可靠的基础。     

Impact of Coastal Radar Observability on the Forecast of the Track and Rainfall of Typhoon Morakot(2009)Using WRF-based Ensemble Kalman Filter Data Assimilation

This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot(2009)using a WRF-based ensemble Kalman filter(EnKF)data assimilation(DA)system.The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone(TC).It was found that assimilating radial velocity(Vr)data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall.The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled.Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment.Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line.However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts.Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance.     

The WRF 3DVar System Combined with Physical Initialization for Assimilation of Doppler Radar Data

The three-dimensional variational data assimilation (3DVar) system of the Weather Research and Forecasting (WRF) model (WRF-Var) is further developed with a physical initialization (PI) procedure to assimilate Doppler radar radial velocity and reflectivity observations. In this updated 3DVar system, specific humidity, cloud water content, and vertical velocity are first derived from reflectivity with PI, then the model fields of specific humidity and cloud water content are replaced with the modified ones, and finally, the estimated vertical velocity is added to the cost-function of the existing WRF-Var (version 2.0) as a new observation type, and radial velocity observations are assimilated directly by the method afforded by WRF-Var. The new assimilation scheme is tested with a heavy convective precipitation event in the middle reaches of Yangtze River on 19 June 2002 and a Meiyu front torrential rain event in the Huaihe River Basin on 5 July 2003. Assimilation results show that the increments of analyzed variables correspond well with the horizontal distribution of the observed reflectivity. There are positive increments of cloud water content, specific humidity, and vertical velocity in echo region and negative increments of vertical velocity in echo-free region where the increments of horizontal winds present a clockwise transition. Results of forecast experiments show that the effects of adjusting cloud water content or vertical velocity directly with PI on forecast are not obvious. Adjusting specific humidity shows better performance in forecasting the precipitation than directly adjusting cloud water content or vertical velocity. Significant improvement in predicting precipitation as well as in reducing the model's spin-up time are achieved when radial velocity and reflectivity observations are assimilated with the new scheme.     

三维变分和物理初始化方法相结合同化多普勒雷达资料的试验研究

以美国新近研发的天气研究预报模式(WRF)配置的三维变分(3D-Var)同化系统WRF 3D-Var为平台,结合物理初始化方法(Physical Initialization,简称PI)来同化多普勒雷达径向风和回波强度观测资料.其基本做法是首先用物理初始化方法由雷达回波资料估计出比湿、云水混合比和垂直速度,然后用估计的比湿和云水混合比对模式的相应变量进行调整,最后再将估计出的垂直速度作为一种新的观测类型添加到现有的WRF 3D-Var目标函数中,同时以WRF 3D-Var提供的方法直接同化径向风.针对2002年6月19日的一次强对流性降水过程和2003年7月5日的一次梅雨锋暴雨过程进行了一组同化多普勒雷达径向风和回波资料的试验研究.同化结果表明:分析变量的增量场和观测的雷达回波有很好的对应关系.在雷达回波区,有正的比湿增量、云水含量增量和垂直速度增量,并且水平风增量在此辐合;在没有雷达回波的地方有负的垂直速度增量.预报结果表明,调整云水含量对降水预报改善不明显,调整比湿对降水预报改进明显,直接用物理初始化估计出的垂直速度替代模式的初始垂直速度,对降水预报改进不明显,但以新的方案同化雷达资料能有效地缩短模式的起转时间(spin-up time),明显改进短时降水预报.     

GPM/DPR雷达与CINRAD雷达降水探测对比

通过对比星载DPR雷达与地基CINRAD雷达的降雨测量值,评估星地雷达联合应用的潜力。为了提高对比的准确性,在尽可能高的时空分辨率下,以几何匹配与格点匹配相结合的方式,提取星地雷达降水样本数据。2015年6月30日降水过程的对比分析结果表明:泰州、常州CINRAD雷达反射率因子在两站中分剖面的平均值偏差0.94 dB,地基雷达之间有很好的一致性;在DPR雷达与常州、泰州CINRAD雷达同时覆盖的降雨区域,星地之间雷达反射率因子的平均值偏差分别为-1.2 dB和-1.6 dB,显示星地雷达也有较好的一致性;现有DPR雷达陆上衰减订正算法在缩小星地雷达偏差方面起到一定作用,平均订正量0.4 dB,只要回波覆盖充分,匹配样本的高度以及其到地基雷达的距离对对比结果没有明显影响,而衰减订正和匹配样本区回波覆盖率是影响星地雷达对比结果的重要因素。     

任意基线雷达反射率因子垂直剖面生成算法

该文提出了一种基于雷达体扫资料的任意基线雷达反射率因子垂直剖面的生成算法。在计算雷达反射率因子垂直剖面上的格点在雷达极坐标中的仰角、方位和斜距位置后, 采用径向、方位上的最近邻居和垂直方向的线性内插相结合的客观分析方法得到格点上的反射率因子分析值。在垂直线性内插时分别用dBZ值和Z值 (单位: mm6/m3) 进行插值。结果表明:用该方法得到的雷达反射率因子垂直剖面从回波强度和空间位置来看都是合理的; 当采用垂直线性内插时, 用dBZ值插值比用Z值插值得到的雷达反射率因子垂直剖面在空间分布上更连续, 反射率因子分析值总体上更接近观测值; 低仰角的插值效果比高仰角的好。     

Doppler Radar Data Assimilation with a Local SVD-En3DVar Method

An observation localization scheme is introduced into an ensemble-based three-dimensional variational (3DVar) assimilation method based on the singular value decomposition technique (SVD-En3DVar) to improve assimilation skill. A point-by-point analysis technique is adopted in which the weight of each observation decreases with increasing distance between the analysis point and the observation point. A set of numerical experiments, in which simulated Doppler radar data are assimilated into the Weather Research and Forecasting (WRF) model, is designed to test the scheme. The results are compared with those obtained using the original global and local patch schemes in SVD-En3DVar, neither of which includes this type of observation localization. The observation localization scheme not only eliminates spurious analysis increments in areas of missing data, but also avoids the discontinuous analysis fields that arise from the local patch scheme. The new scheme provides better analysis fields and a more reasonable short-range rainfall forecast than the original schemes. Additional forecast experiments that assimilate real data from 10 radars indicate that the short-term precipitation forecast skill can be improved by assimilating radar data and the observation localization scheme provides a better forecast than the other two schemes.