Geophysical Model Function for Wind Speed Retrieval from SARAL/AltiKa

With the launch of SARAL/AltiKa altimeter, efforts have been made to develop wind speed retrieval algorithms. Here we present two algorithms for estimating and validating wind speed from AltiKa. The first method is based on a theoretical Geophysical Model Function (GMF) using forward model simulations for Ka band specifications. The second is the model function developed using the matched database of input and output vectors of Normalized Radar Cross Section (NRCS) from AltiKa and wind speed measurements from concurrent Jason-2 altimeters. Since the NRCS depends on both the surface roughness due to surface wind speed and on mean square slope of the surfaces, the significant wave height is used along with wind speed for model development as an proxy variable. Both the theoretical and empirical GMFs are evaluated for retrieval of wind speed from AltiKa and validated with NDBC buoys data. The empirical model provide wind speed retrieval accuracy of 1.4 m/s. The accuracy of wind retrievals from theoretical model is also in the similar range (1.6 m/s), indicating the sound physical basis applicable for the future altimeters with various incidence angles. The retrieved wind speed is applied for various case studies, bringing out all the regional and global features quite well.     

便携式高频地波雷达台湾海峡浪高观测

As an important equipment for sea state remote sensing, high frequency surface wave radar(HFSWR) has received more and more attention. The conventional method for wave height inversion is based on the ratio of the integration of the second-order spectral continuum to that of the first-order region, where the strong external noise and the incorrect delineation of the first- and second-order Doppler spectral regions due to spectral aliasing are two major sources of errors in the wave height. To account for these factors, two more indices are introduced to the wave height estimation, i.e., the ratio of the maximum power of the second-order continuum to that of the Bragg spectral region(RSCB) and the ratio of the power of the second harmonic peak to that of the Bragg peak(RSHB). Both indices also have a strong correlation with the underlying wave height. On the basis of all these indices an empirical model is proposed to estimate the wave height. This method has been used in a three-months long experiment of the ocean state measuring and analyzing radar, type S(OSMAR-S), which is a portable HFSWR with compact cross-loop/monopole receive antennas developed by Wuhan University since 2006. During the experiment in the Taiwan Strait, the significant wave height varied from 0 to 5 m. The significant wave heights estimated by the OSMAR-S correlate well with the data provided by the Oceanweather Inc. for comparison, with a correlation coefficient of 0.74 and a root mean square error(RMSE) of 0.77 m. The proposed method has made an effective improvement to the wave height estimation and thus a further step toward operational use of the OSMAR-S in the wave height extraction.     

利用Sentinel-1影像监测土地回填导致的地表形变

在机场填海区地表稳定散射的范围内,本文运用合成孔径雷达干涉测量（InSAR）技术对机场地表形变安全性进行了监测分析,反演获得了研究区域范围内的年形变速率数据结果和高分辨率形变时序结果,并以此分析了香港国际机场的地表形变区在监测周期内的形变时空分布特征。为证明监测结果的精度和可靠性,本文采用全球导航卫星系统（GNSS）观测站的垂直位移数据,对InSAR方法反演的结果进行了交叉验证,证明两者具有良好的一致性。     

虚拟仪器在天气雷达发射机脉冲测试中的应用

随着我国新一代天气雷达（CINRAD）的广泛布网,雷达的维修维护工作显得日益繁重。利用虚拟仪器测试系统对雷达重要参数指标测试是一种便捷有效的方式。本文从发射机射频脉冲包络以及其测量方法的介绍出发,搭建一套基于PXI(PCI eXtensions for Instrumentation)模块化仪器的虚拟仪器系统,采用LabVIEW(Laboratory Virtual Instrument Engineering Workbench)软件编程实现参数测试测量功能,通过实验完成了对脉冲包络的重要参数测试。虚拟仪器测试系统与传统仪器对比测量结果,验证了该测试系统的可靠性。     

雷达雨量计联合估算降水在城市内涝模型中的应用

为了满足城市暴雨内涝模型对面雨量精细化的需求,在天津城市暴雨内涝模型的基础上,将雷达估算降水产品应用到模型面雨量计算中,针对2012年7月25—26日天津的大暴雨过程,考察4种雷达估算降水产品和两种插值方法计算的内涝模型面雨量。经过对比发现,利用变分方法计算的雷达估算降水产品VAR用曲面插值方法计算内涝模型的面雨量整体效果最好。     

WRF-Hybrid背景误差协方差调整在台风同化及预报中的应用研究

利用雷达径向风单点试验和2006年8月超强台风"桑美"个例,首先研究了静态背景误差协方差的尺度化因子和方差在台风系统雷达资料同化中对台风路径和强度预报的影响。结果表明:在高时空分辨率的雷达资料同化中,较小的尺度化因子能显著改进对台风路径的预报;尺度化因子的影响比方差的影响更为显著。基于上述实验结果,进一步研究了WRFDA-Hybrid系统中"流依赖"控制变量的水平局地化和垂直局地化对台风预报的影响。试验结果表明:当"流依赖"的水平局地化距离与静态背景误差协方差的尺度化因子具有等效影响范围的时候,WRFDA-Hybrid能够得到比较合理的分析结果。同时针对雷达观测资料的空间分布特征,本文提出了一种新的基于雷达探测高度的垂直局地化方案,对台风的强度和路径预报均有显著的改进。     

北京“7.21”特大暴雨云降水结构及云雨转化特征

利用多普勒雷达资料、FY-2E静止卫星和MODIS极轨卫星反演产品,研究2012年7月21日北京特大暴雨的云降水结构及云雨转化特征。结果表明:降水过程三阶段的云降水垂直结构不同。1)在暖区对流降水阶段,降水以暖雨机制启动,雨滴在暖区存在深厚的碰并增长过程,暖雨过程对降水起主要贡献。随着云体的发展,冷雨过程加剧。T-Re分析表明,-10℃层以下云滴凝结碰并显著,-10℃层以上为深厚的冰相增长带,云顶以冰相大粒子为主,云水向雨水转化迅速。2)在锋面对流降水阶段,降水系统为高度组织化的"低质心"强降水液态MCC(Mesoscale Convective Complex)系统。回波强度在冰水混合层增长较快,冻结层是此阶段成雨微物理的关键层。降水粒子在暖云区碰并增长较快,而蒸发或破碎过程并不显著。3)在锋后降水阶段,0℃层附近冰晶粒子与云水的碰并增长较为明显。前期降水存在明显的雨滴蒸发过程。随着云体的发展,暖区云水含量较少,降水粒子不能有效碰并增长。     

Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

To improve the accuracy of short-term(0–12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System(HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting(WRF-ARW)model and the Advanced Regional Prediction System(ARPS) three-dimensional variational data assimilation(3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station(AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting(QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6–9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score(FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.     

基于双多普勒雷达及闪电资料分析一次强降水过程

为进一步了解多普勒雷达及闪电资料在中小尺度天气系统方面的应用以及降水系统动力结构的研究,利用合肥和阜阳两部S波段多普勒雷达资料,通过两步变分反演法反演双雷达,并采用模糊逻辑算法进行云类型识别,再结合垂直累计液态水含量VIL、降水和闪电分布特征,分析了2010年6月7-10日发生在安徽合肥和阜阳的一次持续性强降水过程。结果表明:此次持续性强降水过程与风场的低层辐合和高层辐散、风场的气旋性旋转以及水平风切变相关;此次降水过程是以层状云降水为主的积云混合云降水;另外,以降水为主的层状云,其闪电频数低且以负闪为主,闪电之后20 min左右出现强降水;此次暴雨的VIL值不是很大,强降水区对应的VIL值基本3 kg·m-2;云识别结果、降水区、VIL值与雷达回波强度之间的对应关系较好。     

2013年7月1日河北宁晋极端短时强降水成因研究

2013年7月1日午后至夜间,华北出现一次区域性暴雨和局地大暴雨过程。局地极端降水出现在河北省邢台市宁晋县四芝兰镇,过程雨量409 mm,其中当日17—19时连续2 h雨量超过100 mm。利用常规高空和地面观测资料、NCEP再分析资料和石家庄新一代天气雷达资料,探讨了宁晋极端短时强降水的形成原因。主要结论是:(1)低槽、冷锋、副热带高压及其外围低涡切变线为其主要影响系统,海南附近台风远距离影响加强了水汽自南向北的输送,半定常的地面辐合切变线对新生对流的触发和已有对流的维持及加强起到重要作用;(2)宁晋最强降水期间,其上空具有较强的垂直风切变,有利于高度组织化的对流系统发展;(3)对流系统的后向传播使回波主体移动缓慢、持续时间长,而回波强度大和雨强很强,则导致四芝兰镇极端强降水,此外,具有弱中气旋的超级单体相对较长时间的影响使其对四芝兰镇强降水具有重要贡献;(4)产生极端降水的对流系统属于高质心发展强烈的大陆强对流型,而非更易导致强降水的低质心系统。同时,针对众多学者研究北京"7.21"特大暴雨得到的一些结论进行了进一步探讨和验证。