三维变分同化雷达资料暴雨个例试验

采用中国新一代数值预报模式及其同化系统开展雷达资料的三维变分同化和数值模拟研究.通过一次暴雨个例的对比试验,结果表明:不考虑垂直运动影响的情况下,仅同化多普勒雷达径向风资料可以增加初始场中的中小尺度系统信息,并在一定程度上改善预报开始阶段的降水;同化由反射率因子导出的垂直速度、雨水混合比并令上升区饱和,可以较大改善降水预报结果;联合同化径向速度和反射率因子资料将得到它们的共同影响.模拟的β中尺度对流系统6 h的演变过程与观测十分一致,基本消除了旋转加强现象.发展旺盛阶段的对流单体南北方向范围约50 km,最大上升速度位于500 hPa附近,超过3.0 m/s;雨水最大含量在400 hPa附近,超过5.0 g/kg;云水最大值位于600 hPa,约0.5 g/kg;造成的降水强度可达30 mm/h,具有明显的β中尺度系统的特征.初始场中水汽是否达到β中尺度降水维持所需条件是至关重要的,如果初始场中水汽条件较差,即使含有云水、雨水、垂直速度的信息,这些信息也会很快消亡,难以维持下去;此外,雷达资料的质量控制也是十分重要的.     

不同同化方案在一次梅雨锋暴雨预报中的应用研究

基于ATOVS辐射率资料和GTS常规观测资料融合,通过不同化任何观测资料的控制试验、3DVAR同化试验和ETKF-3DVAR混合同化试验,对2013年7月4—5日一次梅雨锋暴雨天气过程进行模拟分析。结果表明:混合同化方案能够明显地提高暴雨预报准确率,且有效改善了风场、温度场和相对湿度场等各个气象要素的初始场结构,而这些气象要素对于暴雨的预报准确性具有重要作用。且混合同化方案对于中低层大气改进效果较为明显。在数值积分过程中,随着时间的推移,混合同化方案的优势逐渐减弱。     

反演同化和直接同化多普勒雷达径向风的对比试验

针对2003年7月5日江淮流域一次暴雨过程,以NCEP/NCAR 1°×1°再分析资料为背景场,采用WRF(weather research and forecasting)模式及其三维变分同化系统,对雷达径向风和E-VAP(extended velocity azimuth processing)反演的水平风场进行了直接同化和反演同化试验,结果表明:直接同化雷达径向风资料后,增加了初始风场的中小尺度信息,改善了垂直速度条件,且在风场作用下水汽分布得到改善;反演同化资料虽然能增加初始场的中小尺度信息,但效果不如直接同化明显;无论直接同化还是反演同化都能改善降水预报,但直接同化好于反演同化,且间隔5～6 min比30 min的直接同化模拟效果好.     

多普勒雷达资料循环同化在台风“鲇鱼”预报中的应用

高分辨率的中尺度预报模式ARPS及其3DVAR/云分析系统,针对2010年登陆福建的超强台风“鲇鱼”,研究对流可分辨尺度下,每1h循环同化沿海新一代多普勒雷达网资料分析、研究对台风初始场和预报场的改进作用.结果表明:单独同化雷达资料可显著改善初始场中的台风内核区动力和热力结构,以及台风强度和位置,进而提高18h台风强度、路径和降水预报,但预报路径和降水分布与实况仍存在差异.在雷达资料同化基础上加入常规观测资料,对初始场中台风内核区结构改进不大.但在显著调整大尺度背景场,从而进一步减少台风路径预报误差,能准确预报出福建沿海两个强降水区域的位置和强度.总体而言,雷达资料同化主要提高台风结构分析,而常规观测资料同化主要改善环境场分析,两者有效结合使得预报结果和实况最为接近.     

Mesoscale Structure of Rainstorm Retrieved from Dual-Doppler Radar Observations Using the 4DVAR Assimilation Technique

The four-dimensional variational (4DVAR) data assimilation method was applied to dual-Doppler radar data about two Meiyu rainstorms observed during CHeRES (China Heavy Rain Experiment and Study). The purpose of this study is to examine the performance of the 4DVAR technique in retrieving rainstorm mesoscale structure and to reveal the feature of rainstorm mesoscale structure. Results demonstrated that the 4DVAR assimilation method was able to retrieve the detailed structure of wind, thermodynamics, and microphysics fields from dual-Doppler radar observations. The retrieved wind fields agreed with the dual-Doppler synthesized winds and were accurate. The distributions of the retrieved perturbation pressure, perturbation temperature, and microphysics fields were also reasonable through the examination of their physical consistency. Both of the two heavy rainfalls were caused by merging cloud processes. The wind shear and convergence lines at middle and lower levels were their primary dynamical characteristics. The convective system was often related to low-level convergence and upper-level divergence coupled with up-drafts. During its mature stage, the convective system was characterized by low pressure at lower level and high pressure at upper level, associated with warmer at middle level and colder at lower and upper levels than the environment. However, a region of cooling and high pressure occurred in the lower and middle levels compared to warming and low pressure in the upper level during its dissipating stage. The water vapor, cloud water, and rainwater corresponded to the convergence, the updraft and the intensive reflectivity, respectively.     

适应数值模式垂直坐标的GPS掩星反演资料稀疏化方案

GPS掩星反演大气温湿资料具有高垂直分辨率、高精度、受云和降水影响小等优点,针对GRAPES同化预报系统,发展设计了一种既考虑预报模式高度-地形追随垂直坐标不均匀分层特点,又结合掩星反演资料特性的新适应性垂直稀疏化方案。通过个例试验和批量试验,探索了该适应性稀疏化方案对分析预报质量的影响。试验结果表明:选取合适的稀疏参数,新稀疏化方案的GPS掩星反演资料对背景场的调整更加有效,分析场质量更高;位势高度、比湿、温度和风场等预报场的均方根误差均更小;适应性稀疏化方案对改善台风路径预报具有积极作用。批量试验则进一步证实了适应性稀疏化方案对分析场质量有明显的改善作用。     

台风预报误差的流依赖特征及混合资料同化中最优耦合系数

基于集合卡尔曼变换与三维变分(ETKF-3DVAR)混合资料同化系统和欧洲中期天气预报中心(ECWMF)的全球集合预报,以"梅花"台风为例,分析了台风系统预报误差的流依赖特征,讨论了耦合系数在混合同化和预报中的敏感性及其对预报质量的影响。结果显示,台风系统的预报误差协方差具有显著的中小尺度结构特征,集合估计的预报误差协方差结构能够再现其流依赖属性。相对于3DVAR方案,混合资料同化方案的最优耦合系数对台风系统的分析和预报质量具有更好的改善;但不同的耦合系数对台风路径预报有明显的影响,不合适的耦合系数甚至可能导致更坏的结果,只有耦合了相对合适的预报误差协方差的流依赖信息,混合资料同化方案才可能对分析和预报质量有正效果。这表明在混合资料同化系统中,构造一种具有自适应能力的耦合权重函数,实现相对最优权重的自动选择,对充分发挥混合资料同化方案的潜在优势具有重要意义。     

Impact of 4DVAR assimilation of rainfall data on the simulation of mesoscale precipitation systems in a mei-yu heavy rainfall event

The multi-scale weather systems associated with a mei-yu front and the corresponding heavy precipitation during a particular heavy rainfall event that occurred on 4 5 July 2003 in east China were successfully simulated through rainfall assimilation using the PSU/NCAR non-hydrostatic, mesoscale, numerical model （MM5） and its four-dimensional, variational, data assimilation （4DVAR） system. For this case, the improvement of the process via the 4DVAR rainfall assimilation into the simulation of mesoscale precipitation systems is investigated. With the rainfall assimilation, the convection is triggered at the right location and time, and the evolution and spatial distribution of the mesoscale convective systems （MCSs） are also more correctly simulated. Through the interactions between MCSs and the weather systems at different scales, including the low-level jet and mei-yu front, the simulation of the entire mei-yu weather system is significantly improved, both during the data assimilation window and the subsequent 12-h period. The results suggest that the rainfall assimilation first provides positive impact at the convective scale and the influences are then propagated upscale to the meso- and sub-synoptic scales.
Through a set of sensitive experiments designed to evaluate the impact of different initial variables on the simulation of mei-yu heavy rainfall, it was found that the moisture field and meridional wind had the strongest effect during the convection initialization stage, however, after the convection was fully triggered, all of the variables at the initial condition seemed to have comparable importance.     

经验正交函数分解质量控制法在地面观测资料变分同化中的个例研究与应用

同化地面观测资料能够获得丰富的地面大气信息,这对于大气边界层的准确模拟尤为重要。由于地面观测资料同化一直受到地面观测资料质量较差的影响,因此,地面观测资料的质量控制是提高地面资料同化效果的重要方法之一。为了分析基于经验正交函数分解质量控制方法(Empirical Orthogonal Function quality control,EOF-QC)对地面资料同化效果的影响,并进一步检验该方法在实际同化试验中的应用效果,在WRF的三维变分同化系统中引入了经验正交函数分解质量控制法,同时通过一系列同化试验比较了经验正交函数分解质量控制法与原系统自带的基于观测与模拟偏差质量控制法(Observation Minus Background quality control,OMB-QC)的差异。2008年1和7月的多个强降水预报试验结果表明,经验正交函数分解质量控制法能够保留更多天气系统的有效观测信息,更为客观准确地反映大气真实状态;同化经过经验正交函数分解质量控制法后的观测资料,模式预报的温度降低,在北部形成一个气旋性环流,该环流底部的偏西气流带动北部冷空气东移入海,同时冷空气南下也削弱了带有丰富水汽的西南气流,从而使模式预报的降水范围和强度更加合理。降水的空间分布对比结果也表明,经验正交函数质量控制法改善了模式对降水落区和强度的预报能力,各个量级的降水评分有明显提高,模拟结果更接近于实况。各组数值模拟试验结果表明,经验正交函数分解质量控制法在WRF-3DVAR中具有较高的应用潜力。     

The effect of three-dimensional variational data assimilation of QuikSCAT data on the numerical simulation of typhoon track and intensity

In this paper, the three-dimensional variational data assimilation scheme (3DVAR) in the mesoscalemod el version 5 (MM5) of the US Pennsylvania State University/National Center for Atmospheric Research is used to study the effect of assimilating the sea-wind data from QuikSCAT on the prediction of typhoon track and intensity. The case of Typhoon Dujuan (2003) is first tested and the results show appreciable improvements. Twelve other cases in 2003 are then evaluated. The assimilation of the QuikSCAT data produces significant impacts on the structure of Dujuan in terms of the horizontal and vertical winds, sealevel pressure and temperature at the initial time. With the assimilation, the 24-h (48-h) track prediction of 11 (10) out of the 12 typhoons is improved. The 24-h (48-h) prediction of typhoon intensity is also improved in 10 (9) of the 12 cases. These experiments therefore demonstrate that assimilation of the QuikSCAT sea-wind data can increase the accuracy of typhoon track and intensity predictions through modification of the initial fields associated with the typhoon.     

雷达径向风速同化对台风麦莎模拟的影响

本文应用WRF-3DVAR系统同化多普勒雷达径向风速资料,并利用WRF模式对台风麦莎（2005年8月6日00时至7日00时）进行数值模拟,以此检验多普勒雷达径向风速资料在改进模式初始场及提高台风路径和降水预报准确度等方面的应用效果及意义,探讨不同同化时间间隔对同化效果的影响。通过对比同化试验和控制试验发现：雷达径向风速资料能通过调整初始风场结构,改进对台风结构的模拟,从而提高模式对台风麦莎的路径、强度和降水的模拟能力;雷达资料信号在进入模式后有一定的时效性,在一定程度上缩小同化时间间隔有助于提高同化效果。     

Assimilation and Simulation of Typhoon Rusa （2002） Using the WRF System

Using the recently developed Weather Research and Forecasting (WRF) 3DVAR and the WRF model, numerical experiments are conducted for the initialization and simulation of typhoon Rusa (2002).The observational data used in the WRF 3DVAR are conventional Global Telecommunications System (GTS) data and Korean Automatic Weather Station (AWS) surface observations. The Background Error Statistics (BES) via the National Meteorological Center (NMC) method has two different resolutions, that is, a 210-km horizontal grid space from the NCEP global model and a 10-km horizontal resolution from Korean operational forecasts. To improve the performance of the WRF simulation initialized from the WRF 3DVAR analyses, the scale-lengths used in the horizontal background error covariances via recursive filter are tuned in terms of the WRF 3DVAR control variables, streamfunction, velocity potential, unbalanced pressure and specific humidity. The experiments with respect to different background error statistics and different observational data indicate that the subsequent 24-h the WRF model forecasts of typhoon Rusa‘s track and precipitation are significantly impacted upon the initial fields. Assimilation of the AWS data with the tuned background error statistics obtains improved predictions of the typhoon track and its precipitation.     

基于模式约束三维变分技术的连续循环同化试验研究

由于模式约束三维变分同化技术中考虑了模式的动力和物理过程,因此能保证各物理量间的平衡关系,从而滤除由于观测资料引入导致的高频波动,减小模式与初始场的协调时间.由于能在较短时间调整到稳定状态,采用模式约束三维变分同化进行连续循环同化可用较少的计算量达到同化多时次的多种观测资料的目的.该研究利用模式约束三维变分技术,针对2006年"桑美"台风个例,进行了连续循环同化卫星云导风、QuikSCAT海面风、Bogus海平面气压的试验.在台风数值预报中往往需要使用经验构造的台风信息(如Bogus海平面气压,Bogus风场等),该研究采用了模式约束三维变分同化技术同化Bogus海平面气压.由于模式约束三维变分同化技术充分考虑了各物理量间的约束,因此通过同化Bogus海平面气压也调整了初始场中相应的高度场、温度场、风场等变量,使得初始场中的台风涡旋具有较强的协调性,提高了对台风的模拟能力.采用AVN模式6小时间隔的分析场作为侧边界,2006年8月8日20时的分析场作为初估场,文中对8月8日20时到9日05时"桑美"台风的观测资料进行了连续循环同化.采用连续循环同化后台风路径的模拟精度得到了显著提高,对台风降水结构等的模拟也得到了改善.     

GPS ZTD资料同化对台风“利奇马”模拟的影响研究

2019年超级台风“利奇马”对我国东部地区造成了巨大灾害,针对台风“利奇马”,研究GPS ZTD资料同化对于台风“利奇马”登陆后降水预报的影响。在进行GPS ZTD资料同化试验前,采取了稳定性检查、极值检查、双权重检查、偏差订正检查等质量控制方法以改善资料的同化应用水平。模拟试验结果表明在同化探空、风廓线等常规资料基础上,增加质控GPS ZTD有效改善了初始场的水汽条件,使得低层水汽辐合更强,从而改进了台风外围雨带的预报。并且通过循环同化能够改善初始环流场,进而改进了台风路径的预报使得台风主体降水的位置得到改善。     

AMSU-A全空辐射率资料同化对台风“天鸽”的预报影响研究

利用美国NCEP(National Centers for Environmental Prediction)发展的GSI(Gridpoint Statistical Interpolation)同化系统和GSM(Global Spectral Model)全球频谱预报模式作为循环同化系统,选用2017年第13号台风为研究个例,采用全空和晴空两种同化方案对AMSU-A(The Advanced Microwave Sounding Unit-A)辐射率观测开展同化对比试验,并对台风"天鸽"个例进行5 d预报,研究AMSU-A全空辐射率同化对台风天鸽发展过程预报的影响。结果表明,全空同化方案相比晴空同化方案预报的台风路径、台风中心气压以及台风最大风速预报误差更小;全空同化方案对台风"天鸽"生命周期的模拟更加准确,更接近中国气象局发布的台风天鸽最佳路径的最低气压,而晴空同化方案预报的台风发展较弱,无法预报出成熟期的台风强度;全空同化方案能够增加低层通道海上厚云覆盖区域辐射率资料同化量,增幅占AMSUA同化观测总量10%,从而改进海洋区域天气系统的热力场结构。     

GRAPES混合同化方法在青藏高原区域的初步试验

针对青藏高原地区气象观测站点稀少和模式同化分析质量较低的问题,将GRAPES区域集合变分(En-3DVAR)混合同化系统应用于青藏高原地区,进行了单点理想试验和真实观测资料同化分析预报试验,分析评估青藏高原混合同化分析增量及预报误差的水平垂直结构特征及其合理性,并与中国东部平原地区进行比对。单点理想试验表明,En-3DVAR混合同化系统中背景误差协方差具备流依赖属性。真实资料混合同化试验结果表明,基于集合预报估计的分析增量具有流依赖的特征,特别是在高原地区和槽脊系统附近;青藏高原地区分析场的绝对误差总体低于3DVAR系统,其平均绝对误差在中层和高层低于平原地区,说明在青藏高原地区的改进效果略优于平原地区。需要关注的是,青藏高原地区En-3DVAR混合同化分析增量总体大于3DVAR,特别是近地面层u风分量分析增量明显偏大,这可能与青藏高原复杂地形有关。     

Dynamical and Microphysical Retrieval from Simulated Doppler Radar Observations Using the 4DVAR Assimilation Technique

Based on a cloud model and the four-dimensional variational (4DVAR) data assimilation method developed by Sun and Crook (1997), simulated experiments of dynamical and microphysical retrieval from Doppler radar data were performed. The 4DVAR data assimilation technique was applied to a cloud scale model with a warm rain parameterization scheme. The 3D wind, thermodynamical, and microphysical fields were determined by minimizing a cost function, defined by the difference between both radar observed radial velocities and reflectivities and their model predictions. The adjoint of the numerical model was used to provide the gradient of the cost function with respect to the control variables. Experiments have demonstrated that the 4DVAR assimilation method is able to retrieve the detailed structure of wind, thermodynamics, and microphysics by using either dual-Doppler or single-Doppler information. The quality of retrieval depends strongly on the magnitude of constraint with respect to the variables. Retrieving the temperature field, cloud water and water vapor is more difficult than the recovery of the wind field and rainwater. Accurate thermodynamic retrieval requires a longer assimilation period. The inclusion of a background term, even mean fields from a single sounding, helped reduce the retrieval errors. Less accurate velocity fields were obtained when single-Doppler data were used. It was found that the retrieved velocity is sensitive to the location of the retrieval domain relative to the radars while the other fields have very little changes. Two radar volumetric scans are generally adequate for providing the evolution, although the use of additional volumes improves the retrieval. As the amount of the observations decreases, the performance of the retrieval is degraded. However, the missing observations can be compensated by adding a background term to the cost function. The technique is robust to random errors in radial velocity and calibration errors in reflectivity. The boundary conditions from the dual-Doppler synthesized winds are sufficient for the retrieval. When the retrieval is mainly controlled by the observations in the regions away from the boundaries, the simple boundary conditions from velocity azimuth display (VAD) analysis are also available. The microphysical retrieval is sensitive to model errors.     

Application of 4D-Variational data assimilation to the California Current System

The Incremental Strong constraint 4D-Variational (IS4DVAR) data assimilation system of the Regional Ocean Model System (ROMS) is used to study the controllability of a realistic, high resolution configuration of the California Current System. The configuration and results of assimilating both satellite-derived surface observations along with in situ data are presented. Results show consequent improvements in many characteristics of the model circulation, and some of the strengths of the adjoint method for data assimilation are highlighted. General issues of the sensitivity of the results to the configuration of ROMS-IS4DVAR are also discussed.     

四维数据同化在一次梅雨锋暴雨过程中的应用研究

通过2008年梅雨季内的一次暴雨过程来着重研究WRF模式中四维测站同化技术的应用情况以及不同的同化策略对模拟结果的影响,使用的同化资料包括常规高空和地面探测资料。结果表明:高空探测资料的同化能够较好地修正中α尺度系统的移动发展速度,从而有效地改进强降雨带的落区位置;湿度观测资料的同化反而降低了强降雨带的降水强度,这可能因为同化湿度观测量可能减小近饱和区域内的水汽混合比,从而导致这些区域内的潜热加热减小,对流强度变弱,降水减少;地面观测资料的同化能够对模式行星边界层进行修正,这种同化影响通常在模式最低层上表现得较为明显,向上逐渐减小,而边界层模拟质量对降水至关重要,因此地面观测资料的加入使得模拟降水更加接近于实况。区域嵌套模拟试验表明对粗网格区域进行四维分析同化处理可以有效抑制中α尺度模式误差的增长,对细网格区域进行四维测站同化处理则可以进一步抑制中β尺度模式误差增长。     

多部多普勒天气雷达资料同化对暴雨个例模拟的影响分析

利用中尺度模式WRF(Weather Research and Forecasting Model)及其资料同化系统3DVAR,将国内多普勒天气雷达(CINRAD)反射率因子及径向风资料直接用于中尺度数值模拟;对安徽梅雨期一次暴雨过程进行模拟试验,经过质量控制后,分析同时同化安徽省内六部多普勒天气雷达观测资料对模拟结果的影响。结果表明:(1)经过质量控制后,同化雷达径向风和反射率因子对初始场的风场和湿度场均有较为明显的改善,说明用该雷达资料质量控制方案同化雷达资料是可行的;(2)同化多部雷达径向速度资料能使风场气旋性增强,同化反射率资料能调整初始水汽场,使对流层中下层水汽含量增加;(3)同化多部雷达径向风和反射率因子资料,能提前模拟出强降水回波结构,且其中尺度特征更清晰,降水落区和强度预报更接近实况,同化雷达资料对降水预报能持续影响到12 h,并提高了12 h降水预报准确率。