Effect of Length Scale Tuning of Background Error in WRF-3DVAR System on Assimilation of High-Resolution Surface Data for Heavy Rainfall Simulation

We investigated the impact of tuning the length scale of the background error covariance in the Weather Research and Forecasting(WRF) three-dimensional variational assimilation(3DVAR) system.In particular,we studied the effect of this parameter on the assimilation of high-resolution surface data for heavy rainfall forecasts associated with mesoscale convective systems over the Korean Peninsula.In the assimilation of high-resolution surface data,the National Meteorological Center method tended to exaggerate the length scale that determined the shape and extent to which observed information spreads out.In this study,we used the difference between observation and background data to tune the length scale in the assimilation of high-resolution surface data.The resulting assimilation clearly showed that the analysis with the tuned length scale was able to reproduce the small-scale features of the ideal field effectively.We also investigated the effect of a double-iteration method with two different length scales,representing large and small-length scales in the WRF-3DVAR.This method reflected the large and small-scale features of observed information in the model fields.The quantitative accuracy of the precipitation forecast using this double iteration with two different length scales for heavy rainfall was high;results were in good agreement with observations in terms of the maximum rainfall amount and equitable threat scores.The improved forecast in the experiment resulted from the development of well-identified mesoscale convective systems by intensified low-level winds and their consequent convergence near the rainfall area.     

基于雷达资料同化的江西一次暴雨过程的数值模拟试验

采用WRF中尺度模式及其三维变分同化系统WRF-3DVAR,对2014年5月24—25日发生在萍乡、宜春地区一次大暴雨天气过程进行了雷达资料直接同化敏感性试验,并对同化结果和模式降水预报进行了对比分析。结果表明:1)雷达资料的同化能有效改善初始场中风场、湿度场和热力场的量值大小及空间分布,使其包含更多的中尺度系统信息。其中,雷达反射率因子的同化对大气湿度场和温度场的影响较大,而雷达径向速度的同化作用主要是调整大气风场。2)短时降水预报方面,雷达反射率因子的同化对0—12 h短时降水预报的量值影响较大,而径向速度的同化对降水预报的落区影响较大,两者同时的同化对降水预报效果较好。3)雷达资料的同化对较长时间(6—12 h)的降水预报仍有较好效果。     

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。     

多普勒雷达资料同化对北京“7.21”大暴雨过程模拟的影响

利用新一代中尺度预报模式WRFV3.6及其三维变分同化系统(WRF-3DVAR),对2012年7月21日北京地区的一次暴雨过程进行多普勒天气雷达径向风和反射率的同化试验研究,检验和探讨高时空分辨率多普勒天气雷达资料在改进模式初始场及提高对暴雨过程预报的准确率等方面的应用效果及意义。结果发现雷达资料同化能在初始场中加入反映产生降水的低层风场辐合的动力和锋前暖区充足的水汽条件的物理信息,可以在模式积分开始后改善初始场中水汽和风的分布,较快地模拟出局地对流系统的发生、发展,改善由于中尺度观测资料不足而造成的模式初始场里中尺度信息缺乏的问题。径向速度的同化增加了中尺度信息,对初始流场的调整较为显著,侧重于改进风场。而雷达反射率资料的同化对初始温、湿度场和强回波位置的调整更明显,侧重于改进湿度场。累计降水的预报结果显示,同化径向风资料对雨带的位置、范围有较好的改进,同化雷达反射率资料对暴雨强度的预报有明显的改善。通过降水ETS评分发现,同化常规观测试验相对于控制实验,对于5、15 mm和25 mm降水评分能增加0.1左右,径向风同化试验能增加0.2左右,反射率同化试验能增加0.3左右,而径向风加反射率试验增加的评分介于0.2～0.3。雷达资料对于提高定量降水预报的精确度有着重要作用。     

雷达资料同化频次对数值模拟效果影响的试验

采用中尺度数值天气预报模式WRF3.2, 研究了不同的同化时间间隔对2011年7月3~4日成都暴雨模拟的影响。结果表明, 同化了雷达资料后, 使初始场的水汽场、水平风场、垂直速度的分布更加接近实况;除温度场外, 同化频次越高对初始场的影响越大, 水平风场的增量值越大, 呈现的中小尺度信息越多, 更加接近“真实”大气;经过多次同化, 中低层风场的改变已经传递到高层, 引起了高层流场的调整;同化雷达反射率资料是有效的, 能够调整大气中的水汽分布。     

资料同化对一次华南暴雨影响的数值试验研究

针对一次华南暴雨过程,采用WRF区域中尺度模式进行了控制试验和同化试验.利用WRF-3DVAR同化系统同化了常规探空和地面观测资料,分析了两种资料对初值场的影响,以及对降水和各物理量预报效果的影响.结果表明:同化能改进初始场,并可改进暴雨落区和强度预报;同化可提高WRF模式对风场、温度场、高度场以及水汽场的预报能力.但有一定的时效性;同时同化探空和地面资料,比仅同化探空资料对大气低层物理量的预报能力要提高较多.     

多普勒雷达资料在冷涡强对流天气中的同化应用试验

应用WRF模式的三维变分同化系统(WRF-3DVAR),对沈阳多普勒天气雷达资料在东北冷涡暴雨个例中的同化应用进行了试验.研制了多普勒雷达资料质量控制系统,实现了对径向风和反射率因子的直接同化,不但可以反演中尺度三维气象要素场,而且可以为模式提供初始场.以天气尺度资料为背景场同化多普勒雷达资料,WRF-3DVAR可以较好地反演冷涡中尺度对流系统的三维结构,反演的地面强对流辐散气流及在对流层中层涡旋都符合中尺度系统概念模型,通过与实际地面探测资料进行了对比,风场环流基本接近,同化了雷达资料的气象要素场可为预报业务提供较好的包含中小尺度系统的实时三维分析场.通过冷涡个例同化试验,应用WRF-3DVAR同化雷达资料后,中尺度模式对对流降水的预报总体有正的影响,对强对流中的一些中小尺度雨团的预报也略有改善.     

Observation and Numerical Simulations with Radar and Surface Data Assimilation for Heavy Rainfall over Central Korea

This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula;the Weather Research and Forecasting(WRF) model and its three-dimensional variational data assimilation system(3DVAR) were used for this purpose. During data assimilation,the WRF 3DVAR cycling mode with incremental analysis updates(IAU) was used. A maximum rainfall of 335.0 mm occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July 2006.Doppler radar data showed that the heavy rainfall was due to the back-building formation of mesoscale convective systems(MCSs).New convective cells were continuously formed in the upstream region,which was characterized by a strong southwesterly low-level jet(LLJ).The LLJ also facilitated strong convergence due to horizontal wind shear,which resulted in maintenance of the storms.The assimilation of both multiple-Doppler radar and surface data improved the accuracy of precipitation forecasts and had a more positive impact on quantitative forecasting(QPF) than the assimilation of either radar data or surface data only.The back-building characteristic was successfully forecasted when the multiple-Doppler radar data and surface data were assimilated.In data assimilation experiments,the radar data helped forecast the development of convective storms responsible for heavy rainfall,and the surface data contributed to the occurrence of intensified low-level winds.The surface data played a significant role in enhancing the thermal gradient and modulating the planetary boundary layer of the model,which resulted in favorable conditions for convection.     

Assimilation of Doppler Radar Data with an Ensemble 3DEnVar Approach to Improve Convective Forecasting

An ensemble three-dimensional ensemble-variational(3DEnVar)data assimilation(E3DA)system was developed within the Weather Research and Forecasting model’s 3DVar framework to assimilate radar data to improve convective forecasting.In this system,ensemble perturbations are updated by an ensemble of 3DEnVar and the ensemble forecasts are used to generate the flow-dependent background error covariance.The performance of the E3DA system was first evaluated against one experiment without radar DA and one radar DA experiment with 3DVar,using a severe storm case over southeastern China on 5 June 2009.Results indicated that E3DA improved the quantitative forecast skills of reflectivity and precipitation,as well as their spatial distributions in terms of both intensity and coverage over 3DVar.The root-mean-square error of radial velocity from 3DVar was reduced by E3DA,with stronger low-level wind closer to observation.It was also found that E3DA improved the wind,temperature and water vapor mixing ratio,with the lowest errors at the surface and upper levels.3DVar showed moderate improvements in comparison with forecasts without radar DA.A diagnosis of the analysis revealed that E3DA increased vertical velocity,temperature,and humidity corresponding to the added reflectivity,while 3DVar failed to produce these adjustments,because of the lack of reasonable cross-variable correlations.The performance of E3DA was further verified using two convective cases over southern and southeastern China,and the reflectivity forecast skill was also improved over 3DVar.     

Assimilation of Polarimetric Radar Data Using an Ensemble Kalman Filter for the Analysis and Forecast of Tropical Storm Ewiniar

This study explores the potential for directly assimilating polarimetric radar data (including reflectivity Z and differential reflectivity ZDR) using an ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting (WRF) model to improve analysis and forecast of Tropical Storm Ewiniar (2018). Ewiniar weakened but brought about heavy rainfall over Guangdong, China after its final landfall. Two experiments are performed, one assimilating only Z and the other assimilating both Z and ZDR. Assimilation of ZDR together with Z effectively modifies hydrometeor fields, and improves the intensity, shape and position of rainbands. Forecast of 24-hour extraordinary rainfall ≥250 mm is significantly improved. Improvement can also be seen in the wind fields because of cross-variable covariance. The current study shows the possibility of applying polarimetric radar data to improve forecasting of tropical cyclones, which deserves more researches in the future.     

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.     

内蒙古夏季典型短时强降水中尺度特征

利用探空和地面加密自动站逐小时观测资料,对2010—2011年汛期发生在锋面上的四次具有不同发展模态的短时强降水过程的降水系统环境场特征进行了分析。结果表明：对于产生短时强降水的中尺度对流系统（MCS）,地面假相当位温（θ_se）等值线密集区和地面切变线的分布形态及运动是影响其系统模态发展和移动方向的关键因素,且对流单体的新生还与地面辐合区密切相关。纬向型MCS的θ_se等值线密集区呈纬向分布;经向型MCS的θ_se等值线密集区呈经向分布;转向型MCS的θ_se等值线密集区则由经向转为纬向分布。不同发展模态MCS的强降水持续时间与地面θ_se高值区的持续时间关系密切。

     

2003年7月3～5日淮河流域大暴雨中尺度对流系统的观测分析

2003年淮河流域的大洪水主要是由3次集中的持续性大面积强暴雨过程引起, 其中7月3～5日从淮河上游向下游的移动性强降水, 使来自上游的洪水与下游暴雨 "遭遇", 加剧了淮河的洪水水情.作者主要采用探空、卫星和雷达资料, 对造成滁州和南京强暴雨的中尺度对流系统的结构和发生背景进行分析.结果表明: 低槽的东移造成了雨区从淮河上游向下游东移; 降雨前来自中纬度的中层干空气侵入加强了对流层中低层的对流不稳定; 7月4～5日的大范围降水主要由α中尺度对流系统的发生、发展引起, 但突发的局地强降雨是由较小的β中尺度, 甚至γ中尺度系统直接造成; 云顶温度低于-52℃的对流区虽然覆盖范围较大, 但其下部的雷达强回波带与其并不完全对应, 而是位于-52℃云区的中心偏南, 强回波的北侧有100～200 km宽的云砧; 双多普勒雷达反演资料较好地揭示出造成滁州强降雨的是中尺度辐合线及其上的中尺度对流线和对流单体, 辐合线随高度向北倾斜.     

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.     

The Effects of Assimilating Satellite Brightness Temperature and Bogus Data on the Simulation of Typhoon Kalmaegi (2008)

Observational and bogus satellite data are directly assimilated into the Weather Research and Forecasting (WRF) model in simulations of Typhoon Kalmaegi (2008). The data assimilation is performed using the Radiative Transfer for TIROS-N Operational Vertical Sounder (RTTOV) model and the three-dimensional variational data assimilation (3DVAR) technique, with satellite observations taken from the National Oceanic and Atmospheric Administration-16 (NOAA-16) Advanced TIROS Vertical Sounder (ATOVS) system composed of the High-resolution Infrared Radiation Sounder (HIRS), the Advanced Microwave Sounding Unit-A (AMSU-A), and the Advanced Microwave Sounding Unit-B (AMSU-B). Data assimilation experiments are initialized at three different times. Improvements in the numerical simulation of the typhoon are discussed in the context of wind, temperature, pressure, and geopotential fields. The results indicate that assimilation of satellite data can improve both the representation of the initial conditions and the subsequent simulation of the typhoon. Different satellite data have different impacts on the typhoon track. In these simulations, data from AMSU-A play a greater role in improving the simulation of the typhoon than data from AMSU-B or HIRS. Assimilation of satellite data significantly affects the simulation of the subtropical high and the steering of the typhoon by the environmental flow. The subtropical high is enhanced and extends westward in the data assimilation experiments. The background flow therefore steers the typhoon more westward, improving the simulated typhoon track. Although direct assimilation of satellite brightness temperature improves the simulated environmental conditions, it does not significantly improve the simulated intensity of the typhoon. By contrast, initializing the typhoon simulation using bogus data in tandem with satellite data improves not only the environmental conditions but also the simulated inner-core structure of the typhoon. Assimilation of both types of data therefore improves the simulation of both the typhoon track and the typhoon intensity. The results of these experiments offer new insight into improving numerical simulations of typhoons.     

AMSU资料变分同化及在暴雨数值模拟中的应用研究

在中尺度数值模拟中,利用中国气象科学研究院数值天气预报创新基地开发的GRAPES三维变分同化系统,对AMSU-A/B微波遥感资料进行了同化试验,研究了这种资料在我国夏季暴雨数值预报中的作用。以2003年7月4日的一次暴雨过程为例,分析了同化结果及模拟结果,结果表明:(1)单独同化AMSU-A资料主要改进了初始温度场,而单独同化AMSU-B资料主要改进了初始湿度场;(2)无论是同化AMSU-A资料还是同化AMSU-B资料,对暴雨预报都有一定的改进作用,但是同化AMSU-B资料的改进作用更明显;(3)同时同化AMSU-A/B资料比只使用其中一种资料的模拟效果好,可以更好地改进模拟的暴雨落区及强度,使结果与实况更加接近。使用AMSU资料,对我国夏季暴雨数值预报有改进作用。     

雷达资料同化对2015年台风彩虹数值模拟改进

基于WRF中尺度模式,采用集合卡尔曼滤波方法同化中国岸基多普勒天气雷达径向速度资料,对2015年登陆台风彩虹（1522）进行数值试验。从台风强度、路径、结构等方面验证了同化效果,并对不同区域雷达观测资料的同化敏感性进行讨论。试验结果表明:在同化窗内同化分析场台风位置误差相比未同化平均减小15 km,最多时刻减小38 km,同化资料时次越多,确定性预报路径误差越小。同化雷达资料后较好地反映出台风彩虹（1522）近海加强过程,台风中心最低气压同化分析和预报误差相比未同化最大减小超过25 hPa,台风眼的尺度、眼墙处对流非对称结构相比未同化与观测更加接近。试验还表明:台风内核100 km范围内的雷达观测对同化效果影响最大,仅同化这部分资料（约占总量的20%）各方面效果与同化全部资料相近,而仅同化100 km以外资料效果明显不及同化所有资料。仅同化台风内核雷达观测资料可以在不影响同化效果的前提下,使集合同化计算机时减小为原来的1/3,该策略可为台风实际业务预报提供一定参考。     

Parameterized Forward Operators for Simulation and Assimilation of Polarimetric Radar Data with Numerical Weather Predictions

Many weather radar networks in the world have now provided polarimetric radar data(PRD)that have the potential to improve our understanding of cloud and precipitation microphysics,and numerical weather prediction(NWP).To realize this potential,an accurate and efficient set of polarimetric observation operators are needed to simulate and assimilate the PRD with an NWP model for an accurate analysis of the model state variables.For this purpose,a set of parameterized observation operators are developed to simulate and assimilate polarimetric radar data from NWP model-predicted hydrometeor mixing ratios and number concentrations of rain,snow,hail,and graupel.The polarimetric radar variables are calculated based on the T-matrix calculation of wave scattering and integrations of the scattering weighted by the particle size distribution.The calculated polarimetric variables are then fitted to simple functions of water content and volumeweighted mean diameter of the hydrometeor particle size distribution.The parameterized PRD operators are applied to an ideal case and a real case predicted by the Weather Research and Forecasting(WRF)model to have simulated PRD,which are compared with existing operators and real observations to show their validity and applicability.The new PRD operators use less than one percent of the computing time of the old operators to complete the same simulations,making it efficient in PRD simulation and assimilation usage.     

暴雨模拟中多普勒雷达径向速度变分同化的应用

针对2008年6月广东地区的一次强降雨过程,利用WRF中尺度数值模式及其三维变分同化系统(WRF-3DVAR),进行了多普勒雷达径向速度变分同化对暴雨过程模拟效果影响研究。结果表明:WRF-3DVAR能够有效地同化多普勒雷达径向速度,同化后的主要影响在于改进了初始动力场,使得初始场包含有更详尽的中尺度特征信息,进而显著提高模式对广东局地暴雨过程的模拟效果。在高分辨率中尺度数值模式中有效地利用多普勒天气雷达资料,是提高中尺度降雨预报的关键。