一阶有限元浅水模式的变分资料同化

一阶有限元浅水方程的伴随模式应用于气象资料同化场，并利用最优化方法对具有随机扰动的初始场进行优化处理。通过极小化算法，使所定义的目标函数达到最小，从而得到最优的气象要素初始场。数值试验结果表明这种处理是很有效的     

格点同化对大气波导数值模拟的影响

利用NCEP再分析资料为背景场及常规的探空资料和地面资料,以2005年6月2日出现在黄海海域的大气波导为例,运用中尺度数值模式MM5,设计了2种初始场不同的数值模拟试验:1)NCEP资料;2)NCEP资料和常规探空资料。研究结果表明:格点同化能够改善大气波导的MM5数值模拟结果,提高MM5的大气波导参数模拟精度;在大气波导分布上,格点同化对陆地大气波导影响较大,对于海上的模拟区域分布几乎没有影响。     

一次川东暴雨的雷达资料同化试验与诊断分析

为了对大尺度暴雨天气过程的雷达资料四维变分同化效果进行验证,选取2013年6月29日至7月2日发生在川东遂宁地区的一次暴雨天气过程,使用WRF中尺度模式进行雷达资料的同化模拟试验,并使用模式输出进行诊断分析。结果表明,高时空分辨率的雷达资料使短时间窗口的四维变分同化成为可能。同化结果能很好地改善由地形和初始场误差等因素带来的模拟缺陷,模拟输出场能完整再现整个暴雨的发生发展过程。副高西南侧低空急流带来的海上水汽与南亚季风自南向北带来的水汽共同构成了本次过程稳定的水汽供应通道。中β尺度涡旋的不断生消交替形成了该次暴雨过程的3次降水阶段。垂直方向不稳定能量的快速累积,缓慢释放以及垂直方向强的水汽输送交换,是造成该次过程降水时间长,量级大的主要原因。     

应用多普勒天气雷达资料对四川“7·3”暴雨的变分同化试验

针对2011年7月3日四川地区一次强降雨过程,以NECP/NCAR 1°×1°再分析资料为背景场,采用中尺度数值天气预报模式WRF及其三维变分同化系统3DVAR,同时对多普勒天气雷达的径向速度和反射率因子进行了三维变分同化对暴雨模拟效果影响的研究.结果表明:同化了雷达资料后的初始场能够更加精细的刻画初始风场和水汽通量场的分布与数值,能展现出风场的辐合辐散区域,对水汽通量的中心位置有较大影响,大风速区域和水汽通量高值中心有较好的对应关系;同化了多普勒雷达资料后能较为明显的改变降雨落区及强度的预报精度,前6h有明显的改善作用,随着时间的增加改善作用逐渐减小,前9小时改进作用仍很明显,对比24小时实况降雨仍存在一定的改善作用;经过质量控制后的雷达资料对暴雨预报的改善作用要优于未进行质量控制的雷达资料以及每隔一小时加入一次雷达资料要优于每隔半小时加入雷达资料对于暴雨预报的改善作用.     

风廓线雷达资料在降水数值预报中的应用探讨

风场是水汽输送的主要动力,也是影响降水数值预报的重要因子。针对目前常规探空测风的分辨率不高、资料获取时间长、不能及时反映风场中小尺度变化的不足,以及在数值预报中应用受限的问题,采用同化风廓线雷达资料的方法,分析高分辨率的单点风场数据对初始场和预报场的作用。结果表明,把单点风廓线雷达资料在WRF模式中同化是可行的。同化后对风廓线雷达站点初始场的风场、湿度场改善明显,对站点周围一定范围内的流场也有不同程度的影响。同时降水强度和落区的预报结果也有不同程度的改善,尤其是风廓线雷达站下风方向比未同化前更接近实况,在其他方向上距离雷达越近改善效果越明显。另外,同化风廓线资料后,模式预报的涡度散度分布和水汽输送场也有不同程度的改善。     

应用多普勒天气雷达资料对四川“7·3”暴雨的变分同化试验

针对2011年7月3日四川地区一次强降雨过程,以NECP/NCAR l°×1°再分析资料为背景场,采用中尺度数值天气预报模式WRF及其三维变分同化系统3DVAR,同时对多普勒天气雷达的径向速度和反射率因子进行了三维变分同化对暴雨模拟效果影响的研究.结果表明:同化了雷达资料后的初始场能够更加精细的刻画初始风场和水汽通量场的分布与数值,能展现出风场的辐合辐散区域,对水汽通量的中心位置有较大影响,大风速区域和水汽通量高值中心有较好的对应关系;同化了多普勒雷达资料后能较为明显的改变降雨落区及强度的预报精度,前6h有明显的改善作用,随着时间的增加改善作用逐渐减小,前9小时改进作用仍很明显,对比24小时实况降雨仍存在一定的改善作用;经过质量控制后的雷达资料对暴雨预报的改善作用要优于未进行质量控制的雷达资料以及每隔一小时加入一次雷达资料要优于每隔半小时加入雷达资料对于暴雨预报的改善作用.     

FY-3双星MWHS资料对江西暴雨的循环同化试验

为了提高卫星资料在同化系统中使用率及验证同化卫星资料的预报效果,采用循环同化方案并通过江西2012年5月11~14日的暴雨个例进行验证。试验设计了风三卫星MWHS资料的循环同化双星资料方案和单时次同化单星资料方案,并对方案的运行结果进行了分析。结果表明,使用MWHS资料可以改进湿度场和涡度场。相比单时次同化单星MWHS资料,循环同化双星MWHS资料方案能更好地改善湿度场和动力场,模拟的降水落区和强度更接近实况,其TS评分最优。单时次同化单星MWHS资料,选用降水期间探测的卫星资料同化效果更优。     

FY-2D云导风在“鲶鱼”台风模拟中的同化试验

为了能给国内的云导风产品在通道的选择和使用方法上提供一些新的参考,以2010年的“鲶鱼”台风为个例,通过对FY-2D云导风产品在WRF模式中的同化对比试验,分析比较了同化了云导风资料之后的台风路径和位势高度场、风场的变化。结果表明,同化之后台风路径的偏差水汽通道要远大于红外通道,随着积分时间的延长,红外通道数据的加入对模拟台风路径的订正作用比水汽通道显著;模式使用不同同化方案的模拟结果也有明显的差别,其中以每24小时一次冷启动的同化循环方案对台风路径有较准确的模拟,而在分析不同通道导风质量优劣方面,则以热循环同化方案最佳。     

FY-3A卫星MWHS资料同化及四川盆地暴雨数值模拟分析

为研究中国FY-3A(风云三号A卫星)资料在数值模式中对暴雨模拟的作用,以2012年07月03日发生在四川盆地的一次暴雨过程为个例。利用WRF(V3.3)模式和三维变分同化系统WRF-3DVAR,对FY-3A的MWHS(微波湿度计)资料进行同化试验研究。研究结果表明:同化MWHS资料后,相比控制试验,(1)同化方案A在降水区出现+3K的正增量中心和+10%的正增量湿中心,改善了大气能量场和湿度场信息;(2)同化方案A提高了降水区垂直速度和涡度场的数值和分布位置,并较好的刻画出风场的辐合辐散区域和水汽通量高值中心,准确模拟出水汽通量的中心位置;(3)对此次暴雨个例试验研究,在中东部、东北部主降水区,同化方案A模拟降水区分布形式较好,尤其是降水强度得到较大提高降水值达230mm,非常接近实况降水值(227mm),同化MWHS资料可以较好提高WRF模式降水预报能力。     

双权重质量控制法在FY-3B/IRAS资料中的应用研究

变分同化卫星资料前需要采用严格的质量控制方法以剔除离群资料。文中进行了风云三号B星红外分光计资料的质量控制研究。选取2012年12月26日00时至2013年1月4日18时共10天IRAS全球L1c格式资料作为研究对象,基于通道亮温偏差利用双权重质量控制法,剔除受云、地表发射率影响和误差较大的离群资料。结果表明,通过双权重质量控制后,IRAS通道亮温偏差均值和标准差整体有所减少;偏差均值和标准差随时间变化很稳定。最后把此方法耦合到GRAPES同化系统进行IRAS资料的初步质量控制应用得到结果是可行的。     

WAVE ASSIMILATION AND NUMERICAL PREDICTION

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Adjoint Assimilation in Marine and an Example of Application

This paper aims at a review of the work carried out to date on the adjoint assimilation of data in marine ecosystem models since 1995. The structure and feature of the adjoint assimilation in marine ecosystem models are also introduced. To illustrate the application of the adjoint technique and its merits, a 4-variable ecosystem model coupled with a 3-D physical model is established for the Bohai Sea and the Yellow Sea. The chlorophyll concentration data derived from the SeaWiFS ocean colour data are assimilated in the model with the technique. Some results are briefly presented.     

The study of single station inverting the sea surface current by HF ground wave radar based on adjoint assimilation technology

This paper introduces the assimilation technology in an ocean dynamics model and discusses the feasibility of inverting the sea surface current in the detection zone by assimilating the sea current radial velocity detected by single station HF ground wave radar in ocean dynamics model. Based on the adjoint assimilation and POM model, the paper successfully inverts the sea surface current through single station HF ground wave radar in the Zhoushan sea area. The single station HF radar inversion results are also compared with the bistatic HF radar composite results and the fixed point measured results by Annderaa current meter. The error analysis shows that acquisition of flow velocity and flow direction data from the single station HF radar based on adjoint assimilation and POM model is viable and the data obtained have a high correlation and consistency with the flow field observed by HF radar.     

The Nonlinear Interaction Process in the wave Assimilation Model and Its Experiments

This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model.Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite,and the gradinet distribution in the physical space was also analyzed preliminarily.     

Assimilation of high frequency radar data into a shelf sea circulation model

High Frequency (HF) radar current data is assimilated into a shelf sea circulation model based on optimal interpolation (OI) method. The purpose of this work is to develop a real-time computationally highly efficient assimilation method to improve the forecast of shelf current. Since the true state of the ocean is not known, the specification of background error covariance is arduous. Usually, it is assumed or calculated from an ensemble of model states and is kept in constant. In our method, the spatial covariances of model forecast errors are derived from differences between the adjacent model forecast fields, which serve as the forecast tendencies. The assumption behind this is that forecast errors can resemble forecast tendencies, since variances are large when fields change quickly and small when fields change slowly. The implementation of HF radar data assimilation is found to yield good information for analyses. After assimilation, the root-mean-square error of model decreases significantly. Besides, three assimilation runs with variational observation density are implemented. The comparison of them indicates that the pattern described by observations is much more important than the amount of observations. It is more useful to expand the scope of observations than to increase the spatial interval. From our tests, the spatial interval of observation can be 5 times bigger than that of model grid.     

Assimilation of ASAR data with a hydrologic and semi-empirical backscattering coupled model to estimate soil moisture

The most promising approach for studying soil moisture is the assimilation of observation data and computational modeling.However,there is much uncertainty in the assimilation process,which affects the assimilation results.This research developed a one-dimensional soil moisture assimilation scheme based on the Ensemble Kalman Filter(EnKF)and Genetic Algorithm(GA).A two-dimensional hydrologic model-Distributed Hydrology-Soil-Vegetation Model(DHSVM)was coupled with a semi-empirical backscattering model(Oh).The Advanced Synthetic Apertture Radar(ASAR)data were assimilated with this coupled model and the field observation data were used to validate this scheme in the soil moisture assimilation experiment.In order to improve the assimilation results,a cost function was set up based on the distance between the simulated backscattering coefficient from the coupled model and the observed backscattering coefficient from ASAR.The EnKF and GA were used to re-initialize and re-parameterize the simulation process,respectively.The assimilation results were compared with the free-run simulations from hydrologic model and the field observation data.The results obtained indicate that this assimilation scheme is practical and it can improve the accuracy of soil moisture estimation significantly.     

Study on the Transport of COD in the Sea Area Around Maidao off Qingdao Coast Using Data Assimilation

A two-layer pollutant advection-diffusion model is built to investigate the pollutant transport in the sea area around Maidao off Qingdao coast. An adjoint data assimilation technique is applied to estimate the optimal values of the model parameters. The experimental results on the initial field of pollutant indicate that the distribution of Chemical Oxygen Demand (COD) concentra- tion is sensitive to the horizontal eddy diffusivity. An appropriate value of horizontal eddy diffusivity is necessary in order to depict the influence of the initial field precisely, and it is also essential to the simulation of the advection-diffusion process of the pollutant. By inversion of the model parameters and optimization of the initial COD concentrations, the simulation results are improved sig- nificantly. The cost function is reduced to 40% of its first step value. The average misfit between the model outputs and the observa- tions in the upper layer decreases from 0.46 to 0.25 mg L-1, and that in the lower layer decreases from 0.22 to 0.14 mg L-1.