The Regularized WSM6 Microphysical Scheme and Its Validation in WRF 4D-Var

A cold cloud assimilation scheme was developed that fully considers the water substances,i.e.,water vapor,cloud water,rain,ice,snow,and graupel,based on the single-moment WSM6 microphysical scheme and four-dimensional variational(4D-Var)data assimilation in the Weather Research and Forecasting data assimilation(WRFDA)system.The verification of the regularized WSM6 and its tangent linearity model(TLM)and adjoint mode model(ADM)was proven successful.Two groups of single observation and real sounding data assimilation experiments were set up to further verify the correctness of the assimilation scheme.The results showed that the consideration of ice,snow,and graupel in the assimilation system of the 4D-Var,as opposed to their omission in the warm rain Kessler scheme,allowed the water substances to be reasonably updated,further improving the forecast.Before it can be further applied in the assimilation of observational data,radar reflectivities,and satellite radiances,the cold cloud assimilation scheme needs additional verification,including using conventional ground and sounding observations in the 4D-Var assimilation system.

基于4D-VAR和条件植被温度指数的冬小麦单产估测

条件植被温度指数(VTCI)综合了地表主要参数——归一化植被指数(NDVI)和地表温度(LST),能够较为准确地对干旱进行监测,可为抗旱救灾、作物估产等提供科学依据。为了提高VTCI的区域估产精度,以陕西省关中平原为研究区域,将遥感反演的VTCI与CERES-Wheat小麦生长模型模拟的土壤浅层含水率相结合,通过四维变分(4D-VAR)同化算法实现2008—2014年冬小麦主要生育期旬尺度VTCI的同化。将同化和未同化的VTCI分别运用改进的层次分析法、熵值法及两者组合赋权法建立冬小麦单产估测模型,选择最优估测模型对2011年关中平原各县(区)进行单产估测和精度评价,并分析2008—2014年关中平原冬小麦单产的时空分布特征,结果表明:无论是在单点尺度还是区域尺度,同化的VTCI均能更好地响应外部观测数据,区域VTCI纹理性更好,更符合VTCI的先验知识。与未同化VTCI构建的估测模型相比,应用同化的VTCI所建的估测模型的估测精度明显提高,相关系数达到0.784(P<0.001)。应用最优估测模型对2011年关中平原29个县(区)估产结果中,有16个县(区)的估测单产相对误差小于10%,28个县(区)的估测单产相对误差小于15%,总体平均相对误差为8.68%,均方根误差为421.9 kg/hm^2。近年来关中平原的冬小麦单产呈现个别年份波动、总体增长的年际变化规律,且呈现出中部单产最高、西部次之、东部最低的空间分布特征,与实际情况符合。

基于4D-VAR的动态非对称台风初值化方法试验研究

经典BDA台风初值化方案中台风模型为一个不能充分反映个别台风具体特征的轴对称海平面涡旋场,且在同化窗口内强迫发展着的台风向这个静止涡旋场适应。本文针对该特点,提出一种充分融合分析场信息和实况信息并考虑副高影响的非对称台风Bogus方法,利用PSU/NCAR的MM5模式及其伴随模式,通过四维变分同化(4D-VAR)技术,建立动态非对称BDA方案,对多个不同时次的Bogus资料进行同化。通过对夏季受副热带高压影响较大的6个台风的数值模拟试验对比发现,新方案的路径模拟普遍优于经典方案,且对于经典方案没能改善路径模拟的时段,新方法的模拟效果却能得以改进;新方法模拟的强度普遍弱于经典方案,但这种趋势使得新方法的中后期模拟强度较经典方案更接近于实况。另外,当实况中台风强度已大为减弱时,同化试验模拟的台风仍然保持很强的强度,造成气旋的过度发展,这种情况对BDA方案模拟效果的限制作用还需进一步研究。

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.

EXPERIMENTAL STUDY ON A DYNAMIC ASYMMETRICAL TYPHOON INITIALIZATION SCHEME BASED ON 4D-VAR

Axisymmetric bogus vortexes at sea level are usually used in the traditional bogus data assimilation (BDA) scheme. In the traditional scheme, the vortex could not accurately describe the specific characteristics of a typhoon, and the evolving real typhoon is forced to unreasonably adapt to this changeless vortex. For this reason, an asymmetrical typhoon bogus method with information blended from the analysis and the observation is put forward in this paper, in which the impact of the Subtropical High is also taken into consideration. With the fifth-generation Penn State/NCAR Mesoscale Model (MM5) and its adjoint model, a four-dimensional variational data assimilation (4D-Var) technique is employed to build a dynamic asymmetrical BDA scheme to assimilate different asymmetrical bogus vortexes at different time. The track and intensity of six summer typhoons much influenced by the Subtropical High are simulated and the results are compared. It is shown that the improvement in track simulation in the new scheme is more significant than that in the traditional scheme. Moreover, the periods for which the track cannot be simulated well by the traditional scheme can be improved with the new scheme. The results also reveal that although the simulated typhoon intensity in the new scheme is generally weaker than that in the traditional scheme, this trend enables the new scheme to simulate, in the later period, closer-to-observation intensity than the traditional scheme. However, despite the fact that the observed intensity has been largely weakened, the simulated intensity at later periods of the BDA schemes is still very intensive, resulting in overly development of the typhoon during the simulation. The limitation to the simulation effect of the BDA scheme due to this condition needs to be further studied.

Move a Tropical Cyclone with 4D-Var and Vortex Dynamical Initialization in WRF Model

Previous studies showed that 4 D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4 D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4 D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously,and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4 D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation,which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4 D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper.

Incremental 4D-VAR assimilation scheme based on Lorenz model

Four-dimensional variational(4D-VAR) data assimilation method is a perfect data assimilation solution in theory, but the computational issue is quite difficult in operational implementation.The incremental 4D-VAR assimilation scheme is set up in order to reduce the computational cost. It is shown that the accuracy of the observations, the length of the assimilation window and the choice of the first guess have an important influence on the assimilation outcome through the contrast experiment. Compared with the standard 4D-VAR assimilation scheme, the incremental 4D-VAR assimilation scheme shows its advantage in the computation speed through an assimilation experiment.

The four dimensional variational data assimilation with multiple regularization parameters as a weak constraint(Tikh-4D-Var) and its preliminary application on typhoon initialization

Traditional variational data assimilation(VDA) with only one regularization parameter constraint cannot produce optimal error tuning for all observations. In this paper, a new data assimilation method of "four dimensional variational data assimilation(4D-Var) with multiple regularization parameters as a weak constraint(Tikh-4D-Var)" is proposed by imposing different regularization parameters for different observations. Meanwhile, a new multiple regularization parameters selection method, which is suitable for actual high-dimensional data assimilation system, is proposed based on the posterior information of 4D-Var system. Compared with the traditional single regularization parameter selection method, computation of the proposed multiple regularization parameters selection method is smaller. Based on WRF3.3.1 4D-Var data assimilation system, initialization and simulation of typhoon Chaba(2010) with the new Tikh-4D-Var method are compared with its counterpart 4D-Var to demonstrate the effectiveness of the new method. Results show that the new Tikh-4D-Var method can accelerate the convergence with less iterations. Moreover, compared with 4D-Var method, the typhoon track, intensity(including center surface pressure and maximum wind speed) and structure prediction are obviously improved with Tikh-4D-Var method for 72-h prediction. In addition, the accuracy of the observation error variances can be reflected by the multiple regularization parameters.

An application of the A-4DEnVar to coupled parameter optimization

In variational methods,coupled parameter optimization(CPO) often needs a long minimization time window(MTW) to fully incorporate observational information,but the optimal MTW somehow depends on the model nonlinearity.The analytical four-dimensional ensemble-variational(A-4DEnVar) considers model nonlinearity well and avoids adjoint model.It can theoretically be applied to CPO.To verify the feasibility and the ability of the A-4DEnVar in CPO,“twin” experiments based on A-4DEnVar CPO are conducted for the first time with the comparison of four-dimensional variational(4D-Var).Two algorithms use the same background error covariance matrix and optimization algorithm to control variates.The experiments are based on a simple coupled oceanatmosphere model,in which the atmospheric part is the highly nonlinear Lorenz-63 model,and the oceanic part is a slab ocean model.The results show that both A-4DEnVar and 4D-Var can effectively reduce the error of state variables through CPO.Besides,two methods produce almost the same results in most cases when the MTW is less than 560 time steps.The results are similar when the MTW is larger than 560 time steps and less than 880 time steps.The largest MTW of 4 D-Var and A-4DEnVar are 1 200 time steps.Moreover,A-4DEnVar is not sensitive to ensemble size when the MTW is less than 720 time steps.A-4DEnVar obtains satisfactory results in the case of highly nonlinear model and long MTW,suggesting that it has the potential to be widely applied to realistic CPO.

基于GEOS-Chem V12.6.3的全球CO_(2)浓度同化系统的构建

为了研究同化OCO-2卫星柱浓度(XCO_(2))数据对于全球CO_(2)浓度模拟的影响,本文基于GEOS-Chem V12.6.3,采用四维变分(four dimensional variational,4D-Var)的方法,构建了一个同化OCO-2卫星XCO_(2)数据的全球大气CO_(2)浓度同化系统。首先,采用有限差分法验证了观测算子、积云对流、行星边界层和平流4个伴随模块计算结果的正确性。然后,以2018年为例,设计了模拟和同化两个实验,并利用TCCON、地面和航飞3种独立的观测数据进行对比验证。结果显示,同化实验结果与TCCON、地面和航飞观测数据之间的平均误差分别为0.37 mL/m^(3)、0.41 mL/m^(3)和0.51 mL/m^(3),相比于模拟实验,分别改善了40.32%、42.25%和45.15%,表明了同化OCO-2卫星的XCO_(2)数据能显著提高对全球大气CO_(2)浓度模拟的准确性。

闪电资料在中尺度WRF模式中同化方法的研究

利用强对流天气中雷电活动与对流性降水之间的统计关系,将闪电资料反演成降水资料,通过四维变分同化方法,将地闪资料同化入中尺度WRF模式中,并对四川地区一次强降水天气过程进行模拟。结果显示,经过同化的初始场能有效改善初始时刻强对流系统雨带结构,使得模式的初始场较好反应出大气的真实状态,并对暴雨的预报有正面影响。而在其短时模拟效果中,闪电资料的同化更好地模拟出川东北地区的降水过程,雨区的中心位置和强度都得到明显改善,改善了WRF模式在四川地区对强对流天气的模拟能力。

联合资料同化理论及其研究进展

联合资料同化是在"集合预报与资料同化一体化"的思想框架下研究发展的一种数值预报新理论和新方法。它在变分同化系统框架的基础上,充分利用集合预报结果,构造"流依赖"的背景误差协方差,提高对不同尺度天气系统背景误差协方差的刻画能力,进而改善分析和预报的质量。目前该方法已引起国际各主要气象业务中心广泛关注,极具业务应用潜力。本文以联合ETKF-3D-Var为例简要介绍了联合资料同化理论及其研究进展,也说明了联合资料同化的应用前景。

数值模式误差对降水四维变分资料同化及预报的影响

利用一个无量纲的水汽发展方程,针对同化时间窗口内出现和不出现降水两种情况,分析了不同模式误差和初始误差对降水四维变分资料同化预报效果的影响。结果表明,应用四维变分资料同化方法进行降水预报前,应该充分考虑数值模式中的误差,才能得到比较满意的同化及预报结果。假定同化窗口内获得的比湿观测场是准确的,当不存在模式误差时,四维变分资料同化方法可以有效地消除初始场误差,找到比湿真实初始场;而存在模式误差时,四维变分资料同化后的模式初始场会偏离真实的比湿初始场,并且模式误差越大,偏离程度越严重。在一些模式误差情况下,由于模式误差在同化窗口及延伸预报时段的作用不同,进行四维变分资料同化处理后,尽管累积降水量的预报结果在同化时间窗口内优于同化前的预报,而在最终预报时刻反而差于同化前。

基于GRAPES四维变分的静止轨道微波观测系统模拟试验研究

地球静止轨道微波观测同时具有高频次、大视场和穿透云雨的全天候观测能力,因此中国在规划第二代静止轨道气象卫星“风云四号”系列时已经明确提出对静止轨道微波观测的需求。基于中国候选的50、118、183、380和425 GHz五频段静止轨道微波辐射计载荷方案,开展了地球静止轨道微波观测系统模拟试验,理解其观测时间分辨率、频段选取和观测误差对台风预报的影响。试验基于GRAPES全球四维变分同化系统,同化静止轨道微波模拟观测资料,以2018年台风“玛利亚”和“山竹”为例分析了静止轨道微波资料同化对台风预报的影响。试验结果表明,对于静止轨道微波资料同化应用,提高观测资料的时间分辨率、增加通道数量和降低噪声水平能够有效提升台风数值预报性能。

多源卫星观测数据在全球四维变分同化系统中的应用

首先描述高分辨率全球四维变分资料同化系统的基本软件框架,并对多源卫星资料同化的关键技术作阐述;其次通过统计分析,说明新型卫星观测数据的引入不但能够增加同化系统中的信息量,而且能够提高其他类型观测数据的利用率;然后通过一个月的统计检验结果表明:无论是从距平相关还是均方根误差而言,在有效同化无线电掩星和卫星风资料后,高分辨率同化预报系统预报技巧的提高是十分明显的;最后,通过一个强降水个例的分析结果表明:基于新的初始场全球模式降水预报准确性较高,就强降水中心区域的预报而言,模式预报和观测实况较为一致,优于国外模式降水预报。

一次飑线过程的雷达回波分析及其反演风场研究

用常规气象观测资料,中尺度自动气象站资料和多普勒天气雷达资料,对2009年4月15日发生在重庆中西部的飑线过程的进行了分析,发现了"逆风区"在预报中具有一定的提前量。同时通过四维变分(4D-VAR)同化方法反演风场,得到反演的水平风场能较好的反映飑线内部各个发展阶段的对流单体的内部流场结构,同时发现4D-VAR反演风场能较好的反映出飑线不同发展阶段的流场特征。

REM模式伴随系统的建立及其四维变分资料同化初步试验

Regional-Eta-Coordinate-Model(REM)中尺度模式对中国区域性降水显示出公认的较高预报能力,建立其四维变分资料同化系统是完善该模式,进一步提高其预报效果的重要工作。本研究编写了REM模式的切线性模式和伴随模式,介绍了建立REM模式伴随系统的过程,并利用实际天气个例资料,分别对REM模式的切线性模式、伴随模式及定义的目标函数梯度进行了正确性检验,检验结果表明对REM模式的切线性模式及伴随模式编写是成功的。利用REM模式的伴随系统,对1998年06月08日00时到09日00时和2000年08月01日00时到02日00时两个实际天气个例进行了四维变分资料同化试验。从数值试验的结果分析可以看到,进行四维变分资料同化后,两个天气个例在预报结束时刻其预报结果对风场和湿度场的预报都有明显改善,对温度场和高度场的预报也有所改善。对于累积降水的预报,两个个例利用四维变分资料同化后得到的初始场进行的预报结果则有较大不同,在个例1中,变分同化后对降水中心的位置和降水强度的预报都有明显改善,预报结果更接近于观测场;个例2中,变分同化后对降水中心位置和强度的预报则没有改善,产生这种现象的原因可能是由于定义的目标函数中没有加进背景场项,也可能是由于采用的观测资料时次比较少,还需要进一步进行研究和试验。

Numerical Experiments for Typhoon Dan Incorporating AMSU-A Retrieved Data with 3DVM

Two sets of assimilation experiments on a landfalling typhoon--Typhoon Dan （1999） over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation （3DVM） and the 4-dimensional variational data assimilation （4DVar）. Results show that： （1） both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions, and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3- dimensional variational data assimilation （3DVar） circle; （2） inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model; （3） the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.

基于观测与数值模式互动的华东地面气象观测站遴选布局

采用WRF四维变分同化系统,针对华东地区台风、梅雨、强对流典型天气个例,设计开展了不同密度地面站数据同化敏感性试验,并综合评估了对数值预报的影响,得出能较好满足数值预报需求又经济高效的华东地面站布局。结果表明:(1)地面站资料对中尺度数值预报模式在华东区域的预报结果有直接影响,且以正贡献为主,总体而言同化站点越密,改进效果越好。(2)华东地面站平均布局间距在20 km时出现对数值模式影响正贡献相对高值。(3)地面站对数值模式影响的程度和效果与天气系统的特点有直接关系。(4)在华东地区现有区域站中,遴选1532个增补到519个国家站网中,形成总站数2051个、平均间距约20 km、天气系统关键区适度加密的华东地面站网,在控制站网规模的同时,能较好地满足区域数值预报需求。

GRAPES区域扰动预报模式动力框架设计及检验

设计了适用于四维变分同化系统的扰动预报模式GRAPES_PF。根据GRAPES的地形追随坐标非静力原始方程组,采用小扰动分离方法推导微分形式的线性扰动预报方程组,并利用与GRAPES非线性模式相似的数值求解方案求解线性扰动微分方程组。在设计扰动预报模式时采用了两个时间层半隐式半拉格朗日方案对动量方程、热力学方程、水汽方程和连续方程进行时间差分,空间差分方案的变量分布水平方向采用Arakawa C跳点网格,垂直方向采用Charney/Phillips跳层。利用代数消元法进一步推导得到只包含未来时刻扰动Exner气压的亥姆霍兹方程,进而通过广义共轭余差法(GCR)求解,在此基础上得到未来时刻扰动量的预报值。基于所开发的扰动模式开展了数值试验。首先在非线性模式中施加一个中尺度初始扰动高压,得到初始扰动在非线性模式中的后续演变,然后将相同的初始扰动作为扰动模式的初值进行时间积分,将扰动模式预报的结果与非线性模式的结果做了对比。结果表明,所开发的扰动模式GRAPES_PF较好地模拟了惯性重力内波的传播过程:初始高压扰动激发了一个迅速向外传播的惯性重力内波,在气压场向风场适应的过程中,水平风场、垂直运动、位温和湿度等变量均出现了扰动增量,与非线性模式得到的结果相当接近。GRAPES_PF作为GRAPES非线性模式的合理线性模式为建立基于线性扰动预报的区域四维变分同化系统奠定了科学基础。