三维变分和物理初始化方法相结合同化多普勒雷达资料的试验研究

以美国新近研发的天气研究预报模式(WRF)配置的三维变分(3D-Var)同化系统WRF 3D-Var为平台,结合物理初始化方法(Physical Initialization,简称PI)来同化多普勒雷达径向风和回波强度观测资料.其基本做法是首先用物理初始化方法由雷达回波资料估计出比湿、云水混合比和垂直速度,然后用估计的比湿和云水混合比对模式的相应变量进行调整,最后再将估计出的垂直速度作为一种新的观测类型添加到现有的WRF 3D-Var目标函数中,同时以WRF 3D-Var提供的方法直接同化径向风.针对2002年6月19日的一次强对流性降水过程和2003年7月5日的一次梅雨锋暴雨过程进行了一组同化多普勒雷达径向风和回波资料的试验研究.同化结果表明:分析变量的增量场和观测的雷达回波有很好的对应关系.在雷达回波区,有正的比湿增量、云水含量增量和垂直速度增量,并且水平风增量在此辐合;在没有雷达回波的地方有负的垂直速度增量.预报结果表明,调整云水含量对降水预报改善不明显,调整比湿对降水预报改进明显,直接用物理初始化估计出的垂直速度替代模式的初始垂直速度,对降水预报改进不明显,但以新的方案同化雷达资料能有效地缩短模式的起转时间(spin-up time),明显改进短时降水预报.     

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 a...     

A Two-Moment Bulk Microphysics Coupled with a Mesoscale Model WRF: Model Description and First Results

The Chinese Academy of Meteorological Sciences (CAMS) two-moment bulk microphysics scheme was adopted in this study to investigate the representation of cloud and precipitation processes under different environmental conditions.The scheme predicts the mixing ratio of water vapor as well as the mixing ratios and number concentrations of cloud droplets,rain,ice,snow,and graupel.A new parameterization approach to simulate heterogeneous droplet activation was developed in this scheme.Furthermore,the improved CAMS scheme was coupled with the Weather Research and Forecasting model (WRF v3.1),which made it possible to simulate the microphysics of clouds and precipitation as well as the cloud-aerosol interactions in selected atmospheric condition.The rain event occurring on 27-28 December 2008 in eastern China was simulated using the CAMS scheme and three sophisticated microphysics schemes in the WRF model.Results showed that the simulated 36-h accumulated precipitations were generally agreed with observation data,and the CAMS scheme performed well in the southern area of the nested domain.The radar reflectivity,the averaged precipitation intensity,and the hydrometeor mixing ratios simulated by the CAMS scheme were generally consistent with those from other microphysics schemes.The hydrometeor number concentrations simulated by the CAMS scheme were also close to the experiential values in stratus clouds.The model results suggest that the CAMS scheme performs reasonably well in describing the microphysics of clouds and precipitation in the mesoscale WRF model.     

雷达反射率资料的三维变分同化研究

应用天气研究和预报模式(WRF)三维变分系统中一种新的雷达反射率资料间接同化方法来进行反射率资料的三维变分同化研究,评估雷达反射率资料对夏季短时定量降水预报的作用.该方法不直接同化雷达反射率资料,而是同化由反射率资料反演出的雨水和估计的水汽.以2009年夏季北京地区发生的4次强降水过程为例,考察了北京市气象局业务运行的快速更新循环同化预报系统对京津冀地区雷达网的雷达反射率资料的同化性能以及雷达反射率资料和径向风资料同时同化的效果.数值试验结果表明:(1)同化反演雨水或水汽都能改善降水预报,但同化反演水汽对降水预报效果的改善起了更重要的作用;(2)同化反射率资料能极大地提高短时降水预报的效果,其稳定的正面效果可以延伸到6h的预报时效,而同化径向风资料不能得到稳定的正效果;(3)同化雷达资料时,应用快速更新循环同化预报系统是提高短时定量降水预报的一个有效途径.     

Application of Radar Reflectivity Factor in Initializing Cloud-Resolving Mesoscale Model. Part Ⅰ: Retrieval of Microphysical Elements and Vertical Velocity

Assuming that cloud reaches static state in the warm microphysical processes, water vapor mixing ratio(qv), cloud water mixing ratio (qc), and vertical velocity (w) can be calculated from rain water mixing ratio (qr)- Through relation of Z-qr, qr can be retrieved by radar reflectivity factor (Z). Retrieval results indicate that the distributions of mixing ratios of vapor, cloud, rain, and vertical velocity are consistent with radar images, and the three-dimensional spatial structure of the convective cloud is presented. Treating q,v saturated at the echo area, the retrieved qr is about 0.1 g kg-1, qc is always less than 0.3 g kg-1, w is usually below 0.5 m s-1, and rain droplet terminal velocity (vr) is around 5.0 m s-1 in the place where radar reflectivity factor is about 25 dBz; in the place where echo is 45 dBz, the retrieved qr and qc are always about 3.0 g kg-1, w is greater than 5.0 m s-1, and vr is around 7.0 m s-1. In the vertical, the maximum updraft velocity is greater than 3.0 m s-1 at the height of around 5.0 kin, the maximum cloud water content is about 3.0 g kg-1 above 5 km and the maximum rain water content is about 3.0 g kg-1 below 6 kin. Due to the assumption that the cloud is in static state, there will be some errors in the retrieved variables within the clouds which axe rapidly growing or dying-out, and in such cases, more sophisticated radar data control technique will help to improve the retrieval results.     

雷达反射率三维拼图观测资料在北方区域数值模式预报系统中的同化应用研究

以业务应用为目标,开展雷达反射率三维拼图观测资料在北方区域数值预报系统中的同化应用研究。采用雷达反射率间接同化方法同化北方雷达反射率拼图观测资料,重点关注其对降水、湿度、温度及风的预报能力影响。首先,基于2017年8月雷达拼图观测资料批量同化和对比试验,对雷达拼图资料同化应用效果进行定量评估,结果表明雷达拼图资料同化虽然加大了地面风场预报误差,但在降水预报和湿度、温度预报等方面有明显的改善作用。其次,选择在业务中预报难度较大的强降水个例开展分析研究,分析表明:（1）同化雷达拼图观测资料有效提高了模式降水预报性能,临近降水发生的循环起报时次预报效果更好;（2）对于短时间多次强降水过程发生的预报,循环同化雷达拼图资料可及时弥补模式中由于前次降水导致的水汽、能量等消耗及热/动力条件削弱,持续支持降水系统发展。最后,通过考察雷达反射率的不同同化方案,发现同化反演水凝物或者估计水汽均能改善模式降水预报性能,但是同化估计水汽对降水预报性能的改善更为明显,联合使用两方案能同时对水凝物分布、热力场等进行调整,可提高模式降水预报性能。      

THE INFLUENCE OF CLOUD PARAMETERIZATION ADJUSTMENT USING REFLECTIVITY OF DOPPLER ON NOWCASTING WITH GRAPES MODEL

In this study, we attempted to improve the nowcasting of GRAPES model by adjusting the model initial field through modifying the cloud water, rain water and vapor as well as revising vapor-following rain water. The results show that the model nowcasting is improved when only the cloud water and rain water are adjusted or all of the cloud water, rain water and vapor are adjusted in the initial field. The forecasting of the former （latter） approach during 0-3 （0-6） hours is significantly improved. Furthermore, for the forecast for 0-3 hours, the latter approach is better than the former. Compared with the forecasting results for which the vapor of the model initial field is adjusted by the background vapor with those by the revised vapor, the nowcasting of the revised vapor is much better than that of background vapor. Analysis of the reasons indicated that when the vapor is adjusted in the model initial field, especially when the saturated vapor is considered, the forecasting of the vapor field is significantly affected. The changed vapor field influences the circulation, which in turn improves the model forecasting of radar reflectivity and rainfall.     

超强台风“威马逊”(2014)云微物理特征的模拟与对比分析

采用中尺度数值模式WRFv3.5对2014年超强台风“威马逊”进行数值模拟。利用雷达、卫星、自动站逐时降水资料,对比单参数WSM6云方案和双参数WDM6云方案在模拟台风路径、强度、降水分布及水成物含量上的差异,分析雨滴粒子的谱型特征及微物理源、汇项对云中雨水含量的影响。与上海台风研究所的最佳路径数据对比显示,两方案均较好地模拟出了台风“威马逊”的移动路径,WDM6方案的整体路径误差更小;模拟的强度差异则较为显著,WDM6方案的海平面最低气压值偏高,强度偏弱。两方案模拟的累积降雨分布虽与自动站实测资料基本一致,但WDM6方案模拟的强降水概率偏高,弱降水概率偏低。两方案模拟的对流区雪、霰、雨水含量均大于TRMM卫星反演结果,且WDM6方案的对流云较多,总体雨水含量偏高;两方案均模拟出了雷达回波分布的整体特征,但眼区尺度偏大,WDM6方案在融化层以下缺少眼墙之外的弱回波区且大于39 dBz的强回波区偏多,同样显示了雨水含量（或尺度）偏大。由于WDM6方案为暖雨（云、雨水）双参数模式,对云滴活化、云雨转换及云、雨谱型有一定的改进,其能较合理地模拟出雨滴谱随台风发展的演变特征;模拟显示,云、雨滴的收集碰并及固态粒子的融化是雨水的主要源项,WDM6方案增加了云雨水自动转化率及雨水碰并云水率,导致该方案的空中雨水含量偏高,且随高度的降低快速减小;此外,由于WDM6方案使用简单的寇拉公式进行云滴活化,初始云凝结核数的变化即可造成雪、霰、云雨水含量的改变,故建议在具体大气气溶胶条件下,对方案中的云滴生成参数化过程做相应的调整。     

雷达资料对0414号台风“云娜”数值预报的改进

运用NCEP/NCAR再分析资料,研究了2004年12月初登陆我国台湾的冬季台风"南玛都"的性质结构特征,结果表明:冬季台风"南玛都"具有与夏季台风相同的暖湿中心和低层辐合、高层辐散的环流特征,不同的是低层辐合气流中西南气流不明显,台风涡旋气流对大气的扰动偏弱.台风过程海平面气压距平场的EOF分析表明,台风生命史中的扰动主要由EOF1和EOF2构成(占90%的方差),EOF1反映台风结构和强度变化,EOF2反映了台风移动过程中的环境状态变化.     

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.     

WRF模式云参数化方案对一次深对流系统模拟的验证和改进

使用中尺度数值模式WRF中的双参数云微物理方案WDM6针对2008年台风“凤凰”登陆过程中造成的强降水进行数值模拟,通过卫星模拟器利用MTSAT-1R和TRMM卫星观测的红外云顶黑体亮温TBB、PR雷达反射率资料使用统计方法验证模拟结果。通过修改云水向雨水自动转化过程、冰晶核化过程、雪和霰的下落末速度、雪和霰的截距进行敏感性试验,减小模拟结果和卫星观测结果的差异。研究结果表明:WDM6方案模拟的台风“凤凰”登陆后的降水,强对流云系及对流柱状雷达回波基本符合实况,但模拟结果局部偏强。WDM6方案模拟产生了较多的浅对流云,低估了对流云系的出现频率。不同云类型模拟的雷达回波均偏强,对流云系雷达回波垂直分布接近观测。敏感性试验结果说明修改WDM6方案中云水向雨水自动转化率有效地改善了模拟效果。同时发现云滴初始数浓度影响云水向雨水自动转化率并最终影响云系结构和雷达反射率的模拟结果,过高的云滴初始数浓度会使模拟结果变差。     

基于对流云/层状云划分的云分析方法改进

本文基于实况融合降水和雷达反射率因子,采用模糊逻辑法提出了一个新的对流云/层状云判别方法,进而改进了GSI（Gridpoint Statistical Interpolation）同化系统中的云分析方案（简称CUST方案）。以2019年6月19日影响浙江的一次梅雨过程为例,利用WRF（Weather and Forecast Research）模式与GSI同化系统开展了逐小时循环同化试验,分析了CUST方案对降水的模拟改进作用和可能影响过程,并与其他方案进行了对比,探讨了CUST方案的应用效果。结果表明:（1）新提出的CUST方案可较为准确地划分对流云和层状云,以此作为判别因子改进GSI同化系统中的云分析方案切实可行。（2）CUST方案在对流区域采用对流云分析方案,在非对流区域采用层云分析方案,减小了单纯对流云方案在非对流区域的空报现象、以及单纯层云方案在强对流区域的漏报现象,有效提升了短时降水的模拟能力。（3）CUST方案对模式起报初期（6 h甚至3 h内）的改进效果较为明显,且对小雨量级的改进幅度要大于大雨量级。（4）与基于地表感热和潜热通量确定的对流尺度速度作为对流判据的混合云分析方案（简称CSW方案）相比,CUST方案基于实况资料划分的对流云/层状云更为合理,模拟的降水结果占优,说明CUST方案方法有较好的应用前景。     

一次强对流降水及雨水蒸发对其影响的数值研究

基于中尺度数值模式(WRF v3.4),对发生在湖北省红安地区的一次强对流降水天气过程进行了数值模拟。结果表明,此次强对流天气是在水汽充足,高层辐散、低层辐合以及不稳定能量较大的条件下发生发展的。模式模拟得到的地面累积降水和雷达反射率因子与实况相符,云下雨水蒸发过程显著。进行敏感性试验,将雨水蒸发率分别降至1/2、1/4以及完全关闭后,雷达回波强度减弱,对流演变特征发生变化。蒸发过程的减弱使得降水始发阶段以及后期消散阶段的降水强度增强,在对流旺盛阶段降水强度减弱。同时雨水蒸发过程减弱导致云中上升气流减弱,冰雪晶及霰粒子含水量极大值减小、极大值所在高度降低。可见,雨水蒸发对对流云团动力、热力结构及云微物理结构以及云物理过程均有一定程度的影响。     

多普勒天气雷达资料对中尺度模式短时预报的影响

利用中尺度模式ARPS(The Advanced Regional Prediction System)及其资料分析系统ADAS(ARPS Data Analysis System),将国内新一代多普勒雷达(CINRAD)反射率及径向风资料直接用于中尺度数值模拟,通过一次华北地区暴雨过程的模拟对比试验,分析了雷达资料对初始场的改进效果及其对模拟结果的影响,结果表明:(1)利用雷达径向风资料对初始风场进行调整后,自近地面到对流层顶的u,v,w都发生了变化,调整后的初始风场在对流层中层变化最大.(2)利用雷达反射率进行微物理调整和云分析能调整初始场中的云水信息,使得雷达回波附近3 km以下的水汽混合比(qv)增加,4 km以下的雨水混合比(qr)增加,对流层(约10 km以下)的云水混合比(qc)增加,4～9 km的对流层上部云冰混合比(qi)和雪混合比(qs)增加.ADAS通过非绝热初始化调整温度场,从而得到了一个动力和热力上平衡的初始场.(3)模拟的1 h雨量与实况的对比表明,同时利用雷达反射率和径向风改进过的初始场能明显增强3 h内的降水强度和落区预报,改善中尺度数值模式短时定量降水预报.模拟的1 h流场对比分析表明,经雷达径向风调整后,能够在初始场中增加气旋性涡旋等中小尺度风信息,明显减少模式的spin-up时间.(4)通过对雷达径向风和反射率对模式初始场和模拟结果影响的对比分析发现,雷达径向风主要是改进初始风场,而雷达反射率主要是改进初始场中的湿度参数,增加初始场中云水等的含量,调整温度场.通过模拟的6 h降水对比发现,利用雷达径向风调整初始场后,对降水模拟有一定的改进,但效果不甚明显,而雷达反射率资料对定量降水预报改进效果明显,同时使用雷达径向风和反射率资料改进初始场后对降水的模拟效果最明显.     

雷达反射率因子在中尺度云分辨模式初始化中的应用Ⅰ：云微物理量和垂直速度的反演

对于水平网格距小于10 km的高分辨率非静力平衡的显式云分辨模式,云微物理量的初始化以及物理量之间的相互协调是十分重要的,并且一直是云分析领域的一个难题。考虑在云雨处于定常状态的前提下,根据暖云过程,可得到云中水成物之间相互转化以及与垂直速度的约束关系,而雨水含量跟雷达反射率因子(Z)有关。因此,采用合肥新一代天气雷达2003年7月5日02时(北京时)的观测资料,针对雷达探测的特点对雷达原始数据进行了坐标转换,并进行了插值处理和简单的质量控制,然后依据Z-qr关系和定常暖云方案,反演了雨水混合比(qr)、云水混合比(qc)、水汽混合比(qv)和垂直速度(w)。结果表明,由此得到的雷达回波主要特征及量值分布与雷达站的CAPPI图像基本一致;水汽、云水、雨水和垂直速度量值大小的分布与雷达回波强度的分布也是吻合的,体现出了云中水成物和垂直速度的三维分布结构;各物理量的量值也符合梅雨锋暴雨的特点,梅雨锋积层混合云系中层状云和对流云的差别十分明显。在较强的回波区,雨水在6 km以下含量较大,最大值位于4 km左右,可超过3.0 g/kg;上升速度在5 km左右最大,最大值超过5 m/s;云水含量大值区位于5 km以上,在7 km高度上达到最大,超过3.0 g/kg;雨滴末速度虽然上下比较一致,一般几米每秒,但在5 km左右为大值区。     

云分析方法对浙江省一次强对流天气数值模拟的应用初探

基于云分析方法,利用WRF-ARW模式设计一套快速更新循环同化方案,对2019年3月21至22日发生在浙江省的一次强对流天气过程进行模拟研究。通过设计两组对比试验,对云分析同化雷达反射率效果进行诊断分析。在控制试验中,模拟降水落区和降水量与实况差别较大,而采用云分析方法同化雷达反射率（CA-DA）的模拟试验中,降水模拟效果相对较好,雨带明显东移,强度与实况接近。初步结果表明,利用云分析同化雷达反射率因子可以改进模式初始场的风、温度、水汽场以及水凝物等信息,进而缩短模式spin-up时间,提高降水落区及强度的预报。     

C波段雷达反射率因子在CMA-GD模式中的应用

使用CMA-GD模式及云分析系统,引入云南C波段多普勒雷达反射率因子资料,对2019年7月9日过程进行模拟试验,分析引入反射率资料对模式初始场和降水过程预报的影响。（1）引入反射率后,云中和底部的云量有所增加。水汽在900~200 hPa有大范围增加,能有效地调整降水区域的水汽分布。对模式顶层温度的调整较大,而对风场的影响较小。（2）引入反射率后,对3 h内降水强度及落区有较大改善,4~6 h的预报有所改善,7 h以后改善不明显。（3）引入反射率资料后,1~4 h大气可降水量增量较明显,5~9 h增量较前4 h明显减小。（4）在河口上空云水和水汽在950~400 hPa增加,霰、云冰和云雪在600~400 hPa增加,雨滴在1 000~500 hPa增加。水凝物增加,有利于河口站降水的发生。      

Relationship between radar reflectivity and the time scale of warm rain formation in a global cloud-resolving model

The connections between radar reflectivity and the time scale of warm rain formation are examined within a global cloud-resolving model. The parameterizations formulae of auto-conversion and accretion processes in the model reveal specific relationships between the time scale for auto-conversion and radar reflectivity of cloud water as well as between the time scale for accretion and radar reflectivity of rain water. The overall time scale for warm rain formation, determined by combined contributions from these processes, is found to relate with total radar reflectivity in the manner that varies with cloud-rain composition between auto-conversion and accretion limits. The global statistics from the model output reveals that the time scale is closely related with the total radar reflectivity, thus suggesting that the radar reflectivity is a gross measure of the warm rain time scale. The relationship developed is applied to both model-simulated and CloudSat-observed radar reflectivities to compare the time scales of warm rain formation between observation and the model. Comparison of the time scale so derived reveals significant differences between the model and CloudSat observations. These differences suggest that the simulated cloud-rain composition in the model is biased toward larger rain water contents and smaller content of cloud water compared to reality due to an accelerated cloud-to-rain water conversion in the model.     

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。     

ALLOCATION DIFFERENCE ANALYSES OF WATER SUBSTANCES DURING TYPHOON LANDING PROCESSES

Based on a successful simulation of Typhoon Haikui (2012) using WRF (Weather Research & Forecasting) model with the WSM6 microphysics scheme, a high-resolution model output is presented and analyzed in this study. To understand the cause of the average gridded rainfall stability and increases after Haikui’s landfall, this research examines the fields of the physical terms as well as the vapor and condensate distributions and budgets, including their respective changes during the landing process. The environmental vapor supply following the typhoon landfall has no significant difference from that before the landfall. Although Haikui’s secondary circulation weakens, this circulation is not conducive to typhoon rainfall stability or increases, although the amounts of the six kinds of water substances (vapor, cloud water, cloud ice, snow, rain, and graupel) increase in the outer region of the typhoon. This reallocation of water substances is essential to the maintenance of rainfall. The six kinds of water substances are classified as vapor, clouds (cloud water and ice) and precipitation (snow, rain, and graupel) to diagnose their budgets. This sorting reveals that the changes in the budgets of different kinds of water substances, caused by the reduced mixing ratios of snow and ice, the water consumption of clouds, and the transformation of graupel, induce increased concentrations of precipitation fallout, which occur closer to the ground after typhoon landfall. In addition, this pattern is an efficient way for Haikui’s rainfall to remain stable after its landfall. Thus, the allocation and budget analyses of water substances are meaningful when forecasting the typhoon rainfall stability and increases after landfall.