Evaluating the performance of a WRF physics ensemble over South-East Australia

When using the Weather Research and Forecasting (WRF) modelling system it is necessary to choose between many parametrisations for each physics option. This study examines the performance of various physics scheme combinations on the simulation of a series of rainfall events near the south-east coast of Australia known as East Coast Lows. A thirty-six member multi-physics ensemble was created such that each member had a unique set of physics parametrisations. No single ensemble member was found to perform best for all events, variables and metrics. This is reflected in the fact that different climate variables are found to be sensitive to different physical parametrisations. While a standardised super-metric can be used to identify best performers, a step-wise decision approach described here, allows explicit recognition of the “robustness” of choosing one parameterisation over another, allowing the identification of a group of “equally robustly” performing physics combinations. These results suggest that the Mellor-Yamada-Janjic planetary boundary layer scheme and the Betts-Miller-Janjic cumulus scheme can be chosen with some robustness. Possibly with greater confidence, the results also suggest that the Yonsei University planetary boundary layer scheme, Kain-Fritsch cumulus scheme and RRTMG radiation scheme should not be used in combination in this region. Results further indicate that the selection of physics scheme options has larger impact on model performance during the more intensive rainfall events.     

Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8^th of June 2007 along the coast of eastern Australia (abbreviated “Newy”). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ～10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.     

采用不同样本集合同化地面观测对一次飑线过程的影响

针对夏季黄淮地区一次飑线过程,利用WRF (Weather Research and Forecasting) 模式及其Hybrid ETKF-3DVAR同化系统,考察不同生成方案的样本对同化地面观测的影响。集合样本创建方式包括3类:扰动初始背景场的方案 (RCV)、使用不同的物理参数化方案 (PPMP) 以及前两者集成方案 (BLE)。基于增量场分析,同化地面观测主要调整850 hPa以下水平风和水汽混合比的空间结构,其中RCV方案侧重于改变水平风的空间分布,PPMP方案侧重于改变水汽混合比的空间结构,BLE方案兼具二者特征。同化地面观测可以间接改善6 h降水预报,其中PPMP试验的降水预报最好,尤其是对降水位置和强度的预报。对比雷达回波观测,RCV试验和BLE试验对弓状回波模拟得较好,BLE试验的模拟较多体现RCV特征。PPMP试验和RCV试验还可改变冷池的位置和强度,同时影响飑线出现和消亡时间,相对而言,PPMP试验影响更大。     

不同云微物理方案对上海特大暴雨模拟影响的分析

利用中尺度数值预报模式WRF3.5,采用36、12和4 km三重嵌套,在积云参数化方案为BMJ条件下,选用WSM5、WSM6和Lin三种云微物理参数化方案,对发生在上海地区的两次典型特大暴雨（简称“0913”和“0825”）进行模拟试验和对比分析,探讨不同云微物理参数化方案对上海暴雨模拟的影响。结果表明:三种方案总体上都较好地模拟出两次特大暴雨过程,但在降水落区、降水中心、降水强度等方面仍存在差异。再利用地面自动站、观测站的实测雨量以及自动站与CMORPH降水产品融合的逐时降水量网格数据,结合K指数、相对湿度、垂直速度和涡度散度等物理诊断量,从降水落区、降水中心和降水强度等方面对三种云微物理参数化方案的模拟结果进行对比分析。此外,通过对三种方案主要参数的比较以及三种方案模拟的冰、雪、霰粒子混合比的垂直廓线对相应的模拟结果进行解释。结果显示:WSM5微物理方案能更好地模拟出强降水的范围,其模拟的降水量较实测偏大;WSM6方案模拟的降水落区略有偏移,降水量偏小;Lin方案模拟的降水落区偏移较大。      

The Uncertainty of Mesoscale Numerical Prediction of Heavy Rain in South China and the Ensemble Simulations?

In the context of non-hydrostatic MM5 version we have explored the impact of convective parameterization schemes on uncertainty in mesoscale numerical prediction of South China heavy rain and mesoscale heavy rainfall short-range ensemble simulation by using two kinds of physics perturbation methods through a heavy rain case occurring on June 8, 1998 in Guangdong and Fujian Provinces. The results show the physical process of impacts of convective schemes on heavy rainfall is that different latent heat of convective condensation produced by different convective schemes can make local temperature perturbation, leading to the difference of local vertical speed by the intrinsic dynamic and thermodynamic processes of atmosphere,and therefore, making difference of the timing, locations and strength of mesh scale and subgrid scale precipitation later. New precipitations become the new source of latent heat and temperature perturbation,which finally make the dynamic and thermodynamic structures different in the simulations. Two kinds of methods are used to construct different model version stochastically. The first one is using different convective parameterization and planetary boundary layer schemes, the second is adjusting different parameters of convective trigger functions in Grell scheme. The results indicate that the first ensemble simulations can provide more uncertainty information of location and strength of heavy rainfall than the second. The single determinate predictions of heavy rain are unstable; physics ensemble predictions can reflect the uncertainty of heavy rain, provide more useful guidance and have higher application value.Physics ensembles suggest that model errors should be taken into consideration in the heavy rainfall ensembles. Although the method of using different parameters in Grell scheme could not produce good results, how to construct the perturbation model or adjust the parameter in one scheme according to the physical meaning of the parameter still needs further investigation. The limitation of the current study is that it is based on a single case and more cases will be addressed in the future researches.     

华南中尺度暴雨数值预报的不确定性与集合预报试验

利用非静力MM5模式,分析了不同积云对流参数化方案对华南暖区暴雨数值预报的不确定性影响,进行了中尺度暴雨模式扰动集合预报试验。不同对流参数化方案的对流凝结加热引起不同的局地温度扰动,通过大气内部的热力动力过程,导致垂直速度的差异,进而影响网格尺度和次网格尺度降水时间、地点和强度。后续降水再通过凝结潜热释放形成新的扰动源。不同积云对流参数化方案还可引起扰动源能量传播方式不同,最终使模拟大气的动力和热力结构有差异。针对物理过程的不确定性,使用两种模式扰动方法构造集合预报扰动模式,第一种方法是随机组合不同积云对流参数化方案和边界层方案,第二种方法是扰动Grell积云对流参数化方案中主要参数振幅。集合预报结果表明,第一种方法的集合预报效果优于第二种方法,仅扰动参数振幅值似乎还不足以反映华南暴雨预报的不确定性。单一的确定性预报在暴雨落区和强度方面的可信度不稳定,集合产品能给华南暴雨过程提供更有用价值的指导预报,具有较高的应用价值。     

The Uncertainty of Mesoscale Numerical Prediction of Heavy Rain in South China and the Ensemble Simulations

1. IntroductionHeavy rain is a kind of severe natural calamitythat influences South China. After decades of years oftests and theoretical exploration by Chinese scientists,significant progresses have been achieved in its predic-tion and basic theoretical studies (Huang, 1986; Xue,1999; Zhou et al., 2003). Currently, the mesoscale nu-merical model has already been employed as one of themajor tools in the prediction and research on heavyrain in South China, promoting considerably the ac-curac…     

北京“7.21”特大暴雨不同集合预报方案的对比试验

采用6套扰动方案(初值、多物理、3组随机物理和初值与随机物理的混合)对2012年7月21日(“7.21”)北京特大暴雨过程进行了集合降水预报试验,检验了不同方案的集合平均预报、集合区间预报和概率预报较控制预报改进的相对程度,分析了它们对该过程时空不确定性的预报能力、不同扰动方法的离散度贡献以及不同尺度扰动对预报误差的贡献等。结果表明:(1)所有集合方案特别是初值扰动、多物理和混合扰动的集合预报相对控制预报在暴雨强度和位置上都有较显著的改进,并为用户决策提供了包括预报不确定性在内的更多预报信息。(2)3组随机物理产生的集合预报离散度很相似, 都远小于初值扰动和多物理方案产生的离散度, 并且主要集中在强降水中心附近, 因此在初值扰动的基础上加入随机扰动,可以提高强降水中心的离散度, 但对强降水中心以外的地区作用甚微;尺度分析进一步表明随机物理产生的离散度贡献主要集中在较小尺度上(<320 km),在更小的尺度上(<160 km)它甚至可以与初值和多物理扰动的贡献相当,而初值扰动和多物理过程的贡献可以比随机物理过程多延伸400—500 km直到较大的尺度(如>1000 km), 其中多物理过程在较小尺度上(<100 km)可比初值扰动贡献更大, 并且能部分消除预报系统偏差。(3) 所有集合扰动方案所产生的离散度尺度谱都与实际预报误差尺度谱分布一致, 即随空间尺度增大而减小,但在幅度上都小于预报误差(离散度不够大),并且这种差异随着空间尺度的减小而加速增大,在小尺度上相差甚大。     

基于WRF模式的清江流域降雨-径流模拟研究

基于WRF模式,采用4层嵌套方案,选取3种积云参数化方案和7种微物理方案组成21种组合,对清江流域2016—2018年6—10月6次典型降雨事件进行数值预报,结合CMORPH卫星-地面自动站-雷达三源融合降水产品,采用TS评分和FSS评分,分析不同分辨率和云微物理方案的降雨预报效果;基于较优组合方案的WRF模式与WRF-Hydro水文模式耦合进行径流模拟,分析WRF模式在水文模拟中的应用效果。结果表明:3 km和1 km分辨率对降雨中心位置及强度预报的差别不大,对降雨落区都有较好的预报能力;在积云参数化方案中,KF方案和BMJ方案的降雨预报效果优于GF方案;在微物理方案中,WSM3、WSM5、WSM6、Thompson方案的预报结果与融合数据有较好的一致性;基于较优组合方案BMJ_WSM3,将WRF模式与WRF-Hydro模式耦合,耦合模式能较好地模拟洪水过程,径流模拟相关系数都在0.67以上,且NSE最高可达0.79。      

基于不同微物理过程的广西沿海南风型暖区暴雨的数值模拟研究

基于WRFV3.6.1,利用其8个云微物理参数化方案对2010—2016年华南汛期（4—9月）的6个南风型暖区暴雨个例进行数值模拟与多方案集成试验,并采用基于对象的诊断评估方法（MODE）对模拟结果进行评估。结果发现对于大多数个例,WRF模式都能较好地模拟出暖区暴雨的降水带,对暖区降水带模拟最好的参数化方案是WSM6方案,其次是Lin方案;模拟效果较差的参数化方案为CAM5.1与NSSL 2-mon方案。选取模拟结果较好的个例进行诊断分析,发现不同参数化方案得到的动力学特征以及云微物理特征相关变量存在较大差异,导致模拟降水的差异。在单方案模拟的基础上,开展多方案集成试验,发现多方案集成方法能够有效降低模式模拟的不确定性,产生更稳定的模拟结果。     

基于多模式集合方案的中国东部夏季降水概率季度预测

借助ENSEMBLES计划提供的5个海-气耦合模式(CGCM)的多初值后报降水资料,采用常用的4种多模式集合方案,即等权集合(EE)、对单个集合成员先订正再等权集合(Cali-EE)、基于多元线性回归的集合方案(MLR)、基于贝叶斯统计学的集合方案(Bayes),制作1960—2005年中国东部夏季降水概率密度函数(PDF)季度预测。在此基础上,比较最优(技巧最高)集合方案与气候学预测(衡量概率密度函数预测是否有技巧的基准)的技巧,初步评估目前基于多模式集合方案的、中国东部夏季降水的概率密度函数季度预测能力。结果表明,Bayes方案在华南最优,Cali-EE在长江流域、江淮流域以及中国北方的中部最优,MLR在中国北方的东部最优;基于这些最优集合方案的概率密度函数预测产品均具有高校准度,且其锐度高于或接近气候学预测;并且,对于所有区域,最优集合方案的预测技巧总是高于气候学预测,这暗示即使不提取模式其他变量中所包含的预测信息,对于中国东部夏季降水季度预测,常用的多模式集合方案也已具备制作有技巧的概率密度函数预测产品的能力。     

基于GRAPES_Meso的集合预报扰动方案设计与比较

基于GRAPES_Meso区域集合预报系统,设计了三种集合预报扰动方案,即多初值、多初值多物理、多初值多物理多边值,并针对三种方案进行了连续一个月的批量试验,重点分析了2008年7月23日江淮暴雨过程.结果表明,对于降水预报,三种集合扰动方案均相对于控制预报均有所改善,多初值多物理与多初值多物理多边值方案对小雨、中雨预报改进效果显著,对暴雨预报略有改进;多初值方案仅能产生有限的集合离散度且难以增长,引入物理参数方案扰动及边界条件扰动能显著提高集合离散度,改善各物理量场的预报效果;通过比较,多初值多物理多边值为最优方案.该批量试验表明,模式物理过程及边界条件是影响GRAPES _Meso区域集合预报不确定性的不可忽视因素.     

Probabilistic seasonal prediction of summer rainfall over East China based on multi-model ensemble schemes

The skill of probability density function (PDF) prediction of summer rainfall over East China using optimal ensemble schemes is evaluated based on the precipitation data from five coupled atmosphere-ocean general circulation models that participate in the ENSEMBLES project. The optimal ensemble scheme in each region is the scheme with the highest skill among the four commonly-used ones: the equally-weighted ensemble (EE), EE for calibrated model-simulations (Cali-EE), the ensemble scheme based on multiple linear regression analysis (MLR), and the Bayesian ensemble scheme (Bayes). The results show that the optimal ensemble scheme is the Bayes in the southern part of East China; the Cali-EE in the Yangtze River valley, the Yangtze-Huaihe River basin, and the central part of northern China; and the MLR in the eastern part of northern China. Their PDF predictions are well calibrated, and are sharper than or have approximately equal interval-width to the climatology prediction. In all regions, these optimal ensemble schemes outperform the climatology prediction, indicating that current commonly-used multi-model ensemble schemes are able to produce skillful PDF prediction of summer rainfall over East China, even though more information for other model variables is not derived.     

区域集合预报基于SKEB和多物理过程的混合模式扰动方法研究

为了研究随机动能后向散射(stochastic kinetic energy backscatter,SKEB)模式扰动方法在区域集合预报中的应用效果,基于WRF模式构建了集合预报系统,针对SKEB的扰动振幅进行了敏感性试验,以了解SKEB扰动的作用特征;发展了一种多物理过程组合(multi-physics,MPHY)与SKEB相结合的混合模式扰动方法(SKEB-MPHY),并对比了SKEB、MPHY以及SKEB-MPHY的预报效果,以探索区域集合预报的最优模式扰动实现方案。试验结果表明:SKEB方法通过固定的动能耗散率计算出流函数及温度扰动,从而对模式积分产生影响,且耗散率大小与预报离差正相关,垂直结构扰动不利于预报离差的发展。SKEB、MPHY以及SKEB-MPHY方法的对比试验表明,对于高空动力场预报离散度的增长,SKEB方法比MPHY方法占优,而低层温度预报离散度增长,MPHY比SKEB扰动方法占优,混合模式扰动方法的扰动增长能力在三种方案中表现最好。集合预报检验结果表明SKEB-MPHY方法评分优于单独的SKEB和MPHY方法。降水个例分析及降水评分结果表明与单独采用MPHY方法相比,引入SKEB方法可以对大雨预报有所改进。本文研究结果表明SKEB方法及在其基础上建立的混合模式扰动方法具有较好的应用前景。     

WRF模式中微物理和积云参数化方案的对比试验

为了研究微物理参数化方案对珠江三角洲(简称珠三角)降水模拟的影响,利用WRF中尺度数值预报模式,在3 km模式分辨率下,在微物理方案为WSM6方案条件下,选用KF、BMJ、GD以及G3等四种积云参数化方案对2010年5月14日广东珠三角地区的一次暴雨过程进行了模拟试验。结果显示,KF方案对于降水带和降水量的模拟与实况较为一致。在积云参数化方案为KF条件下,分别选用Kessler、Lin et al、WSM 3、WSM5、Ferrier(New eta)和WSM6等6种微物理方案再次对这次暴雨过程进行模拟试验,模拟结果的对比分析表明:选用Lin et al微物理方案时,模式较好地模拟出了强降水雨带的位置和降水强度;而其他5种参数方案的模拟效果均不好,降水量明显偏小,雨带位置偏差较大;同时对低空急流、K指数和上升速度等物理量分析可知,Lin et al方案能较好地模拟出降水实况。     

IMPACTS OF DIABATIC PHYSICS PARAMETERIZATION SCHEMES ON MESOSCALE HEAVY RAINFALL SHORTRANGE SIMULATION

Based on the non-hydrostatic version of Mesoscale Model version 5 (MMS) and the data sets of four heavy rainfall scenarios occurring in August 2001 in China,this paper investigates the impacts of diabatic physical processes on predictions of dynamic and thermodynamic elements of heavy rainfall in China,deeply analyzes the effects of convective schemes on mesoscale heavy rain simulations and discusses the feasibility of using model physics perturbations in ensemble simulation of heavy rain,The results show that diabatic physical processes have little impact on the short-range prediction of geopotential height.However,planetary boundary layer schemes and convective schemes have significant influence on moisture divergence flux,vertical velocity,and unstable stratification,which are the three basic conditions of torrential rain.The forecast deviations in different convection schemes increase rapidly in the first 12 h time periods of simulation and the deviation structures are well correlated to that of sub-grid scale rainfall,while in the later periods of simulation with less correlation.Diabatie physical processes influence the structure and evolution of the simulations.For the rain storm events with a homogeneous thermal environmental condition in China.the numerical model ensembles could be created by perturbing the planetary parameterization scheme and convective parameterization.     

Performance assessment of three convective parameterization schemes in WRF for downscaling summer rainfall over South Africa

Austral summer rainfall over the period 1991/1992 to 2010/2011 was dynamically downscaled by the weather research and forecasting (WRF) model at 9 km resolution for South Africa. Lateral boundary conditions for WRF were provided from the European Centre for medium-range weather (ECMWF) reanalysis (ERA) interim data. The model biases for the rainfall were evaluated over the South Africa as a whole and its nine provinces separately by employing three different convective parameterization schemes, namely the (1) Kain–Fritsch (KF), (2) Betts–Miller–Janjic (BMJ) and (3) Grell–Devenyi ensemble (GDE) schemes. All three schemes have generated positive rainfall biases over South Africa, with the KF scheme producing the largest biases and mean absolute errors. Only the BMJ scheme could reproduce the intensity of rainfall anomalies, and also exhibited the highest correlation with observed interannual summer rainfall variability. In the KF scheme, a significantly high amount of moisture was transported from the tropics into South Africa. The vertical thermodynamic profiles show that the KF scheme has caused low level moisture convergence, due to the highly unstable atmosphere, and hence contributed to the widespread positive biases of rainfall. The negative bias in moisture, along with a stable atmosphere and negative biases of vertical velocity simulated by the GDE scheme resulted in negative rainfall biases, especially over the Limpopo Province. In terms of rain rate, the KF scheme generated the lowest number of low rain rates and the maximum number of moderate to high rain rates associated with more convective unstable environment. KF and GDE schemes overestimated the convective rain and underestimated the stratiform rain. However, the simulated convective and stratiform rain with BMJ scheme is in more agreement with the observations. This study also documents the performance of regional model in downscaling the large scale climate mode such as El Niño Southern Oscillation (ENSO) and subtropical dipole modes. The correlations between the simulated area averaged rainfalls over South Africa and Nino3.4 index were ?0.66, ?0.69 and ?0.49 with KF, BMJ and GDE scheme respectively as compared to the observed correlation of ?0.57. The model could reproduce the observed ENSO-South Africa rainfall relationship and could successfully simulate three wet (dry) years that are associated with La Niña (El Niño) and the BMJ scheme is closest to the observed variability. Also, the model showed good skill in simulating the excess rainfall over South Africa that is associated with positive subtropical Indian Ocean Dipole for the DJF season 2005/2006.     

物理过程参数化方案对中尺度暴雨数值模拟影响的研究

利用中尺度非静力MM 5模式和中国 2 0 0 1年 8月的 4个暴雨个例 ,研究了非绝热物理过程对中国暴雨动力和热力场预报的影响 ,深入分析了对流参数化方案在中尺度暴雨预报中的作用 ,讨论了利用模式扰动方法开展中国暴雨集合预报的可行性。结果表明 ,在短期数值预报中 ,非绝热物理过程对高度场预报影响较小 ,但边界层方案和对流参数化方案对产生暴雨的 3个基本条件即水汽通量散度、垂直速度、不稳定层结的影响很明显。不同对流参数化方案所预报的中尺度热力、动力场离差的结构特征与所预报降水的离差特征相似 ,且主要是在模式积分初期迅速增加 ,其后即趋于稳定。对中国热力场较均匀的暴雨过程 ,可以通过扰动模式的边界层和对流参数化方案 ,构造集合预报模式     

On the Influences of Urbanization on the Extreme Rainfall over Zhengzhou on 20 July 2021: A Convection-Permitting Ensemble Modeling Study

This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale [1-km resolution in the innermost domain(d3)]. Two ensembles of simulation(CTRL, NURB), each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes, were conducted using different land cover scenarios:(i) the real urban ...     

Representing Model Uncertainty by Multi-Stochastic Physics Approaches in the GRAPES Ensemble

To represent model uncertainties more comprehensively,a stochastically perturbed parameterization(SPP)scheme consisting of temporally and spatially varying perturbations of 18 parameters in the microphysics,convection,boundary layer,and surface layer parameterization schemes,as well as the stochastically perturbed parameterization tendencies(SPPT)scheme,and the stochastic kinetic energy backscatter(SKEB)scheme,is applied in the Global and Regional Assimilation and Prediction Enhanced System-Regional Ensemble Prediction System(GRAPES-REPS)to evaluate and compare the general performance of various combinations of multiple stochastic physics schemes.Six experiments are performed for a summer month(1-30 June 2015)over China and multiple verification metrics are used.The results show that:(1)All stochastic experiments outperform the control(CTL)experiment,and all combinations of stochastic parameterization schemes perform better than the single SPP scheme,indicating that stochastic methods can effectively improve the forecast skill,and combinations of multiple stochastic parameterization schemes can better represent model uncertainties;(2)The combination of all three stochastic physics schemes(SPP,SPPT,and SKEB)outperforms any other combination of two schemes in precipitation forecasting and surface and upper-air verification to better represent the model uncertainties and improve the forecast skill;(3)Combining SKEB with SPP and/or SPPT results in a notable increase in the spread and reduction in outliers for the upper-air wind speed.SKEB directly perturbs the wind field and therefore its addition will greatly impact the upper-air wind-speed fields,and it contributes most to the improvement in spread and outliers for wind;(4)The introduction of SPP has a positive added value,and does not lead to large changes in the evolution of the kinetic energy(KE)spectrum at any wavelength;(5)The introduction of SPPT and SKEB would cause a 5%-10%and 30%-80%change in the KE of mesoscale systems,and all three stochastic schemes(SPP,SPPT,and SKEB)mainly affect the KE of mesoscale systems.This study indicates the potential of combining multiple stochastic physics schemes and lays a foundation for the future development and design of regional and global ensembles.