Impact of cloud microphysical processes on hurricane intensity, part 2: Sensitivity experiments

Summary Seven different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating hurricane intensity forecasts using mesoscale model MM5. Microphysical processes such as melting of graupel, snow and cloud ice hydrometeors, suppression of evaporation of falling rain, the intercept parameter and fall speed of snow and graupel hydrometeors are modified in the existing NASA Goddard Space Flight Center (GSFC) microphysical parameterization scheme. We studied the impacts of cloud microphysical processes by means of track, intensity, precipitation, propagation speed, kinematic and thermodynamic vertical structural characteristics of hurricane inner core. These results suggest that the set of experiments where (a) melting of snow, graupel and cloud ice were suppressed (b) melting of snow and graupel were suppressed and (c) where the evaporation of rain water was suppressed all produced most intense storms. The major findings of this study are the interconversion processes such as melting and evaporation among hydrometeors and associated feedback mechanism are significantly modulate the intensity of the hurricane. In particular an experiment where the melting of graupel, snow and cloud ice hydrometeors was eliminated from the model parameterization scheme produced the most explosively intensified storm. In the experiment where rain water evaporation was eliminated from the model, it produced a stronger storm as compared to the control run but it was not as strong as the storms produced from absence of melting processes. The impact on intensity due to variations made in intercept parameters of the hydrometeors (i.e., snow and graupel) were not that evident compared to other experiments. The weakest storm was noted in the experiment where the fall speeds of the snow hydrometeors were increased two fold. This study has isolated some of the factors that contributed to a stronger hurricane and concludes with a motivation that the findings from this study will help in further improvement in the design of sophisticated explicit microphysical parameterization for the mesoscale non-hydrostatic model for realistic hurricane intensity forecasts.     

台风“云娜”在近海强度变化及结构特征的数值研究Ⅰ:云微物理参数化对云结构及降水特征的影响

首先对AREM模式模拟的台风基本结构和云结构进行验证,检验了模拟结果的可靠性.在此基础上,设计了5组试验来研究云微物理参数化方案对台风"云娜"云结构及降水特征的影响.试验设计主要突出冰相云微物理过程、云微物理特征引发的冷却效应以及霰下落速度的重要性.结果表明:云微物理参数化过程对云的发展和降水特征的影响更为显著.各试验的水凝物分布和强度不同,降水类型和强度存在较大差异,由此引起的云中热力结构也有较大区别;在所有试验方案中,24 h降水率最大差异为52.5 mm/h.云微物理过程对云和降水特征的具体影响表现在:(1)如果不考虑雨水蒸发冷却效应,此时台风内核上升运动强度最强(达到-19 Pa/s),雨水和霰粒子增长最明显,相对于对照试验增量分别为1.8和2.5 g/kg.(2)霰和雪的融化对于螺旋雨带中雨滴的增长十分重要,但他们可能不是云墙中雨水形成的主导因子.(3)不同方案的降水模拟特征也存在较大差别,采用暖云参数化后,降水区域最小,但其中对流降水比例最大(63.19%);霰落速减半后,降水区域最大,其中非对流降水比例也最大(51.15%).     

Impact of Cloud Microphysical Processes on the Simulation of Typhoon Rananim near Shore.Part Ⅰ: Cloud Structure and Precipitation Features

By using the Advanced Regional Eta-coordinate Model (AREM),the basic structure and cloud features of Typhoon Rananim are simulated and verified against observations.Five sets of experiments are designed to investigate the effects of the cloud microphysical processes on the model cloud structure and precipitation features.The importance of the ice-phase microphysics,the cooling effect related to microphysical characteristics change,and the influence of terminal velocity of graupel are examined.The results indicate that the cloud microphysical processes impact more on the cloud development and precipitation features of the typhoon than on its intensity and track.Big differences in the distribution pattern and content of hydrometeors,and types and amount of rainfall occur in the five experiments,resulting in different heating and cooling effects.The largest difference of 24-h rain rate reaches 52.5 mm h-1.The results are summarized as follows:1) when the cooling effect due to the evaporation of rain water is excluded,updrafts in the typhoon's inner core are the strongest with the maximum vertical velocity of-19 Pa s-1 and rain water and graupel grow most dominantly with their mixing ratios increased by 1.8 and 2.5 g kg-1,respectively,compared with the control experiment; 2) the melting of snow and graupel affects the growth of rain water mainly in the spiral rainbands,but much less significantly in the eyewall area; 3) the warm cloud microphysical process produces the smallest rainfall area and the largest percentage of convective precipitation (63.19％),while the largest rainfall area and the smallest percentage of convective precipitation (48.85％) are generated when the terminal velocity of graupel is weakened by half.     

A STUDY OF THE INFLUENCE OF MICROPHYSICAL PROCESSES ON TYPHOON NIDA (2016) USING A NEW DOUBLE-MOMENT MICROPHYSICS SCHEME IN THE WEATHER RESEARCH AND FORECASTING MODEL

The basic structure and cloud features of Typhoon Nida (2016) are simulated using a new microphysics scheme (Liuma) within the Weather Research and Forecasting (WRF) model. Typhoon characteristics simulated with the Liuma microphysics scheme are compared with observations and those simulated with a commonly- used microphysics scheme (WSM6). Results show that using different microphysics schemes does not significantly alter the track of the typhoon but does significantly affect the intensity and the cloud structure of the typhoon. Results also show that the vertical distribution of cloud hydrometeors and the horizontal distribution of peripheral rainband are affected by the microphysics scheme. The mixing ratios of rain water and graupel correlate highly with the vertical velocity component and equivalent potential temperature at the typhoon eye-wall region. According to the simulation with WSM 6 scheme, it is likely that the very low typhoon central pressure results from the positive feedback between hydrometeors and typhoon intensity. As the ice-phase hydrometeors are mostly graupel in the Liuma microphysics scheme, further improvement in this aspect is required.     

Impact of Different Cloud Microphysics Parameterization Schemes on Typhoon Intensity and Structure

The impact of different cloud microphysics parameterization schemes on the intensity and structure of the Super-strong Typhoon Rammasun (1409) in 2014 is investigated using the Weather Research and Forecasting model version 3.4 with eight cloud microphysics parameterization schemes. Results indicate that the uncertainty of cloud microphysics schemes results in typhoon forecast uncertainties, which increase with forecast time. Typhoon forecast uncertainty primarily affects intensity predictions, with significant differences in predicted typhoon intensity using the various cloud microphysics schemes. Typhoon forecast uncertainty also affects the predicted typhoon structure. Greater typhoon intensity is accompanied by smaller vortex width, tighter vortex structure, stronger wind in the middle and lower troposphere, greater height of the strong wind region, smaller thickness of the eyewall and the outward extension of the eyewall, and a warmer warm core at upper levels of the eye. The differences among the various cloud microphysics schemes lead to the different amounts and distributions of water vapor and hydrometeors in clouds. Different hydrometeors have different vertical distributions. In the radial direction, the maxima for the various hydrometeors forecast by a single cloud microphysics scheme are collocated with each other and with the center of maximum precipitation. When the hydrometeor concentration is high and hydrometeors exist at lower altitudes, more precipitation often occurs. Both the vertical and horizontal winds are the strongest at the location of maximum precipitation. Results also indicate that typhoon intensities forecast by cloud microphysics schemes containing graupel processes are noticeably greater than those forecast by schemes without graupel processes. Among the eight cloud microphysics schemes investigated, typhoon intensity forecasts using the WRF Single-Moment 6-class and Thompson schemes are the most accurate.     

云微物理过程对台风数值模拟的影响

将中国气象科学研究院（CAMS）混合双参数云微物理方案用于中尺度天气模式WRF,开展了对2013年超强台风天兔（1319）的模拟,通过与台风最佳路径、强度及热带降雨测量卫星（TRMM）资料对比,分析CAMS云微物理方案在模拟台风中的适用性及云微物理过程对模拟台风天兔的影响机制。设计了3组敏感性试验:修改雪粒子质量和落速系数（EXP1）,采用海洋性云滴参数（EXP2）,同时修改雪粒子质量和落速系数并采用海洋性云滴参数（EXP3）。结果表明:EXP1和EXP3由于霰碰并雪速率的增加及减小的雪下落通量,导致雪含量显著降低,同时也减少了整体冰相物的含量;EXP2和EXP3模拟的台风眼区对流有效位能快速减小,再现了前期台风的快速增强过程,路径偏差也最小;各试验模拟的小时降水率总体偏强,EXP3的降水空间分布与实况更接近,明显降低雪粒子含量,并一定程度上改善模拟的台风路径、强度及降水分布等。该结果不但可为改进适用于台风的云微物理参数化方案提供思路,也可加深云微物理过程对台风影响的认识。     

A study of the microphysical processes in a numerically simulated heavy snowfall event in North China: the sensitivity of different snow intercept parameters

We performed a modeling study of the cloud processes in a heavy snowfall event occurring in North China on 20–22 December 2004. The nonhydrostatic Mesoscale Model (MM5) was used to carry out experiments with the Reisner-2 explicit microphysical parameterizations in four nested domains to test the sensitivity of simulated heavy snowfall to different snow intercept parameters. Results show that while the different intercept parameters do not significantly affect the accumulated snowfall amounts at the surface in either total amount or location, some microphysical characteristics of the modeled heavy snowfall event are impacted. The budget of cloud microphysics is analyzed to determine the dominant cloud processes. In the control experiment (CTL) with the snow intercept (N _os) specified as a function of temperature, the primary simulated hydrometeor is snow, and its mixing ratio is an order of magnitude larger than that of the other cloud species. Relative to CTL, the experiment with a fixed intercept (CON3E6) produced lower snow mixing ratios, more cloud water and graupel mixing ratios. Among the two experiments, while snowfall is slightly smaller in CON3E6, other processes like the rate of graupel fall, condensation and evaporation of cloud water, deposition and sublimation of graupel are all larger in CON3E6 than in CTL. Among CTL, CON3E6, and two more experiments (CON2E7: with a smaller fixed intercept; and NOSQS: N _os a function of snow mass mixing ratio), the budget shows that CON3E6 produces the smallest deposition and sublimation of snow, the largest deposition of cloud ice, and the largest conversion from cloud ice to snow.     

SENSITIVITY OF LANDFALLING TYPHOON STRUCTURE AND PRECIPITATION TO VARYING CLOUD MICROPHYSICAL PROCESSES

Typhoon KROSA in 2007 is simulated using GRAPES, a mesoscale numerical model, in which a two-parameter mixed-phase microphysics scheme is implanted. A series of numerical experiments are designed to test the sensitivity of landfalling typhoon structure and precipitation to varying cloud microphysics and latent heat release. It is found that typhoon track is sensitive to different microphysical processes and latent heat release. The cloud structures of simulated cyclones can be quite different with that of varying microphysical processes. Graupel particles play an important role in the formation of local heavy rainfall and the maintenance of spiral rainbands. Analysis reveals that the feedback of latent heat to dynamic fields can significantly change the content and distribution of cloud hydrometeors, thus having an impact on surface precipitation.     

不同微物理方案对台风“彩虹”(2015)降水影响的比较研究

本文以GFS资料为初始场,利用WRF（v3.6.1）模式对2015年第22号台风“彩虹”进行了数值研究。采用CMA（中国气象局）台风最佳路径、MTSAT卫星、自动站降水为观测资料,对比了4个微物理方案（Lin、WSM6、GCE和Morrison）对“彩虹”台风路径、强度、结构、降水的模拟性能。模拟发现上述4个云微物理方案都能较好地模拟出“彩虹”台风西行登陆过程,但是其模拟的台风强度、结构及降水存在较大差异;就水成物而言,除GCE方案对雨水的模拟偏高以外,其他方案对云水、雨水过程的模拟较为接近,其差异主要存在于云冰、雪、霰粒子的模拟上。本文对比分析了WSM6和Morrison两个方案模拟的云微物理过程,发现WSM6方案模拟的雪和霰粒子融化过程显著强于Morrison方案,但是冰相粒子间转化过程的强度明显弱于Morrison方案。云微物理过程的热量收支分析表明:WSM6方案模拟的眼区潜热更强,暖心结构更为显著,台风中心气压更低。细致的云微物理转化分析表明,此次台风降水的主要云微物理过程是水汽凝结成云水和凝华为云冰;生成的云水一方面被雨水收集碰并直接转化为雨水,另一方面先被雪粒子碰并收集转化为霰,然后霰粒子融化成雨水;而生成的云冰则通过碰并增长转化为雪。小部分雪粒子通过碰并收集过冷水滴并淞附增长为霰粒子,随后融化为雨水,大部分雪粒子则直接融化形成地面降水。     

Numerical comparison study of cloud microphysical parameterization schemes for a moderate snowfall event in North China

Summary A moderate snowfall event in North China is simulated using the high-resolution mesoscale model MM5. A fourfold-nest experiment, with a minimum horizontal grid size of 2 km, is run. In order to study the cloud microphysics processes associated with the snowfall, two experiments were conducted in two inner domains, one using the Goddard scheme (Goddard experiment), and the other using the Reisner scheme (Reisner experiment). The analysis focused on the comparison of the cloud microphysics processes which occurred in the experiments. It is shown that there is no implicit precipitation of cumulus parameterization in the domain of grid scale 18 km. The snowfall distribution patterns in the experiments are slightly different, but the microphysical characteristics and processes may have considerable differences between the two experiments: (1) The water substances in the cloud have cloud water, cloud ice and snow, but no rainwater and graupel in the Goddard experiment. However, the water substances in the cloud have cloud ice, snow, and graupel, but no cloud water and rainwater in the Reisner experiment. (2) The cloud ice mixing ratios in the Goddard experiment are larger than those in the Reisner experiment. (3) In the Goddard experiment, the dominant cloud microphysical processes include the growth of cloud water by the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow and the Bergeron process of cloud ice. In the Reisner experiment, the dominant cloud microphysical processes include the depositional growth of cloud ice, the conversion of cloud ice to snow, the deposition of snow, and the deposition growth of graupel. (4) There is only snowfall in the Goddard experiment. Meanwhile, there is ice fall, snow fall, and graupel in the Reisner experiment. But the ice fall and graupel in the Reisner experiment is very slight and can be ignored.     

一次梅雨锋暴雨过程数值模拟的云微物理参数化敏感性研究

梅雨锋暴雨中的云微物理过程对降水的演变有着重要影响。本文通过WRF模式（3.4.1版本）,针对2018年6月29～30日一次梅雨锋背景下的暴雨过程进行数值模拟,分别采用了Morrison、Thompson和MY云微物理参数化方案进行对比分析,结果发现:（1）三个方案模拟的背景场在天气尺度上,都与ERA5再分析资料一致,能够模拟出有利于强降水发生的环流场。云微物理过程对梅雨期暴雨的局地环流有着显著影响,不同方案存在明显差异,本次过程中,Thompson方案模拟出更强的局地环流系统变率和上升气流。三个方案的模拟降水均有所夸大,小时降水率始终大于观测值。冰相粒子融化或雨滴搜集云滴的高估可能是造成降水模拟值偏强的重要原因之一,总体来看,Morrison方案的模拟效果相对最优。（2）冰相粒子融化、雨滴搜集云滴是雨滴增长的关键源项,蒸发则是其最重要的汇项。总的来说,雨滴对云滴的搜集量大于冰相粒子融化。但上述过程在不同方案中存在空间上的差异,从而使得模拟降水的空间分布存在差异。（3）Thompson方案中,冰相粒子融化量最大,雨滴蒸发项显著大于其它两个方案,在底层表现得最为明显。同时,该方案水汽凝结效应最强,使得雨滴搜集更多云滴。该方案模拟的雨滴最多,降水最强。该方案中凝华的主要产物为雪,且其在与过冷水碰并增长过程中占主导地位,故模拟的雪最多。（4）Morrison方案中,水汽主要凝华为雪和少量霰（冰晶忽略不计）;Thompson方案中水汽基本凝华为雪,其它冰相粒子极少;MY方案中,水汽主要凝华为雪和冰晶,冰晶总量略少于雪,但显著大于其它方案。（5）云滴在凇附过程中的总体贡献大于雨滴。Morrison和MY方案中,霰粒子搜集云滴增长的量均最大。Morrison方案中,其它凇附过程不同程度发挥作用,而MY方案中,其它凇附过程几乎可忽略不计。并且,霰粒子搜集云滴的增长量大于凝华过程产生的雪粒子总量。贝吉龙及凇附效应的差异,是不同方案中冰相粒子分布差异的关键原因之一。     

热带气旋“苏迪罗”（2015）海上活动时段降水物理过程模拟诊断研究——海表温度敏感性试验

利用WRF模式,在前期工作（王晓慧等,2018）模拟试验基础上,设计敏感性试验,借助三维降水诊断方程,分析揭示了海表温度（SST）变化对热带气旋（TC）“苏迪罗”（2015）海上活动时段降水物理过程的可能影响。对照试验（CTL试验:SST随时间变化）和敏感性试验（SNC试验:SST固定为初始值）的SST存在明显差异（CTL试验平均SST低于SNC试验）。对比分析表明:两试验模拟的海上时段TC路径差异不大,但SNC试验模拟的TC强度较CTL试验偏强;TC环流区域内,两试验垂直速度差值在对流层基本为正（SNC试验上升运动更强）,随着SST差值不断增大,垂直运动差值也不断加大;SNC试验的降水强度（P_S）大于CTL试验,但P_S差值随SST差值增大并非线性变化,体现了P_S变化的复杂性;SNC试验的Q_WVA（垂直积分的三维水汽通量辐合/辐散率）均基本大于CTL试验（后期差别更大）,SST的不同可通过影响垂直运动,造成Q_WVA的差异,进而影响P_S;分析时段内,两试验TC环流区域大气均持续变干（正值Q_WVL）,且存在较明显海面蒸发（正值Q_WVE）,其中,两试验之间的Q_WVL差异不明显,但SNC试验的Q_WVE总体上强于CTL试验（尤其是分析时段中后期）;两试验间云相关过程变率差异的时间变化复杂,最大差异量级与Q_WVE相当;SST对水凝物发展和深对流活动有一定影响,伴随SST差异的逐渐增大,水凝物含量差异也逐渐增大,液相水凝物中,雨滴差异较大,而与液相水凝物相比,冰相水凝物差异更为突出,尤其是较大的冰相粒子（雪和霰）;SNC试验中,零度层下更多的霰粒子和雨滴,在更强上升运动配合下,有助于云滴和雨滴碰并（P_racw）及霰粒子融化（P_gmlt）微物理过程的加强,进而造成更强降水。TC环流区域时间和空间平均的物理量对比分析揭示,两试验降水物理过程定性上基本相似,但定量上存在明显不同,SNC试验的P_S与CTL试验相比,增幅达8.8%,这种差异主要源于降水宏、微观物理过程的差异,其中,不同SST环境下Q_WVE的差异最为显著。     

北京一次短时局地大暴雨过程的特征及对云物理方案的敏感性数值模拟试验

云物理过程是云和降水形成的重要环节。本文针对2011年6月23日发生在北京地区的一次大暴雨过程进行了云降水与天气特征分析,并开展了WRF模式中10种不同云微物理方案对此次暴雨强度、落区和发生时间的敏感性数值模拟试验。研究结果表明,此次大暴雨是由多单体组织、合并形成深厚的中尺度对流系统,并具有明显的短时局地特征和有利的高低空、高低纬度大中尺度天气环流形势及强烈的水汽输送条件。暴雨强度、落区和发生时间的数值模拟结果对云物理方案非常敏感。不同云物理方案对累积降水量≥50 mm和≥100 mm的暴雨模拟的ETS评分显示,只有Thompson方案对此暴雨量级的评分均为正,其他方案的ETS评分均不理想,特别是对累积降水量≥100 mm的大暴雨模拟。在小时暴雨强度和发生时间方面,Thompson方案模拟效果也较好,其次是Lin方案和WSM6方案;对区域累积最大降水量和落区的模拟方面,Thompson方案和Morrison方案模拟的最大累积降水量更接近观测值,但在落区方面,一些具有完整云物理过程的单参数方案（Lin方案、WSM6方案）模拟效果较好,但模拟的最大降水量偏小。针对暖雨的双参数方案WDM6对区域平均降水模拟较好,但对暴雨极端降水模拟较差。对造成差异的原因分析表明,不同云物理方案的差异主要体现在雪和霰的参数化方面,由于采用的粒子谱分布、密度和末速度不同,导致云中粒子间的碰并和形成过程不同,大部分云物理方案模拟的霰含量高,雪含量低。这种云微物理过程的差异会导致云动力过程的反馈作用出现明显不同,但这种反馈作用的差异主要体现在降水粒子对上升气流的拖曳作用不同。尽管云中相变潜热过程对云动力过程具有很重要的影响,但不同云物理方案在相变潜热过程和温度廓线分布方面造成的差异并不明显。因此,云物理方案中考虑合理的粒子谱分布、形态和密度变化,有利于提高暴雨的模拟效果。     

云凝结物平流输送对降水云系发展影响的数值模拟研究

大气动力学中"平流输送"是非常重要的宏观动力学过程,云凝结物的平流输送与降水云系的发展演变密切相关,它把宏观动力过程与各种云凝结物粒子的时空演变联系起来,云凝结物的平流输送可以增加或减少局地大气中云凝结物的含量,改变云凝结物的空间分布状况,影响云凝结物的微观物理过程,进而促进或抑制降水云系的发展演变.本文在数值模拟研究中.通过改变云凝结物平流输送的状况来研究宏观动力过程对云微观物理过程的影响,因而利用ARPS模式开展3个分别排除云凝结物水平平流输送、垂直平流输送和三维平流输送的敏感试验,进行关于云凝结物平流输送对降水云系发展演变影响的敏感性数值模拟研究.结果表明,云凝结物的平流输送对水汽比湿的影响很小.云凝结物的三维平流输送有利于增加降水云系中雪和霰的混合比含量,抑制云水、雨水和云冰混合比含量的增长.云凝结物的水平平流输送可以降低降水云系中云水和雨水的混合比含量,增加云冰和雪的混合比含量;云凝结物垂直平流输送的作用是增加降水云系中雨水、雪和霰的混合比含量,减少云与冰混合比含量.云凝结物三维平流输送效应的分析表明,云凝结物的三维平流输送主要通过调整云凝结物的微物理过程源汇项以及降水粒子(雨水、雪和霰)的下落末速项来改变降水云系中云凝结物的垂直结构;另外,雪的三维平流输送对雪本身的分布也有一定影响.     

理想地形下不同云微物理方案对登陆台风降水增幅影响的数值研究

利用WRF（Weather Research and Forecasting）模式,在理想岛屿地形条件下设计了云的微物理冰相过程中水凝物中有霰和无霰的两个对比试验,考察了台风登陆时复杂冰相和简单冰相对台风移动路径、强度和降水增幅的影响。结果表明：1）云微物理过程中有霰的复杂冰相过程时,具有更强烈的云“播撒”效应,因而对台风降水具有明显增幅作用。2）当台风受到理想地形作用时,地形对云“播撒”效应引起的增幅作用具有放大作用,此时台风眼墙非绝热加热量形成明显增强中心,使得台风降水增幅明显。3）当台风登陆时,云微物理冰相过程使得台风越山时存在向西北指向的涡度变化倾向。     

New RAMS cloud microphysics parameterization part I: the single-moment scheme

A new cloud microphysical parameterization is described. Features of this new scheme include: the use of generalized gamma distributions as the basis function for all hydrometeor species; the use of a heat budget equation for hydrometeor classes, allowing heat storage and mixed phase hydrometeors; partitioning hydrometeors into seven classes (including separate graupel and hail categories); the use of stochastic collection rather than continuous accretion approximations and extension of the ice nucleation scheme to include homogeneous nucleation of ice from haze particles and cloud droplets.The versatility and credibility of the new scheme is explored, using sensitivity experiments for a simple two-dimensional convective cloud simulation.     

NUMERICAL SIMULATION OF ACIDIFICATION PROCESSES IN COLD CUMULUS CLOUDS

In this paper, a 1-D time dependent cold cumulus chemistry model is presented. In the coldcumulus model, 4 categories of hydrometeors: cloud drops, raindrops, cloud ice crystals, graupelparticles, and 18 microphysical interactions are considered, In the chemical model, the source andsink terms for pollutants include: the complicated interactions between pollutants (gases andaerosol particles) and the hydrometeors (especially ice crystals and graupel particles), the ex-changes of chemical compounds between two hydrometeors accompanying microphysical processesand the aqueous oxidations of S (IV) to S (VI). The two models are combined to study the acidifi-cation processes in cold cumulus clouds.     

A Comparison of Two Bulk Microphysics Parameterizations for the Study of Aerosol Impacts on an Idealized Supercell

Idealized supercell storms are simulated with two aerosol-aware bulk microphysics schemes(BMSs),the Thompson and the Chen-Liu-Reisner(CLR),using the Weather Research and Forecast(WRF)model.The objective of this study is to investigate the parameterizations of aerosol effects on cloud and precipitation characteristics and assess the necessity of introducing aerosols into a weather prediction model at fine grid resolution.The results show that aerosols play a decisive role in the composition of clouds in terms of the mixing ratios and number concentrations of liquid and ice hydrometeors in an intense supercell storm.The storm consists of a large amount of cloud water and snow in the polluted environment,but a large amount of rainwater and graupel instead in the clean environment.The total precipitation and rain intensity are suppressed in the CLR scheme more than in the Thompson scheme in the first three hours of storm simulations.The critical processes explaining the differences are the auto-conversion rate in the warm-rain process at the beginning of storm intensification and the low-level cooling induced by large ice hydrometeors.The cloud condensation nuclei(CCN)activation and auto-conversion processes of the two schemes exhibit considerable differences,indicating the inherent uncertainty of the parameterized aerosol effects among different BMSs.Beyond the aerosol effects,the fall speed characteristics of graupel in the two schemes play an important role in the storm dynamics and precipitation via low-level cooling.The rapid intensification of storms simulated with the Thompson scheme is attributed to the production of hail-like graupel.     

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.     

台风眼壁的云结构与降水形成机制分析

使用带有详细微物理过程的ARPS模式,对台风韦帕（Wipha）进行三重嵌套细网格模拟,利用模式结果,对台风眼壁强降水中心的云结构和降水形成机制进行分析,结果表明：冰相微物理过程是启动和形成台风眼壁暴雨的主要降水形成机制。在9000～14000 m高空,云水在很低的温度下经均质核化产生冰晶,或经非均质核化形成云冰;冰晶通过凝华增长（psfi,贝吉龙过程）、雨水收集云冰产生雪（praci）和冰晶粘附雨水成雪（piacr）过程生长为雪;霰产生主要包括4个过程：冰晶接触雨水使其成霰（piacr）、雪撞冻云水使其成霰（psacr）、雨水收集云冰转化成霰（praci）或雨水冻结为霰（pgfr）;霰粒子通过收集云冰干增长（dgaci）,霰撞冻云滴增长（dgacw）等过程生长;霰融化（pgmlt）和雪融化（psmlt）成雨水后再通过碰并云水等暖云生长过程,最后形成雨水。霰过程的强弱在雨水形成机制中很重要。（29.5°N、121.8°E）和（28.3°N、120.4°E）强降水中心冰晶转化率没有太大差别,但是（29.5°N、121.8°E）强降水中心上空冰晶通过贝吉龙过程快速成长为雪和霰,霰粒子增长过程远远强于（28.3°N、120.4°E）强降水中心,低空又有较高的云水转化率,使降水粒子在暖云中继续快速生长,冷暖云过程的有利配置使（29.5°N、121.8°E）出现较强雨水转化率。