东北冷涡中尺度云系降水机制研究 II: 数值模拟

在利用卫星、雷达和机载PMS(粒子测量系统)等观测资料对2003年7月8日东北冷涡积层混合云系的降水形成机制分析的基础上,将观测分析与数值模拟研究相结合,用中尺度数值模式对积层混合云系做数值模拟,并结合观测资料进一步分析了积层混合云系的微物理结构、粒子形成过程和降水形成机制,获得如下结果:(1)混合云中对流云具有分层的微物理结构.冰晶含水量最大值出现的高度最高,其次由高到低的排序是雪、云水、霰和雨;雨水主要出现在云的暖区;各种粒子中以雨水含水量最高,其次是霰.对流云体生命期较长,微物理结构基本稳定.(2)粒子形成增长过程有差异.冰晶通过凝华过程增长.雪主要来源于冰晶,产生后主要通过撞冻、收集冰晶和凝华过程增长,其中撞冻过冷云水增长对雪质量贡献最大,其产生率极大值高度与过冷云水相当.丰富的过冷云水,给雪的撞冻增长提供了有利条件.在高、中和低层雪的形成有着不同的机制,高层雪收集冰晶长大后,下落到低层又以雪撞冻过冷云水的结淞增长为主要过程.霰主要由雨滴冻结和雪的转化产生,过冷雨滴与冰晶接触冻结成霰;过冷雨滴收集雪,雪随着雨滴的冻结而转化成霰.因此霰的产生与过冷雨滴关系极大.霰主要撞冻云水、收集雪和冰晶增长,其中撞冻是霰的重要增长过程.雨水主要由霰的融化形成,降水主要是由冷云过程产生的.在过冷层,霰撞冻增长占优势.云上部的冰晶和雪对云的中部具有播撒作用,过冷层中存在丰富的过冷水,对冰相粒子的撞冻增长有利.对云水消耗的分析表明,雨滴对云滴的收集、霰和雪对云水的撞冻增长是消耗云水的主要过程.(3)从各种粒子的形成和增长过程可以看出,大部分雨水由霰融化形成,暖云过程贡献要小得多.可见,降水主要是由冷云过程产生的,这与观测分析的结果一致.     

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.     

冻滴微物理过程的分档数值模拟试验研究

霰和冻滴是深对流降水的主要来源。由于二者密度差异造成的不同下落末速度必然会导致云微物理过程的变化以及降水时空分布的改变。我们在以色列特拉维夫大学二维轴对称对流云全分档模式的基础上,将水成物粒子从34档增加到40档,修改了霰和雪的密度,加入冻滴分档处理的微物理过程,发展了一个包括液滴、冰晶、雪、霰和冻滴更为详细的云微物理分档模式。利用改进后的模式模拟了一次理想的强对流天气过程,分析了改进模式与原模式模拟的云微物理量场以及水成物粒子的时空分布特征,模拟结果表明:（1）由于冻滴的产生,较大的下落末速度导致在云内-3℃至-8℃较早地出现了冻滴,并造成了大量的冰晶繁生。（2）冻滴形成前期,液态水中心区域位于垂直上升速度大值中心上方,形成液态水累积区;冻滴形成期,液态水累积区位于0℃层以上,雨滴冻结生成冻滴,霰与半径大于100 μm的液滴碰并生成冻滴;冻滴增长期,在垂直上升气流的支撑下,冻滴碰并过冷水增长,导致冻滴含量增大,液态水含量减小。因此,改进模式能较好的模拟冻滴的形成过程,可以将该分档处理的微物理方案耦合到三维WRF（Weather Research and Forecasting model）模式中,更深入地研究强雷暴风切变在冰雹生成过程中的作用。     

Numerical Simulation of Macro- and Micro-structures of Intense Convective Clouds with a Spectral Bin Microphysics Model

By use of a three-dimensional compressible non-hydrostatic convective cloud model with detailed microphysics featuring spectral bins of cloud condensation nuclei (CCN), liquid droplets, ice crystals, snow and graupel particles, the spatial and temporal distributions of hydrometeors in a supercell observed by the (Severe Thunderstorm Electrification and Precipitation Study) STEPS triple-radar network are simulated and analyzed. The bin model is also employed to study the effect of CCN concentration on the evolution characteristics of the supercell. It is found that the CCN concentration not only affects the concentration and spectral distribution of water droplets, but also influences the characteristics of ice crystals and graupel particles. With a larger number of CCN, more water droplets and ice crystals are produced and the growth of graupel is restrained. With a small quantity of CCN the production of large size water droplets are promoted by initially small concentrations of water droplets and ice crystals, leading to earlier formation of small size graupel and restraining the recycling growth of graupel, and thus inhibiting the formation of large size graupel (or small size hail). It can be concluded that both the macroscopic airflow and microphysical processes influence the formation and growth of large size graupel (or small size hail). In regions with heavy pollution, a high concentration of CCN may restrain the formation of graupel and hail, and in extremely clean regions, excessively low concentrations of CCN may also limit the formation of large size graupel (hail).     

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。     

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.     

基于飞机观测的华北积层混合云降水微物理特征的数值模拟研究

基于2009年5月1日积层混合云降水2架飞机观测数据分析,使用中尺度模式WRFV3对此次过程积云区和层云区的微物理特征和转化过程进行数值模拟比较研究。飞机观测数据分析表明,此次积层混合云中的层云区和积云区冰粒子形状和形成过程有明显差别,层云区的粒子形状组成比较复杂,包含针状、柱状和辐枝状等,而积云区主要以辐枝状粒子为主,聚并、凇附过程明显。数值模式能较好地模拟出此次积层混合云降水过程的基本特征,包括回波分布、飞行路径上降水粒子的数浓度和液态水含量等。数值模拟结果表明,云水相对丰富、上升气流强的层云区凇附过程较强,产生的雪在低层融化为雨水,为后期高层形成的雪和霰提供丰富的液态水,能发展成对流较强的积云区,存在播种—供给机制。在积云区,水成物的比例从大到小依次为雪（51.9%）、霰（31.0%）和雨水（16.0%）;雪的主要源项包括淞附增长（56.8%）和凝华增长（40.1%）,霰的主要源项包括凇附增长（46.6%）、雨水碰并雪成霰（42.6%）和凝华增长（16.1%）,雨水的主要源项是霰（77.6%）和雪（22.4%）的融化。而相对云水较少、上升气流较弱的层云区将保持层云的状态,层云区水成物的比例从大到小依次为雪（90.4%）、雨水（6.1%）、冰晶（3.5%）;高层冰晶和雪通过凝华过程增长,雪在零度层下融化为弱的降水。     

Idealized simulation of the Colorado hailstorm case: comparison of bulk and detailed microphysics

One of the purposes of the Fourth Cloud Modeling Workshop was to compare different microphysical treatments. In this paper, the results of a widely used bulk treatment and five versions of a detailed microphysical model are presented. Sensitivity analysis was made to investigate the effect of bulk parametrization, ice initiation technique, CCN concentration and collision efficiency of rimed ice crystal–drop collision. The results show that: (i) The mixing ratios of different species of hydrometeors calculated by bulk and one of the detailed models show some similarity. However, the processes of hail/graupel formation are different in the bulk and the detailed models. (ii) Using different ice initiation in the detailed models' different processes became important in the hail and graupel formation. (iii) In the case of higher CCN concentration, the mixing ratio of liquid water, hail and graupel were more sensitive to the value of collision efficiency of rimed ice crystal–drop collision. (iv) The Bergeron–Findeisen process does not work in the updraft core of a convective cloud. The vapor content was always over water saturation; moreover, the supersaturation gradually increased after the appearance of precipitation ice particles.     

CAMS复杂云微物理方案与GRAPES模式耦合的数值试验

CAMS复杂云微物理方案是混合相双参数方案, 包括11个云物理变量和31个云物理过程, 能够同时预报水成物的比质量和数浓度。通过在GRAPES非静力中尺度模式中增加预报量并修改相关程序后, 实现了二者的耦合, 耦合后模式运行稳定。选取2005年8月15—17日我国华北地区一次暴雨过程, 利用耦合后的模式进行48 h模拟试验, 同时还选取了GRAPES模式中其他3个比较复杂的微物理方案进行模拟, 着重分析了降水和水成物分布的模拟结果。研究结果表明: CAMS方案能够模拟出与实测相接近的雨带分布特征, 并且对降水演变的模拟结果与其他方案比较一致, 对暴雨中心位置的模拟有待改进。CAMS方案模拟的水成物垂直分布与其他方案相比具有相似的总体特征, 各相态粒子的量级和分布合理, 不同方案的结果在量值上有所差别。个例分析结果显示出CAMS方案对降水和水成物的分布能够合理描述。今后应通过更多个例进行更为精细的模拟试验, 对新方案进行检验。     

区域冷锋降水微物理机制研究

20世纪利用一维层状云模式对2002年4月4~5日河南省冷锋降水过程进行了模拟。数值模拟结果显示,此次冷锋降水属于冷云降水过程,冷锋前后云中主要以冰相粒子为主,云中水质粒自上而下的空间分布依次为冰晶、雪、云水、霰、雨水。冷锋前后,各种水质粒有着不同的含量及数密度,但形成水质粒的主要微物理过程都表现为:冰晶数密度的增加主要依靠核化、繁生,大部分雪主要靠凝华、撞冻过冷云水和冰晶增长,霰的质量增加主要靠撞冻雪、过冷云水和雪自动转化而来,大部分的雨水是由霰融化而来,因而此次冷锋降水机制表现为“水汽—雪—霰—雨水”。     

2014年夏季青藏高原云和降水微物理特征的数值模拟研究

为了加强对青藏高原（高原）云和降水微物理特征的深入认识,采用高分辨率中尺度数值预报模式（WRF）,对第三次青藏高原大气科学试验2014年7月3-25日发生的6次不同强度云和降水过程进行了数值模拟分析。研究结果表明:（1）青藏高原夏季云和降水过程具有独特性。高原夏季对流的促发机制主要是午后高原加热造成的,云和降水具有明显的日变化。午夜后,对流性降水一般转化为层状云降水,具有明显的0℃层回波亮带,并且会产生强降水。大部分对流云云顶高度超过15 km（海拔高度）,最大上升气流速度为10-40 m/s。（2）6次云过程中均具有高过冷云水含量,主要分布在0—-20℃层,冰晶含量主要分布在-20℃层以上的区域,强盛的对流云中,可出现在-40℃层以上区域;雨水集中分布在融化层之下,说明其主要依赖降水性冰粒子的融化过程;雪和霰粒子含量高,分布范围广,说明云中冰相过程非常活跃。（3）高原夏季云中水凝物的转化过程和降水的形成机理具有明显特点。霰粒子的融化过程是地面雨水的主要来源,暖雨过程对降水的直接贡献很小,但通过暖雨过程形成的过冷雨滴的异质冻结过程对云中霰胚的形成十分重要。霰粒子的增长主要依靠凇附过程以及聚并雪晶的增长过程。      

利用GRAPES模式研究气溶胶对云和降水过程的影响

在GRAPES中尺度模式的双参数微物理方案中加入了气溶胶活化参数化过程,实现了对云滴数浓度的预报。选取不同季节两个降水过程进行模拟,并分别开展了不同气溶胶背景下的两个试验进行对比分析,研究气溶胶对云和降水可能的影响。结果表明:气溶胶浓度增加后,因为活化产生了更多尺度较小的云滴,抑制了云雨的自动转化,使大气中滞留了更多的云水,暖云降水减小;另一方面,云水的增加会使冰相粒子,尤其是雪和霰通过碰并云水等过程而增大,最后融化成雨增加冷云降水,同时冰相粒子增加会释放更多的潜热,促进上升气流的发展,进一步增加冷云降水。气溶胶对降水的影响存在空间不一致性,暖云较厚的地方暖雨过程受到的抑制明显,使地面降水减小,冷云厚度相对较厚时,冷云降水的增加会大于暖云降水的抑制,使地面降水增加。同时由于在云降水发展的不同阶段冷暖云的变化,气溶胶对降水的影响也存在着时间不一致性。     

NUMERICAL SIMULATION OF MICROPHYSICAL PROCESSES IN CUMULONIMBUS——PART Ⅰ:MICROPHYSICAL MODEL

A comprehensive parameterized model of microphysical processes in cumulonimbus clouds is presented.The transformation rates of the water contents and number concentrations of the cloud droplets,rain drops,ice crystals,graupels and hails are deduced on theoretical and experimental results for 26 kinds of micro-physical processes,which include condensation,deposition,evaporation,collection,ice nucleation,ice mul-tiplication,melting,freezing,and autoconversions of cloud to rain,ice to graupel and graupel to hail.     

冰晶异质核化对雷暴云电过程影响的数值模拟

引入一种新型冰晶异质核化方案, 基于二维雷暴云模式, 探讨雷暴云电过程对三种异质核化的响应。结果表明: 浸润核化是冰晶生成的最重要异质核化过程, 较高数浓度的冰晶消耗雷暴云内液态水含量, 抑制淞附过程, 导致霰粒子比含水量低, 表现为较强的负极性非感应起电率; 接触核化生成的冰晶量最少, 仅对雷暴云中下层3~5 km处的冰晶有贡献, 同时霰粒子数浓度较低, 导致该方案下的起电过程最弱; 沉积核化主要影响云砧处的冰晶, 有利于提高霰收集云滴的效率, 表现为极高的霰比含水量, 促进低温区非感应起电过程的发生。总体上来看, 三个方案下的电荷结构均由较复杂的多极性发展为偶极性。其中浸润方案中主正电荷区的抬升最明显, 而接触方案过低的冰晶分布高度与沉积方案过高的冰晶分布高度, 都直接导致了次正电荷区更快消散。      

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.     

青海省秋季一次对流云人工增雨的数值模拟

利用中国气象科学研究院的三维对流云数值模式，模拟了青海省2002年秋季一次对流云过程，分析了青海省秋季对流云云体发展的动力学特点和微物理特征。数值模拟结果表明，青海省秋季的对流云降水几乎全部是由霰的融化形成的，而自然云中冰晶含量少、冰霰自动转化形成霰胚的过程非常微弱。但采用合适的方法催化以后，冰晶的核化、繁生量增加，通过冰霰自动转化过程形成大量霰胚，霰胚再通过其他冷云微物理过程迅速增长，融化成降水。催化后各种微物理机制都比催化前活跃，同时催化改变了云体的动力场分布，在动力过程和微物理过程的相互促进下，使增雨取得了很好的效果。     

三维强风暴动力-电耦合数值模拟研究Ⅰ:模式及其电过程参数化方案

为了研究风暴中的动力、微物理和电过程三者间的相互作用 ,在已有的工作基础上 ,建立了一个三维强风暴动力 电耦合数值模式。模式中将云中水物质分为水汽、云水、雨水、冰晶、雪、霰和雹 7类 ,各种粒子采用双变参数谱。考虑了详细的起电过程 ,它们包括扩散、电导、感应和非感应以及次生冰晶起电机制。此外 ,在模式中加入了云内放电参数化过程和云顶处屏蔽电荷层形成的参数化方案用以研究整个雷暴生命史内的电活动特征。最后利用CCOPE(CooperativeConvectivePrecipitationExperiment)计划中 1981年 7月 19日的风暴资料对模式的性能进行了验证 ,模拟结果显示此模式可以较好地描述风暴中动力、微物理和电结构的发展演变过程。     

Dominant cloud microphysical processes of a torrential rainfall event in Sichuan,China

High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting (WRF) Model were used to study the dominant cloud microphysical processes of the torrential rainfall. The results showed that: (1) In the strong precipitation period, particle sizes of all hydrometeors increased, and mean-mass diameters of graupel increased the most significantly, as compared with those in the weak precipitation period; (2) The terminal velocity of raindrops was the strongest among all hydrometeors, followed by graupel’s, which was much smaller than that of raindrops. Differences between various hydrometeors’ terminal velocities in the strong precipitation period were larger than those in the weak precipitation period, which favored relative motion, collection interaction and transformation between the particles. Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity, and the stronger the precipitation was, the greater the differences between them were; (3) The orders of magnitudes of the various hydrometeors’ sources and sinks in the strong precipitation period were larger than those in the weak precipitation period, causing a difference in the intensity of precipitation. Water vapor, cloud water, raindrops, graupel and their exchange processes played a major role in the production of the torrential rainfall, and there were two main processes via which raindrops were generated: abundant water vapor condensed into cloud water and, on the one hand, accretion of cloud water by rain water formed rain water, while on the other hand, accretion of cloud water by graupel formed graupel, and then the melting of graupel formed rain water.     

Cloud microphysical and precipitation responses to a large-scale forcing in the tropical deep convective regime

Summary Cloud microphysical and precipitation responses to a large-scale forcing in the tropical deep convective regime are investigated based on hourly zonally-averaged, vertically-integrated simulation data from a two-dimensional coupled ocean-cloud resolving atmosphere model. The model is forced by the large-scale vertical velocity and zonal wind observed and derived from TOGA COARE for a 50-day period. The accretion of cloud water by graupel induces growth of graupel that enhances raindrops through its melting during a weak-forcing period, whereas the large deposition rate of vapor associated with a large upper-tropospheric upward motion causes growth of snow from the conversion of cloud ice and enhancement of graupel from the accretion of snow during a strong-forcing period. The local changes of raindrops and graupel switch from the negative to positive values as the forcing strengthens in the weak-forcing case, whereas the variations of cloud hydrometeors are not sensitive to the strength of the forcing in the strong-forcing case. Phase analysis indicates that cloud water leads the surface rain rate by 1 hour. The surface rain rate can be calculated based on the conservation of vapor and cloud hydrometeors and the budget of raindrops. The vapor source and local changes of cloud hydrometeors could have impacts in the calculation of the surface rain rate. The vapor source determines the surface rain rate in the strong-forcing case whereas the cloud variations could become important in the weak-forcing case. In the budget of raindrops, the sum of the collection of cloud water by raindrops, the melting of graupel, and the evaporation of raindrops determines the surface rain rate in the strong-forcing case whereas the other rain-related microphysical processes become important in the weak-forcing case.