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1.
With the Reisner-2 bulk microphysical parameterization of the fifth-generation Pennsylvania State University–U.S. National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5), this paper investigates the microphysical sensitivities of Typhoon Chanchu. Four different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating intensity forecasts and microphysics budgets of the typhoon. The set of sensitivity experiments were conducted ... 相似文献
2.
东北冷涡中尺度云系降水机制研究 II: 数值模拟 总被引：1，自引：1，他引：0
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. 相似文献
3.
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。 相似文献
4.
X. Li 《Meteorology and Atmospheric Physics》2006,94(1-4):87-102
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. 相似文献
5.
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 总被引：2，自引：1，他引：1
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%). 相似文献
6.
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. 相似文献
7.
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. 相似文献
8.
将DeMott冰核浓度参数化方案引入到WRF中尺度数值模式中,模拟了新疆阿克苏地区一次多单体型强对流风暴,并对背景大气条件和沙尘条件下气溶胶作为冰核,对云中微物理结构和降水变化的影响进行了敏感性试验和对比分析,结果显示:在背景大气条件和沙尘条件下增加冰核浓度对降水中心强度影响较小,并且总体上看降水分布变化不大,但是降水局部的变化量较明显;不同背景条件下IN（Ice Nuclei）浓度的增加使得冰晶和雪的质量混合比和数浓度均有较大幅度的增加,其中雪的主要源项为凝华增长过程,而霰增长主要来源于冰相粒子碰并过冷云滴,并且在背景大气和沙尘条件下增加IN都使得霰的数浓度增加,尺度减少。 相似文献
9.
利用GRAPES模式研究气溶胶对云和降水过程的影响 总被引：5，自引：3，他引：2
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。 相似文献
10.
应用MM5中尺度模式,选用4种不同云微物理方案(Dudhia简单冰相方案、Reisner混合相方案、Reisner2霰方案和Schultz微物理方案),对2002年7月12-13日祁连山区降水过程进行了数值模拟试验。模拟结果的对比分析表明,不同云微物理方案在祁连山区降水的模拟中对降水落区的模拟均偏南;除Reisner2霰方案外,其他3种方案对降水中心落点的模拟影响不大,降水中心强度对云微物理方案不敏感;显式降水和参数化降水对云微物理方案有不同程度的依赖性;云微物理过程通过影响动力条件发生发展的时间和强度,来影响强降水发生的时间和强度。通过各云微物理参数的分析发现,各物理过程中微物理参数参与降水的过程不同:对Dudhia简单冰相方案来说,雨水和云水是形成降水的主要过程;Reisner混合相方案中降水的形成主要是由于雨水、云水、雪和霰的碰并过程,冰晶的碰并相对较弱;在Reisner2霰方案中,雨水、云水、冰晶、雪和霰均参与碰并碰冻过程;Schultz微物理方案中冰晶、雪和霰的碰并过程更为重要。 相似文献
11.
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。 相似文献
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13.
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. 相似文献
14.
NUMERICAL SIMULATION OF MICROPHYSICAL PROCESSES IN CUMULONIMBUS——PART Ⅰ:MICROPHYSICAL MODEL 
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下载免费PDF全文 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. 相似文献
15.
过冷雨水低含量条件下冰雹形成和增长机制及其催化效果的数值模拟 总被引：11，自引：5，他引：11
利用中国科学院大气物理研究所开发的三维全弹性冰雹云模式，对美国对流降水协作试验（CCOPE）期间观测的1981年8月1日雹云进行模拟，讨论在过冷雨水低含量条件下冰雹形成和增长机制及其碘化银催化效果。结果表明:(1) 自然云的模拟与观测事实一致，如最大上升气流速度、云顶高度、流场结构以及雹胚组成等。(2) 雹胚以霰为主，霰主要来自冰雪晶与过冷小水滴的碰冻，其次来自雪的积聚转化；霰、冻滴和冰雹在形成后主要靠碰并过冷云水增长。(3)人工催化试验表明，碘化银主要以凝华核（包括凝结－冻结）的作用产生大量的人工冰晶，加速了过冷水向冰晶的转化，过冷云水因而大量减少；催化后霰和冻滴的数浓度增大，对过冷云水的竞争增强，其平均尺度减小导致转化成雹的数量减少；冰雹碰冻过冷云水的增长在催化后也被削弱，导致冰雹总质量进一步减少。此外，催化后降雨量也显著减少。 相似文献
16.
一次飑线过程的云微物理参数化方案数值试验及其成因分析 总被引：2，自引：1，他引：1
利用WRF模式6种适合高分辨率且包含多种固态水成物粒子的云微物理参数化方案,分别对2012年5月16日江苏北部一次飑线过程进行数值试验,结果表明:LIN方案模拟的飑线回波反射率、强降水TS评分、结构和强度等均要优于其余5种微物理参数化方案。分析不同参数化试验结果中不同水成物粒子占比随时间的变化特征,并针对LIN方案采取敏感性试验和水成物转化微物理过程分析指出,在此次飑线过程中的各水成物粒子中,霰/雹粒子占比最大,是降水过程中最重要的粒子;地面降水直接来源是雨水,雨水主要来源于中层霰/雹粒子的融化,小部分来源于云水的自动转化;中层霰/雹粒子最主要来源是通过雨霰转化过程中的雨水撞冻冰雹微物理过程,其次是霰撞冻云水的微物理过程,而冰相物质雪晶和云冰的碰并、撞冻和自动转化过程微乎其微。 相似文献
17.
利用WRF模式中三种云微物理参数化方案(Lin、Eta和WSM6)对青藏高原一次强降水过程进行模拟试验,将模拟降水结果与实测资料进行对比,以评估不同云微物理参数化方案对该区域降水过程的模拟性能。结果表明:三种方案均能够模拟出此次降水天气过程的发生,但在主要降水区域和降水强度两方面仍与实测资料存在偏差;在水凝物方面,三种方案对冰粒子的模拟较接近,Lin和WSM6方案模拟的雪粒子差异较大,但霰粒子无明显差异。进一步对比分析了Lin和WSM6方案模拟的云微物理转化过程,结果表明:这两种方案都表现出了霰向雨水转化的特点。在Lin方案中,通过水汽向霰粒子凝华、霰碰并水汽凝华生成的雪粒子以及霰碰并云水这三种过程生成的霰粒子最终融化为雨水。而在WSM6方案中,一方面水汽凝结成云水,云水被雪和霰粒子碰并收集转化为霰,之后霰融化为雨水;另一方面水汽凝华为冰粒子,一部分冰转化为雪,雪直接融化为雨水或转化为霰融化为雨水,另一部分冰转化为霰,霰融化为雨水。 相似文献
18.
A Simulation Study on the Characteristics of Cloud Microphysics of
Heavy Rainfall in the Meiyu Front 下载免费PDF全文
下载免费PDF全文 A heavy rainfall in the Meiyu front during 4--5 July 2003 is simulated by use of the non-hydrostatic mesoscale model MM5 (V3--6) with different explicit cloud microphysical parameterization schemes. The characteristics of microphysical process of convective cloud are studied by the model outputs. The
simulation study reveals that: (1) The mesoscale model MM5 with explicit cloud microphysical process is capable of simulating the instant heavy rainfall in the Meiyu front, the rainfall simulation
could be improved significantly as the model resolution is increased, and the Goddard scheme is better than the Reisner or Schultz scheme. (2) The convective cloud in the Meiyu front has a
comprehensive structure composed of solid, liquid and vapor phases of water, the mass density of water vapor is the largest one in the cloud; the next one is graupel, while those of ice, snow, rain
water and the cloud water are almost same. The height at which mass density peaks for different hydrometeors is almost unchangeable during the heavy rainfall period. The mass density variation of rain water, ice, and graupel are consistent with that of ground precipitation, while that of water vapor in the low levels is 1--2 h earlier than the precipitation. (3) The main contribution to the water vapor budget in the atmosphere is the convergence of vapor flux through advection and convection, which provides the main vapor source of the rainfall. Besides the basic process of the auto-conversion of cloud water to rain water, there is an additional cloud microphysical process that is essential to the formation of instant heavy rainfall, the ice-phase crystals are transformed into graupels first and then the increased graupels mix with cloud water and accelerates the conversion of cloud water to rain water. The positive feedback mechanism between latent heat release and convection is the main cause to maintain and develop the heavy precipitation. 相似文献
19.
华北一次暴雨过程中潜热对中尺度系统和降水影响的数值研究 总被引：2，自引：0，他引：2
针对2005年7月22日的发生于华北的暴雨中尺度对流系统,在用中尺度ARPS模式数值模拟和分析云场、动力场以及微物理过程释放的潜热垂直分布和作用特征的基础上,通过改变主要微物理过程潜热做敏感性数值试验,研究和分析了潜热对云系发展演变、云系宏观动力场、水汽场、云场和降水的影响,总结出云暖区潜热的影响途径。结果表明,在对流云团中,5000 m以上微物理过程起加热作用,以下起冷却作用。不同物理过程潜热加热的云层高度不同:高层起加热作用的主要为水汽凝结、云冰初生和雪凝华增长、霰撞冻云水过程;中层起加热/冷却作用的主要为水汽凝结、霰/雹融化过程;低层雨水的蒸发过程起冷却作用。微物理过程潜热通过影响云系和降水发展过程、云系动力场,进而影响水汽场、云场和降水。忽略霰/雹融化潜热,相当于增加云系暖区潜热,促进了低层气旋性环流的形成,增强了低层动力场的辐合,使得低层辐合区增多、增强;中低层水汽通量辐合区增多、面积扩大,明显地促进了对流云系的发展,增大了含水量和覆盖范围,云系的降水量显著增加,强降水区覆盖范围扩大。即使减少20%的凝结潜热,云系的发展也受到极大抑制,没有气旋性环流生成,低层辐合区缩小、强度降低,水汽通量辐合区也同样缩小、强度降低,云系对流发展减弱、含水量降低,因此,降水量大为减小,降水范围也显著缩小。此外,微物理过程潜热还影响到此次中尺度对流系统发展演变过程,改变了云系的形态、影响到系统的移动和系统中对流云团的发展强度和分布情况。 相似文献
20.
W. S. Lin C.-H. Sui C. Bueh A. Wang S. Fan C. Wu S. Fong J. Li J. Meng 《Meteorology and Atmospheric Physics》2007,95(3-4):195-204
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. 相似文献