A process oriented characterization of tropical oceanic clouds for climate model evaluation, based on a statistical analysis of daytime A-train observations

This paper aims at characterizing how different key cloud properties (cloud fraction, cloud vertical distribution, cloud reflectance, a surrogate of the cloud optical depth) vary as a function of the others over the tropical oceans. The correlations between the different cloud properties are built from 2?years of collocated A-train observations (CALIPSO-GOCCP and MODIS) at a scale close to cloud processes; it results in a characterization of the physical processes in tropical clouds, that can be used to better understand cloud behaviors, and constitute a powerful tool to develop and evaluate cloud parameterizations in climate models. First, we examine a case study of shallow cumulus cloud observed simultaneously by the two sensors (CALIPSO, MODIS), and develop a methodology that allows to build global scale statistics by keeping the separation between clear and cloudy areas at the pixel level (250, 330?m). Then we build statistical instantaneous relationships between the cloud cover, the cloud vertical distribution and the cloud reflectance. The vertical cloud distribution indicates that the optically thin clouds (optical thickness <1.5) dominate the boundary layer over the trade wind regions. Optically thick clouds (optical thickness >3.4) are composed of high and mid-level clouds associated with deep convection along the ITCZ and SPCZ and over the warm pool, and by stratocumulus low level clouds located along the East coast of tropical oceans. The cloud properties are analyzed as a function of the large scale circulation regime. Optically thick high clouds are dominant in convective regions (CF?>?80?%), while low level clouds with low optical thickness (<3.5) are present in regimes of subsidence but in convective regimes as well, associated principally to low cloud fractions (CF?<?50?%). A focus on low-level clouds allows us to quantify how the cloud optical depth increases with cloud top altitude and with cloud fraction.     

青藏高原那曲地区一次深对流云垂直结构的多源卫星和地基雷达观测对比分析

为了加强对青藏高原深对流云垂直结构的深入认识,利用TRMM、CloudSat和Aqua多源卫星观测资料及地基垂直指向雷达（C波段调频连续波雷达和KA波段毫米波云雷达）资料,对第三次青藏高原大气科学试验期间2014年7月9日13-16时（北京时）发生在那曲气象站附近的深厚强对流云和那曲气象站以西100 km左右的深厚弱对流云的垂直结构特征进行了分析,得到的结果如下:（1）深厚强对流云和深厚弱对流云的水平尺度均较小（10-20 km）,垂直发展高度较高（15-16 km,均指海拔高度）;深厚强对流云在0℃层以下雷达反射率因子递增非常快,表明对流云内固态降水粒子下落至0℃层以下后融化过程有很重要的作用;在对流减弱阶段有明显的0℃层亮带出现,亮带位于5.5 km左右（距地1 km）;（2）对比TRMM测雨雷达和C波段调频连续波雷达观测到的雷达反射率因子,发现TRMM测雨雷达在11 km以下存在高估;（3）深对流云主要为冰相云,云内10 km以上主要是丰富小冰粒子,而10 km以下是较少的大冰晶粒子;深厚强对流云和深厚弱对流云的微物理过程都主要包括混合相过程和冰化过程,混合相过程分为两种:一种是-25℃（深厚强对流云）或-29℃（深厚弱对流云）高度以下以凇附增长为主,另一种是该高度以上主要以冰晶聚合、凝华增长为主,该过程冰晶粒子有效半径增长较快。这些空基和地基的观测证据进一步揭示了青藏高原深对流云的垂直结构特征,为模式模拟青藏高原深对流云的检验提供了依据。      

新疆降雹云团的特征分析

普查1998－2001年4－8月的资料，得到全疆438个降雹云团。2000年降雹云团出现最多，按尺度大小将降雹云团分为雷暴云、对流云、中尺度对流系统、冷云核、系统云系云区有云团边缘6类。强以流云团是冰雹云的主体。新疆降雹云团尺度小、形状不规则、云顶温度较高。     

CloudSat/CALIPSO卫星资料分析云的全球分布及其季节变化特征

全球气候模式（GCM）中云的参数化方案具有不确定性,了解云的时、空变化能为参数化方案提供有效参考。利用搭载在属于A-Train卫星序列的CloudSat和CALIPSO上的94 GHz云廓线雷达（CPR）以及正交极化云-气溶胶激光雷达（CALIOP）联合的2级云分类产品,分析了2007年3月-2010年2月8种云类及三相态的云量地理分布、纬向垂直分布的季节变化特征以及云层分布概率。结果发现,卷云的分布体系与深对流云相似,主要集中在西太平洋暖池、全球各季风区及赤道辐合带,分布格局与气压带、风带季节性移动一致。层云与层积云主要分布在中低纬度非季风区以及中高纬度的洋面上。高积云与高层云的分布形成明显的海陆差异,雨层云与积云的分布形成明显的纬度差异。冰云分布与卷云相似,云高随纬度递增而递减;水云分布与层积云相似,平均分布于2 km高度;混合云集中于高纬度地区及赤道辐合带,中纬度地区随纬度变化集中于海拔0-10 km的弧形带。层状云多以多层云形式出现,积状云多以单、双层云的形式出现,层状云的云重叠现象比积状云更显著。积状和层状云的分布特征与积云和层云降水的分布特征基本一致,验证了不同类型降水的卫星观测结果,同时为气候模式的云量诊断方案提供对比验证的数据。      

对流尺度数值预报中的云物理初始化方法改进及个例试验

通过在云初始化方案中增加由地表感热和潜热通量确定的对流尺度速度作为对流判据,同时增加层云云冰、云水计算方案,改进云分析方法,并基于第2代华东快速更新循环同化模式预报系统,针对2015年4月28日华东强对流个例,进行对比试验,分析了改进的云初始化方案对云分析结果和模式预报效果的影响。试验表明:在云分析中增加对流判据,使得平均40%左右的云分析格点判定为非对流格点,对流格点分布与正的感热通量分布相似,在陆地上有显著日变化。在对流和层云格点判定之后,增加层云云冰、云水计算方案分析层云格点,显著地减小了模式初始场的云冰、云水混合比,有效地减弱了模式积分初始阶段云冰、云水含量的剧烈调整,尤其是在陆地区域。采用改进的云初始化方案进行预报,可以减少模式前1 h和前6 h的降水强度;尤其在个例的循环试验中,强降水中心强度和面积的预报比原方案显著减弱。      

上海地区几类强降水雨滴谱特征分析

用Parsivel激光降水粒子谱仪资料对2013年上海地区4—10月份期间4种类型 (层状云、对流暖云主导型、对流冷云主导型和强台风影响下的混合暖云型) 降水过程的雨滴谱特征进行了分析。通过平均雨滴谱及其拟合特征、雨滴数密度与含水量分布、雨滴尺度与速度二维谱分布等对比分析发现:各类降水中, 雨滴谱的峰值结构与雨强大小有关, 其中直径介于0.187~1.312 mm的小雨滴均出现峰值且总数最多。各尺度雨滴数密度及其比例决定了其降水量贡献比, 在冷云强降水中的雨强贡献最大的雨滴尺度要显著大于其他3种类型。雨滴谱宽按大小排列依次为对流冷云主导型、混合暖云型、对流暖云主导型和层状云。最后综合运用雨滴谱、雷达、雨量站、闪电等观测资料对9月13日对流冷云主导型降水过程进行分析后发现:在雷暴的演变过程中, 雨滴谱特征与雷达反射率因子、垂直液态水含量、自动站雨强、闪电频次等要素均有较好的相关性。冷云产生的冰晶和冰雹融化后的大雨滴进入中低层的广谱小雨滴群, 并通过破碎分裂增加了大雨滴的形成概率, 尤其是捕捉碰并过程更加快了大雨滴的增长速度, 使雨强在短时间内迅速加强。雨滴谱中各档粒子数的演变, 揭示了降水强度的变化, 用雨滴谱资料可有效弥补现有雷达定量估测降水的偏差, 且在冷云中改善明显。     

Vertical Structures of Convective and Stratiform Clouds in Boreal Summer over the Tibetan Plateau and Its Neighboring Regions

Cloud is essential in the atmosphere, condensing water vapor and generating strong convective or large-scale persistent precipitation. In this work, the relationships between cloud vertical macro- or microphysical properties, radiative heating rate, and precipitation for convective and stratiform clouds in boreal summer over the Tibetan Plateau (TP) are analyzed and compared with its neighboring land and tropical oceans based on CloudSat/CALIPSO satellite measurements and TRMM precipitation data. The precipitation intensity caused by convective clouds is twofold stronger than that by stratiform clouds. The vertical macrophysics of both cloud types show similar features over the TP, with the region weakening the precipitation intensity and compressing the cloud vertical expansion and variation in cloud top height, but having an uplift effect on the average cloud top height. The vertical microphysics of both cloud types under conditions of no rain over the TP are characterized by lower-level ice water, ice particles with a relatively larger range of sizes, and a relatively lower occurrence of denser ice particles. The features are similar to other regions when precipitation enhances, but convective clouds gather denser and larger ice particles than stratiform clouds over the TP. The atmospheric shortwave (longwave) heating (cooling) rate strengthens with increased precipitation for both cloud types. The longwave cooling layer is thicker when the rainfall rate is less than 100 mm d^?1, but the net heating layer is typically compressed for the profiles of both cloud types over the TP. This study provides insights into the associations between clouds and precipitation, and an observational basis for improving the simulation of convective and stratiform clouds over the TP in climate models.     

基于CloudSat–CALIPSO资料的全球不同类型云的水平和垂直分布特征

基于Cloud Sat-CALIPSO(Cloud Sat–Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations)卫星观测资料,分析了全球总云量和8类云的云量、云底高、云顶高、云厚度的水平和垂直分布。分析结果表明,全球平均总云量为66.7%,其中卷云(Ci)和层积云(Sc)云量之和与其他6类云量总和相当,是全球云量最多的两类云。积状云云量呈现从赤道向极地递减的特征,层状云则相反,反映了二者不同的生成环境,同时下垫面地形和天气系统也严重影响云的分布。8类云的高度及厚度特征有显著差异。Ci的云底高度和云顶高度都较高,厚度则较薄;高层云(As)和高积云(Ac)的云底高度和云顶高度都位于大气中层,但As比Ac出现的高度高且厚度大;层云(St)、层积云和积云(Cu)的云底高度和云顶高度都很低,属于薄的低云;雨层云(Ns)和深对流云(DC)云底较低但云顶伸展很高,归属于厚云类。总体而言,海洋上云底高度较陆地低;赤道等大气不稳定地区,云底较高,云厚度较大;高原地区则表现出"高云不高,低云不低,云厚较薄"的特征。     

Effect of aerosol pollution on clouds and its dependence on precipitation intensity

In this study, simulations performed with a large-eddy resolving numerical model are used to examine the effect of aerosol on cumulus clouds, and how this effect varies with precipitation intensity. By systematically varying the surface moisture fluxes, the modeled precipitation rate is forced to change from weak to strong intensity. For each of these intensities, simulations of a high-aerosol case (a polluted case with a higher aerosol concentration) and a low-aerosol case (a clean case with a lower aerosol concentration) are performed. Whether or not precipitation and associated sub-cloud evaporation and convective available potential energy (CAPE) are large, liquid–water path (LWP) is larger in the high-aerosol case than in the low-aerosol case over the first two-thirds of the entire simulation period. In weak precipitation cases, reduction in aerosol content leads to changes in CAPE in the middle parts of cloud layers, which in turn induces larger LWP in the low-aerosol case over the last third of the simulation period. With strong precipitation, stronger stabilization of the sub-cloud layers in the low-aerosol case counters the CAPE changes in the middle parts of cloud layers, inducing smaller LWP in the low-aerosol case over the last third of the simulation period. The results highlight an interaction between aerosol effects on CAPE above cloud base and those in sub-cloud layers, and indicate the importance of a consideration of aerosol effects on CAPE above cloud base as well as those in sub-cloud layers. In the high-aerosol case, near the beginning of the simulation period, larger environmental CAPE does not necessarily lead to larger in-cloud CAPE and associated larger cloud intensity because aerosol-induced increase in cloud population enhances competition among clouds for the environmental CAPE. This demonstrates the importance of the consideration of cloud population for an improved parameterization of convective clouds in climate models.     

江淮地区孤立对流云统计特征

孤立对流云是江淮地区重要的降水云系,通过分析江淮地区2013—2016年6—9月的多普勒天气雷达数据,统计得到664个对流云,其中孤立对流云196个,占江淮地区对流云发生频率的29.5%,7月和8月是江淮地区孤立对流云的高发期,6月相对较少,9月最少,同时12:00（北京时,下同）—18:00是孤立对流云的高发时段,05:00—07:00孤立对流云发生频率最低。针对2013年7月20日安徽定远出现的孤立对流云个例,综合分析多普勒天气雷达和C波段连续波雷达探测资料,发现此次暖区孤立对流云内部强反射率因子中心交替生成,导致内部反射率因子呈强弱交替出现的波状结构,沿着移动方向由弱到强,降水粒子下落速度与之对应,降水粒子最大落速出现在孤立对流云中下部的强反射率因子区域,速度超过10 m·s-1。     

台风利奇马(1909)与台风摩羯(1814)云特征对比

利用FY-2H,Aqua,CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation)和GPM(Global Preciptation Measurement)卫星产品,对比同在浙江温岭沿海登陆且路径相似的台风利奇马(1909)和...     

一次极端降水的中尺度雨团分析

利用常规观测资料、ECMWF ERA-Interim 0.125°×0.125°分析资料、FY-2G卫星云图和多普勒天气雷达资料等,对2017年8月18-19日漯河极端降水的中尺度特征及降水成因进行分析。结果表明:(1)本次过程在200 hPa高空分流区、500 hPa高空槽以及副热带高压、低层急流切变、地面低压倒槽等天气尺度系统合理配置及其相互作用下发生。(2)探空显示漯河上空具有较高的对流潜势,有利于中尺度雨团初生和发展。低层饱和、厚暖云层、弱风切变有利于暴雨云团产生,高CAPE值、高比湿和高降水效率是极端雨团的重要原因。(3)中尺度对流云团一个随槽前西南气流东移北上,一个随低层切变线南压,相向合并发展为M_βCS,有利于暴雨云团增强。不同于以往本地区的云团"同向合并",持续的列车效应以及低质心高效率的中尺度对流单体后向传播导致强回波长时间维持,极端降水发展。(4)地面中尺度辐合线和强辐合中心对强降水起到动力触发作用,有利于对流发展。冷池出流与交汇北上的东南风和偏东风相互作用,导致水平温度梯度增大形成和冷池前侧锋生加强,一方面致使雨团组织化发展和单体后向传播,另一方面也在降水区下游触发新生雨团,冷池持续增强。(5)本次过程整层风场较弱,且低层气流传播速度大于引导气流速度,平移与传播方向的反向夹角大,导致两者矢量和大幅度偏离了引导气流方向,同时产生的减速效应导致暴雨中尺度系统移动缓慢,导致极端降水形成。     

HORIZONTAL AND VERTICAL DISTRIBUTIONS OF CLOUD COVER OVER EASTERN CHINA AND THE EAST CHINA SEA

Based on data from satellite and surface observations,the horizontal and vertical distributions of clouds over eastern China and the East China Sea are examined.Three maximum centers of cloud cover are clearly visible in the horizontal distribution of total cloud cover.Two of these maxima occur over land.As the clouds mainly originate from the climbing airflows in the southern and eastern slopes of the Tibetan Plateau,they can be classified as dynamic clouds.The third center of cloud cover is over the sea.As the clouds mainly form from the evaporation of the warm Kuroshio Current,they can be categorized as thermodynamic clouds.Although the movement of the cloud centers reflect the seasonal variation of the Asian summer monsoon,cloud fractions of six cloud types that are distinct from the total cloud cover show individual horizontal patterns and seasonal variations.In their vertical distribution,cloud cover over the land and sea exhibits different patterns in winter but similar patterns in summer.In cold seasons,limited by divergent westerlies in the middle troposphere,mid-level clouds prevail over the leeside of the Tibetan Plateau.At the same time,suppressed by strong downdraft of the western Pacific subtropical high,low clouds dominate over the ocean.In warm seasons both continental and marine clouds can penetrate upward into the upper troposphere because they are subject to similar unstable stratification conditions.     

青藏高原、东亚季风区、西北太平洋地区云系结构及相联加热机制的对比分析

应用7年(2006年5月18日—2013年5月18日)的CloudSat卫星观测资料,对比分析了青藏高原、东亚季风区、西北太平洋地区云发生频率的特征,并利用欧洲中心再分析资料,计算了三个地区的视热源、视水汽汇Q₁、Q₂,分析探讨了三个地区与云发生频率相联系的加热机制。结果表明:青藏高原、东亚季风区、西北太平洋地区云的发生频率分别为35%、22%、27%,其中:青藏高原和东亚季风区的低云频率最大,中云次之;西北太平洋地区的高云和低云的频率大,分别为19%和16%。具体云型来看,青藏高原多高层云、雨层云;东亚季风区多高层云和卷云,夏季深对流云频率增大明显;西北太平洋地区多卷云、深对流云和高层云。三个地区视水汽汇Q₂的垂直分布特征及季节变化与云发生频率对应较好,青藏高原的低云(雨层云)、中云(高层云)形成过程中,凝结释放潜热,加热大气;东亚季风区低云(深对流云)、中云(高层云)对加热大气贡献大;西北太平洋地区大气的主要加热机制是深对流云形成过程中凝结释放潜热以及湿静能涡旋垂直输送。      

台湾锋前暖区一次积云对流过程

用ＴＡＭＥＸ中尺度试验加密观测资料，研究影响台湾地区的一次梅雨锋前暖区强对流过程，利用积云群整体诊断模式，对积云对流物理过程以及云中参数进行估算，结果给出锋前对流云团与环境场相互作用的物理图像     

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。      

基于CloudSat/CALIPSO卫星资料的青藏高原云辐射及降水的研究进展

青藏高原上空的云及其相关联的降水和辐射影响了高原上空非绝热加热的空间结构。2006年卫星发射升空的CloudSat/CALIPSO卫星提供了定量的、完整的云垂直结构信息。本文回顾了国内外基于该资料进行的青藏高原上云宏观和微观结构特征,云与降水相关性,云辐射效应以及模式中的云-辐射问题方面的研究。指出抬升的青藏高原上水汽较少,限制了高原上云的垂直高度,对云层厚度和层数有显著压缩作用。在云量及其季节变化上,单层云的相对贡献大于亚洲季风区的其他区域;夏季对流云比较浅薄,积云发生频率最高,云内滴谱较宽;降水云以积云和卷云为主,云对总降水的贡献随着云层数增多而减小,降水增强时高层冰粒子的密集度趋于紧密;夏季青藏高原地区云的净辐射效应在8 km高度存在一个厚度仅1 km左右但较强的辐射冷却层,而在其下（4~7 km高度之间）为强的辐射加热层。最后展望了未来需要进一步开展的研究。     

一次热带海洋对流云微物理过程的数值模拟

为了理解微物理过程以及次生对流云对热带对流云团发展演变过程的影响,利用二维云分辨模式对2006年1月20日靠近澳大利亚西北部的印度尼西亚暖池附近的一次对流云降水过程进行数值模拟,分析了对流云发展演变不同阶段各种微物理过程的特征,尤其对次生对流的形成以及并合过程进行了深入分析.结果表明:本个例所研究的热带对流云团具有发展...     

一场突发性局地大暴雨触发作用的分析和探讨

利用多种非常规高时空分辨率观测资料并结合ERA5(ECMWF Reanalysis V5)再分析资料,分析了2019年6月2日长春市区的一场突发性局地大暴雨的中尺度特征,结果发现,低层或高层冷中心、暖湿气流和冷池出流三者之间不同的相互作用是该过程两段不同强度降水产生的根本原因：第一时段降水较强,并伴有强雷电和冰雹,700 hPa附近较弱冷中心在低层偏南风急流作用下北移至长春站北部并叠加在高层强冷中心之下,其下沉气流在边界层顶附近受该处降水形成的冷池和冷锋后部冷平流阻挡向南回流,冷池出流强度增强并在长春站附近迫使强暖湿气流抬升,长春站上空层结不稳定性加强,当上游对流云团东移至该地时强烈发展,回波强度超过60 dBZ,后向传播作用形成东西向线状对流,列车效应显著;第二时段降水相对较弱,仅伴有雷电,长春上空中低层仍为暖平流控制,高层冷空气继续加强并南压,其下沉气流在边界层顶附近受低层急流作用向北辐散,冷平流较强并与第一阶段强降水产生的冷池出流(较弱冷平流)在长春站附近辐合,迫使其低层相对较暖的气团抬升,700 hPa以下转为垂直上升运动,对流云团移至该处再次发展并与周围对流云团合并形成线状对...     

Evaluation of clouds and radiative fluxes in the EC-Earth general circulation model

Observations, mostly from the International Satellite Cloud Climatology (ISCCP), are used to assess clouds and radiative fluxes in the EC-Earth general circulation model, when forced by prescribed observed sea surface temperatures. An ISCCP instrument simulator is employed to consistently compare model outputs with satellite observations. The use of a satellite simulator is shown to be imperative for model evaluation. EC-Earth exhibits the largest cloud biases in the tropics. It generally underestimates the total cloud cover but overestimates the optically thick clouds, with the net result that clouds exert an overly strong cooling effect in the model. Every cloud type has its own source of bias. The magnitude of the cooling due to the shortwave cloud radiative effect ( \(\mid \hbox {SWCRE}\mid\) ) is underestimated for the stratiform low-clouds, because the model simulates too few of them. In contrast, \(\mid \hbox {SWCRE}\mid\) is overestimated for trade wind cumulus clouds, because in the model these are too thick. The clouds in the deep convection regions also lead to overestimate the \(\mid \hbox {SWCRE}\mid\) . These clouds are generally too thick and there are too few mid and high thin clouds. These biases are consistent with the positive precipitation bias and the overly strong mass flux for deep convective plumes. Potential sources for the various cloud biases in the model are discussed.