热带地区云量日变化的气候特征

利用国际卫星云气候计划（ISCCP）1984—2003年共20年云量资料,统计分析了热带地区的云量日变化特征,研究结果表明,云量峰值时间和变化幅度在全球的分布都较为均匀,而海陆差异明显。高云和低云在变化机制上相对独立,其云量日变化并非同步。全球云量日变化由4类基本形式组成,分别为洋面高云型、陆面高云型、洋面低云型和陆面低云型。高云日变化与地表辐射加热状况密切相关,其形式在洋面和陆面类似,均为早晨出现云量最小值而午后到达云量峰值。相比于洋面,陆面高云的峰值在夜间持续时间较长,可发展至更为稳定深厚的云系。低云多在局地5时附近出现云量峰值,18时左右达到云量极小值,其中陆面低云在12时出现第二峰值。     

近二十年全球变暖背景下东亚地区云量变化特征分析

利用ISCCP的D2云气候资料集，采用趋势分析方法得到了东亚地区1984—2006年各种不同种类云量的变化趋势，并重点分析了全球变暖背景下气温与不同云量变化之间的关系。结果表明：近20年东亚地区总云量和高、低云量呈现波动减少趋势，减少量分别为2.24%、1.65%和1.68%，中云量呈增加趋势，增加量为1.07%；且云量变化存在较大的区域差异。温室效应所导致的东亚地区气温改变和水汽含量变化，是导致云量分布变化的重要原因，在青藏高原、孟加拉湾及热带辐合带区域的气温与高云存在显著负相关，与中、低云存在正相关，而在西太平洋、日本以东以北洋面的气温与低云呈显著负相关，与高云呈正相关。     

利用REOF对全球云量趋势变化的分析

文章利用ISCCP月平均云气候资料集的总云量数据,分析了总云量在全球的时空分布,并对四季云量分布进行对比;采用趋势分析和旋转经验正交函数分解的方法,比较了1983—2009年全球平均总云量的变化趋势,结果显示:27a以来全球云量总体呈现减少趋势,尤其是赤道太平洋地区最明显,高纬度地区云量略有增加。云量低值中心位于南北回归线附近,赤道辐合带有一云量高值中心。总体而言,南半球云量多于北半球,洋面云量多于陆面;春夏两季云量多于秋冬两季。     

南海及周边地区云量分布及低云量与南海海温的关系

利用国际卫星云气候计划提供的月平均云气候资料集,分析了南海及周边地区云量的分布特征,并进一步研究了低云量与南海海温的关系。结果表明:(1)南海及周边地区总云量分布存在显著的季节性差异特征。(2)低云主要分布在南海海区,中云为华南地区,而高云则主要位于靠近赤道区域。(3)低云受海表温度影响较大,而中高云则主要与强对流相对应。低云主要分布于南海海表冷水中心南侧的暖水区内的温度梯度区,其高值区分布与海表温度梯度分布基本一致,海表温度梯度的大小与高值中心的低云量成正比。(4)低云量高值中心位置与水平海温梯度区两侧基本一致,高温暖水受西边界强迫上升在海表层辐合,有利于低云的生成。     

末次冰期冰盛期中国地区水循环因子变化的模拟研究

ISCCP卫星资料(1983—2006年)的结果显示:青藏高原地区是高云的高值中心;而以四川为中心直到同纬度的中国东南沿海地区是中云的高值区,同时,青藏高原地区是中云的低值中心。利用全球气候模式CCM3嵌套区域模式MM5模拟了现代和末次冰期冰盛期的气候。MM5模拟的结果与ISCCP的卫星资料对比表明:模拟结果再现了中国地区高云和中云分布的主要特征。这暗示云分布的气候特征可能主要由相对湿度决定。同时,通过MM5的结果与NCEP资料的对比也说明,模式可以较好地模拟水汽和温度的垂直分布。在此基础上,研究了末次冰期冰盛期水循环因子的变化。模拟结果显示:末次冰期冰盛期夏季对流层的温度降低,在对流层中上层存在温度降低的中心;而在冬季在南方的对流层中层存在降温中心,在北方的对流层中上层温度升高。大气中水汽含量与温度变化有很好的正相关,除了冬季北方对流层中上层水汽增加外,水汽含量一般降低,而且在近地层降低的最多,随高度增高水汽变化逐渐变小。但是,水汽的相对变化在对流层上层存在降低的高值中心。相对湿度存在变化,最大的变化超过15%,而且有增加,也有减少。在区域尺度相对湿度不是保守的。相对湿度变化与中云和低云的变化一致。在末次冰期冰盛期,中国地区高云量减少,除中国西南地区外,中云和低云量减少,低云量减少的最多。降水的变化与中云和低云的变化相对应,云量增加降水增加,云量减少降水也减少。从相对湿度和有效降水可以看到在西南地区末次冰期冰盛期变得潮湿,在夏季西北地区也变得潮湿。     

中国西北地区云时空分布特征的初步分析

利用国际卫星云气候计划（ISCCP）获取的1983年7月－1993年12月的月平均云资料，分析了西北地区云的分布特片和季节变化，发现西北地区的云量与地形有很好的一致性；塔里木盆地是云量最少的地区，而且以云层较薄的积云和高云为主，在天山，昆仑山，祁连山一带，存在着云量的极大值区，其中云层较厚，水汽含量较高的层云，雨层云，深对流云占了很大的比例，值得注意的一点是，云的这种时空分布特征具有明显的地域性和稳定性，有利于开展人工增雨工作。     

全球典型低云区中各类低云云量与水平温度平流关系的单点个例分析

选取欧洲中心40年再分析资料(ERA40)中2001年7月的775hPa和925hPa等压面上的风场和温度场资料与ISCCP同时段的低云资料,利用条件概率方法(云频数)和逐日演变的动态方法分析全球典型低云区单点的云量与水平温度平流的关系.结果表明:全球典型低云区单点上各种云的云量与水平温度平流之间的关系是十分复杂的,在某种平流下各种云均有可能出现,某种云也能在不同的平流下出现.全球典型低云区单点云量与水平温度平流的逐日演变没有明显的同步性.因此,从已知的水平温度平流条件来预报各类低云云量是没有充分的观测事实作为依据的.     

梅雨前后亚洲季风区平均散度风环流和水汽输送的研究

分析了１９８３年江淮流域梅雨期及其前后亚洲季风区平均散度风环流和垂直积分水汽输送的辐散分量。在入梅前强水汽辐合中心位于华南，出梅后则位于印度季风区，梅雨期这两地区都存在着强水汽辐合中心，并且强水汽辐合区和中国东部雨带的位置变化及热源分布有着密切关系。同时指出，江谁流域梅雨与大尺度辐散环流的变化、热源的配置及水汽辐合的位置有着较好的对应关系。     

海气耦合气候模式对大气中水汽输送、辐散辐合与海气间水通量交换的模拟

基于ECMWF再分析结果对LASG第三代全球海洋-大气-陆地耦合系统模式(GOALS)的两个版本和第四代耦合气候模式初始版(FGCM-0)所模拟的大气水汽输送与辐散辐合特征、海气间水通量交换,进行了评估分析.结果表明:(1)对垂直积分的水汽通量场的流函数及其对应的无辐散水汽通量矢量的模拟,三个耦合模式都能够较为合理地再现副热带大洋的涡旋结构、中纬度西风带的东向水汽输送、赤道东风带的西向水汽输送和东亚夏季风水汽输送等行星尺度特征及其季节变化,只是GOALS的涡旋位置、FGCM-0的涡旋中心强度,较之实际略有偏差.(2)反映在垂直积分的水汽通量场的势函数和对应的无旋水汽矢量上,对南北半球副热带大洋水汽辐散区、热带辐合带(ITCZ)、东亚夏季风区强烈的水汽辐合特征等的模拟,FGCM-0的结果相对合理.GOALS的热带辐合中心过于集中在印度尼西亚群岛附近,东亚夏季风水汽辐合中心偏南.(3)关于海气水通量交换,FGCM-0较为理想地再现了副热带的净蒸发、ITCZ和中高纬度的净降水特征以及夏季ITCZ的季节性北移,但对南太平洋辐合带(SPCZ)、副热带南大西洋的净蒸发特点,以及阿拉伯海和盂加拉湾季节变化的差异,模拟结果不理想.FGCM-0在模拟SPCZ上的偏差,是由海气耦合过程造成的.GOALS未能合理再现ITCZ和SPCZ降水大于蒸发的特点,其净降水集中在西太平洋暖池区;但对副热带南大西洋、北印度洋水通量季节变化的模拟相对合理.     

1995—2010年静止卫星云量数据检验和评价

对利用FY2和GMS静止气象卫星建立的东亚地区气候数据集(EAGSCDR FY2 and GMS Geostationary Satellite Climate Data Record over East Asia)进行了检验和评估,使用的检验源数据包括中国地面气候资料与国际卫星云气候计划ISCCP D2月平均云量数据集.对由上述3种不同观测手段得到的多年平均总云量的空间分布特征分析结果表明:3种资料的总云量分布形势有较好的一致性,但是在40°N以北地区,ISCCP和EAGSCDR得到的总云量在量值上高于地面观测值.用地面观测资料检验华南及长江流域EAGSCDR的云检测产品的结果表明,总的准确率为82.10％,总漏判率6.85％,总误判率为11.05％,秋冬季节准确率偏低.EAGSCDR与ISCCP云量都是由卫星资料处理得到的,二者差异主要来自算法的不同,检验结果表明,EAGSCDR中的云量产品精度优于ISCCP云量,并且其时间分辨率可达到1 h,空间分辨率达到5 km,由此可见,EAGSCDR的云产品比ISCCP云产品更有优势.     

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。     

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。      

全球云水量气候分布及变化趋势特征分析

采用20世纪再分析版本2c数据集的云水量逐月再分析数据,通过数理统计方法,分析了1960～2014年全球、海洋和陆地上空云水量的分布和变化特征及其与水汽通量的关系。结果表明:1）全球云水量空间分布不均,海洋高于陆地且比例约为4﹕3,中低纬海洋、陆地上空云水量变化趋势分别为0.07 g m?2 (10 a)?1和?0.04 g m?2 (10 a)?1,季节性差异主要体现于夏季在热带辐合带和南半球海洋高,冬季在北半球海洋和南半球陆地高。2）对比六大洲发现,云水量最高的南美洲有最快增加趋势,为0.46 g m?2 (10 a)?1,同时云水量最低的非洲有最快降低趋势,为?0.59 g m?2 (10 a)?1。3）中低层整层水汽通量散度场的辐合、辐散区和云水量的高、低值区相对应,云水量与水汽通量散度变化呈负相关（相关系数为?0.44）,负相关关系在赤道附近的低纬地区显著。本文揭示了在全球变暖背景下,大气中云水量分布和变化的时空格局,为模式参数化和未来气候预估提供参考。     

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。      

Evaluation of cloud properties in the NOAA/NCEP global forecast system using multiple satellite products

Knowledge of cloud properties and their vertical structure is important for meteorological studies due to their impact on both the Earth’s radiation budget and adiabatic heating within the atmosphere. The objective of this study is to evaluate bulk cloud properties and vertical distribution simulated by the US National Oceanic and Atmospheric Administration National Centers for Environmental Prediction Global Forecast System (GFS) using three global satellite products. Cloud variables evaluated include the occurrence and fraction of clouds in up to three layers, cloud optical depth, liquid water path, and ice water path. Cloud vertical structure data are retrieved from both active (CloudSat/CALIPSO) and passive sensors and are subsequently compared with GFS model results. In general, the GFS model captures the spatial patterns of hydrometeors reasonably well and follows the general features seen in satellite measurements, but large discrepancies exist in low-level cloud properties. More boundary layer clouds over the interior continents were generated by the GFS model whereas satellite retrievals showed more low-level clouds over oceans. Although the frequencies of global multi-layer clouds from observations are similar to those from the model, latitudinal variations show discrepancies in terms of structure and pattern. The modeled cloud optical depth over storm track region and subtropical region is less than that from the passive sensor and is overestimated for deep convective clouds. The distributions of ice water path (IWP) agree better with satellite observations than do liquid water path (LWP) distributions. Discrepancies in LWP/IWP distributions between observations and the model are attributed to differences in cloud water mixing ratio and mean relative humidity fields, which are major control variables determining the formation of clouds.     

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.     

A study of vertical cloud structure of the Indian summer monsoon using CloudSat data

Precise specification of the vertical distribution of cloud optical properties is important to reduce the uncertainty in quantifying the radiative impacts of clouds. The new global observations of vertical profiles of clouds from the CloudSat mission provide opportunities to describe cloud structures and to improve parameterization of clouds in the weather and climate prediction models. In this study, four years (2007–2010) of observations of vertical structure of clouds from the CloudSat cloud profiling radar have been used to document the mean vertical structure of clouds associated with the Indian summer monsoon (ISM) and its intra-seasonal variability. Active and break monsoon spells associated with the intra-seasonal variability of ISM have been identified by an objective criterion. For the present analysis, we considered CloudSat derived column integrated cloud liquid and ice water, and vertically profiles of cloud liquid and ice water content. Over the South Asian monsoon region, deep convective clouds with large vertical extent (up to 14 km) and large values of cloud water and ice content are observed over the north Bay of Bengal. Deep clouds with large ice water content are also observed over north Arabian Sea and adjoining northwest India, along the west coast of India and the south equatorial Indian Ocean. The active monsoon spells are characterized by enhanced deep convection over the Bay of Bengal, west coast of India and northeast Arabian Sea and suppressed convection over the equatorial Indian Ocean. Over the Bay of Bengal, cloud liquid water content and ice water content is enhanced by ~90 and ~200 % respectively during the active spells. An interesting feature associated with the active spell is the vertical tilting structure of positive CLWC and CIWC anomalies over the Arabian Sea and the Bay of Bengal, which suggests a pre-conditioning process for the northward propagation of the boreal summer intra-seasonal variability. It is also observed that during the break spells, clouds are not completely suppressed over central India. Instead, clouds with smaller vertical extent (3–5 km) are observed due to the presence of a heat low type of circulation. The present results will be useful for validating the vertical structure of clouds in weather and climate prediction models.     

Cloud albedo feedback and the super greenhouse effect in a global coupled GCM

Two competing cloud-radiative feedbacks identified in previous studies i.e., cloud albedo feedback and the super greenhouse effect, are examined in a sensitivity study with a global coupled ocean-atmosphere general circulation model. Cloud albedo feedback is strengthened in a sensitivity experiment by lowering the sea-surface temperature (SST) threshold in the specified cloud albedo feedback scheme. This simple parameterization requires coincident warm SSTs and deep convection for upper-level cloud albedos to increase. The enhanced cloud albedo feedback in the sensitivity experiment results in decreased maximum values of SST and cooler surface temperatures over most areas of the planet. There is also a cooling of the tropical troposphere with attendant global changes of atmospheric circulation reminiscent of those observed during La Niña or cold events in the Southern Oscillation. The strengthening of the cloud albedo feedback only occurs over warm tropical oceans (e.g., the western Pacific warm pool), where there is increased albedo, decreased absorbed solar radiation at the surface, stronger surface westerlies, enhanced westward currents, lower temperatures, and decreased precipitation and evaporation. However, the weakened convection over the tropical western Pacific Ocean alters the large-scale circulation in the tropics such that there is increased upper-level divergence over tropical land areas and the tropical Indian Ocean. This results in increased precipitation in those regions and intensified monsoonal regimes. The enhanced precipitation over tropical land areas produces increased clouds and albedo and wetter and cooler land surfaces. These additional contributions to decreased absorbed solar input at the surface combine with similar changes over the tropical oceans to produce the global cooling associated with the stronger cloud albedo feedback. Increased low-level moisture convergence and precipitation over the tropical Indian Ocean enhance slightly the super greenhouse effect there. But the stronger cloud albedo feedback is still the dominant effect, although cooling of SSTs in that region is less than in the tropical western Pacific Ocean. The sensitivity experiment demonstrates how a regional change of radiative forcing is quickly transmitted globally through a combination of radiative and dynamical processes in the coupled model. This study points to the uncertainties involved with the parameterization of cloud albedo and the major implications of such parameterizations concerning the maximum values of SST, global climate sensitivity, and climate change.Support is provided by the Office of Health and Environmental Research of the U.S. Department of Energy, as part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

浙江一次江淮气旋后部强对流暴雨过程诊断研究

利用地面降水观测、NCEP/NCAR FNL再分析、ECMWF模式预报场和FY-2H静止卫星TBB资料, 对2020年6月30日浙江省一次暴雨过程进行了综合分析。结果表明: (1) 200 hPa南亚高压强高空辐散、中纬度低槽东移、副热带高压带状稳定的阻塞形势、江淮气旋后部下摆冷空气与暖湿气流交汇形成的冷式切变等共同提供了有利的环境条件; (2)对流层中低层水汽通量向高空伸展、700 hPa正的垂直螺旋度中心都对暴雨落区有示踪作用, 高层正水汽通量散度强于低层负水汽通量散度, 垂直螺旋度和垂直速度中心几乎重合, 先低层强辐合后强垂直上升运动均为本次暴雨的发生提供了重要的水汽和动力条件; (3)暴雨发生在MPV、MPV1和MPV2为正负过渡的零值区, 为对流不稳定和斜压不稳定相结合区域, θ_se线密集区与地面近乎垂直, 湿位涡的高值中心位于θ_se梯度最大处, 高空湿位涡下传触发了位势不稳定能量的释放, 引起大范围的强对流暴雨; (4) 850 hPa冷切变线附近的降水云团, 是由多个块状对流云团合并加强形成完整的带状积雨云团, 而上游不断有新生对流云团生成东移补充消散的老单体, 触发阶段对流云后向传播, 扰动发展阶段对流云团合并过程, 形成对流云串的“列车效应”。