山西夏季层积云降水微物理特征分析

利用Droplet Measureinent TeehnologY（DMT）资料,分析了山西2008年7月17日降水性层积云的云微物理结构,通过对云中粒子浓度、直径、二维图像以及谱型分布变化,并结合宏观记录特征,详细分析了飞机上升和下降阶段云系的垂直结构特征。结果表明：飞机上升阶段云系为高积云,飞机下降阶段云系为高积云一层积云结构,Cloud Droplet Probe（CDP）和Cloud Imaging Probe（CIP）测得粒子浓度偏大,最大浓度分别为236em。和9．74cm^-3。层积云云中微物理量水平分布特征具有明显的不均匀性。上升阶段降水的雨滴主要是冰粒子融化形成的,冷云过程占主导地位,在0℃层附近存在明显的融化层亮带。下降阶段降水机制为高积云冷云过程和层积云暖云过程相结合。     

西南地区云水量与可降水量比值的分布特征和变化趋势

采用1980～2009年云水量和可降水量的NCEP逐月再分析资料,通过统计分析,研究30a来西南地区（云南、贵州、讴庆、四川）云水量与可降水量比值的时空分布特征和变化趋势。结果表明：（1）西南地区年、季17孟水量与可降水比值均具有明显的地区性差异,由西北向东南递减,高值区位于川西高原;（2）云水量与可降水比值年内分布不均匀,从2月到8月逐渐减小,9月至1月逐渐增大,同时,季节差异较大,夏季最小,冬季最大;（3）30a来,整个西南地区年、夏季和秋季云水量与可降水量比值呈显著减少趋势。     

基于卫星红外窗亮温探测上冲云顶

上冲云顶是卷云砧上的穹顶状突起,表示存在强对流切变和强烈上升气流,是强雷暴的重要指示者.伴随上冲云顶的雷暴经常产生灾害性天气,如航空湍流、强降雨、冰雹、破坏性的风和龙卷等.本文以2010年9月6日发生在安徽北部地区的一次特大暴雨过程为例,用卫星红外窗区通道观测亮温探测上冲云顶,并将高时空分辨率的局地分析预报系统(LAPS)的中尺度分析场资料与用红外窗方法探测到的上冲云顶进行定性比较,结果表明造成此次强降雨过程的对流系统即为一个伴随上冲云顶的强雷暴系统,LAPS中尺度分析场资料客观地验证了上冲云顶的存在.     

多普勒雷达资料循环同化在台风“鲇鱼”预报中的应用

高分辨率的中尺度预报模式ARPS及其3DVAR/云分析系统,针对2010年登陆福建的超强台风“鲇鱼”,研究对流可分辨尺度下,每1h循环同化沿海新一代多普勒雷达网资料分析、研究对台风初始场和预报场的改进作用.结果表明:单独同化雷达资料可显著改善初始场中的台风内核区动力和热力结构,以及台风强度和位置,进而提高18h台风强度、路径和降水预报,但预报路径和降水分布与实况仍存在差异.在雷达资料同化基础上加入常规观测资料,对初始场中台风内核区结构改进不大.但在显著调整大尺度背景场,从而进一步减少台风路径预报误差,能准确预报出福建沿海两个强降水区域的位置和强度.总体而言,雷达资料同化主要提高台风结构分析,而常规观测资料同化主要改善环境场分析,两者有效结合使得预报结果和实况最为接近.     

2019年7月17日江苏东南部特大暴雨的 双偏振雷达观测分析

利用S波段双偏振雷达数据,结合再分析数据、自动气象站、探空和二维闪电探测数据,采用多普勒雷达风场反演和粒子相态识别等方法,分析了2019年7月17日江苏省东南部多站破历史记录的超强降水对流风暴的偏振特征和云微物理特征;并选取了打破当地强降水历史记录如皋站和潞城站,分析了影响两站的对流单体的异同。影响如皋的对流风暴几无闪电活动,对流质心接近地面,上升气流相对较弱。且0 ℃和-35 ℃层间霰粒子数目相对较少,闪电几乎不存在。在融化层以下,由于强烈的暖雨过程,较大的冰相粒子落下并融化和低层雨滴的聚并增长,导致低层雨滴数量迅速增加,带来地面极端强降水。潞城地区雷暴活动明显,影响其对流风暴发展旺盛。-35~0 ℃层存在强烈的上升运动,抬升低层大量的液相粒子通过淞附作用形成的霰,并与高层冰晶不断碰撞,在云层中形成强大的电场,产生强烈的负闪,且在地面产生了极强的降水。这表明融化层以上的冰相微观物理过程,对于降水的发生和增强非常重要。     

气溶胶浓度对暖云不同生长阶段物理特征影响的模拟研究

基于云微物理过程完善的TAU2D分档云模式, 模拟研究了用热泡扰动生成的暖云在不同气溶胶数浓度(Na)背景条件下各演变阶段云微物理量的变化特征。结果表明: 在暖云的发展过程中Na越高, 云滴尺度变小, 云滴间的碰并增长发动较晚, 云滴谱因碰并增长而实现的滴谱拓宽变弱, 云滴谱相对较窄, 云滴谱标准差较小, 因此云体发展越缓慢, 云体生命周期越长, 形成降水就越晚; 反之, 云滴尺度越大, 碰并增长发动越早, 云滴谱拓宽更明显, 云滴谱标准差越大, 云体生命周期相对更短, 降水开始时刻越早。高Na背景下, 碰并阶段云滴谱较凝结阶段更宽, 沉降阶段因云体下沉蒸发导致小尺度云滴减少, 使其滴谱较碰并阶段略有拓宽。在凝结阶段, 低气溶胶背景下云滴数浓度(N)和离散度(ε)间呈现正相关关系, 而高气溶胶背景下两者为负相关关系。在碰并阶段, N与ε的相关性关系为负相关, 且随着气溶胶数浓度的增加, 负相关程度降低。在沉降阶段, N和ε间为负相关关系。     

Calculating the Climatology and Anomalies of Surface Cloud Radiative Effect Using Cloud Property Histograms and Cloud Radiative Kernels

Cloud radiative kernels (CRK) built with radiative transfer models have been widely used to analyze the cloud radiative effect on top of atmosphere (TOA) fluxes, and it is expected that the CRKs would also be useful in the analyses of surface radiative fluxes, which determines the regional surface temperature change and variability. In this study, CRKs at the surface and TOA were built using the Rapid Radiative Transfer Model (RRTM). Longwave cloud radiative effect (CRE) at the surface is primarily driven by cloud base properties, while TOA CRE is primarily decided by cloud top properties. For this reason, the standard version of surface CRK is a function of latitude, longitude, month, cloud optical thickness (τ) and cloud base pressure (CBP), and the TOA CRK is a function of latitude, longitude, month, τ and cloud top pressure (CTP). Considering that the cloud property histograms provided by climate models are functions of CTP instead of CBP at present, the surface CRKs on CBP-τ histograms were converted to CTP-τ fields using the statistical relationship between CTP, CBP and τ obtained from collocated CloudSat and MODIS observations. For both climate model outputs and satellites observations, the climatology of surface CRE and cloud-induced surface radiative anomalies calculated with the surface CRKs and cloud property histograms are well correlated with those calculated from surface radiative fluxes. The cloud-induced surface radiative anomalies reproduced by surface CRKs and MODIS cloud property histograms are not affected by spurious trends that appear in Clouds and the Earth's Radiant Energy System (CERES) surface irradiances products.     

Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors

Cloud microphysical properties are significantly affected by entrainment and mixing processes. However, it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution. Previously, the relationship between relative dispersion and entrainment rate was found to be positive or negative. To reconcile the contrasting relationships, the Explicit Mixing Parcel Model is used to determine the underlying mechanisms. When evaporation is dominated by small droplets, and the entrained environmental air is further saturated during mixing, the relationship is negative. However, when the evaporation of big droplets is dominant, the relationship is positive. Whether or not the cloud condensation nuclei are considered in the entrained environmental air is a key factor as condensation on the entrained condensation nuclei is the main source of small droplets. However, if cloud condensation nuclei are not entrained, the relationship is positive. If cloud condensation nuclei are entrained, the relationship is dependent on many other factors. High values of vertical velocity, relative humidity of environmental air, and liquid water content, and low values of droplet number concentration, are more likely to cause the negative relationship since new saturation is easier to achieve by evaporation of small droplets. Further, the signs of the relationship are not strongly affected by the turbulence dissipation rate, but the higher dissipation rate causes the positive relationship to be more significant for a larger entrainment rate. A conceptual model is proposed to reconcile the contrasting relationships. This work enhances the understanding of relative dispersion and lays a foundation for the quantification of entrainment-mixing mechanisms.     

Assessment of FY-4A and Himawari-8 Cloud Top Height Retrievalthrough Comparison with Ground-Based MillimeterRadar at Sites in Tibet and Beijing

正1Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics,Chinese Academy of Sciences, Beijing 100029, China2University of Chinese Academy of Sciences, Beijing 100049, China     

The Significant Role of Radiosonde-measured Cloud-base Height in the Estimation of Cloud Radiative Forcing

The satellite-based quantification of cloud radiative forcing remains poorly understood, due largely to the limitation or uncertainties in characterizing cloud-base height (CBH). Here, we use the CBH data from radiosonde measurements over China in combination with the collocated cloud-top height (CTH) and cloud properties from MODIS/Aqua to quantify the impact of CBH on shortwave cloud radiative forcing (SWCRF). The climatological mean SWCRF at the surface (SWCRF_SUR), at the top of the atmosphere (SWCRF_TOA), and in the atmosphere (SWCRF_ATM) are estimated to be ?97.14, ?84.35, and 12.79 W m^?2, respectively for the summers spanning 2010 to 2018 over China. To illustrate the role of the cloud base, we assume four scenarios according to vertical profile patterns of cloud optical depth (COD). Using the CTH and cloud properties from MODIS alone results in large uncertainties for the estimation of SWCRF_ATM, compared with those under scenarios that consider the CBH. Furthermore, the biases of the CERES estimation of SWCRF_ATM tend to increase in the presence of thick clouds with low CBH. Additionally, the discrepancy of SWCRF_ATM relative to that calculated without consideration of CBH varies according to the vertical profile of COD. When a uniform COD vertical profile is assumed, the largest SWCRF discrepancies occur during the early morning or late afternoon. By comparison, the two-point COD vertical distribution assumption has the largest uncertainties occurring at noon when the solar irradiation peaks. These findings justify the urgent need to consider the cloud vertical structures when calculating the SWCRF which is otherwise neglected.