A Comparative Study of Cloud Liquid Water Content from Radiosonde Data at a Tropical Location

In this paper, some features of cloud liquid water content with respect to rain and water vapor are presented. Cloud liquid water density profile is obtained from radiosonde observation with Salonen's model and Karsten's model at Kolkata, a tropical location in the Indian region. Cloud liquid water contents (LWC) are obtained from these profiles which show a prominent seasonal variation. The monsoon months exhibit much higher values of LWC than in other months. However Salonen's model yields higher LWC values than that obtained with Karsten's model. The variation of daily total rainfall with LWC shows a positive relationship indicating the role of LWC in controlling the rainfall. Also the variation pattern of LWC with integrated water vapor (IWV) content of the atmosphere indicates that a threshold value of water vapor is required for cloud to form and once cloud is formed LWC increases with IWV.

Analysis on the Macro and Micro Physical Characteristics of Stratiform Cloud in Henan

By using the microphysical data of stratiform cloud in Henan which were observed by PMS airborne cloud particle measure system on March 23 in 2007 and combining with the radar,satellite,sounding data,the macro and micro physical structure characteristics of cloud were analyzed.The results showed that the average diameter of small cloud drop which was measured by FSSP-100 in the warm layer of cloud was mainly during 5-12 μm,and the average value was 7.33 μm.The biggest diameter of small cloud drop changed during 14-47 μm,and the average value was 27.80 μm.The total number concentration scope of small cloud drop was during 47.73-352.00 drop/cm3,and the average value was 160 drop/cm3.In the cold layer of cloud,the biggest diameter of small cloud particle(included the cloud droplet and the ice crystals)which was measured by FSSP-100 was 24.8 μm.The total number concentration scope of small cloud particle was during 0.899-641.000 drop/cm3,and the average value was 297 drop/cm3.The airborne King heat line liquid water content instrument observed that the super-cooling liquid water existed in the cloud.The super-cooling cloud water content changed during 0.02-0.20 g/m3,and the average value was 0.093 g/m3.The biggest value which was 0.202 g/m3 appeared in 4 368 m height(the temperature was-8.5 ℃).The particle spectrum type in the cloud was mainly the negative exponent type and the single peak type.

东亚地区云微物理量分布特征的CloudSat卫星观测研究

本文利用2007～2010年整四年最新可利用的CloudSat卫星资料,对东亚地区（15°～60°N,70°～150°E）云的微物理量包括冰/液态水含量、冰/液态水路径、云滴数浓度和有效半径等的分布特征和季节变化进行了分析.本文将整个东亚地区划分为北方、南方、西北、青藏高原地区和东部海域五个子区域进行研究,结果显示：东亚地区冰水路径值的范围基本在700 g m-2以下,高值区分布在北纬40度以南区域,在南方地区夏季的平均值最大,为394.3 g m-2,而在西北地区冬季的平均值最小,为78.5 g m-2;而液态水路径的范围基本在600 g m-2以下,冬季在东部海域的值最大,达到300.8 g m-2,夏季最大值为281.5 g m-2,分布在南方地区上空.冰水含量的最高值为170 mg m-3,发生在8km附近,南方地区夏季的值达到最大,青藏高原地区的季节差异最大;而液态水含量在东亚地区的范围小于360 mg m-3,垂直廓线从10km向下基本呈现逐渐增大的趋势,峰值位于1～2 km高度上.冰云云滴数浓度在东亚地区的范围在150 L-1以下,水云云滴数浓度的值小于80 cm-3,垂直廓线的峰值均在夏季最大.冰云有效半径在东亚地区的最大值为90 μm,发生在5km左右;水云有效半径在东亚地区的值分布在10km以下,最大值为10～12 μm,基本位于1～2 km高度上.从概率分布函数来看,东亚地区冰/水云云滴数浓度的分布呈现明显的双峰型,其他量基本为单峰型.本文的结果可以为全球和区域气候模式在东亚地区对以上云微物理量的模拟提供一定的观测参考依据.

基于CloudSat卫星资料分析青藏高原东部夏季云的垂直结构

本文利用CloudSat卫星资料,对青藏高原东部2006-2010年6-8月云垂直结构的空间分布进行分析,结果表明：（1）夏季青藏高原东部云发展可达到平流层,且高原东部云在5km以下以水云存在,5-10km以液相和固相共存的混态存在,在垂直高度10km以上以冰云存在。由于CloudSat卫星资料云相的反演问题,可能会造成水云和混态云的发展上限偏低,冰云的发展下限抬升。（2）研究区整层水汽输送和云水平均路径空间分布存在一定的差异性,云水含量纬向分布表现为在26.5°-30.5°N附近存在一个明显的峰值区,经向分布表现为95°E以西云水含量低于以东。（3）研究区以单云层为主,尤其在青藏高原主体。单云层平均云层厚度4182 m,云顶高度、云厚限于水汽的输送,表现为由南向北波动下降。多层云发生频率在27°N以北明显减少,说明强烈的对流运动更容易激发多层云的产生。

基于专家PID控制的云水含量传感器设计

本文设计了一种基于热线法的便携式微型云水含量传感器。该传感器探头采用环形加热片和测温铂电阻的新结构,保证了加热的均匀性和测温的准确性。通过理论公式推导和流体仿真,传感器设计的可行性得到了进一步验证,并得出云水含量与加热片加热功率之间的函数关系。采用32位STM32F103C8T6芯片为核心,其性能保证了传感器系统的稳定性。通过专家PID控制算法实时控制传感器迎风面温度。仿真结果表明:专家PID系统的响应速度更快,适应性更强。为进行实验测试,搭建了风洞实验平台。通过实验测量,当测试云水含量值为0.5 g/m^(3)时,加热片加热功率为1.4 W,计算出实际值为0.58 g/m^(3),满足设计要求。

基于CloudSat/CALIPSO资料的我国北方2个区域云垂直分布差异研究

选用2008年1月—2014年10月的Cloud Sat/CALIPSO卫星资料,对中国北方两个4°×4°区域云垂直结构及其微物理参量进行了对比研究,区域1(114~118°E,37.5~41.5°N)和区域2(110°E^114°E,37.5~41.5°N)纬度相同经度不同。结果表明:1)区域1(E1)和区域2(E2)暖云层、混合云层和冷云层的云出现概率(Cloud Occurrence Probability,COP)差别较大。E1暖云层COP春季最大,E2则在夏、秋季达到较大值;E1混合层COP最大值出现在冬季,E2则出现在春季;2个区域冷云层COP均在春季达到最大。2)2个区域的COP高值区厚度有明显的季节性差异,E1的COP高值主要出现在夏、冬季,E2则主要出现在春、夏季。E1秋、冬季云体雷达回波最大值强于E2,但春、夏季弱于区域1。3)E2在春、秋季的液水含量、冰水含量、云滴有效半径均高于E1。

长江三角洲地区高空云过程气溶胶——云相互作用的观测研究

气溶胶—云相互作用过程对于评估大气云和气溶胶的寿命及气候效应至关重要。目前关于气溶胶—云相互作用的研究主要以飞机航测、卫星反演和模式模拟为主,地基直接观测由于布置难度大、实验时间长、人力物力耗费等原因开展得较少。当前针对气溶胶—云相互作用机制的理解还比较低,亟需外场观测资料深入认识其过程。本研究以长江三角洲地区高山站点的云雾为背景,利用雾滴谱仪、地用逆流虚拟撞击器、混合凝聚核粒子计数器、扫描电迁移率颗粒物粒径谱仪等仪器,研究了大明山顶(海拔1483 m)7月份多云雾期间云滴和气溶胶的特性,探讨了气溶胶对云形成和发展的影响以及云对气溶胶颗粒物的清除作用。云形成初期对气溶胶颗粒物的清除率约为20%~50%。研究显示水汽过饱和度越高且颗粒物粒径越大,清除率越高,这表明粒径较大的吸湿性颗粒物容易活化为云凝结核。对比同一云雾事件中气溶胶数浓度差异较大的三个阶段,我们发现较低的气溶胶数浓度有利于形成液态水含量高的浓云,此时云团由数量相对较少而粒径大的云滴组成,而大气颗粒物数量增多会使云雾变淡,此时的云团由大量细小的云滴组成。本研究分析了8μm以上云滴的云凝结核数量分布特征,发现大云滴的云凝结核几乎都是100 nm以上的颗粒物;随着气溶胶数浓度升高,8μm以上大云滴的数量减少,且大云滴云凝结核的平均直径变大。这些结果显示气溶胶数浓度升高会促使云滴的数量增多而等效直径变小,在水汽有限的自然环境中,气溶胶数浓度越高,颗粒物的临界活化直径越大。总之,我们发现大气气溶胶的数浓度—粒径分布特性影响着云滴的数量和粒径,云的形成和发展也对气溶胶颗粒物有较强的清除作用。

利用CloudSat卫星资料分析云微物理和光学性质的分布特征

利用2007年1月2010年12月高垂直分辨率CloudSat卫星的2B数据产品,对云微物理特征量(包括云中液态水/冰水含量、液态水/冰水路径、云滴有效半径等)以及云光学参数(云光学厚度等)的全球分布和季节变化进行了统计分析,并研究了云微物理性质对光学性质的影响。结果表明,冰水路径分布在北美南部、南美大陆、非洲大陆、澳大利亚和南亚的陆地上空,以及太平洋、大西洋和印度洋的洋面上空,高值区最大值达600 g·m-2以上;垂直方向上,高值区位于赤道地区8 km附近以及中纬度地区4~8 km高度上。液态水路径在300 g·m-2以上的高值区主要位于太平洋、印度洋和大西洋的中低纬度海域上空,垂直上液态水含量随高度递减。冰云有效半径在高纬度地区近地面层达200μm以上,在赤道附近4~8 km上有1个高值区,南北半球中纬度地区2~4 km上有2个高值区,最大值均达到80μm以上。在1 km以下的边界层水云有效半径值较大,达到12μm以上。总云光学厚度在全球大部分地区【40,高值区普遍位于中高纬度的广阔地区和低纬度靠近大陆的洋面上空;垂直方向上,云光学厚度的高值集中在2 km以下的边界层。云光学厚度的分布受云量、云水含量和云滴有效半径的影响,云量大的地区基本为云光学厚度的大值区。

基于CloudSat资料的中国地区深对流云物理特征研究

利用2007-2010年和2013-2014年Cloud Sat卫星资料,分析了中国11个地理区域的深对流云发生率、冰/液态水路径、冰/液态水含量等分布特征及其季节变化。结果显示,深对流云发生率整体呈现从东南到西北递减的趋势,高值区主要集中在西北地区东南部、西藏东南部、西南地区东部和南部、黄淮西部和南部、江汉、江淮、江南和华南等地,就各个地区不同季节而言,江南地区夏季的值最大,达到10.34%。在垂直高度上,深对流云发生率分布在18 km以下,最大值为11.31%,出现在江南夏季4.08~4.56 km高度上。深对流云中冰水路径最大值出现在华南夏季,液态水路径最大值出现在黄淮秋季,西藏地区的深对流云中冰水路径的比例明显高于液态水路径。冰水含量在垂直高度上存在两个高值区,分别位于6~8 km、14~18 km,最大值发生在江南夏季19.44 km左右高度上,达到1 018.87 mg·m^(-3),季节差异较大的高度位于14~18 km。液态水含量最大值发生在江淮冬季,达到411.50 mg·m^(-3),高度在9.36 km左右,垂直高度上最大值在2~6 km上均有出现。该结果可以更好地揭示深对流云的气候特征,并为人工影响天气以及数值模式中对深对流云物理量的模拟提供一定的参考依据。

Properties of Cloud and Precipitation over the Tibetan Plateau

The characteristics of seasonal precipitation over the Tibetan Plateau （TP） were investigated using TRMM （Tropical Rain- fall Measuring Mission） precipitation data （3B43）. Sensitive regions of summer precipitation interannual variation anomalies were investigated using EOF （empirical orthogonal function） analysis. Furthermore, the profiles of cloud water content （CWC） and precipitable water in different regions and seasons were analyzed using TRMM-3A12 data observed by the TRMM Microwave Imager. Good agreement was found between hydrometeors and precipitation over the eastern and southeastern TP, where water vapor is adequate, while the water vapor amount is not significant over the western and northern TE Further analysis showed meridional and zonal anomalies of CWC centers in the ascending branch of the Hadley and Walker Circulation, especially over the south and east of the TE The interannual variation of hydrometeors over the past decade showed a decrease over the southeastern and northwestern TP, along with a corresponding increase over other regions.

Aircraft Observations of Liquid and Ice in Midlatitude Mixed-Phase Clouds

ABSTRACT This paper reports airborne measurements of midlatitude altostratus clouds observed over Zhengzhou, Henan Province, China on 3 March 2007. The case demonstrates mixed-phase conditions at altitudes from 3200 to 4600 m （0°C to -7.6°C）, with liquid water content ranging from 0.01 to 0.09 g m-3. In the observed mixed-phase cloud, liquid water content exhibited a bimodal distribution, whereas the maximum ice particle concentration was located in the middle part of the cloud. The liquid and ice particle data showed significant horizontal variability on the scale of a few hundred meters. The cloud droplet concentration varied greatly over the horizontal sampling area. There was an inverse relationship between the cloud droplet concentration and ice particle concentration. A gamma distribution provided the best description of the cloud droplet spectra. The liquid droplet distributions were found to increase in both size and concentration with altitude. It was inferred from the profile of the spectra parameters that the cloud droplet sizes tend to form a quasi-monodisperse distribution. Ice particle spectra in the cloud were fitted well by an exponential distribution. Finally, a remarkable power law relationship was found between the slope （λ） and intercept （No） parameters of the exponential size distribution.

Comparison of Cloud Properties between Cloud Sat Retrievals and Airplane Measurements in Mixed-Phase Cloud Layers of Weak Convective and Stratus Clouds

Cloud microphysical properties including liquid and ice particle number concentration （NC）, liquid water content （LWC）, ice water content （IWC） and effective radius （RE） were retrieved from CloudSat data for a weakly convective and a widespread stratus cloud. Within the mixed-phase cloud layers, liquid-phase fractions needed to be assumed in the data retrieval process, and one existing linear （Pl） and two exponential （P2 and P3） functions, which estimate the liquid-phase fraction as a function of subfreezing temperature （from -20℃ to 0℃）, were tested. The retrieved NC, LWC, IWC and RE using Pl were on average larger than airplane measurements in the same cloud layer, Function P2 performed better than p1 or P3 in retrieving the NCs of cloud droplets in the convective cloud, while function Pl performed better in the stratus cloud. Function P3 performed better in LWC estimation in both convective and stratus clouds. The REs of cloud droplets calculated using the retrieved cloud droplet NC and LWC were closer to the values of in situ observations than those retrieved directly using the Pl function. The retrieved NCs of ice particles in both convective and stratus clouds, on the assumption of liquid-phase fraction during the retrieval of liquid droplet NCs, were closer to those of airplane observations than on the assumption of function P1.

基于CloudSat的台风深对流云微物理参数相关性分析

以2009年14号台风“彩云”为例,基于CloudSat相关云产品统计了台风深对流云中水云和冰云的有效粒子半径、云水含量谱分布的特征。在此基础上探讨了两个云微物理参量的相关性,并对不同发展时期的多个台风进行了该关系的应用检验。研究结果表明,不论是水云还是冰云,若以云水含量为横坐标,以云有效粒子半径为纵坐标,台风深对流云像元散点图的分布存在明显的下边界线,且边界值随着有效粒子半径和云水含量参数值的增大而逐渐提高;零度层以下低层水云的有效粒子半径与液态水含量呈正相关关系,可采用对数关系式进行拟合。经检验,该拟合关系式对其他发展阶段的台风同样适用,证实了该关系的普适性。

Relationship between Cloud Characteristics and Radar Reflectivity Based on Aircraft and Cloud Radar Co-observations

Cloud properties were investigated based on aircraft and cloud radar co-observation conducted at Yitong, Jilin, Northeast China. The aircraft provided in situ measurements of cloud droplet size distribution, while the millimeter-wavelength cloud radar vertically scanned the same cloud that the aircraft penetrated. The reflectivity factor calculated from aircraft measurements was compared in detail with sinmltaneous radar observations. The results showed that the two reflectivities were comparable in warm clouds, but in ice cloud there were more differences, which were probably associated with the occurrence of liquid water. The acceptable agreement between reflectivities obtained in water cloud confirmed that it is feasible to derive cloud properties by using aircraft data, and hence for cloud radar to remotely sense cloud properties. Based on the dataset collected in warm clouds, the threshold of reflectivity to diagnose drizzle and cloud particles was studied by analyses of the probability distribution function of reflectivity from cloud particles and drizzle drops. The relationship between refiectivity factor （Z） and cloud liquid water content （LWC） was also derived from data on both cloud particles and drizzle. In comparison with cloud droplets, the relationship for drizzle was blurred by many scatter points and thus was less evident. However, these scatters could be partly removed by filtering out the drop size distribution with a large ratio of reflectivity and large extinction coefficient but small effective radius. Empirical relationships of Z-LWC for both cloud particles and drizzle could then be derived.

近43年江西省太阳辐射变化特征及其影响因素研究

基于江西省20个国家站1980—2022年逐日气象数据,利用Mann-Kendall趋势检验法、Pearson相关分析法分析了太阳辐射的长期变化趋势及其与气溶胶光学厚度、整层大气水汽含量、低云量和总云量之间的关系。研究发现:1)近43年来,受气溶胶光学厚度和整层大气水汽含量显著增长的影响,江西省太阳辐射以-5.7×10^(-3) MJ m^(-2) decade^(-1)的速度下降,总云量、低云量的微弱变化对太阳辐射的影响有限;2)夏季、秋季和冬季太阳辐射分别以-24×10^(-3) MJ m^(-2) decade^(-1)、-2.4×10^(-3) MJ m^(-2) decade^(-1)、-2.8×10^(-3) MJ m^(-2) decade^(-1)的速度下降,而春季太阳辐射以11.5×10^(-3) MJ m^(-2) decade^(-1)的速度上升,其中,夏季太阳辐射的下降受气溶胶光学厚度和低云量显著增加的影响,秋、冬季太阳辐射的下降受气溶胶光学厚度显著增加的影响,春季太阳辐射的增长主要取决于总云量的显著下降;3)气溶胶光学厚度和整层大气水汽含量增加导致80%的台站太阳辐射呈下降趋势,总云量和低云量下降导致20%的台站太阳辐射呈上升趋势,而修水、赣州站太阳辐射与4个影响因素的变化趋势相同的原因还需进一步研究。

基于CloudSat资料的洋面非降水暖云空间分布及云内液相水含量垂直结构

利用CloudSat卫星搭载的云廓线雷达(cloud profiling radar,CPR)2007~2009年三年的观测资料,针对洋面非降水暖云有效廓线样本,分别对积云(Cu)、层云(St)、层积云(Sc)和高积云(Ac)等四类云型,分析了其在全球尺度的水平分布特征,并在此基础上特别考察了非降水暖云液相水含量(liquid water content,LWC)的垂直变化特性.研究发现,洋面非降水暖云中四类云型的样本占比从高至低依次为层积云76.46%、层云12.48%、积云7.45%、高积云3.61%,层积云在非降水暖云的总覆盖面积中占据主导作用.在样本量全球标准化后,四类云型的空间分布形式存在较大差异,层积云与层云主要集中于北美和南美大陆西侧近岸海域,积云与高积云则广泛分布于太平洋、大西洋和印度洋的洋面上,且高值位于大洋中部.尽管四类云型的生消机制和宏观形态存在很大差异,但不同云型LWC呈现出较为相似的垂直结构.对经几何厚度标准化后的LWC廓线进行比较,发现在四类典型非降水暖云中,由云底到云顶LWC一致呈现为先增后减的规律.云体中下部向上近似线性递增的结构基本反映了LWC的准绝热增长特性,而云体上部及云顶附近的向上递减结构明确反映了云顶普遍受到上空干空气侵入混合的强烈影响,由此导致了自云顶向下逐层衰减的云水蒸发.以云高和云厚两个参数分类的廓线统计结果还显示,LWC垂直结构受到云顶高度和云层几何厚度的影响.云层几何厚度增大时,LWC由云底到云中的递增结构会变厚,由云中到云顶的递减结构会变薄.几何厚度相同但云顶高度不同的云层,其LWC含量也有所不同,这表明对于特定云型,在生成及发展过程中,不同阶段所对应的LWC廓线结构也存在差异.

基于Ka波段云雷达观测的中国西天山降雨云宏微观物理特征研究

利用Ka毫米波云雷达与自动气象站降雨资料,研究了西天山地区2019年和2020年5~8月的降雨云宏微观特性。结果表明:(1)降雨主要发生在夜间,累积降雨量集中在21:00(北京时间,下同)至次日07:00,降雨频次和累积降雨量相关系数为0.71。大雨强频次虽最少,但对总累积降雨量贡献较显著。(2)小雨强、中雨强、大雨强平均反射率因子最大值分别为30 dBZ、35.8 dBZ和39.5 dBZ,最大平均液态水含量分别为1.5 g m^(-3)、4.2 g m^(-3)和7.3 g m^(-3)。(3)不同降雨强度对应的反射率因子都有两个集中区域,2.0~4.4 km反射率因子集中在15~26 dBZ,地面附近的小雨强、中雨强、大雨强对应的反射率因子分别集中在24~32 dBZ、29~38 dBZ和31~42 dBZ。1.75 km以下中雨强和大雨强液态含水量小于1gm^(-3)的频率明显少于小雨强,降雨强度的越大降雨粒子径向速度越集中。

基于Holt-ARIMA-Lagrange Multiplier的CWC信息熵时序研究

降水云系的发展过程及其特征分析,是云降水物理学中的一个重要问题.本文选取一次云发展过程中的700 hPa云水含量(Cloud Water Content, CWC)和大气垂直方向上气流速度(Omega, OMG)的1 h值,以信息熵来度量CWC空间分布的混沌程度,辅以OMG的时间变化来判断云的发展,并提出了一种基于多尺度分解、Holt模型、自回归滑动平均模型(Autoregressive Integrated Moving Average Model, ARIMA)和Lagrange Multiplier的组合预测方法.结果表明:1)CWC熵具有非线性和非平稳性;2)在云的不同发展阶段,北方CWC熵序列的均值都小于南方,方差普遍大于南方;3)OMG区域均值与CWC熵的小波低频重构的极值点在时间上有很好的对应关系,相近的极值点在南方中占50%,在北方中占83.3%,表明CWC熵可以在一定程度上反映云系的发展;4)CWC熵序列往往具有多种时间尺度特征,故进行多尺度分解之后再组合建模的Holt-ARIMA-Lagrange Multiplier模型比单一预测方法、单层分解的预测模型更优,准确率提高3%以上.

NUMERICAL STUDY OF REMOTE SENSING OF CLOUD LIQUID WATER CONTENT BY SPACE-BORNE COMBINED RADAR-RADIOMETER

A retrieval method of microwave(MW)space-borne remote sensing of cloud liquid water content by the combined radar-radiometer is suggested.A three-layer cloud model is chosen to represent the typical stratified precipitating cloud.The retrieval method mainly follows our previously suggested scheme with some modifications.Numerical comparative study shows that in space-borne remote sensing of cloud liquid water content by the combined method is much better than by radar only;Also the retrieval accuracy of cloud liquid water content may be improved when using the three-layer cloud model in the combined method.

机载毫米波雷达反演降水性积层混合云暖区液态水含量及其与飞机观测的对比

液态水含量(Liquid Water Content,LWC)是重要的云参数,对了解云微物理过程以及在人工影响天气效果检验等方面有重要的指导意义。针对已有研究的反射率因子(Z)与LWC经验公式适用范围有限的问题,利用2018—2020年飞机观测资料,在验证中国首部机载云雷达(Ka-band Precipitation Radar,KPR)探测能力和数据可靠性的基础上,采用分档平均方案,建立了适用于降水性积层混合云的Z-LWC经验公式(Z=2454.71×LWC^(1.614)),决定系数达0.995,均方根误差(RMSE)为0.2 g/m^(3)。验证表明,该经验公式反演的液态水含量与飞机实测的LWC吻合较好,且在大多数情况下都优于已有经验公式反演的结果。