红外高光谱资料模拟大气廓线反演对云的敏感性

用不同云顶高度和不同有效云量时的星载红外高光谱观测值,模拟大气温湿垂直廓线反演对云参数的敏感性。用特征向量统计反演法按照云顶高度和有效云量分类反演了大气温湿廓线,统计了不同云高（200,300,500,700和850hPa）及云高有50hPa误差时温度、水汽混合比反演的均方根误差随有效云量的变化。结果表明,随着有效云量的增大,云顶以下各高度层上的温度、水汽混合比反演误差都明显增大。云高有50hPa误差较准确已知而言,温度和水汽混合比的反演误差增大,但温度反演对云高误差的敏感性比水汽反演要高。     

利用美国NOAA卫星遥测云顶高度的数值试验

无论从气象角度还是气候角度讲,对卫星云辐射测值进行反演判释研究,从而提取诸如云顶高度、云顶温度、云的放射率、云厚以及云的含水量等参数都十分必要。本文主要介绍用NOAA卫星红外和微波通道测值,按其辐射率差比方法,定量判释两层云高的初步数值试验结果。经与地面实况对照分析表明:适当选择两组探测通道组合可以遥感两层云高,但还不能判释出中云和低云并存时各自的高度。     

卫星(IASI 探测仪)观测云顶高与地基云雷达观测的对比验证

IASI（Infrared Atmospheric Sounding Interferometer）是搭载在欧洲METOP-A 卫星上,采用干涉分光技术的新一代超高光谱红外大气探测仪器,其光谱测量范围涵盖了多个吸收带,可用于反演大气、海洋、云和大气成分,为地球大气遥感、气象业务和科学研究提供了丰富的遥感资料,是各国学者关注的又一热点。为深入了解IASI 在国内的云产品情况,本文利用2008 年10 月15 日～12 月15 日期间IASI 在安徽寿县地区的云参数观测资料和中美 [美国能源部大气辐射测量（ARM）计划] 联合在安徽省寿县进行大气辐射综合观测试验期间,相同时段云雷达[ARM W-band（95 GHz）Cloud Radar,WACR]的观测资料进行了对比分析和验证。在以寿县ARM 移动观测设施（AMF）为中心,半径为20 km 的范围内,IASI（2 次/d）共有有效观测129 次,其中与WACR（1 次/2 s）匹配的IASI 有效观测共80 时次。结果表明:对于单层云,二者云高相关系数为0.8312,标准差为1.8423 km;对于双层及多层云,IASI 反演云顶高结果绝大多数在WACR 的最上和最下层云之间,且靠近较厚的云层。对比结果显示,一般情况下,IASI 反演云顶高结果明显低于WACR;IASI 反演云顶高结果受到视场中云量、云层厚度及云层中粒子浓度大小的影响:视场中云量越大,云层越厚,云层中粒子浓度越大,IASI 反演云高的结果越接近真实云高。     

FY-2C静止气象卫星资料对不透明云云顶气压的反演研究

采用红外窗区通道法尝试对FY-2C静止气象卫星图像上的不透明云的云顶气压进行反演,并结合MODIS反演产品和CloudSat/CPR雷达探测产品对反演结果进行对比分析。结果表明:（1） 对于厚实密蔽的云层,不透明云云顶气压的反演结果与MODIS反演结果一致性较好,特别是对于发展较强的对流云和厚实密蔽的多层云,易满足云层比辐射率近似为1的条件,可近似看作黑体;（2） 对于单层云和光学厚度不够厚的云层,反演结果更接近辐射中心,尤其是对于锋面云带暖水云上空覆盖卷云的情况,由于FY-2C对于薄卷云的检测不如MODIS细致,导致反演结果与MODIS和CloudSat存在一定偏差。      

FY 2F卫星和毫米波云雷达云高观测的个例对比分析

风云二号静止卫星上装载有可见光、水汽、中长波红外等探测通道,其中红外通道资料可提供卫星云顶温度数据。基于FY-2F静止卫星云顶温度资料,结合局地实时探空数据对北京南郊和朝阳站点上空云层进行云高反演,并展开与地基毫米波云雷达探测云顶高关系的对比,分析3种不同云厚(薄云、适中、厚云)条件下的云高观测结果。研究结果表明,二者云顶高匹配度受几何云厚的影响,其吻合度呈现出厚云最佳,薄云最差的特征。     

利用FY-2C卫星数据反演云辐射特性

本文利用FY-2C静止卫星提供的可见光、中红外和热红外观测数据, 开展了水云光学厚度、粒子有效半径和云顶温度的云参数遥感探测理论和反演方法研究。基于FY-2C可见光、中红外(3.75 μm)与热红外(11 μm)通道辐射率对云光学厚度、 云滴有效半径、云顶温度辐射参数的敏感性分析, 提出三通道同时反演云的光学厚度、云滴有效半径及云顶温度的迭代方案; 通过个例分析进行了云参数反演试验, 并将结果与MODIS的云反演产品进行了对比, 最后对反演误差进行了分析。主要结论如下:(1) 个例反演得到的云参数与各通道探测数据有着较好的对应关系, 迭代计算标准偏差在允许的计算精度范围内(<0.89%), 反演结果具有合理性; (2) 通过与MODIS云反演产品的对比可以看到, 两者云光学厚度、云滴有效半径的均值和直方图分布都非常一致, 而MODIS的云顶温度比FY-2C反演值要高, 考虑到FY-2C的 11 μm通道测量的辐射值与MODIS相比偏小, 因此认为我们的反演方法与MODIS方法的精度是相当的。     

基于MODIS云宏微观特性的卫星云分类方法

利用MODIS云光学厚度、云粒子有效半径、云顶高度、云相态等产品,以及表征6种云类的云光学厚度、云粒子有效半径、云顶高度、云相态的特征值,采用最小距离分类法和多阈值判识法相结合,对卫星观测像元的云进行分类,包括层云、层积云、积云、积雨云、雨层云、高积云/高层云、卷云以及卷云伴随高积云或高层云的多层云、卷云伴随层云或层积云的多层云、高积云或高层云伴随层积云或层云的多层云10类。2008年、2013年卫星分类结果与地面站云类观测对比,达到60%的一致性;将相同时间的地面小时降水量与分类结果叠加显示,出现降水处多为雨层云或积雨云。     

基于CloudSat云分类资料的华北地区云宏观特征分析

利用2007年1月至2008年12月的CloudSat 2B-CLDCLASS-LIDAR云分类资料对华北地区(36°~42°N,110°~120°E)各类云在单层及多层云中的出现频率、平均高度及平均厚度进行统计分析。结果表明:华北地区单层云和多层云出现频率存在明显的季节变化,夏季最大,春秋次之,冬季最小。单层云的出现频率远高于多层云,单层云出现频率在春、夏、秋、冬4个季节分别为44.3%、46.1%、37.8%和32.8%,而多层云中2层云所占比例最大。单层云和多层云各云层平均高度、平均厚度分析显示,3层云上层云顶云底高度最高,3层云下层云顶云底高度最低,单层云平均厚度明显大于多层云,云层数越多,各云层的平均厚度越小。对不同类型云出现频率分析显示,卷云主要出现在单层云及多层云中、上层,高层云和高积云在单层云和多层云各云层中均占有一定的比例,层云主要出现在多层云下层,层积云、积云、深对流云主要出现在单层云及多层云下层,雨层云主要出现在夏季单层云中。卷云、高层云、高积云的平均高度及厚度在不同云系统中存在显著的差异。     

地基热红外云高观测与云雷达及激光云高仪的相互对比

2008年5月至12月中美（美国能源部大气辐射测量（ARM）计划）联合利用ARM移动观测设施（AMF）在安徽省寿县进行了大气辐射综合观测试验,地基云参数观测仪器主要有:（1）云雷达（ARM W-band (95 GHz) Cloud Radar）,观测结果为反射率廓线,时间分辨率为2 s;（2）云高仪（Vaisala Ceilometer）,观测结果为云底高度和后向散射廓线,时间分辨率为15 s.两者均为天顶方向观测.扫描式全天空红外成像仪（SIRIS-1型）于11月27日～12月30日在寿县参加了观测,观测方式为全天空扫描,时间间隔为15分钟.三种云观测仪器共并行观测16天.利用全天空红外成像仪测得的天空红外亮温和同步观测的地面气象数据进行了等效云底高的反演.以全天空红外成像仪天顶方向观测时间前后15次云雷达反射率廓线的平均廓线,云高仪12次观测中有云时次云底高的平均值分别作为同步观测结果,利用平均反射率廓线进行了各层云的云底、云顶、回波峰值高度和回波积分值的提取和计算.三种观测仪器以10 km云底高为限,共同步观测1661次,其中云雷达、红外成像仪和云高仪分别观测到云:428,287,225次.本文分3种情况:（1）全部有云观测情况,（2）单层云,（3）双层及三层云,分别进行了三个仪器观测云高的对比.对比结果:情况（1）,云雷达与云高仪、云雷达与红外成像仪的相关系数分别为0.6和0.82;情况（2）,三者共同观测75次,云雷达与红外成像仪相关系数为0.85,与云高仪相关系数为0.53,标准差分别为0.88 和1.61 km;情况（3）,红外成像仪云底高绝大多数在云雷达观测的最上、最下层云之间,有时接近上层云,有时接近下层云.对比结果显示,地基热红外对于观测中低云高具有稳定、可靠、经济和便捷等优势,但观测结果较云雷达系统偏高.文中同时提出了初步的校正方法.     

地基双波段测云系统及其对比试验

针对地基测云系统中云在可见光波段与红外波段中表现出的不同特性,用双站数字式云高仪所测云高进行标校,结合地面实时观测天顶红外辐射亮温及地面环境参数,分析地面到云层底大气对红外辐射亮温的影响,从中发现利用天空红外辐射亮温来遥感云底高度的可行性,研发地基双波段测云系统。该系统以对流层大气的垂直温度递减率为理论基础,建立云层底到地面的温度递减梯度参数K,根据递减梯度参数反演天顶方向的云高。该算法不依赖于探空数据,通过实时定标形式得出符合仪器所在地的云底高反演公式。通过与维萨拉激光云高仪CL31进行数据对比分析得出,地基双波段测云系统反演结果具有较高的准确性。     

Cloud Base Height and Effective Cloud Emissivity Retrieval with Ground-Based Infrared Interferometer

Based on ground-based Atmospheric Emitted Radiance Interferometer (AERI) observations in Shouxian, Anhui province, China, the authors retrieve the cloud base height (CBH) and effective cloud emissivity by using the minimum root-mean-square difference method. This method was originally developed for satellite remote sensing. The high-temporal-resolution retrieval results can depict the trivial variations of the zenith clouds continu-ously. The retrieval results are evaluated by comparing them with observations by the cloud radar. The comparison shows that the retrieval bias is smaller for the middle and low cloud, especially for the opaque cloud. When two layers of clouds exist, the retrieval results reflect the weighting radiative contribution of the multi-layer cloud. The retrieval accuracy is affected by uncertainties of the AERI radiances and sounding profiles, in which the role of uncertainty in the temperature profile is dominant.     

京津冀地区夏季降水冰云和非降水冰云云特征对比分析

利用2013～2016年的Aqua MODIS卫星和CloudSat卫星的二级产品资料,对发生在京津冀地区夏季的降水冰云和非降水冰云进行了统计。基于此,对比分析了两类冰云的云类型,研究了二者在云特征参数、云层数及垂直结构上的差异,并且探究了二者在不同通道下云特征参数的相对大小。结果表明:1）京津冀地区的降水冰云以深对流云和雨层云为主,分别占48.63%和34.65%,而非降水冰云以高层云和卷云为主,分别占55.62%和31.58%。2）降水冰云和非降水冰云的平均云顶温度、云顶高度、光学厚度、积分云水总量、有效粒子半径分别为230.99 K、10.90 km、53.26、937.98 g/m2、31.45m和236.17 K、10.10 km、12.81、209.00 g/m2、27.54 μm。3）降水冰云以单层云为主,占80.39%,双层云占18.75%;而非降水冰云仍以单层云为主,占85.35%,双层云则占14.38%,比降水冰云低。4）相较于非降水冰云,降水冰云中卷云和高积云云体位置较高,而高层云和深对流云位置较低。5）随高度变化,降水冰云冰水含量是双峰结构,而非降水冰云是单峰结构;二者的粒子数浓度则差异不大;非降水冰云的粒子有效半径在5～7.5 km随高度变化不大,而降水冰云则随高度减小。6）降水冰云的积分云水总量、光学厚度和粒子有效半径>≥模态[、、分别代表该云特征参数在1.6、2.1、3.7 μm通道中的数值,当n=1, 2, 3时,分别代表光学厚度（b₁）、积分云水总量（b₂）、有效半径这三种（b₃）]的比例都高于非降水冰云,而二者在云参数≥≥模态的比例则有差异。     

Analysis of ice water path retrieval errors over tropical ocean

Retrieval of multi-layered cloud properties, especially ice water path (IWP), is one of the most perplexing problems in satellite cloud remote sensing. This paper develops a method for improving the IWP retrievals for ice-over-water overlapped cloud systems using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Visible and Infrared Scanner (VIRS) data. A combined microwave, visible and infrared algorithm is used to identify overlapped clouds and estimate IWP separately from liquid water path. The retrieval error of IWP is then evaluated by comparing the IWP to that retrieved from single-layer ice clouds surrounding the observed overlapping systems. The major IWP retrieval errors of overlapped clouds are primarily controlled by the errors in estimating the visible optical depth. Optical depths are overestimated by about 10–40% due to the influence of the underlying cloud. For the ice-over-warm-water cloud systems (cloud water temperature Tw > 273 K), the globally averaged IWP retrieval error is about 10%. This cloud type accounts for about 15% of all high-cloud overlapping cases. Ice-over-super-cooled water clouds are the predominant overlapped cloud system, accounting for 55% of the cases. Their global averaged error is 17.2%. The largest IWP retrieval error results when ice clouds occur over extremely super-cooled water clouds (Tw 6 255 K). Overall, roughly 33% of the VIRS IWP retrievals are overestimated due to the effects of the liquid water clouds beneath the cirrus clouds. To improve the accuracy of the IWP retrievals, correction models are developed and applied to all three types of overlapped clouds. The preliminary results indicate that the correction models reduce part of the retrieval error.     

CPR雷达探测北半球夏季多层云系结构统计特征分析

利用2007~2010年北半球夏季（6~8月）CloudSat卫星搭载的云廓线雷达（Cloud Profile Radar,CPR）探测结果对0°~60°N区域单层、双层和三层云系的水平分布、垂直结构特征及各云层云类组成、云水路径等物理量分布进行分析。云量的统计结果表明CPR探测的单层、双层和三层云系的云量分别为36.63%、8.26%和1.40%,云量的水平分布表明其高值区主要位于对流旺盛区域,且高值区的云层云顶高、厚度大,而低值区则多位于副热带高压区域。对不同云类的出现频率统计分析结果表明,单层云系中各云类的出现频率相近;多层云系的上层以卷云为主,下层以层积云为主。对比海陆差异发现洋面卷云和层积云的出现频率显著高于陆面,但高层云和高积云的出现频率低于陆面。云水路径分析表明,单层云系的冰水路径和液水路径均最大,而在多层云系中云层越高、厚度越大、冰水路径越大,液水路径则随着云层的降低增大。     

单层不同类型云系统的特性及高云重叠的影响

通过时空匹配主动遥感产品（2B-CLDCLASS-LIDAR）的云类型参数与被动遥感产品（Clouds and the Earth's Radiant Energy System-Single Scanner Footprint: CERES-SSF）的云宏微观物理特性和大气层顶处辐射通量参数（2007/01~2010/12），本文在全球尺度上统计分析了不同类型单层云以及高云重叠的双层云的云特性和大气层顶云辐射强迫。尽管主动和被动卫星遥感产品相互独立，但被动遥感反演的云光学厚度和云相态等参数能够合理反映不同类型云之间的差异。不同类型单层云表现出的云特性差异能进一步影响大气层顶的辐射能量收支。本文通过对比不同类型单层云的Clouds and the Earth's Radiant Energy System（CERES）视场样本数量随短波和长波云辐射强迫的分布，发现它们的高值区形状、位置和面积存在差异，反映了其各自独特的辐射特性。层积云的CERES视场样本数量密集区类似椭球结构，而其它云类型则趋于指数曲线结构。当进一步考虑高云重叠的影响时，统计结果表明:重叠的高云比高云单层状态有更蔽光和更厚的云体；高云重叠的底层云类型则比其单层状态有更透光和更薄的云体；高云重叠的双层云（除了高云重叠积云）对地气系统的净冷却效应要弱于其低层云类型单层状态。本文研究结果旨在加深理解云辐射反馈机制，并为改进模式中云重叠参数化方案提供一定观测依据。     

The First Observed Cloud Echoes and Microphysical Parameter Retrievals by China's 94-GHz Cloud Radar

By using the cloud echoes first successfully observed by China's indigenous 94-GHz SKY cloud radar, the macrostructure and microphysical properties of drizzling stratocumulus clouds in Anhui Province on 8 June2013 are analyzed, and the detection capability of this cloud radar is discussed. The results are as follows.(1) The cloud radar is able to observe the time-varying macroscopic and microphysical parameters of clouds,and it can reveal the microscopic structure and small-scale changes of clouds.(2) The velocity spectral width of cloud droplets is small, but the spectral width of the cloud containing both cloud droplets and drizzle is large. When the spectral width is more than 0.4 m s-1, the radar reflectivity factor is larger(over –10 dBZ).(3) The radar's sensitivity is comparatively higher because the minimum radar reflectivity factor is about–35 dBZ in this experiment, which exceeds the threshold for detecting the linear depolarized ratio(LDR) of stratocumulus(commonly –11 to –14 dBZ; decreases with increasing turbulence).(4) After distinguishing of cloud droplets from drizzle, cloud liquid water content and particle effective radius are retrieved. The liquid water content of drizzle is lower than that of cloud droplets at the same radar reflectivity factor.     

A validation of the multivariate and minimum residual method for cloud retrieval using radiance from multiple satellites

The Multivariate and Minimum Residual(MMR) cloud detection and retrieval algorithm, previously developed and tested on simulated observations and Advanced Infrared Sounder radiance, was explored and validated using various radiances from multiple sensors. For validation, the cloud retrievals were compared to independent cloud products from Cloud Sat, MODIS(Moderate Resolution Imaging Spectroradiometer), and GOES(Geostationary Operational Environmental Satellites). We found good spatial agreement within a single instrument, although the cloud fraction on each pixel was estimated independently. The retrieved cloud properties showed good agreement using radiances from multiple satellites, especially for the vertically integrated cloud mask. The accuracy of the MMR scheme in detecting mid-level clouds was found to be higher than for higher and lower clouds. The accuracy in retrieving cloud top pressures and cloud profiles increased with more channels from observations. For observations with fewer channels, the MMR solution was an "overly smoothed" estimation of the true vertical profile, starting from a uniform clear guess. Additionally, the retrieval algorithm showed some meaningful skill in simulating the cloudy radiance as a linear observation operator, discriminating between numerical weather prediction(NWP) error and cloud effects. The retrieval scheme was also found to be robust when different radiative transfer models were used. The potential application of the MMR algorithm in NWP with multiple radiances is also discussed.     

Observational Diagnosis of Cloud Phase in the Winter Antarctic Atmosphere for Parameterizations in Climate Models

The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instruments for the period 2000--2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months (June, July, and August) reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0oC. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs (》-40oC) for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.