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.     

Diagnosis and testing of low-level cloud parameterizations for the NCEP/GFS model using satellite and ground-based measurements

The objective of this study is to investigate the quality of clouds simulated by the National Centers for Environmental Prediction global forecast system (GFS) model and to examine the causes for some systematic errors seen in the simulations through use of satellite and ground-based measurements. In general, clouds simulated by the GFS model had similar spatial patterns and seasonal trends as those retrieved from passive and active satellite sensors, but large systematic biases exist for certain cloud regimes especially underestimation of low-level marine stratocumulus clouds in the eastern Pacific and Atlantic oceans. This led to the overestimation (underestimation) of outgoing longwave (shortwave) fluxes at the top-of-atmosphere. While temperature profiles from the GFS model were comparable to those obtained from different observational sources, the GFS model overestimated the relative humidity field in the upper and lower troposphere. The cloud condensed water mixing ratio, which is a key input variable in the current GFS cloud scheme, was largely underestimated due presumably to excessive removal of cloud condensate water through strong turbulent diffusion and/or an improper boundary layer scheme. To circumvent the problem associated with modeled cloud mixing ratios, we tested an alternative cloud parameterization scheme that requires inputs of atmospheric dynamic and thermodynamic variables. Much closer agreements were reached in cloud amounts, especially for marine stratocumulus clouds. We also evaluate the impact of cloud overlap on cloud fraction by applying a linear combination of maximum and random overlap assumptions with a de-correlation length determined from satellite products. Significantly better improvements were found for high-level clouds than for low-level clouds, due to differences in the dominant cloud geometry between these two distinct cloud types.     

A Comparison of Cloud Layers from Ground and Satellite Active Remote Sensing at the Southern Great Plains ARM Site

Using the data collected over the Southern Great Plains ARM site from 2006 to 2010, the surface Active Remote Sensing of Cloud(ARSCL) and Cloud Sat-CALIPSO satellite(CC) retrievals of total cloud and six specified cloud types [low, mid–low(ML), high–mid–low(HML), mid, high–mid(HM) and high] were compared in terms of cloud fraction(CF), cloud-base height(CBH), cloud-top height(CTH) and cloud thickness(CT), on different temporal scales, to identify their respective advantages and limitations. Good agreement between the two methods was exhibited in the total CF. However, large discrepancies were found between the cloud distributions of the two methods at a high(240-m) vertical grid spacing. Compared to the satellites, ARSCL retrievals detected more boundary layer clouds, while they underestimated high clouds. In terms of the six specific cloud types, more low- and mid-level clouds but less HML- and high-level clouds were detected by ARSCL than by CC. In contrast, the ARSCL retrievals of ML- and HM-level clouds agreed more closely with the estimations from the CC product. Lower CBHs tended to be reported by the surface data for low-, ML- and HML-level clouds; however, higher CTHs were often recorded by the satellite product for HML-, HM- and high-level clouds. The mean CTs for low- and ML-level cloud were similar between the two products; however, the mean CTs for HML-, mid-, HM- and high-level clouds from ARSCL were smaller than those from CC.     

基于CALIPSO卫星资料的京津冀地区MODIS卷云云顶高度订正

卷云在大气辐射中扮演着重要角色,对天气系统和气候变化产生重要影响。相比传统地基观测手段,卫星遥感更容易探测到高层卷云的信息,本文利用CALIOP主动遥感仪器可获取较为准确的薄卷云特性的特点,针对MODIS被动遥感探测器反演的薄卷云云顶高度的偏差开展订正研究。研究选取2013～2017年京津冀地区MODIS云产品,结合CALIPSO卫星的卷云云顶高度数据,基于交叉验证的方法得到线性拟合方案,对MODIS卷云云顶高度进行订正。订正后的MODIS与CALIPSO卷云云顶高度差值的分布区间由?3～2 km变为?2.0～2.5 km,峰值由?0.8 km左右变为0.2 km左右。订正效果随云顶高度和云光学厚度的不同有所变化,其中较低层卷云和光学薄卷云的订正效果更明显。     

NCEP 全球预报系统在ARM SGP站点预报大气温度、湿度和云量的检验

利用美国大气辐射测量项目(ARM)制作的“气候模拟最佳估计”(CMBE)观测数据集,检验美国环境预报中心(NCEP)全球预报系统(GFS)2001～2008年在ARM Southern Great Plains(SGP)站点预报的大气温度、相对湿度和云量的垂直分布,主要结论如下:(1)NCEP GFS较好地预报出了温度...     

Comparison of model predicted cloud parameters and surface radiative fluxes with observations on the 100 km scale

Summary Cloud parameters and surface radiative fluxes predicted by regional atmospheric models are directly compared with observations for a 10-day period in late summer 1995 characterized by predominantly large-scale synoptic conditions. Observations of total cloud cover and vertical cloud structure are inferred from measurements with a ground-based network of Lidar ceilometers and IR-radiometers and from satellite observations on a 100 kilometer scale. Ground-based observations show that at altitudes below 3 km, implying liquid water clouds, there is a considerable portion of optically non-opaque clouds. Vertical distributions of cloud temperatures simultaneously inferred from the ground-based infrared radiometer network and from satellite can only be reconciled if the occurrence of optically thin cloud structures at mid- and high tropospheric levels is assumed to be frequent. Results of three regional atmospheric models, i.e. the GKSS-REMO, SMHI-HIRLAM, and KNMI-RACMO, are quantitatively compared with the observations. The main finding is that all models predict too much cloud amount at low altitude below 900 hPa, which is then compensated by an underestimation of cloud amount around 800 hPa. This is likely to be related with the finding that all models tend to underestimate the planetary boundary layer height. All models overpredict the high-level cloud amount albeit it is difficult to quantify to what extent due to the frequent presence of optically thin clouds. Whereas reasonably alike in cloud parameters, the models differ considerably in radiative fluxes. One model links a well matching incoming solar radiation to a radiatively transparent atmosphere over a too cool surface, another model underpredicts incoming solar radiation at the surface due to a too strong cloud feedback to radiation, the last model represents all surface radiative fluxes quite well on average, but underestimates the sensitivity of atmospheric transmissivity to cloud amount. Received August 31, 2000 Revised March 15, 2001     

Stratiform Cloud—Inversion Characterization During the Arctic Melt Season

Data collected during July and August from the Arctic Ocean Experiment 2001 illustrated a common occurrence of specific-humidity (q) inversions, where moisture increases with height, coinciding with temperature inversions in the central Arctic boundary layer and lower troposphere. Low-level stratiform clouds and their relationship to temperature inversions are examined using radiosonde data and data from a suite of remote sensing instrumentation. Two low-level cloud regimes are identified: the canonical case of stratiform clouds, where the cloud tops are capped by the temperature inversion base (CCI—Clouds Capped by Inversion) and clouds where the cloud tops were found well inside the inversion (CII—Clouds Inside Inversion). The latter case was found to occur more than twice as frequently than the former. The characteristic of the temperature inversion is shown to have an influence on the cloud regime that was supported. Statistical analyses of the cloud regimes using remote sensing instruments suggest that CCI cases tend to be dominated by single-phase liquid cloud droplets; radiative cooling at the cloud top limits the vertical extent of such clouds to the inversion base height. The CII cases, on the other hand, display characteristics that can be divided into two situations—(1) clouds that only slightly penetrate the temperature inversion and exhibit a microphysical signal similar to CCI cases, or (2) clouds that extend higher into the inversion and show evidence of a mixed-phase cloud structure. An important interplay between the mixed-phase structure and an increased potential for turbulent mixing across the inversion base appears to support the lifetime of CII cases existing within the inversion layer.     

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。      

Examinations of cloud variability and future change in the coupled model intercomparison project phase 3 simulations

Low-level cloud variability is critical to the radiation balance of Earth due to its wide spatial coverage. Using the adjusted International Satellite Cloud Climatology Project (ISCCP) observations of Clement et al. (2009), and the Coupled Model Intercomparison Project Phase 3 (CMIP3) model simulations, this study examines the observed and the simulated low-cloud variations and their relationships with large-scale environmental variables. From the observational analysis, significant correlations are found between low clouds and those of sea surface temperature (SST), lower tropospheric stability (LTS), and sea level pressure (SLP) over tropical marine areas of low cloud prevailing regions during most of the year. Increase of SST coincides with the reduction of LTS and increased vertical motion, which tends to reduce low-level clouds in subtropical oceans. Among the 14 models investigated, CGCM3 and HadGEM1 exhibit more realistic representation of the observed relationship between low-level clouds and large-scale environments. In future climate projection, these two models show a good agreement in the reduction of low-cloud throughout much of the global oceans in response to greenhouse gas forcing, suggesting a positive low-cloud feedback in a climate change context.     

华北太行山东麓一次稳定性积层混合云飞机观测研究:对流云/对流泡和融化层结构特征

对云中微物理过程的研究是研究云降水形成过程和人工影响降水的重要基础,目前对积层混合云的对流区/对流泡中的微物理结构了解甚少。本文利用河北省“十三五”气象重点工程——云水资源开发利用工程的示范项目（2017～2019年）“太行山东麓人工增雨防雹作业技术试验”飞机和地面雷达观测数据,重点分析研究了2017年5月22日一次典型稳定性积层混合云对流泡和融化层的结构特征。研究结果表明,此次积层混合云高层存在高浓度大冰粒子,冰粒子下落过程中的增长在不同区域存在明显差异,在含有高过冷水含量的对流泡中,冰粒子增长主要是聚并和凇附增长,而在过冷水含量较低的云区以聚并增长为主。由于聚并增长形成的大冰粒子密度低,下落速度小,穿过0℃层时间更长,出现大量半融化的冰粒子,使融化现象更为明显。镶嵌在层状云中的对流泡一般处于0℃～-10℃（高度4～6 km）层之间,垂直和水平尺度约2 km,最大上升气流速度可达5 m s-1。对流泡内平均液态水含量是周围云区的2倍左右,小云粒子平均浓度比周围云区高一个量级,大粒子（直径800 μm以上）的浓度也更高。在具有较高过冷水含量的对流泡中降水形成符合“播撒—供给”机制,但在过冷水含量较低的区域并不符合这一机制。     

基于WRF模式和CloudSat卫星资料对黄淮下游一次强对流天气过程的诊断分析和数值模拟

利用Cloud Sat卫星资料和WRF中尺度模式,结合NCEP再分析资料及FY2G静止气象卫星资料,研究了发生在黄淮地区的一次深对流天气过程,分析了此次过程的天气特征、动力结构,重点分析了该次强对流过程中各水成物的时空演变特征。结果表明:(1)黄淮下游地区处于副高西北边缘,温度高,湿度大,对流潜势好。在地面冷锋和低层切变线的抬升触发下,气流不断辐合上升,同时高层冷平流与低层暖湿空气为强对流的发展提供了热力不稳定条件;(2)使用静止卫星TBB产品可以很好的定位、追踪深对流系统,但单一的TBB产品无法分辨深对流云和较厚的高云。本文结合Cloud Sat卫星资料和TBB产品把剖面上的云分为3种:非对流云(NDC),一般深对流云(DC),深对流核(DCC);(3)深对流云核(DCC)位于对流系统南部边缘,在3种云中DCC中冰相粒子粒径大、数浓度多、冰水含量大,且其最大值区域都位于12 km高度附近,这一区域可能是对流云内冰晶凝华增长、凇附增长、聚并增长形成大冰相粒子的关键发生区;(4)耦合了NSSL双参方案的WRF模式对于本次过程体现了较好的模拟效果,并通过模拟再现了此次天气过程中水成物的分布特征,发现本次过程深对流云中存在过冷水累积带特征。冰核核化形成的冰晶通过碰并过程形成雪晶,霰又由雪晶碰撞冻结过冷水滴以及过冷雨滴冻结产生,之后不断增长转化形成冰雹,雹增长到足够大后降落,其中雪晶和过冷水累积带对霰(雹胚)及雹的产生及增长至关重要。     

Springtime cloud properties in the Taiwan Strait: synoptic controls and local processes

This paper examines the springtime cloud properties in the Taiwan Strait (TS), with emphases on their dependence on synoptic controls and local processes, using a suite of in situ and remote sensing observations. Cloud properties in the TS are inferred from a combination of MODIS and in situ observations and further classified into two synoptic conditions: continental cold air surge and frontal system. The study reveals a predominance of synoptic-scale controls in regulating the cloud properties in the TS. The sensitivity of clouds to the local thermodynamic mechanisms as well as the underlying surface conditions is fundamentally dependent on synoptic-scale flow patterns. The springtime clouds over the TS are commonly a mixture of stratocumulus and alto clouds. More precisely, there is a preponderance of stratocumulus over the strait. A preferential occupancy of stratiform alto clouds is recognized during cold air surge, whereas vertical development of cloud layers (mostly the stratocumulus) is commonly observed with frontal passage. The most distinct difference between the local clouds formation associated with the two synoptic conditions is the suppression of very low cloud and fog along with cold air surge. Stratus clouds and fog are present within the northward prefrontal airflow from warmer to colder water sites, along with an increase in stability relating to lower altitudes of boundary layer clouds. Although the rainfall occurrences are about the same for both synoptic conditions, the frontal rain amounts are larger on average.     

Cloud Classification and Distribution of Cloud Types in Beijing Using Ka-Band Radar Data

A cloud clustering and classification algorithm is developed for a ground-based Ka-band radar system in the vertically pointing mode. Cloud profiles are grouped based on the combination of a time–height clustering method and the k-means clustering method. The cloud classification algorithm, developed using a fuzzy logic method, uses nine physical parameters to classify clouds into nine types: cirrostratus, cirrocumulus, altocumulus, altostratus, stratus, stratocumulus, nimbostratus,cumulus or cumulonimbus. The performance of the clustering and classification algorithm is presented by comparison with all-sky images taken from January to June 2014. Overall, 92% of the cloud profiles are clustered successfully and the agreement in classification between the radar system and the all-sky imager is 87%. The distribution of cloud types in Beijing from January 2014 to December 2017 is studied based on the clustering and classification algorithm. The statistics show that cirrostratus clouds have the highest occurrence frequency(24%) among the nine cloud types. High-level clouds have the maximum occurrence frequency and low-level clouds the minimum occurrence frequency.     

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.     

中尺度强暴雨云团云特征的多种卫星资料综合分析

针对2002年6月23—27日发生于江淮地区的一次中尺度强暴雨过程，利用FY-1D，EOS和NOAA卫星的可见光、红外、微波通道遥感观测、反演资料，从相态、光学厚度、垂直结构等各方面分析云特征，并将分析结果与同时段地面雨量观测进行对比分析，发现云光学厚度大且云顶粒子为大粒子、冰相态是此次降雨过程中云团的主要云特征，地面雨量的大小与云光学厚度密切相关，两者间基本呈正相关关系；稳定少变的大光学厚度云或云光学厚度显著增大均可带来强的地面降水。微波资料可以很好地体现降雨云团的垂直结构。分析结果显示，卫星遥感对揭示中尺度强暴雨云团的云特征，具有很好的指示作用。     

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。     

Characterization of cloud microphysical properties in different cloud types over East Asia based on CloudSat/CALIPSO satellite products

利用CloudSat/CALIPSO卫星资料,本文揭示了东亚三个代表性区域的云微物理属性,为评估和改进模式云微物理过程提供重要的观测基础.研究的云微物理量包括云水/冰质量,数浓度和有效半径.研究表明:暖云中云水质量和数浓度随高度增加而减小,有效半径处于8-14μm范围.对于冰云,云冰质量和有效半径随高度增加而减小,而数浓度在垂直方向上变化不大.此外,云微物理属性在不同云型之间存在显著差异:积云的云水质量和数浓度最大,而卷云的云水质量和数浓度最小.从三个区域的对比结果来看,相比于华东和西北太平洋地区,青藏高原地区暖云的云水质量和数浓度较小,而冰云的则较大.     

Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies(GISS) Model E2 atmospheric general circulation model(GCM; post-CMIP5,hereafter P5). In this study, single column model(SCM P5) simulated cloud fractions(CFs), cloud liquid water paths(LWPs)and precipitation were compared with Atmospheric Radiation Measurement(ARM) Southern Great Plains(SGP) groundbased observations made during the period 2002–08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase(10%–20%) but precipitation increased significantly(56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.     

FGOALS2两个模式版本对青藏高原东侧冬季层云的模拟特征

冬季青藏高原东部（22°N～32°N，102°E～118°E）层云区是唯一存在于副热带陆地的层云密集区，环流特征较为复杂，大多数耦合气候系统模式对该地区层云的模拟存在较大的偏差。对该地区层云模拟能力的系统分析评估是改进模式性能的重要基础。本文基于国际卫星云计划（ISCCP）卫星资料，评估了中国科学院大气物理研究所两个版本的气候系统模式FGOALS-s2和FGOALS-g2的大气环流模式试验（AMIP）对青藏高原东侧层云的模拟能力。通过分析云辐射强迫等相关特征、大气环流、稳定度、以及地表气温和云的关系，探讨了模式偏差的可能原因。结果表明，两个模式都不同程度地低估了青藏高原东侧的低层云量和云水含量。在垂直结构模拟方面，FGOALS-s2模式能较好地模拟出高原东侧低云主导的特征，其模拟的云顶高度与卫星资料更为接近；而FGOALS-g2模式则高估了该地区的平均云顶高度。分析表明，两个模式均低估了高原东侧的低层稳定度，同时不同程度地低估了该地区中低层水平水汽输送，导致层云云量的模拟偏少。此外，FGOALS-g2高估了高原东侧的上升运动和垂直水汽输送，使得模拟的低云偏少而云顶高度偏高。