测量云液水柱含量的一个设想

云液态水柱含量是一个重要的气象学和云雾物理参数.对于云液水柱含量测量已发展了多种技术,但由于云在时空上变化很大,目前地基、飞机以及卫星测量的全部资料,都不能满足数值天气预报、人工增雨及气候变化研究等方面的工作需要.作者提出一种测云水的新方法,即从卫星-地面的微波衰减来确定云水(斜)柱量,并研究了此方法中的测量通道选择及测量方式问题,进行了初步的误差分析研究.结果表明,此方法在现有技术条件下可行,云水的测量精度不难达到20%～30%的水平.与卫星被动微波遥感结合起来,可获得精度更高的云水全球分布资料.     

中国及其周边地区多种水凝物资料的气候态特征比较

对云的水凝物含量进行研究有利于认识云的辐射性质和强迫效应,以及改善模式的预报性能。利用目前几种较为常用的卫星观测资料（ISCCP、MODIS和CloudSat）和再分析资料（CFSR和ERA-Interim）,对中国及其周边地区的多种水凝物变量,包括积分的云水路径、液水路径和冰水路径,以及分层的液态水含量和冰水含量的气候态水平及垂直分布特征进行了比较研究。结果表明,在总的水凝物含量方面,无论是描述整个中国及其周边地区的水平分布特征和主要变化模态,还是不同海陆区域的月变化特点,MODIS、ERA和CFSR三种资料都显示出较高的一致性,而ISCCP的绝对数值和变化幅度与它们均存在一定差异。在液态水含量方面,无论是水平还是垂直分布,ERA-Interim都有最高的数值,作为观测数据的MODIS和ISCCP则显著偏低。对于冰水含量,不同资料间无论是水平和垂直分布形式还是具体数值都存在明显差异。通过分析不同水凝物资料间气候态分布的差异性特征,有利于认识目前常用的几种水凝物资料的“不确定性”程度,从而更好地估计云的辐射效应,以及理解其在气候变化中所扮演的角色。      

Cloud vertical distribution from radiosonde,remote sensing,and model simulations

Knowledge of cloud vertical structure is important for meteorological and climate studies due to the impact of clouds on both the Earth’s radiation budget and atmospheric adiabatic heating. Yet it is among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product over the Southern Great Plains and along with ground-based and space-borne remote sensing products, use it to evaluate cloud layer distributions simulated by the National Centers for Environmental Prediction global forecast system (GFS) model. The primary objective of this study is to identify advantages and limitations associated with different cloud layer detection methods and model simulations. Cloud occurrence frequencies are evaluated on monthly, annual, and seasonal scales. Cloud vertical distributions from all datasets are bimodal with a lower peak located in the boundary layer and an upper peak located in the high troposphere. In general, radiosonde low-level cloud retrievals bear close resemblance to the ground-based remote sensing product in terms of their variability and gross spatial patterns. The ground-based remote sensing approach tends to underestimate high clouds relative to the radiosonde-based estimation and satellite products which tend to underestimate low clouds. As such, caution must be exercised to use any single product. Overall, the GFS model simulates less low-level and more high-level clouds than observations. In terms of total cloud cover, GFS model simulations agree fairly well with the ground-based remote sensing product. A large wet bias is revealed in GFS-simulated relative humidity fields at high levels in the atmosphere.     

Cloud microphysical properties in tropical convective and stratiform regions

Summary Cloud microphysical properties in tropical convective and stratiform regions are examined based on hourly zonal-mean data from a two-dimensional cloud-resolving simulation. The model is integrated for 21 days with the imposed large-scale vertical velocity, zonal wind and horizontal advections obtained from Tropical Ocean Global Atmosphere Coupled Ocean-atmosphere Response Experiment (TOGA COARE). Time-mean cloud microphysical budgets are analyzed in raining stratiform regions, convective regions, and non-raining stratiform regions, respectively. In raining stratiform regions, ice water path (IWP) and liquid water path (LWP) have similar magnitudes. The collection process contributes slightly more to the growth of raindrops than the melting processes do, and surface rain rate is higher than the raindrop-related microphysical rate, indicating that the hydrometeor convergence from the convective regions plays a role in surface rainfall processes. In convective regions, IWP is much smaller than LWP, the collection process is dominant in producing raindrops, and surface rain rate is lower than the raindrop-related microphysical rate. In non-raining stratiform regions, IWP is much larger than LWP, and the melting processes are important in maintaining the raindrop budget. The statistical analysis of hourly data suggests that the slopes of linear regression equations between IWP and LWP in three regions are different. Rain producing processes in convective regions are associated with the water cloud processes regardless of convection intensity.     

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.     

青藏高原云水气候特征分析

利用2001~2016年MODIS月平均液相云水路径（Cloud Liquid Water Path,LWP）、冰相云水路径（Cloud Ice Water Path,IWP）资料和ERA-Interim再分析等资料,分析了青藏高原空中云水的分布特征、变化趋势以及与大气环流变化和水汽输送变化的关系。结果显示,LWP和IWP的年平均分布形态与降水、可降水量对应较好,林芝地区聚集了丰富的LWP、IWP、降水量和可降水量。受印度洋季风影响,LWP和IWP存在明显的季节变化,夏季LWP和IWP最丰富,冬季最少。水汽传输和高原的动力、热力作用是影响夏季LWP和IWP分布的主要因素,夏季高原南部相对湿度大,水汽抬升强烈,促进了LWP和IWP的形成和积累。LWP和IWP随海拔高度的变化特征较为相似,3000~5500 m海拔高度区间内二者的总体变化特征与青藏高原降水的梯度变化特征一致,为随高度先较快升高后保持稳定的分布特征。青藏高原年平均和季节平均LWP和IWP在2001~2016年间均以减少趋势为主,这一变化趋势与云量和降水变化趋势一致,LWP和IWP的减少趋势与水汽输送通量散度的增加密切相关。     

APPLICATIONS OF THE CLOUDSAT TROPICAL CYCLONE PRODUCT IN ANALYZING THE VERTICAL STRUCTURE OF TROPICAL CYCLONES OVER THE WESTERN PACIFIC

Cloud profiling radar (CPR) onboard CloudSat allows for deep penetration into dense clouds/precipitation. In this study, tropical cyclones (TCs) are classified into three stages as developing, mature, and decaying. The circular TC area with the radius of 500 km is divided into five regions. The vertical structure characteristics of 94 Western Pacific TCs at different stages in different regions from June 2006 to February 2014 are statistically quantified using the CloudSat tropical cyclone overpass product (the CSTC Product). Contoured frequency by altitude diagrams (CFADs) of radar reflectivity show an arc-like feature and exhibit opposite distributions with a boundary at 5 km. Bright bands are found at this altitude, indicating melting layers. Deep convective (DC) clouds have the largest occurrence probability in the inner region, while Ci clouds occur more frequently in the outer region at 10-15 km. As clouds have the second largest vertical scale after DC clouds. Distributions of Ac, Cu, and Ns clouds at different stages have few distinctions. As the altitude increases, the ice effective radius and the distribution width parameter decrease while the particle number concentration increases. Moist static energy (MSE), cloud thickness (CT), liquid water path (LWP), ice water path (IWP), water vapor (WV), and rain rate (RR) all diminish along the radial direction and are significantly larger at the mature stage. The average value of MSE at the developing stage is larger than that at the decaying stage.     

Development and initial assessment of a new land index for microwave humidity sounder cloud detection

This paper describes a new quality control (QC) scheme for microwave humidity sounder (MHS) data assimilation. It consists of a cloud detection step and an O–B (i.e., differences of brightness temperatures between observations and model simulations) check. Over ocean, cloud detection can be carried out based on two MHS window channels and two Advanced Microwave Sounding Unit-A (AMSU-A) window channels, which can be used for obtaining cloud ice water path (IWP) and liquid water path (LWP), respectively. Over land, cloud detection of microwave data becomes much more challenging due to a much larger emission contribution from land surface than that from cloud. The current MHS cloud detection over land employs an O–B based method, which could fail to identify cloudy radiances when there is mismatch between actual clouds and model clouds. In this study, a new MHS observation based index is developed for identifying MHS cloudy radiances over land. The new land index for cloud detection exploits the large variability of brightness temperature observations among MHS channels over different clouds. It is shown that those MHS cloudy radiances that were otherwise missed by the current O–B based QC method can be successfully identified by the new land index. An O–B check can then be employed to the remaining data after cloud detection to remove additional outliers with model simulations deviated greatly from observations. It is shown that MHS channel correlations are significantly reduced by the newly proposed QC scheme.     

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.     

Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models

The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ~20% and 11%, respectively) results in relatively smaller bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.     

Application of aircraft observations over Beijing in cloud microphysical property retrievals from CloudSat

Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure.The cloud lognormal size distributions derived from 12 flights over Beijing,China,in 2008-09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals.We present the distribution parameters of stratiform cloud droplet （diameter ＜500 tm and ＜1500 μm） and discuss the effect of large particles on distribution parameter fitting.Based on three retrieval schemes with different lognormal size distribution parameters,the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations.The results showed that the liquid water content （LWC） retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006.We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009.The CloudSat cloud water path （CWP） retrievals were compared with Moderate Resolution Imaging Spectroradiometer （MODIS） liquid water path （LWP） data.The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP.These results strongly suggest that it is necessary to consider particles with diameters greater than 50 tm in CloudSat LWC retrievals.     

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8 km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10 km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5 km左右;水云有效半径在东亚地区的值分布在10 km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。     

Remote sensing of cloud liquid water

Summary A method is presented to infer cloud liquid water path (LWP in kg/m²) over the ocean from passive microwave measurements of SSM/I. The algorithm to retrieve LWP is based on simulated satellite observations. They are calculated with a radiative transfer model applied to about 3000 radiosonde ascents over the Atlantic Ocean. Since radiosonde observations do not contain direct information about cloud water and ice, these parameters are parameterized based on relative humidity and temperature using modified adiabatic liquid water density profiles. A multiple linear regression is applied to the simulated radiances and the calculated LWP to derive the algorithm. The retrieval accuracy based on the regression analysis including instrumental noise is 0.03 kg/m². Validation of the LWP-algorithm was pursued through a comparison with measurements of a ground-based 33 GHzmicrowave radiometer on board of R.V. Poseidon during the International Cirrus Experiment 1989 at the North Sea (ICE'89). The LWP values agree within the range of uncertainty caused by the different sampling characteristics of the observing systems. The retrieval accuracy for clear-sky cases determined using colocated METEOSAT data over the North Sea is 0.037 kg/m² and confirms the accuracy estimated from regression analysis for the low liquid water cases.The algorithm was used to derive maps of monthly mean LWP over the Atlantic Ocean. As an example the Octobers of the 5 years 1987–1991 were selected to demonstrate the interannual variability of LWP. The results were compared with the cloud water content produced by the climate model ECHAM-T2 from the Max-Planck-Institut Hamburg.Observations during ICE'89 were used to check the accuracy of the applied radiative transfer model. Brightness temperatures were calculated from radiosonde ascents launched during the overpass of DMSP-F8 in cloud-free situations. The channel-dependent differences range from about –2 to 3 K.The possibility to identify different cloud types using microwave and infrared observations was examined. The main conclusion is that simultaneous microwave and infrared measurements enable the separation of dense cirrus and cirrus with underlying water clouds. A classification of clouds with respect to their top heights and LWP was carried out using a combination of SSM/I derived LWP and simultaneously recorded Meteosat IR-data during ICE'89.With 11 Figures     

CONVECTIVE-STRATIFORM RAINFALL PARTITION BY RADIANCE-DERIVED CLOUD CONTENT: A MODELING STUDY

A new scheme that separates convective-stratiform rainfall is developed using threshold values of liquid water path (LWP) and ice water path (IWP). These cloud contents can be predicted with radiances at the Advanced Microwave Sounding Unit (AMSU) channels (23.8, 31.4, 89, and 150 GHz) through linear regression models. The scheme is demonstrated by an analysis of a two-dimensional cloud resolving model simulation that is imposed by a forcing derived from the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE). The rainfall is considered convective if associated LWP is larger than 1.91 mm or IWP is larger than 1.70 mm. Otherwise, the rainfall is stratiform. The analysis of surface rainfall budget demonstrates that this new scheme is physically meaningful.     

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.     

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.     

Ice microphysics and climatic temperature feedback

The potential effects of ice microphysics involving ice crystal size distribution and ice water path (IWP) on climatic temperature perturbations are investigated by using a one-dimensional radiative-turbulent climate model. We define a mean effective size, denoting the width of ice crystals weighted by the geometric cross section area, to represent ice crystal size distribution. Based on aircraft measurements, both the mean effective size and IWP are related to temperature and may be parameterized as functions of temperature. The radiative properties of cirrus clouds are further parameterized in terms of these two basic cloud physics parameters. Using CO₂ doubling as the radiative forcing, feedbacks among temperature, the mean effective size and IWP, and the radiative properties of clouds are analyzed from the model results. We show that overall, a positive feedback associated with ice microphysics and the coupled radiative transfer is produced by temperature increase.     

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。     

Evaluation of Summer Monsoon Clouds over the Tibetan Plateau Simulated in the ACCESS Model Using Satellite Products

Cloud distribution characteristics over the Tibetan Plateau in the summer monsoon period simulated by the Australian Community Climate and Earth System Simulator(ACCESS) model are evaluated using COSP [the CFMIP(Cloud Feedback Model Intercomparison Project) Observation Simulator Package]. The results show that the ACCESS model simulates less cumulus cloud at atmospheric middle levels when compared with observations from CALIPSO and CloudSat, but more ice cloud at high levels and drizzle drops at low levels. The model also has seasonal biases after the onset of the summer monsoon in May. While observations show that the prevalent high cloud at 9–10 km in spring shifts downward to 7–9 km,the modeled maximum cloud fractions move upward to 12–15 km. The reason for this model deficiency is investigated by comparing model dynamical and thermodynamical fields with those of ERA-Interim. It is found that the lifting effect of the Tibetan Plateau in the ACCESS model is stronger than in ERA-Interim, which means that the vertical velocity in the ACCESS model is stronger and more water vapor is transported to the upper levels of the atmosphere, resulting in more high-level ice clouds and less middle-level cumulus cloud over the Tibetan Plateau. The modeled radiation fields and precipitation are also evaluated against the relevant satellite observations.     

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。