An Evaluation of the Effects of Cloud Parameterization in the R42L9 GCM

Cloud is one of the uncertainty factors influencing the performance of a general circulation model (GCM). Recently, the State Key Laboratory of Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP) has developed a new version of a GCM (R42L9). In this work, roles of cloud parameterization in the R42L9 are evaluated through a comparison between two 20-year simulations using different cloud schemes. One scheme is that the cloud in the model is diagnosed from relative humidity and vertical velocity, and the other one is that diagnostic cloud is replaced by retrieved cloud amount from the International Satellite Cloud Climatology Project (ISCCP), combined with the amounts of high-, middle-, and low-cloud and heights of the cloud base and top from the NCEP. The boreal winter and summer seasonal means, as well as the annual mean, of the simulated top-of-atmosphere shortwave radiative flux, surface energy fluxes, and precipitation are analyzed in comparison with the observational estimates and NCEP reanalysis data. The results show that the scheme of diagnostic cloud parameterization greatly contributes to model biases of radiative budget and precipitation. When our derived cloud fractions are used to replace the diagnostic cloud amount, the top-of-atmosphere and surface radiation fields are better estimated as well as the spatial pattern of precipitation. The simulations of the regional precipitation, especially over the equatorial Indian Ocean in winter and the Asia-western Pacific region in summer, are obviously improved.

THE INFLUENCE OF CLOUD PARAMETERIZATION ADJUSTMENT USING REFLECTIVITY OF DOPPLER ON NOWCASTING WITH GRAPES MODEL

In this study, we attempted to improve the nowcasting of GRAPES model by adjusting the model initial field through modifying the cloud water, rain water and vapor as well as revising vapor-following rain water. The results show that the model nowcasting is improved when only the cloud water and rain water are adjusted or all of the cloud water, rain water and vapor are adjusted in the initial field. The forecasting of the former(latter) approach during 0-3(0-6) hours is significantly improved. Furthermore, for the forecast for 0-3 hours, the latter approach is better than the former. Compared with the forecasting results for which the vapor of the model initial field is adjusted by the background vapor with those by the revised vapor, the nowcasting of the revised vapor is much better than that of background vapor. Analysis of the reasons indicated that when the vapor is adjusted in the model initial field, especially when the saturated vapor is considered, the forecasting of the vapor field is significantly affected. The changed vapor field influences the circulation, which in turn improves the model forecasting of radar reflectivity and rainfall.

The Importance of the Shape Parameter in a Bulk Parameterization Scheme to the Evolution of the Cloud Droplet Spectrum during Condensation

The shape parameter of the Gamma size distribution plays a key role in the evolution of the cloud droplet spectrum in the bulk parameterization schemes. However, due to the inaccurate specification of the shape parameter in the commonly used bulk double-moment schemes, the cloud droplet spectra cannot reasonably be described during the condensation process. Therefore, a newly-developed triple-parameter condensation scheme with the shape parameter diagnosed through the number concentration, cloud water content, and reflectivity factor of cloud droplets can be applied to improve the evolution of the cloud droplet spectrum. The simulation with the new parameterization scheme was compared to those with a high-resolution Lagrangian bin scheme, the double-moment schemes in a parcel model, and the observation in a 1.5D Eulerian model that consists of two cylinders. The new scheme with the shape parameter varying with time and space can accurately simulate the evolution of the cloud droplet spectrum. Furthermore, the volume-mean radius and cloud water content simulated with the new scheme match the Lagrangian analytical solutions well, and the errors are steady, within approximately 0.2%.

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 0°C. 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 （ -40°C） 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.

Cloud Parameters Retrieved by the Bispectral Reflectance Algorithm and Associated Applications

Retrieval of cloud parameters is fundamental for descriptions of the cloud process in weather and cloud models, and is also the base for theoretical and applicational investigations on weather modification, aerosol- cloud-precipitation interaction, cloud-radiative climate effects, and so on. However, it is still difficult to ob- rain full information of cloud parameters over a wide area under the current level of science and technology. Luckily, parameters at the top of clouds can be retrieved with the satellite spectrum remote sensing, which is useful in obtaining global cloud properties. In this paper, cloud parameters retrieved by the bispectral reflectance （BSR） method and other methods developed on the basis of the BSR are briefly summarized. Recent advances in studies on the indirect effects of aerosol on cloud parameters are reviewed. The rela- tionships among cloud parameters and precipitation intensity, type, and structure are elaborated on, based upon the pixel-level merged datasets derived from daily measurements of precipitation radar and visible and infrared scanner, together with cloud parameters retrieved by the BSR. It is revealed that cloud particle effective radius and liquid water path near cloud tops are effective to identify the thickness and intensity of convective precipitating clouds. Furthermore, the differences in cloud parameters and precipitation intensity for precipitating and non-precipitating clouds over land and ocean are compared in this paper.

Daytime precipitation identification scheme based on multiple cloud parameters retrieved from visible and infrared measurements

Visible and infrared(VIR) measurements and the retrieved cloud parameters are commonly used in precipitation identification algorithms, since the VIR observations from satellites, especially geostationary satellites, have high spatial and temporal resolutions. Combined measurements from visible/infrared scanner(VIRS) and precipitation radar(PR) aboard the Tropical Rainfall Measuring Mission(TRMM) satellite are analyzed, and three cloud parameters, i.e., cloud optical thickness(COT), effective radius(Re), and brightness temperature of VIRS channel 4(BT4), are particularly considered to characterize the cloud status. By associating the information from VIRS-derived cloud parameters with those from precipitation detected by PR, we propose a new method for discriminating precipitation in daytime called Precipitation Identification Scheme from Cloud Parameters information(PISCP). It is essentially a lookup table(LUT) approach that is deduced from the optimal equitable threat score(ETS) statistics within 3-dimensional space of the chosen cloud parameters. South and East China is selected as a typical area representing land surface, and the East China Sea and Yellow Sea is selected as typical oceanic area to assess the performance of the new scheme. It is proved that PISCP performs well in discriminating precipitation over both land and oceanic areas. Especially, over ocean, precipitating clouds(PCs) and non-precipitating clouds(N-PCs) are well distinguished by PISCP, with the probability of detection(POD) near 0.80, the probability of false detection(POFD) about 0.07, and the ETS higher than 0.43. The overall spatial distribution of PCs fraction estimated by PISCP is consistent with that by PR, implying that the precipitation data produced by PISCP have great potentials in relevant applications where radar data are unavailable.

On the Radiative Properties of Ice Clouds:Light Scattering, Remote Sensing,and Radiation Parameterization

Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the singlescattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed.With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared（IR） bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed.The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models（GCMs）. The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven.

Parameterization of Longwave Optical Properties for Water Clouds

Based on relationships between cloud microphysical and optical properties, three different parameterization schemes for narrow and broad band optical properties in longwave region for water clouds have been presented. The effects of different parameterization schemes and different number of broad bands used on cloud radiative properties have been investigated. The effect of scattering role of cloud drops on longwave radiation fluxes and cooling rates in cloudy atmospheres has also been analyzed.

MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS

Clouds have important effects on the infi＇ared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3D-var （Global and Regional Assimilation and Prediction Enhanced System）, cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. Results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.

基于车载点云数据的城市道路特征目标提取与三维重构

随着现代城市交通管理、智能驾驶、城市规划和地理信息系统领域的发展,对高效、自动化的城市道路特征提取和三维重构技术的需求日益迫切。提出一种从激光点云数据中自动提取道路特征并建立三维模型的方法,该方法能够有效处理大规模复杂环境下的数据。首先通过提取路缘石描述算子来确定边界线,然后生成点云数据的地理参考图像,提取出精细化的道路标识线。接着在平滑度约束下进行杆状地物检测,再通过分类算法区分路灯和行道树。最后,分析了道路模型三维重构所需的参数,并提出一种连续四边形重建方法,实现了对道路元素的三维重构。实验结果显示,该研究方法在道路点云数据目标提取的评价精度达到92%,验证了其有效性。

The Cloud Processes of a Simulated Moderate Snowfall Event in North China

The understanding of the cloud processes of snowfall is essential to the artificial enhancement of snow and the numerical simulation of snowfall. The mesoscale model MM5 is used to simulate a moderate snowfall event in North China that occurred during 20-21 December 2002. Thirteen experiments are performed to test the sensitivity of the simulation to the cloud physics with different cumulus parameterization schemes and different options for the Goddard cloud microphysics parameterization schemes. It is shown that the cumulus parameterization scheme has little to do with the simulation result. The results also show that there are only four classes of water substances, namely the cloud water, cloud ice, snow, and vapor, in the simulation of the moderate snowfall event. The analysis of the cloud microphysics budgets in the explicit experiment shows that the condensation of supersaturated vapor, the depositional growth of cloud ice, the initiation of cloud ice, the accretion of cloud ice by snow, the accretion of cloud water by snow, the deposition growth of snow, and the Bergeron process of cloud ice are the dominant cloud microphysical processes in the simulation. The accretion of cloud water by snow and the deposition growth of the snow are equally important in the development of the snow.

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.

Impacts of an Improved Low-Level Cloud Scheme on the Eastern Pacific ITCZ-Cold Tongue Complex

A statistically-based low-level cloud parameterization scheme is introduced, modified, and applied in the Flexible coupled General Circulation Model (FGCM-O). It is found that the low-level cloud scheme makes improved simulations of low-level cloud fractions and net surface shortwave radiation fluxes in the subtropical eastern oceans off western coasts in the model. Accompanying the improvement in the net surface shortwave radiation fluxes, the simulated distribution of SSTs is more reasonably asymmetrical about the equator in the tropical eastern Pacific, which suppresses, to some extent, the development of the double ITCZ in the model. Warm SST biases in the ITCZ north of the equator are more realistically reduced, too. But the equatorial cold tongue is strengthened and extends further westward, which reduces the precipitation rate in the western equatorial Pacific but increases it in the ITCZ north of the equator in the far eastern Pacific. It is demonstrated that the low-level cloud-radiation feedback would enhance the cooperative feedback between the equatorial cold tongue and the ITCZ. Based on surface layer heat budget analyses, it is demonstrated that the reduction of SSTs is attributed to both the thermodynamic cooling process modified by the increase of cloud fractions and the oceanic dynamical cooling processes associated with the strengthened surface wind in the eastern equatorial Pacific, but it is mainly attributed to oceanic dynamical cooling processes associated with the strengthening of surface wind in the central and western equatorial Pacific.

Scaling the Microphysics Equations and Analyzing the Variability of Hydrometeor Production Rates in a Controlled Parameter Space

A set of microphysics equations is scaled based on the convective length and velocity scales. Comparisons are made among the dynamical transport and various microphysical processes. From the scaling analysis, it becomes apparent which parameterized microphysical processes present off-scaled influences in the integration of the set of microphysics equations. The variabilities of the parameterized microphysical processes are also studied using the approach of a controlled parameter space. Given macroscopic dynamic and thermodynamic conditions in different regions of convective storms, it is possible to analyze and compare vertical profiles of these processes. Bulk diabatic heating profiles for a cumulus convective updraft and downdraft are also derived from this analysis. From the two different angles, the scale analysis and the controlled-parameter space approach can both provide an insight into and an understanding of microphysics parameterizations.

CMA-GFS V4.0模式关键技术研发和业务化

针对CMA-GFS V3.3强降水预报偏弱、西北太平洋副热带高压等天气系统预报衰减偏快以及模式计算效率偏低等问题,对模式物理过程与动力框架关键技术开展研发改进。在预报性能方面,通过在云微物理方案中增加霰粒子相关的微物理过程、调整蒸发速率,并在积云对流方案中改进触发条件、卷入率、准平衡闭合假定等关键因子的参数化方法,缓解模式强降水预报不足和小雨过多的问题;采用质量守恒修正算法解决模式长时间积分质量损失问题,改善天气形势预报。在计算效率方面,研制二维参考廓线方案延长模式积分时间步长,开发预条件经典斯蒂菲尔迭代(PCSI)算法提高Helmholtz方程的求解效率,对辐射方案、预估-修正算法等进行计算效率优化。通过上述关键技术的研发和应用,CMA-GFS在降水和天气形势方面的预报技巧得到显著提升,计算效率提高1/3左右,满足模式在0.125°分辨率下业务运行的时效要求,为CMA-GFS V3.3升级到V4.0奠定了基础。

云滴谱离散度的理论、观测和数值模拟研究进展

云滴谱离散度(ε)作为衡量云滴粒子尺度分布以及离散程度的参数,在气溶胶-云-降水过程中有着重要作用。其中ε与云滴(N_(c))或背景气溶胶数浓度(N_(d))的相关关系是描述云内微物理和动力过程,以及量化气溶胶对云和降水影响的重要因子之一。很多气溶胶间接效应的研究中,未考虑云滴谱离散度带来的影响,这使得相关理论研究和模式模拟仍然具有一定的局限性。本文基于云滴谱离散度的概念,从多个方面回顾了近年来云滴谱离散度相关理论、观测和数值模拟研究进展,包括ε与N_(c)或N_(d)的相关性,云滴谱离散度对云中微物理参量和动力过程的影响机制,以及由云滴谱离散度引起的气溶胶间接效应的估算及其不确定性等。从过往研究来看,影响ε的因素很多,不仅是云滴数浓度,还包括云中的上升速度、液水含量等,甚至气溶胶的理化特性、云中的凝结、碰并、夹卷和蒸发等过程都会对ε产生不同的影响。背景气溶胶浓度的变化一定程度上会改变云滴尺度和浓度分布进而影响ε。受地区差异和云条件影响,ε与N_(c)或N_(d)的相关性存在很大差别,既有正相关也有负相关,甚至不相关。即使针对同一云团,在云的不同部位甚至云的不同发展阶段,ε可呈现出不同程度的变化。ε可通过改变暖云的云水-雨水转化效率从而对降水即第二间接效应产生影响;又可通过影响云滴有效半径从而改变云的光学特性来影响第一间接效应。不同的ε-N_(c)参数化关系会导致全球模式中间接效应的估算出现不同程度的抵消或增强,由此可导致地面气象场和降水分布发生改变。总之,ε与云中相关参量之间的关系以及对间接效应产生的影响还存在很大的不确定性,需要对背后的机理进行更加深入的研究。本文归纳总结了当前云滴谱离散度相关研究面临的问题和存在的挑战,对未来的研究重点和工作方向进行展望,部分结论可为进一步认识云滴谱离散度在气溶胶-云相互关系中的作用提供参考。

云微物理参数化对华北降雪影响的数值模拟

对发生在华北地区的一次降雪过程进行了中尺度数值模拟。结果表明,高纬强冷空气南下和低纬倒槽的水汽输送是造成这次长时间降雪过程的主要原因。采用混合方案的中尺度数值模拟表明,这次降雪天气不是对流云造成的,而是稳定性的非对流云降雪。敏感性试验也表明,采用其他积云参数化方案对模拟的降雪量基本没有影响。控制试验模拟的24h降雪量与实际观测比较吻合。模拟结果表明,当采用Dudhia简单冰相方案时,会有过多的云冰、过冷却水及雪;当采用Reisner 1混合相方案时,会有过多的云冰和雪;修改的各个Reisner 2方案对此次降雪的预报改进不大,但各个Reisner 2方案的敏感性试验中云冰混合比、过冷却水混合比和雪混合比稍微有差异。

台风“云娜”在近海强度变化及结构特征的数值研究Ⅰ:云微物理参数化对云结构及降水特征的影响

首先对AREM模式模拟的台风基本结构和云结构进行验证,检验了模拟结果的可靠性。在此基础上,设计了5组试验来研究云微物理参数化方案对台风"云娜"云结构及降水特征的影响。试验设计主要突出冰相云微物理过程、云微物理特征引发的冷却效应以及霰下落速度的重要性。结果表明:云微物理参数化过程对云的发展和降水特征的影响更为显著。各试验的水凝物分布和强度不同,降水类型和强度存在较大差异,由此引起的云中热力结构也有较大区别;在所有试验方案中,24 h降水率最大差异为52.5 mm/h。云微物理过程对云和降水特征的具体影响表现在:(1)如果不考虑雨水蒸发冷却效应,此时台风内核上升运动强度最强(达到-19 Pa/s),雨水和霰粒子增长最明显,相对于对照试验增量分别为1.8和2.5 g/kg。(2)霰和雪的融化对于螺旋雨带中雨滴的增长十分重要,但他们可能不是云墙中雨水形成的主导因子。(3)不同方案的降水模拟特征也存在较大差别,采用暖云参数化后,降水区域最小,但其中对流降水比例最大(63.19%);霰落速减半后,降水区域最大,其中非对流降水比例也最大(51.15%)。

一个统计低云方案及其在大气环流模式中应用初探

文中利用湍流耗散特征时间尺度和湍流垂直扩散系数对湍流二阶距进行参数化 ,将一个统计云方案与一阶湍流闭合方案进行耦合。基于数值试验 ,在不同的相对湿度、温度垂直梯度、以及湍流耗散特征时间尺度条件下 ,对该方案云量模拟能力的分析 ,发现该统计云方案对其采用的参数及湍流耗散特征时间尺度敏感。基于该数值模拟分析 ,修改了该统计云方案 ,并结合其他边界层积云参数化方案 ,给出了一个基于统计的低云参数化方案。将其初步应用于NCARCCM 3后发现 :该方案可以显著增强CCM 3对副热带低云的模拟能力 ,可以合理地模拟出大洋东部大陆西岸冷海域低云量大值中心 ,显示出该方案对于改进大气环流模式低云参数化具有潜在的应用前景。

三相云显式降水方案和高原东部“96.1”暴雪成因的中尺度数值模拟

对“96.1”高原暴雪天气过程进行的天气学成因分析指出 ,欧洲阻高崩溃 ,里海—咸海横槽转竖 ,槽后向南入侵青藏高原的干冷偏北气流与槽前来自孟加拉湾和中印半岛向北不断推进的强劲西南暖湿气流 ,在青藏高原东北部交汇而形成、发展并持续的切变线 ,是产生高原暴雪的中尺度天气系统。 通过将冰相云微物理过程参数化和三相云显式降水方案引入MM4而发展的中尺度模式模拟系统 ,在采用常规观测资料的条件下 ,基本上成功地模拟出了“96.1”高原暴雪中尺度切变线的生成、发展和演变结构。结果表明 ,发展和改进的该中尺度模式模拟系统可用于青藏高原复杂地形和下垫面上中尺度系统发生、发展及结构演变的数值模拟研究。 模拟的流场及诸物理场时空演变揭示 :流场辐合线与暴雪切变线时空演变一致表明 ,流场对高原中尺度系统的表征有本质上的重要性 ;散度场和涡度场相互耦合是暴雪切变线发生、发展的重要动力机制 ;垂直上升运动的加强和持续是水汽凝结和冻结成雪的必要条件 ;湿对流不稳定为暴雪提供了热力不稳定条件 ;辐合带、涡度带、上升运动区和深厚湿舌的迭置是产生暴雪的强耦合结构。模拟的暴雪带和降水量与观测分析大体一致 ,表明三相云显式降水方案基本上是合理的。