A subgrid parameterization of orographic precipitation

Summary Estimates of the impact of global climate change on land surface hydrology require climate information on spatial scales far smaller than those explicitly resolved by global climate models of today and the foreseeable future. To bridge the gap between what is required and what is resolved, we propose a subgrid-scale parameterization of the influence of topography on clouds, precipitation, and land surface hydrology. The parameterization represents subgrid variations in surface elevation in terms of probability distributions of discrete elevation classes. Separate cloud, radiative, and surface processes are calculated for each elevation class. Rainshadow effects are not treated by the parameterization; they have to be explicitly resolved by the host model. The simulated surface temperature, precipitation, and snow cover for each elevation class are distributed to different geographical locations according to the spatial distribution of surface elevation within each grid cell.The subgrid parameterization has been implemented in the Pacific Northwest Laboratory's climate version of the Penn State/NCAR Mesoscale Model. The scheme is evaluated by driving the regional climate model with observed lateral boundary conditions for the Pacific Northwest and comparing simulated fields with surface observations. The method yields more realistic spatial distributions of precipitation and snow cover in mountainous areas and is considerably more computationally efficient than achieving high resolution by the use of nesting in the regional climate model.With 17 Figures     

Evaluation of cloud and precipitation parameterization using a single-column model: A TWP-ICE case study

Cloud and precipitation parameterization schemes are evaluated, and their sensitivity to the method and/or parameters used to determine cloud physical processes is examined using a singlecolumn version of the Unified Model (SCUM). In the experiment for TWP-ICE, cloud fraction is overestimated (underestimated) in the upper (lower) troposphere due to the wet (dry) bias. The precipitation rate is well simulated during the active monsoon period, but overestimated during the suppressed monsoon and clear skies periods. In the moist convection scheme, trigger condition and entrainment process affect the lower tropospheric humidity through the impact on convective occurrence frequency and intensity, respectively. Strengthening the trigger condition and using the adaptive entrainment method alleviate the low-level dry bias. In the microphysics scheme, more large-scale precipitation is produced with prognostic rain, due to rain sedimentation considering vertical velocity of rain drop, than with diagnostic rain. Less ice/snow deposition with the prognostic two-ice category results in lower ice water content and upper-level cloud fraction than with the diagnostic splitting method for the twoice category. In the cloud macrophysics scheme, the prognostic cloud fraction and cloud/ice water content scheme produces a larger cloud fraction and more cloud/ice water content than the diagnostic scheme, mainly due to detrainment from moist convection (cloud source) that surpasses the effect of convective heating and drying (cloud sink). This affects temperature by influencing the radiative, convective, and microphysical processes. The experiment with combined modifications in cloud and precipitation schemes shows that interaction between modified moist convection and cloud macrophysics schemes results in more alleviation of the cold bias not only at the lower levels but also at the upper levels.     

Methode de representation de la turbulence associee aux precipitations dans un modele tri-dimensionnel de convection nuageuse

A method is presented for the parameterization of subgrid-scale processes in the framework of a three-dimensional micro-scale model which simulates the initiation of precipitation in the planetary boundary layer. The method uses truncated second-order moment equations which involve combinations of dynamical, thermodynamical and water variables; the water variables include water vapor, cloud droplets and rain water, with the hypothesis of a Marshall-Palmer raindrop distribution.The method is applied to the case of a trade-wind cumulus layer where water vapor content is artificially increased. As some approximations concerning the water variables are not easy to verify by experimental methods, results should be considered only as indicative; they show the extent to which a more complete parameterization of subgrid-scale processes may compensate for the inevitable lack of spatial resolution in an atmospheric boundary-layer model.     

Variability of precipitation intensity: sensitivity to treatment of moist convection in an RCM and a GCM

The present study investigates the sensitivity of the frequency distribution of precipitation rates to the closure employed in the penetrative mass flux cumulus parameterization of Zhang and McFarlane in the Canadian regional climate model (CRCM) and in the Canadian Centre for Climate Modelling and Analysis third generation global atmospheric general circulation model (AGCM3). The effects of an alternative prognostic closure for mass flux cumulus parameterization in place of the original diagnostic closure are investigated. A set of experiments is performed in which changes in the frequency distribution of precipitation rates and cloud base mass-flux are examined as a function of the parameters that define each closure scheme. The relationship between the frequency distribution of precipitation and cloud base mass flux is examined and a self-consistent relation is found when the depth of convection is taken into account. Experiments performed with the prognostic closure favor relatively strong cloud base mass-flux and deep penetrative convection with relatively more intense convective precipitation. The mean of the frequency distribution of convective precipitation is larger and the heavier events become more intense. Also, experiments performed with the prognostic closure favor less frequent convective activity. However these changes in the distribution of convective component of precipitation are generally offset by opposite changes in the distribution of the resolved large-scale component of precipitation, resulting in relatively smaller changes in total precipitation. The altered partition of precipitation between convective and large-scale components is found to alter the energy balance and the thermodynamic equilibrium structure of the troposphere. The robustness found in the CRCM results regarding the sensitivity of the frequency distribution of precipitation to changes in the closure of the deep convection parameterization is investigated by performing a similar analysis of AGCM3 simulations. A remarkable similarity of AGCM3 and CRCM results is found suggesting that the closure sensitivity identified in this study is robust.     

Evaluation of Statistical Distributions for the Parametrization of Subgrid Boundary-Layer Clouds

In numerical weather prediction and climate models, planetary boundary-layer (PBL) clouds are linked to subgrid-scale processes such as shallow convection. A comprehensive statistical analysis of large-eddy simulations (LES), obtained for warm PBL cloud cases, is carried out in order to characterize the distributions of the horizontal subgrid cloud variability. The production of subgrid clouds is mainly associated with the variability of the total water content. Nevertheless, in the case of PBL clouds, the temperature variability cannot be completely discarded and the saturation deficit, which summarizes both temperature and total water fluctuations, provides a better representation of the cloud variability than the total water content. The probability density functions (PDFs) of LES saturation deficit generally have the shape of a main asymmetric bell-shaped curve with a more or less distinct secondary maximum specific to each type of PBL clouds. Unimodal theoretical PDFs, even those with a flexible skewness, are not sufficient to correctly fit the LES distributions, especially the long tail that appears for cumulus clouds. They do not provide a unified approach for all cloud types. The cloud fraction and the mean cloud water content, diagnosed from these unimodal PDFs, are largely underestimated. The use of a double Gaussian distribution allows correction of these errors on cloud fields and provides a better estimation of the cloud-base and cloud-top heights. Eventually, insights for the design of a subgrid statistical cloud scheme are provided, in particular a new formulation for the weight of the two Gaussian distributions and for the standard deviation of the convective distribution.     

Cloud-radiation feedbacks in a general circulation model and their dependence on cloud modelling assumptions

The general circulation model (GCM) used in this study includes a prognostic cloud scheme and a rather detailed radiation scheme. In a preceding paper, we showed that this model was more sensitive to a global perturbation of the sea surface temperatures than most other models with similar physical parametrization. The experiments presented here show how this feature might depend on some of the cloud modelling assumptions. We have changed the temperature at which the water clouds are allowed to become ice clouds and analyzed separately the feedbacks associated with the variations of cloud cover and cloud radiative properties. We show that the feedback effect associated with cloud radiative properties is positive in one case and negative in the other. This can be explained by the elementary cloud radiative forcing and has implications concerning the use of the GCMs for climate sensitivity studies.     

Cirrus cloud horizontal and vertical inhomogeneity effects in a GCM

Summary A set of the inhomogeneity factor for high-level clouds derived from the ISCCP D1 dataset averaged over a five-year period has been incorporated in the UCLA atmospheric GCM to investigate the effect of cirrus cloud inhomogeneity on climate simulation. The inclusion of this inhomogeneous factor improves the global mean planetary albedo by about 4% simulated from the model. It also produces changes in solar fluxes and OLRs associated with changes in cloud fields, revealing that the cloud inhomogeneity not only affects cloud albedo directly, but also modifies cloud and radiation fields. The corresponding difference in the geographic distribution of precipitation is as large as 7 mm day⁻¹. Using the climatology cloud inhomogeneity factor also produces a warmer troposphere related to changes in the cloudiness and the corresponding radiative heating, which, to some extent, corrects the cold bias in the UCLA AGCM. The region around 14 km, however, is cooler associated with increase in the reflected solar flux that leads to a warmer region above. An interactive parameterization for mean effective ice crystal size based on ice water content and temperature has also been developed and incorporated in the UCLA AGCM. The inclusion of the new parameterization produces substantial differences in the zonal mean temperature and the geographic distribution of precipitation, radiative fluxes, and cloud cover with respect to the control run. The vertical distribution of ice crystal size appears to be an important factor controlling the radiative heating rate and the consequence of circulation patterns, and hence must be included in the cloud-radiation parameterization in climate models to account for realistic cloud processes in the atmosphere.     

THE LIMITATION OF CLOUD-BASE MASS FLUX IN CUMULUS PARAMETERIZATION AND ITS APPLICATION IN A HIGH-RESOLUTION MODEL

A large area of unrealized precipitation is produced with the standard convective parameterization scheme in a high-resolution model, while subgrid-scale convection that cannot be explicitly resolved is omitted without convective parameterization. A modified version of the convection scheme with limited mass flux at cloud base is introduced into a south-China regional high-resolution model to alleviate these problems. A strong convection case and a weak convection case are selected to analyze the influence of limited cloud-base mass flux on precipitation forecast. The sensitivity of different limitation on mass flux at cloud base is also discussed. It is found that using instability energy closure for Simplified Arakawa- Schubert Scheme will produce better precipitation forecast than the primary closure based on quasi-equilibrium assumption. The influence of the convection scheme is dependent on the upper limit of mass flux at cloud base. The total rain amount is not so sensitive to the limitation of mass flux in the strong convection case as in the weak one. From the comparison of two different methods for limiting the cloud-base mass flux, it is found that shutting down the cumulus parameterization scheme completely when the cloud-base mass flux exceeds a given limitation is more suitable for the forecast of precipitation.     

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     

GRAPES-Meso模式浅对流云辐射效应的改进试验

在万子为等（2015）对GRAPES-Meso模式浅对流参数化改进的基础上,进一步引入了浅对流云量诊断计算,并设计旨在完善浅对流云辐射效应的浅云云量和云中水凝物的补偿方案,以改进模式低层云量偏少和浅对流云辐射效应不足的问题。通过对数值试验结果的诊断和对比分析以及与观测的比较,重点考察了浅对流云量计算与浅对流激发的协调性、浅对流云对低云补偿后所产生的辐射效应以及对模式地面要素预报的影响等,验证了改进方案的合理性与有效性。结果表明:（1）浅对流云量诊断计算合理,其云覆盖区与浅对流激发区相吻合,引入浅对流云量的计算可减小模式云量的计算偏差、使其向观测结果靠近;（2）改进方案在浅对流发生区低层0.5-4 km高度范围内,对影响模式云辐射过程的浅云云量和云中水凝物形成有效补偿,最明显的浅云补偿在1-1.5 km高度处,浅对流活跃时期浅对流过程对浅云水凝物（云水和雨水之和）的补偿量可达20%-55%;（3）云光学厚度对浅云水凝物的补偿响应合理,即水凝物的补偿引起云光学厚度增大,两者的变化特征在时空分布上十分相似,且云光学厚度之变化受云水补偿的影响比受雨水补偿的影响更明显;（4）在白天时段,浅云补偿所产生的辐射效应使模式地表太阳总辐射有所下降,缩小了与观测的偏差,进而使地表温度和地面2 m气温模拟偏差减小。改进方案在缓解模式云量偏少、地表太阳总辐射偏强和地面2 m气温偏高等方面的作用,在批量试验中得到了验证。      

Climate sensitivity of the NCAR Community Climate Model (CCM2) to horizontal resolution

The dependence on horizontal resolution of the climate simulated by the National Center for Atmospheric Research Community Climate Model (CCM2) is explored. Simulations employing R15, T21, T31, T42, T63, and T106 horizontal spectral truncations are compared. Parameters associated with the diagnostic cloud scheme are modified for each resolution to provide similar global average cloud radiative forcing at each resolution. Overall, as with earlier studies, there are large differences between the low resolution R15 and T21 simulations and the medium resolution T42 simulation. Many climate statistics show a monotonic signal with increasing resolution, with the largest variation occurring from low to medium resolution. Although the monotonic signal is often from the low resolution simulations toward atmospheric analyses, in some cases it continues beyond the analyses at the highest resolution. Where convergence occurs, it is not always to the atmospheric analyses, and the highest resolution simulations are not the best by all measures. Although many climate statistics converge, the processes that maintain the climate do not, especially when considered on a regional basis. The implication is that the finer scales are required to capture the nonlinear processes that force the medium scales. Overall, it appears that, at a minimum, T42 resolution is required, but higher resolution would be better. Applications at T42 should take into consideration how model errors indicated by these resolution signals might affect any findings.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

全球云水量气候分布及变化趋势特征分析

采用20世纪再分析版本2c数据集的云水量逐月再分析数据,通过数理统计方法,分析了1960～2014年全球、海洋和陆地上空云水量的分布和变化特征及其与水汽通量的关系.结果表明:1)全球云水量空间分布不均,海洋高于陆地且比例约为4﹕3,中低纬海洋、陆地上空云水量变化趋势分别为0.07 g m?2(10 a)?1和?0.04...     

利用TWP-ICE试验资料对比两种边界层参数化方案

利用高分辨率WRF单气柱模式,选取了两种边界层参数化方案(YSU,MYJ),对TWP-ICE(Tropical Warm Pool International Cloud Experiment)试验期间的个例进行数值模拟,比较了两种方案对边界层结构、云和降水模拟的影响。结果表明:季风活跃期,YSU方案模拟的湍流交换系数较小,湍流混合偏弱,边界层内热通量偏小,使地表热量和水汽不易向上输送,水汽含量在近地表明显偏多,而在边界层及其以上大气层具有显著的干偏差,因此该方案模拟的云中液态水和固态水含量偏低,云量偏少,降水率偏小;MYJ方案对于季风活跃期的边界层结构具有较好的模拟能力,其模拟的云和降水更为准确。季风抑制期,MYJ方案模拟的夜间边界层结构存在较大误差,这是因为该方案模拟的夜间湍流交换系数较大,湍流混合偏强,边界层内热通量偏大,模拟的位温和水汽混合比在边界层内随高度变化较小,而观测廓线在边界层内存在较大梯度。季风抑制期两种方案模拟的云和降水均比观测值偏多,方案之间的差异较小。     

The thermodynamic influence of subgrid orography in a global climate model

Assessments of the impacts of climate change typically require information at scales of 10 km or less. Such a resolution in global climate simulations is unlikely for at least two decades. We have developed an alternative to explicit resolution that provides a framework for meeting the needs of climate change impact assessment much sooner. We have applied to a global climate model a physically based subgrid-scale treatment of the influence of orography on temperature, clouds, precipitation, and land surface hydrology. The treatment represents subgrid variations in surface elevation in terms of fractional area distributions of discrete elevation classes. For each class it calculates the height rise/descent of air parcels traveling through the grid cell, and applies the influence of the rise/descent to the temperature and humidity profiles of the elevation class. Cloud, radiative, and surface processes are calculated separately for each elevation class using the same physical parametrizations used by the model without the subgrid orography parametrization. The simulated climate fields for each elevation class can then be distributed in post-processing according to the spatial distribution of surface elevation within each grid cell. Parallel 10-year simulations with and without the subgrid treatment have been performed. The simulated temperature, precipitation and snow water are mapped to 2.5-minute (~5 km) resolution and compared with gridded analyses of station measurements. The simulation with the subgrid scheme produces a much more realistic distribution of snow water and significantly more realistic distributions of temperature and precipitation than the simulation without the subgrid scheme. Moreover, the 250-km grid cell means of most other fields are virtually unchanged by the subgrid scheme. This suggests that the tuning of the climate model without the subgrid scheme is also applicable to the model with the scheme.     

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...     

A new snow parameterization for the Météo-France climate model

Both observational and numerical studies demonstrate the sensitivity of the atmosphere to variations in the extent and mass of snow cover. There is therefore a need for simple but realistic snow parameterizations in forecast and climate models. A new snow hydrology scheme has recently been developed at Météo-France for use in the ARPEGE climate model and has been successfully tested against local field measurements in stand-alone experiments. This study describes the global validation of the parameterization in a 3-year integration for the present-day climate within the T42L30 version of ARPEGE. Results are compared with those from a control simulation and with available observed climatologies, in order to assess the impact of the new snow parameterization on the simulated surface climate. The seasonal cycle of the Northern Hemisphere snow cover is clearly improved when using the new scheme. The snow pack is still slightly overestimated in winter, but its poleward retreat is better reproduced during the melting season. As a consequence, the modified GCM performs well in simulating the springtime continental heating, which may play a strong role in the simulation of the Asian summer monsoon.     

Test of a convectively forced gravity wave drag parameterization in a general circulation model

The influence of gravity wave drag induced by cumulus convection (GWDC) on a simulated boreal summer climate was evaluated in a general circulation model. For this, the GWDC scheme developed by Chun and Baik was implemented into a version of the National Centers for Environmental Prediction (NCEP) global spectral model (GSM). Ensemble simulations with the two different convection schemes, the simplified Arakawa-Schubert (SAS) scheme and Community Climate Model (CCM) convection scheme, were conducted for the boreal summer of 1996. A cloud factor to modulate the stress intensity with respect to the cloud type was introduced in this study, in order to prevent unrealistic behaviors of the GWDC scheme in GSM. The effect of gravity wave drag on the zonal mean of wind and temperature fields was focused. On the whole, the effect of GWDC in this study is positive on the simulated seasonal climate. It is evident that biases in temperature in the polar region as well as in the zonal and meridional winds in the upper atmosphere are reduced. The percentage of reduction of the bias in zonal winds is about 10–20%. Such a response of the GWDC forcing widely appears not only in tropical regions but also in mid-latitude regions. These characteristics are prominent in the case of the SAS scheme, which is due to the various convective cloud types. The magnitude of GWDC forcing is generally small, but still positive, in the case of the CCM scheme, which is due to rather homogeneous cloud types. It is also found that the role of a particular GWDC forcing depends upon the inherent systematic biases of a particular model. It is concluded that incorporation of the GWDC parameterization in GCMs should be taken into account to improve the seasonal prediction.     

云微物理参数化方案对地面气温模拟性能的评估与改进

午后地面气温对对流的发生发展具有重要作用,对其准确预报一直是中尺度数值模式的基本要求。针对一次冷云过程,本文基于WRFv3.9.1模式评估了5种云微物理参数化方案对华东地区地面气温的模拟效果。结果表明,各方案模拟的午后及午夜地面气温都存在较大偏差。其中,WDM6方案对地面气温模拟的效果最佳,Thompson方案模拟的云冰含量过低,模拟效果最差。因此对WDM6方案进行进一步评估和改进,通过修改冰核浓度、初始云凝结核数、优化WDM6方案以及替换方案中云水向雨水自动转化过程的公式的方式设计了敏感性试验,以改进WDM6方案对地面气温的模拟。结果表明,使用Grabowski公式替换WDM6方案中的Berry公式,能提高云水含量,有效改善地面气温的模拟。并通过一次梅雨过程对改进方案进行了有效性验证。最后在此基础上将改进后的WDM6方案应用于江苏省精细化天气分析和预报系统PWAFS模式中,显著提高了PWAFS模式对午后地面气温的模拟效果,为模式的业务应用提供了技术支撑。     

冰晶粒子不同形状假定对辐射收支和气候的影响

将包含多形状冰晶粒子的冰云辐射参数化方案应用于全球气候模式中,详细讨论了冰云粒子从球形假定到多形状假定的变化对辐射场和气候场的影响。结果显示,冰晶粒子形状假定的引入对冰云光学厚度、辐射通量和加热率以及温度场均有明显的影响。采用新的冰云方案使得全球平均云光学厚度值降低0.28（23%）;热带地区降低最为明显,其差异绝对值可达1.02,而在中高纬度陆地地区,两者的冰云光学厚度差别较小。冰晶粒子形状假定改变将导致全球平均的大气顶出射长波辐射通量增加5.52 W/m2（2.3%）。与观测资料的比较表明,多形状冰晶粒子假定明显减小了球形粒子假定对长波出射辐射的低估。对大气加热率廓线的模拟显示,多形状冰晶粒子假定会减弱短波辐射对大气的加热作用,同时增强长波辐射对大气的冷却作用;在热带对流层中高层,这两种影响尤为显著。冰晶粒子形状假定的改变对温度场有明显的影响,热带地区的对流层高层大气温度降低幅度可超过1.5 K。研究表明,冰晶粒子形状假定的改变对模拟的辐射和温度场均有重要的影响。      

Resolved Versus Parametrized Boundary-Layer Plumes. Part III: Derivation of a Statistical Scheme for Cumulus Clouds

We present a statistical cloud scheme based on the subgrid-scale distribution of the saturation deficit. When analyzed in large-eddy simulations (LES) of a typical cloudy convective boundary layer, this distribution is shown to be bimodal and reasonably well-fitted by a bi-Gaussian distribution. Thanks to a tracer-based conditional sampling of coherent structures of the convective boundary layer in LES, we demonstrate that one mode corresponds to plumes of buoyant air arising from the surface, and the second to their environment, both within the cloud and sub-cloud layers. According to this analysis, we propose a cloud scheme based on a bi-Gaussian distribution of the saturation deficit, which can be easily coupled with any mass-flux scheme that discriminates buoyant plumes from their environment. For that, the standard deviations of the two Gaussian modes are parametrized starting from the top-hat distribution of the subgrid-scale thermodynamic variables given by the mass-flux scheme. Single-column model simulations of continental and maritime case studies show that this approach allows us to capture the vertical and temporal variations of the cloud cover and liquid water.