A Sensitivity Study Of The Subtropical Ocean Surface Energy Balance To The Parameterization Of Precipitation From Stratocumulus Clouds

In the `First Lagrangian' of the Atlantic Stratocumulus Experiment(ASTEX), a cloudy air mass was tracked as it was advected by thetrade winds toward higher sea surface temperatures. In this study,a full diurnal cycle observed during this experiment is simulated andthe impact of the precipitation parameterization is examined. The modelwe use is the one dimensional version of the hydrostatic primitiveequation model MAR (Modéle Atmosphérique Régional) developed at the Université catholique de Louvain (UCL).It includes an E- turbulence closure, a wide-band formulationof the radiative transfer, and a parameterized microphysical schemeallowing partial condensation. The model realistically reproducesthe diurnal clearing of the cloud layer as well as the formation ofcumulus clouds under the stratocumulus deck. Nevertheless, as thesurface warms and the boundary layer becomes more convective,the simulation progressively differs from the observed evolution.Further experiments are carried out with different precipitationparameterizations commonly used in mesoscale modelsand general circulation models (GCMs).A strong sensitivity of the simulated liquid water path evolution isfound. The impact on the surface energy flux and the solar fluxreflected by the cloud is also examined. For both fluxes averagedover 24 hours, differences as large as 20 W m^-2 are obtainedbetween the various simulations. Low cloudiness covers large areasover the ocean and such errors on the reflected solar flux may stronglyaffect the Earth's radiative budget in GCM simulations. We estimatethat the impact on the globally averaged outgoing solar flux could beas large as 5 W m^-2. Furthermore, when atmospheric models arecoupled to ocean models, errors in the surface energy exchanges mayinduce significant drift in the simulated climate.     

积层混合云结构和云微物理的数值模拟

对三维非静力中尺度模式ARPS的云微物理方案进行了改进,利用改进后的模式模拟了华北地区的积层混合云降水个例,通过对模拟结果的分析并结合实况资料研究了积层混合云的降水特征、云物理结构特征和微物理过程。结果表明,积层混合云降水分布不均匀,雨区中存在多个强降水中心,云系中微物理量在水平和垂直方向上分布都不均匀,积云中的垂直液态水积分含量大大高于层云中含量,此次降水冰相过程占主导地位,霰的融化是最主要的雨生成项。     

GCM intercomparison of global cloud regimes: present-day evaluation and climate change response

The radiative feedback from clouds remains the largest source of variation in climate sensitivity amongst general circulation models (GCMs). A cloud clustering methodology is applied to six contemporary GCMs in order to provide a detailed intercomparison and evaluation of the simulated cloud regimes. By analysing GCMs in the context of cloud regimes, processes related to particular cloud types are more likely to be evaluated. In this paper, the mean properties of the global cloud regimes are evaluated, and the cloud response to climate change is analysed in the cloud-regime framework. Most of the GCMs are able to simulate the principal cloud regimes, however none of the models analysed have a good representation of trade cumulus in the tropics. The models also share a difficulty in simulating those regimes with cloud tops at mid-levels, with only ECHAM5 producing a regime of tropical cumulus congestus. Optically thick, high top cloud in the extra-tropics, typically associated with the passage of frontal systems, is simulated considerably too frequently in the ECHAM5 model. This appears to be a result of the cloud type persisting in the model after the meteorological conditions associated with frontal systems have ceased. The simulation of stratocumulus in the MIROC GCMs is too extensive, resulting in the tropics being too reflective. Most of the global-mean cloud response to doubled CO₂ in the GCMs is found to be a result of changes in the cloud radiative properties of the regimes, rather than changes in the relative frequency of occurrence (RFO) of the regimes. Most of the variance in the global cloud response between the GCMs arises from differences in the radiative response of frontal cloud in the extra-tropics and from stratocumulus cloud in the tropics. This variance is largely the result of excessively high RFOs of specific regimes in particular GCMs. It is shown here that evaluation and subsequent improvement in the simulation of the present-day regime properties has the potential to reduce the variance of the global cloud response, and hence climate sensitivity, amongst GCMs. For the ensemble of models considered in this study, the use of observations of the mean present-day cloud regimes suggests a potential reduction in the range of climate sensitivity of almost a third. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Parametric representation of heat and moisture fluxes in cloud-topped mixed layers

Aircraft measurements were made from the NCAR Electra in stratus and stratocumulus clouds off the coast of California in June 1976. Several types of cloud conditions were observed, including (1) a broken layer less than 100 m thick, capped by an inversion at ~1000 m, (2) a broken stratocumulus layer ~300 m thick with an inversion at ~500 m, and (3) a solid stratocumulus layer ~250 m thick with an inversion at ~500 m. Although these observations indicate that a variety of cloud conditions may exist in mixed layers, simple one-dimensional mixed-layer models implicitly assume a solid cloud layer with no unsaturated region within the cloud. In order to generalize these simple models, a parametric representation of the heat and moisture fluxes is considered. In this scheme, the fluxes are parameterized in terms of the product of a cloud mass flux and the characteristic difference between the thermodynamic properties of an updraft-downdraft circulation. This representation allows for an explicit representation of the buoyancy flux when the downdraft has no liquid water.Data collected during these flights were used to calculate heat and moisture fluxes and to obtain the mean difference in the thermodynamic properties of the updrafts and downdrafts at a given level. The mass flux was calculated using updraft-downdraft differences and the fluxes. The mass fluxes obtained using various thermodynamic quantities are examined for consistency. The vertical distribution of the mass flux is determined. These results indicate that a mass flux formulation could prove to be useful in modeling applications where cloud conditions may vary between solid and broken.     

A quantitative performance assessment of cloud regimes in climate models

Differences in the radiative feedback from clouds account for much of the variation in climate sensitivity amongst General Circulation Models (GCMs). Therefore metrics of model performance which are demonstrated to be relevant to the cloud response to climate change form an important contribution to the overall evaluation of GCMs. In this paper we demonstrate an alternative method for assigning model data to observed cloud regimes obtained from clustering histograms of cloud amount in joint cloud optical depth—cloud top pressure classes. The method removes some of the subjectivity that exists in previous GCM cloud clustering studies. We apply the method to ten GCMs submitted to the Cloud Feedback Model Intercomparison Project (CFMIP), evaluate the simulated cloud regimes and analyse the climate change response in the context of these regimes. We also propose two cloud regime metrics, one of which is specifically targeted at assessing GCMs for the purpose of obtaining the global cloud radiative response to climate change. Most of the global variance in the cloud radiative response between GCMs is due to low clouds, with 47% arising from the stratocumulus regime and 18% due to the regime characterised by clouds undergoing transition from stratocumulus to cumulus. This result is found to be dominated by two structurally similar GCMs. The shallow cumulus regime, though widespread, has a smaller contribution and reduces the variance. For the stratocumulus and transition regimes, part of the variance results from a large model spread in the radiative properties of the regime in the control simulation. Comparison with observations reveals a systematic bias for both the stratocumulus and transition regimes to be overly reflective. If this bias was corrected with all other aspects of the response unchanged, the variance in the low cloud response would reduce. The response of some regimes with high cloud tops differ between the GCMs. These regimes are simulated too infrequently in a few of the models. If the frequency in the control simulation were more realistic and changes within the regimes were unaltered, the variance in the cloud radiative response from high-top clouds would increase. As a result, use of observations of the mean present-day cloud regimes suggests that whilst improvements in the simulation of the cloud regimes would impact the climate sensitivity, the inter-model variance may not reduce. When the cloud regime metric is calculated for the GCMs analysed here, only one model is on average consistent with observations within their uncertainty (and even this model is not consistent with the observations for all regimes), indicating scope for improvement in the simulation of cloud regimes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Impacts of aerosol chemical composition on microphysics and precipitation in deep convection

Aerosols affect precipitation by modifying cloud properties such as cloud droplet number concentration (CDNC). Aerosol effects on CDNC depend on aerosol properties such as number concentration, size spectrum, and chemical composition. This study focuses on the effects of aerosol chemical composition on CDNC and, thereby, precipitation in a mesoscale cloud ensemble (MCE) driven by deep convective clouds. The MCE was observed during the 1997 department of energy's Atmospheric Radiation Measurement (ARM) summer experiment. Double-moment microphysics with explicit nucleation parameterization, able to take into account those three properties of aerosols, is used to investigate the effects of aerosol chemical composition on CDNC and precipitation. The effects of aerosol chemical compositions are investigated for both soluble and insoluble substances in aerosol particles. The effects of soluble substances are examined by varying mass fractions of two representative soluble components of aerosols in the continental air mass: sulfate and organics. The increase in organics with decreasing sulfate lowers critical supersaturation (S_c) and leads to higher CDNC. Higher CDNC results in smaller autoconversion of cloud liquid to rain. This provides more abundant cloud liquid as a source of evaporative cooling, leading to more intense downdrafts, low-level convergence, and updrafts. The resultant stronger updrafts produce more condensation and thus precipitation, as compared to the case of 100% sulfate aerosols. The conventional assumption of sulfate aerosol as a surrogate for the whole aerosol mass can be inapplicable for the case with the strong sources of organics. The less precipitation is simulated when an insoluble substance replaces organics as compared to when it replaces sulfate. When the effects of organics on the surface tension of droplet and solution term in the Köhler curve are deactivated by the insoluble substance, S_c is raised more than when the effects of sulfate on the solution term are deactivated by the insoluble substance. This leads to lower CDNC and, thus, larger autoconversion of cloud liquid to rain, providing less abundant cloud liquid as a source of evaporative cooling. The resultant less evaporative cooling produces less intense downdrafts, weaker low-level convergence, updrafts, condensation and, thereby, less precipitation in the case where organics is replaced by the insoluble substance than in the case where sulfate is replaced by the insoluble substance. The variation of precipitation caused by the change in the mass fraction between the soluble and insoluble substances is larger than that caused by the change in the mass fraction between the soluble substances.     

Cloud-radiation feedback and atmosphere-ocean coupling in a stochastic multicloud model

Despite recent advances in supercomputing, current general circulation models (GCMs) have significant problems in representing the variability associated with organized tropical convection. Furthermore, due to high sensitivity of the simulations to the cloud radiation feedback, the tropical convection remains a major source of uncertainty in long-term weather and climate forecasts. In a series of recent studies, it has been shown, in paradigm two-baroclinic-mode systems and in aquaplanet GCMs, that a stochastic multicloud convective parameterization based on three cloud types (congestus, deep and stratiform) can be used to improve the variability and the dynamical structure of tropical convection, including intermittent coherent structures such as synoptic and mesoscale convective systems. Here, the stochastic multicloud model is modified with a parameterized cloud radiation feedback mechanism and atmosphere-ocean coupling. The radiative convective feedback mechanism is shown to increase the mean and variability of the Walker circulation. The corresponding intensification of the circulation is associated with propagating synoptic scale systems originating inside of the enhanced sea surface temperature area. In column simulations, the atmosphere ocean coupling introduces pronounced low frequency convective features on the time scale associated with the depth of the mixed ocean layer. However, in the presence of the gravity wave mixing of spatially extended simulations, these features are not as prominent. This highlights the deficiency of the column model approach at predicting the behavior of multiscale spatially extended systems. Overall, the study develops a systematic framework for incorporating parameterized radiative cloud feedback and ocean coupling which may be used to improve representation of intraseasonal and seasonal variability in GCMs.     

A GCSS Boundary-Layer Cloud Model Intercomparison Study Of The First Astex Lagrangian Experiment

Three single-column models (all with an explicit liquid water budget and compara-tively high vertical resolution) and three two-dimensional eddy-resolving models (including one with bin-resolved microphysics) are compared with observations from the first ASTEX Lagrangian experiment. This intercomparison was a part of the second GCSS boundary-layer cloud modelling workshop in August 1995.In the air column tracked during the first ASTEX Lagrangian experiment, a shallow subtropical drizzling stratocumulus-capped marine boundary layer deepens after two days into a cumulus capped boundary layer with patchy stratocumulus. The models are forced with time varying boundary conditions at the sea-surface and the capping inversion to simulate the changing environment of the air column.The models all predict the observed deepening and decoupling of the boundary layer quite well, with cumulus cloud evolution and thinning of the overlying stratocumulus. Thus these models all appear capable of predicting transitions between cloud and boundary-layer types with some skill. The models also produce realistic drizzle rates, but there are substantial quantitative differences in the cloud cover and liquid water path between models. The differences between the eddy-resolving model results are nearly as large as between the single column model results. The eddy resolving models give a more detailed picture of the boundary-layer evolution than the single-column models, but are still sensitive to the choice of microphysical and radiative parameterizations, sub-grid-scale turbulence models, and probably model resolution and dimensionality. One important example of the differences seen in these parameterizations is the absorption of solar radiation in a specified cloud layer, which varied by a factor of four between the model radiation parameterizations.     

Validation of GCM control simulations using indices of daily airflow types over the British Isles

In this study, the control simulations of two general circulation model (GCM) experiments are assessed in terms of their ability to reproduce realistic real world weather. The models examined are the UK Meteorological Office high-resolution atmospheric model (UKHI) and a coupled ocean/atmosphere model of the Max Planck Institut für Meteorologic, Hamburg (MPI). An objective classification of daily airflow patterns over the British Isles is used as a basis for comparing the frequencies of model-generated weather types with the frequencies derived from 110 years of observed mean-sea-level pressure (MSLP) fields. The weather-type frequencies generated by the GCMs, and their relationships with simulated monthly mean temperatures and total precipitation over the UK, are compared, season by season, with similar results derived using the observational data. An index of gale frequencies over the British Isles, derived from a similar objective analysis of daily MSLP fields, is used to evaluate the ability of the GCMs to simulate the observed frequency of storm events. One advantage of using 110 years of observational data is that the observed decadal-scale variability of climate can be introduced into this type of validation exercise. Both the GCMs assessed here are too cyclonic in winter. The seasonality of both anticyclonic and cyclonic types is much too strong in MPI and summer precipitation in this model is greatly underestimated. MPI simulates the annual cycle of temperature well, while UKHI successfully reproduces the annual cycle of precipitation. The analysis also indicates that the summer temperature variability of the two models is not driven by circulation changes.This paper was presented at the Second International Conference on Modelling of Global Climate Variability, held in Hamburg 7–11 September 1992 under the auspices of the Max Planck Institute for Meteorology. Guest Editor for these papers is L. Dümenil     

A study of a two-dimensional cloudiness transition during a cold air outbreak event

A two-dimensional version of a hydrostatic mesoscale model with a partial cloudiness scheme is used to study a cold air outbreak event during MASEX (Mesoscale Air-Sea Exchange experiment). The model produces a weak mesoscale circulation which is slightly advected offshore and simulates well an observed cloudiness transition zone of 80 km where the cloud cover ranges between 0 and 100%. It is shown that the cloud top entrainment instability criterion can explain the observed cloudiness phenomenon i.e., the transition from a cumulus field to a solid stratocumulus cloud layer.The usefulness of the partial cloudiness scheme is demonstrated by comparing the results to those obtained with a simple all or nothing condensation scheme. A model sensitivity study shows that the sea surface temperature and the horizontal advection speed control the surface heat and moisture fluxes and so explain the structure and horizontal extent of the cloudiness transition zone.     

Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study

This study incorporated the Weather Research and Forecasting (WRF) model double-moment 6-class (WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso). A rainfall event that occurred during 3–5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme (WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warmrain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei (CCN) number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration (N_c) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration (N_r), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event.     

GCM Simulations of Stable Isotopes in the Water Cycle in Comparison with GNIP Observations over East Asia

In this paper, we examine the performance of four isotope incorporated GCMs, i.e., ECHAM4 (University of Hamburg), HadCM3 (Hadley Centre), GISS E (Goddard Institute of Space Sciences), and MUGCM (Melbourne University), by comparing the model results with GNIP (Global Network of Isotopes in Precipitation) observations. The spatial distributions of mean annual δD and mean annual deuterium excess d in precipitation, and the relationship between δ18 o and δD in precipitation, are compared between GCMs and GNIP data over East Asia. Overall, the four GCMs reproduce major characteristics of δD in precipitation as observed by GNIP. Among the four models, the results of ECHAM4 and GISS E are more consistent with GNIP observed precipitation δD distribution. The simulated d distributions are less consistent with the GNIP results. This may indicate that kinetic fractionation processes are not appropriately represented in the isotopic schemes of GCMs. The GCM modeled MWL (meteoric water line) slopes are close to the GNIP derived MWL, but the simulated MWL intercepts are significantly overestimated. This supports that the four isotope incorporated GCMs may not represent the kinetic fractionation processes well. In term of LMWLs (local meteoric water lines), the simulated LMWL slopes are similar to those from GNIP observations, but slightly overestimated for most locations. Overall, ECHAM4 has better capability in simulating MWL and LMWLs, followed by GISS E. Some isotopic functions (especially those related to kinetic fractionation) and their parameterizations in GCMs may have caused the discrepancy between the simulated and GNIP observed results. Future work is recommended to improve isotopic function parameterization on the basis of the high-resolution isotope observations.     

Using meteosat data to validate a prognostic cloud generation scheme

We have designed a cloud generation scheme for use in the LMD GCM. It predicts the mixing ratio of the cloud's condensed water as a new prognostic variable. At present it does not fully interact with the radiation schemes, but the aim is to predict the cloud optical properties. We have used the Meteosat/ISCCP data to evaluate this scheme. Such a comparison allows us to place some constraints on the coefficients which are used in the parameterizations, such as the precipitation thresholds for the cloud's liquid water content and the relative variability of water vapour within a grid box. There is generally a good agreement between observed and simulated results, although there appear some discrepancies in the cloud's apparent temperatures.     

A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction

For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy Diffusivity\Mass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w _*. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCS\ARM) and conserve a realistic evolution of stratocumulus (EUROCS\FIRE).     

Parameterization and Explicit Modeling of Cloud Microphysics: Approaches,Challenges, and Future Directions

Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs) but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs) and large-eddy simulation(LES) models. Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years, this study concentrates purposely on several topics that ...     

Turbulence in Continental Stratocumulus,Part I: External Forcings and Turbulence Structures

Comprehensive, ground-based observations from the US Department of Energy Atmospheric Radiation Measurements program Southern Great Plains site are used to study the variability of turbulence forcings and cloud-scale turbulence structures in a continental stratocumulus cloud. The turbulence observations are made from an upward facing cloud (35 GHz) Doppler radar. Cloud base and liquid water path are characterized using a lidar at the surface and a microwave radiometer. The turbulence characterizations are compared and contrasted with those observed in marine stratocumulus clouds. During the 16-h observation period used in this study the cloud-base and cloud-top heights evolve with time and changes in liquid water path observed by the radiometer are consistent with variations in cloud depth. Unlike marine stratocumulus clouds, a diurnal cycle of cloud thickness and liquid water path is not observed. The observed surface latent, sensible, and virtual sensible heat fluxes and the radiative fluxes exhibit a diurnal cycle with values increasing from sunrise to afternoon and decreasing afterwards. During the night, the sensible heat, virtual sensible heat and the net radiative fluxes at the surface are slightly negative. Solar radiative heating prevails in the cloud layer during the day and strong radiative cooling exists at cloud top even during the day. Unlike marine stratocumulus, surface heating described by the convective velocity scale \(W_\mathrm{s}^{*}\) and cloud-top cooling described by \(W_\mathrm{r}^{*}\) are both important in driving the in-cloud turbulence during the day, whereas cloud-top cooling is the exclusive contributor during the night. The combined \(W_\mathrm{s}^{*}\) and \(W_\mathrm{r}^{*}\) (the total velocity scale \(W_\mathrm{t}^{*})\) provides a useful way to track the evolution of the turbulence structure in the cloud. The variance of the radar-measured radial velocity, which is related to resolved turbulence, follows the diurnal cycle and is consistent with the total velocity scale \(W_\mathrm{t}^{*}\) variations. It is higher during the day and lower during the night, which is contrary to that in marine stratocumulus. The \(W_\mathrm{t}^{*}\) values are lowest around sunset when the radiative cooling is also small due to upper-level clouds observed above the low-level stratus. The vertical distribution of the variance results from the surface heating during the day and cloud-top cooling during the night. The squared spectrum width, which is related to turbulence structures within the radar sampling volume (unresolved turbulence) also follows the diurnal cycle. Its vertical distribution indicates that the unresolved turbulence more closely relates to the processes near cloud top. Turbulence in the cloud requires about an hour to respond to the external forcings of surface heating and cloud-top radiative cooling. Positive skewness prevails during the day and negative skewness prevails at night with a sharp transition around sunset. Resolved turbulence dominates near cloud base whereas unresolved turbulence dominates near cloud top. The turbulence characteristics and variability defined in this study can be used to evaluate the time evolution of turbulence structures in large eddy simulation forced by surface and cloud-top radiative forcings.     

Numerical experiments with a one-dimensional higher order turbulence model: Simulation of the Wangara Day 33 case

A one-dimensional stratocumulus model is developed and incorporated into a cloud/mesoscale model to simulate the evolution of the marine stratocumulus-capped mixed layer. This paper describes the formulation of the higher-order turbulence model. In a companion paper (Chen and Cotton, 1983), the formulation of the atmospheric radiation model, the partial condensation and the cloud fractional parameterization are described. The second-order moments of this model are partially diagnosed. In order to close the system, the parameterization for the third-order moments given by Zeman and Lumley (1976) is adopted and is generalized to include total water and cloud water. A new scheme to parameterize the skewness terms is proposed in order to satisfy the enforced realizability. Those skewness terms are used to close the third-order moments. In this paper, experiments are carried out to test the turbulence model by using the Wangara Day 33 data, which represents a ‘dry’ case study. Sensitivity experiments using the turbulence length scale parameterizations formulated by Andréet al. (1978) and Sun and Ogura (1980) are reformed and are compared.     

Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO₂ and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.     

混合相层状云系模式和中尺度低涡云系的实例模拟

在Ａｎｔｈｅｓｅｔａｌ．的中尺度模式基础上引入胡志晋的双参数层状云模式并重新编制了程序，构成一个包含三种水相态和比较详细云物理过程的三维层状云系模式。为保持在较长时步中计算的稳定和精度，对微物理过程的计算采用混合格式，少数过程采用时间分裂格式，在相变过程的处理上设计了同时计算不同相态相变的参数化方案，按Ｌａｇｒａｎｇｉａｎ方法设计了粒子下落格式。用干模式、积云参数化模式、两相显式模式和本文模式对两个中尺度低涡个例作了模拟，对比分析不同模式的模拟能力。结果表明本文模式对涡环流结构、云场和降水分布的摸拟比其他模式更合理，更接近实况。