Towards evaluating cloud response to climate change using clustering technique identification of cloud regimes

Most of the discrepancies in the climate sensitivity of general circulation models (GCMs) are believed to be due to differences in cloud radiative feedback. Analysis of cloud response to climate change in different ‘regimes’ may offer a more detailed understanding of how the cloud response differs between GCMs. In which case, evaluation of simulated cloud regimes against observations in terms of both their cloud properties and frequency of occurrence will assist in assessing confidence in the cloud response to climate change in a particular GCM. In this study, we use a clustering technique on International Satellite Cloud Climatology Project (ISCCP) data and on ISCCP-like diagnostics from two versions of the Hadley Centre GCM to identify cloud regimes over four different geographical regions. The two versions of the model are evaluated against observational data and their cloud response to climate change compared within the cloud regime framework. It is found that cloud clusters produced by the more recent GCM, HadSM4, compare more favourably with observations than HadSM3. In response to climate change, although the net cloud response over particular regions is often different in the two models, in several instances the same basic processes may be seen to be operating. Overall, both changes in the frequency of occurrence of cloud regimes and changes in the properties (optical depth and cloud top height) of the cloud regimes contribute to the cloud response to climate change.     

A methodology study of the validation of clouds in GCMs using ISCCP satellite observations

The cloudiness fields simulated by a general circulation model and a validation using the International Satellite Cloud Climatology Project (ISCCP) satellite observations are presented. An adapted methodology is developed, in which the issue of the sub-grid scale variability of the cloud fields, and how it may affect the comparison exercise, is considered carefully. In particular different assumptions about the vertical overlap of cloud layers are made, allowing us to reconstruct the cloud distribution inside a model grid column. Carrying out an analysis directly comparable to that of ISCCP then becomes possible. The relevance of this method is demonstrated by its application to the evaluation of the cloud schemes used in Laboratoire de Météoroligie Dynamique (LMD) general circulation model. We compare cloud properties, such as cloud-top height and cloud optical thickness, analysed by ISCCP and simulated by the LMD GCM. The results show that a direct comparison of simulated low cloudiness and that shown from satellites is not possible. They also reveal some model deficiencies concerning the cloud vertical distribution. Some of these features depend little on the cloud overlap assumption and may reveal inadequate parameterisation of the boundary layer mixing or the cloud water precipitation rate. High convective clouds also appear to be too thick.     

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

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

A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity

Low-latitude cloud distributions and cloud responses to climate perturbations are compared in near-current versions of three leading U.S. AGCMs, the NCAR CAM 3.0, the GFDL AM2.12b, and the NASA GMAO NSIPP-2 model. The analysis technique of Bony et al. (Clim Dyn 22:71–86, 2004) is used to sort cloud variables by dynamical regime using the monthly mean pressure velocity ω at 500 hPa from 30S to 30N. All models simulate the climatological monthly mean top-of-atmosphere longwave and shortwave cloud radiative forcing (CRF) adequately in all ω-regimes. However, they disagree with each other and with ISCCP satellite observations in regime-sorted cloud fraction, condensate amount, and cloud-top height. All models have too little cloud with tops in the middle troposphere and too much thin cirrus in ascent regimes. In subsidence regimes one model simulates cloud condensate to be too near the surface, while another generates condensate over an excessively deep layer of the lower troposphere. Standardized climate perturbation experiments of the three models are also compared, including uniform SST increase, patterned SST increase, and doubled CO₂ over a mixed layer ocean. The regime-sorted cloud and CRF perturbations are very different between models, and show lesser, but still significant, differences between the same model simulating different types of imposed climate perturbation. There is a negative correlation across all general circulation models (GCMs) and climate perturbations between changes in tropical low cloud cover and changes in net CRF, suggesting a dominant role for boundary layer cloud in these changes. For some of the cases presented, upper-level clouds in deep convection regimes are also important, and changes in such regimes can either reinforce or partially cancel the net CRF response from the boundary layer cloud in subsidence regimes. This study highlights the continuing uncertainty in both low and high cloud feedbacks simulated by GCMs.     

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.     

A hybrid technique for computing the monthly mean net longwave surface radiation over oceanic areas

Summary Global maps of the monthly mean net upward longwave radiation flux at the ocean surface have been obtained for April, July, October 1985 and January 1986. These maps were produced by blending information obtained from a combination of general circulation model cloud radiative forcing fields, the top-of-the-atmosphere cloud radiative forcing from ERBE and TOVS profiles and sea surface temperature on ISCCP C1 tapes. The fields are compatible with known meteorological regimes of atmospheric water vapor content and cloudiness. There is a vast area of high net upward longwave radiation flux (> 80 W m^–2) in the eastern Pacific Ocean throughout most of the year. Areas of low net upward longwave radiation flux (< 40 Wm^–2) are the tropical convective regions and extra tropical regions that tend to have persistent low cloud cover. The technique used in this study relies on GCM simulations and so is subject to some of the uncertainties associated with the model. However, all input information regarding temperature, moisture and cloud cover is from satellite data having near global coverage. This feature of the procedure alone warrants its consideration for further use in compiling global maps of the net longwave radiation at the surface over the oceans.With 9 Figures     

Organization of tropical convection in a GCM with varying vertical resolution; implications for the simulation of the Madden-Julian Oscillation

 Experiments using a GCM with two different vertical resolutions show differences in the amount of variability in the tropical upper tropospheric zonal wind component associated with the Madden-Julian Oscillation (MJO). The GCM with lower vertical resolution shows very little variability in this quantity whereas when the vertical resolution is doubled in the free troposphere, the GCM produces variability which is of the same strength as observations. However, the eastward propagation of an enhanced convective region from the Indian Ocean into the west Pacific is not well represented in either simulation of this atmospheric GCM. A water-covered or “aqua-planet” version of the same GCM is used to investigate the behaviour of tropical convection when the vertical resolution is doubled. When the vertical resolution is increased, the spectrum of tropical cloud types changes from a bimodal distribution with peaks representing shallow cumulus and deep cumulonimbus clouds to a trimodal distribution with a third peak in mid-troposphere near the melting level. Associated with periods when these mid-level congestus clouds are dominant, the detrainment from these clouds significantly moistens the mid-troposphere. The appearance of these congestus clouds is shown to be partly due to improved resolution of the freezing level and the convective processes occurring at this level. However, due to the way in which convective detrainment is parametrized in this model, the vertical profile becomes rather noisy and this too contributes to the change in the nature of the convective clouds. The resulting cloud distribution more closely resembles observations, particularly during the suppressed phase of the MJO when cumulus congestus is the dominant cloud type. Received: 17 April 2000 / Accepted: 30 November 2000     

Sensitivity of the Simulated Tropical Intraseasonal Oscillation to Cumulus Parameterizations

The sensitivity of the simulated tropical intraseasonal oscillation or MJO (Madden and Julian oscilla tion)to different cumulus parameterizations is studied by using an atmospheric general circulation model (GCM)-SAMIL(Spectral Atmospheric Model of IAP LASG).Results show that performance of the model in simulating the MJO alters widely when using two different cumulus parameterization schemes-the moist convective adjustment scheme(MCA)and the Zhang-McFarlane(ZM)scheme.MJO simulated by the MCA scheme was found to be more realistic than that simulated by the ZM scheme.MJO produced by the ZM scheme is too weak and shows little propagation characteristics.Weak moisture convergence at low levels simulated by the ZM scheme is not enough to maintain the structure and the eastward propagation of the oscillation.These two cumulus schemes produced different vertical structures of the heating profile.The heating profile produced by the ZM scheme is nearly uniform with height and the heating is too weak compared to that produced by the MCA,which maybe contributes greatly to the failure of simulating a reasonable MJO.Comparing the simulated MJO by these two schemes indicate that the MJO simulated by the GCM is highly sensitive to cumulus parameterizations implanted in.The diabatic heating profile plays an important role in the performance of the GCM.Three sensitivity experiments with different heating profiles are designed in which modified heating profiles peak respectively in the upper troposphere(UH), middle troposphere(MH),and lower troposphere(LH).Both the LH run and the MH run produce eastward propagating signals on the intraseasonal timescale,while it is interesting that the intraseasonal timescale signals produced by the UH run propagate westward.It indicates that a realistic intraseasonal oscillation is more prone to be excited when the maximum heating concentrates in the middle-low levels,especially in the middle levels,while westward propagating disturbances axe more prone to be produced when the maximum heating appears very high.     

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.     

The Impact of Cloud Representation on the Sub-Seasonal Forecasts of Atmospheric Teleconnections and Preferred Circulation Regimes in the Northern Hemisphere

Abstract

The impact of cloud representation on the simulation of mid-latitude recurrent large-scale flows and forecast skill of mid-latitude atmospheric teleconnections is evaluated using the Community Climate System Model, version 4 (CCSM4), and the super-parameterized CCSM4 (SP-CCSM4). Patterns of low-level atmospheric circulation anomalies and convection associated with the Madden–Julian oscillation (MJO) are affected by the method used for the representation of cloud processes. The configuration of the model using super-parameterization for the representation of cloud processes produces MJO-related patterns that agree better with observations than the configuration of the model using a conventional cloud parameterization scheme. The recurrent circulation regimes of the mid-latitudes are also sensitive to the representation of cloud processes. In the North Atlantic sector, the inability of CCSM4 to simulate the Scandinavian blocking regime is corrected in the super-parameterized version of the model. In the North Pacific sector, the strength of the clustering (measured by a variance ratio) is too large in CCSM4 compared with observations and SP-CCSM4. The SP-CCSM4 model has better forecast skill for the MJO amplitude and phase than the model with conventional representation of moist convective processes. In turn, the improved forecast skill of the super-parameterized model results in better forecast skill for mid-latitude teleconnections in 500 hPa geopotential height anomalies forced by the MJO convection.     

A treatment for the stratocumulus-to-cumulus transition in GCMs

Numerical models of climate have great difficulties with the simulation of marine low clouds in the subtropical Pacific and Atlantic Oceans. It has been especially difficult to reproduce the observed geographical distributions of the different cloud regimes in those regions. The present study discusses mechanisms proposed in previous works for changing one regime into another. One criterion is based on the theory of stratocumulus destruction through cloud top entrainment instability due to buoyancy reversal—situations in which the mixture of two air parcels becomes denser than either of the original parcels due to evaporation of cloud water. Another criterion is based on the existence of decoupling in the boundary layer. When decoupled, the stratocumulus regime changes to another in which these clouds can still exist together with cumulus. In a LES study, the authors have suggested that a combination of those two criteria can be used to diagnose whether, at a location, the cloud regime corresponds to a well-mixed stratocumulus regime, a shallow cumulus regime, or to a transitional regime where the boundary layer is decoupled. The concept is tested in the framework of an atmospheric general circulation model (GCM). It is found that several outstanding features of disagreement between simulation and observation can be interpreted as misrepresentations of the cloud regimes by the GCM. A novel criterion for switching among regimes is proposed to alleviate the effects of these misrepresentations.     

Do stratocumulus clouds detrain? FIRE I data revisited

Analyses of aircraft observations of the stratocumulus-topped boundary layer during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE I) show the frequent presence of clear, but relatively moist, air patches near the stratocumulus cloud-top interface. A conditional sampling of measurements in these clear air patches shows that their thermodynamic properties do more resemble boundary-layer air characteristics than those of free troposphere air. From an aircraft leg through cloud tops it is demonstrated that turbulent mixing across the cloud-top interface can lead to the local dissipation of the cloud top. Analogous to the terminology used for shallow cumulus parameterizations this process can be considered as detrainment, with which we mean that after a mixing event across the cloud-top boundaries, mixed unsaturated parcels become part of the clear environment of the cloud.     

Validation of model improvements for the GISS GCM

The general circulation model of the NASA/Goddard Institute for Space Studies (GISS GCM) was designed primarily for global climate change and climate sensitivity applications. The modelling group at GISS has developed new and more physically appropriate parameterizations of meteorological/hydrological processes which are being validated in an effort to improve the performance of the Model II version of the GISS GCM. This study discusses some preliminary evaluations of this testing based on multiple-year simulations at 4° latitude by 5° longitude horizontal resolution. These runs individually incorporate new formulations of the planetary boundary layer (PBL), the moist cumulus convection scheme and the ground hydrology and compare results using B-grid and C-grid numerics. The new PBL produces a realistically stronger tropical surface circulation, while the new cumulus scheme generates more realistic distributions of tropical convection and moisture. The main impact of the more sophisticated ground hydrology model is to increase surface air temperatures. Improvements in modelled sea level pressure and rainfall features by the C-grid are somewhat offset by increases in speed excesses at the cores of the summer hemisphere westerly jets. Each modelling innovation targeted a different aspect of the climate not adequately represented by Model II. However, since the various modelling changes were tested individually, the present evaluation could not demonstrate many dramatic improvements in the simulated climates. This documentation of impacts should, however, serve as a benchmark for the validation of future simulations of the GISS GCM that combine all of the modelling improvements.     

Sensitivity of the Simulated Tropical Intraseasonal Oscillation to Cumulus Parameterizations

The sensitivity of the simulated tropical intraseasonal oscillation or MJO （Madden and Julian oscillation） to different cumulus parameterizations is studied by using an atmospheric general circulation model （GCM）--SAMIL （Spectral Atmospheric Model of IAP LASG）. Results show that performance of the model in simulating the MJO alters widely when using two different cumulus parameterization schemes-the moist convective adjustment scheme （MCA） and the Zhang-McFarlane （ZM） scheme. MJO simulated by the MCA scheme was found to be more realistic than that simulated by the ZM scheme. MJO produced by the ZM scheme is too weak and shows little propagation characteristics. Weak moisture convergence at low levels simulated by the ZM scheme is not enough to maintain the structure and the eastward propagation of the oscillation. These two cumulus schemes produced different vertical structures of the heating profile. The heating profile produced by the ZM scheme is nearly uniform with height and the heating is too weak compared to that produced by the MCA, which maybe contributes greatly to the failure of simulating a reasonable MJO. Comparing the simulated MJO by these two schemes indicate that the MJO simulated by the GCM is highly sensitive to cumulus parameterizations implanted in. The diabatic heating profile plays an important role in the performance of the GCM. Three sensitivity experiments with different heating profiles are designed in which modified heating profiles peak respectively in the upper troposphere （UH）, middle troposphere （MH）, and lower troposphere （LH）. Both the LH run and the MH run produce eastward propagating signals on the intraseasonal timescale, while it is interesting that the intraseasonal timescale signals produced by the UH run propagate westward. It indicates that a realistic intraseasonal oscillation is more prone to be excited when the maximum heating concentrates in the middle-low levels, especially in the middle levels, while westward propagating disturbances     

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     

Impact of resolving the diurnal cycle in an ocean–atmosphere GCM. Part 2: A diurnally coupled CGCM

Coupled ocean atmosphere general circulation models (GCM) are typically coupled once every 24 h, excluding the diurnal cycle from the upper ocean. Previous studies attempting to examine the role of the diurnal cycle of the upper ocean and particularly of diurnal SST variability have used models unable to resolve the processes of interest. In part 1 of this study a high vertical resolution ocean GCM configuration with modified physics was developed that could resolve the diurnal cycle in the upper ocean. In this study it is coupled every 3 h to atmospheric GCM to examine the sensitivity of the mean climate simulation and aspects of its variability to the inclusion of diurnal ocean-atmosphere coupling. The inclusion of the diurnal cycle leads to a tropics wide increase in mean sea surface temperature (SST), with the strongest signal being across the equatorial Pacific where the warming increases from 0.2°C in the central and western Pacific to over 0.3°C in the eastern equatorial Pacific. Much of this warming is shown to be a direct consequence of the rectification of daily mean SST by the diurnal variability of SST. The warming of the equatorial Pacific leads to a redistribution of precipitation from the Inter tropical convergence zone (ITCZ) toward the equator. In the western Pacific there is an increase in precipitation between Papa new guinea and 170°E of up to 1.2 mm/day, improving the simulation compared to climatology. Pacific sub tropical cells are increased in strength by about 10%, in line with results of part 1 of this study, due to the modification of the exchange of momentum between the equatorially divergent Ekman currents and the geostropic convergence at depth, effectively increasing the dynamical response of the tropical Pacific to zonal wind stresses. During the spring relaxation of the Pacific trade winds, a large diurnal cycle of SST increases the seasonal warming of the equatorial Pacific. When the trade winds then re-intensify, the increase in the dynamical response of the ocean leads to a stronger equatorial upwelling. These two processes both lead to stronger seasonal basin scale feedbacks in the coupled system, increasing the strength of the seasonal cycle of the tropical Pacific sector by around 10%. This means that the diurnal cycle in the upper ocean plays a part in the coupled feedbacks between ocean and atmosphere that maintain the basic state and the timing of the seasonal cycle of SST and trade winds in the tropical Pacific. The Madden–Julian Oscillation (MJO) is examined by use of a large scale MJO index, lag correlations and composites of events. The inclusion of the diurnal cycle leads to a reduction in overall MJO activity. Precipitation composites show that the MJO is stronger and more coherent when the diurnal cycle of coupling is resolved, with the propagation and different phases being far more distinct both locally and to larger lead times across the tropical Indo-Pacific. Part one of this study showed that that diurnal variability of SST is modulated by the MJO and therefore increases the intraseasonal SST response to the different phases of the MJO. Precipitation-based composites of SST variability confirm this increase in the coupled simulations. It is argued that including this has increased the thermodynamical coupling of the ocean and atmosphere on the timescale of the MJO (20–100 days), accounting for the improvement in the MJO strength and coherency seen in composites of precipitation and SST. These results show that the diurnal cycle of ocean–atmosphere interaction has profound impact on a range of up-scale variability in the tropical climate and as such, it is an important feature of the modelled climate system which is currently either neglected or poorly resolved in state of the art coupled models.     

Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models

 This study compares radiative fluxes and cloudiness fields from three general circulation models (the HadAM4 version of the Hadley Centre Unified model, cycle 16r2 of the ECMWF model and version LMDZ 2.0 of the LMD GCM), using a combination of satellite observations from the Earth Radiation Budget Experiment (ERBE) and the International Satellite Cloud Climatology Project (ISCCP). To facilitate a meaningful comparison with the ISCCP C1 data, values of column cloud optical thickness and cloud top pressure are diagnosed from the models in a manner consistent with the satellite view from space. Decomposing the cloud radiative effect into contributions from low-medium- and high-level clouds reveals a tendency for the models' low-level clouds to compensate for underestimates in the shortwave cloud radiative effect caused by a lack of high-level or mid-level clouds. The low clouds fail to compensate for the associated errors in the longwave. Consequently, disproportionate errors in the longwave and shortwave cloud radiative effect in models may be taken as an indication that compensating errors are likely to be present. Mid-level cloud errors in the mid-latitudes appear to depend as much on the choice of the convection scheme as on the cloud scheme. Convective and boundary layer mixing schemes require as much consideration as cloud and precipitation schemes when it comes to assessing the simulation of clouds by models. Two distinct types of cloud feedback are discussed. While there is reason to doubt that current models are able to simulate potential `cloud regime' type feedbacks with skill, there is hope that a model capable of simulating potential `cloud amount' type feedbacks will be achievable once the reasons for the remaining differences between the models are understood. Received: 23 January 2000 / Accepted: 24 January 2001     

Stochastic simulations of the Madden�CJulian oscillation activity

The Madden?CJulian oscillation (MJO) is the most prominent form of tropical intraseasonal variability. This study investigated the following questions. Do interannual-to-decadal variations in tropical sea surface temperature (SST) lead to substantial changes in MJO activity? Was there a change in the MJO in the 1970s? Can this change be associated to SST anomalies? What was the level of MJO activity in the pre-reanalysis era? These questions were investigated with a stochastic model of the MJO. Reanalysis data (1948?C2008) were used to develop a nine-state first order Markov model capable to simulate the non-stationarity of the MJO. The model is driven by observed SST anomalies and a large ensemble of simulations was performed to infer the activity of the MJO in the instrumental period (1880?C2008). The model is capable to reproduce the activity of the MJO during the reanalysis period. The simulations indicate that the MJO exhibited a regime of near normal activity in 1948?C1972 (3.4?events?year^?1) and two regimes of high activity in 1973?C1989 (3.9 events) and 1990?C2008 (4.6 events). Stochastic simulations indicate decadal shifts with near normal levels in 1880?C1895 (3.4 events), low activity in 1896?C1917 (2.6 events) and a return to near normal levels during 1918?C1947 (3.3 events). The results also point out to significant decadal changes in probabilities of very active years (5 or more MJO events): 0.214 (1880?C1895), 0.076 (1896?C1917), 0.197 (1918?C1947) and 0.193 (1948?C1972). After a change in behavior in the 1970s, this probability has increased to 0.329 (1973?C1989) and 0.510 (1990?C2008). The observational and stochastic simulations presented here call attention to the need to further understand the variability of the MJO on a wide range of time scales.     

An Assessment of MJO and Tropical Waves Simulated by Different Versions of the GAMIL Model

Simulated outgoing longwave radiation (OLR) outputs by two versions of the grid-point atmospheric general circulation model (GAMIL) were analyzed to assess the influences of improvements in cloud microphysics and convective parameterization schemes on the simulation of the Madden-Julian oscillation (MJO) and other tropical waves. The wavenumber-frequency spectral analysis was applied to isolate dominant modes of convectively coupled equatorial waves, including the MJO, Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), and inertio-gravity (IG) waves. The performances of different versions of the GAMIL model (version 1.0 (GAMIL1.0) and version 2.0 (GAMIL2.0)) were evaluated by comparing the power spectrum distributions of these waves among GAMIL1.0, GAMIL2.0, and observational data. GAMIL1.0 shows a weak MJO signal, with the maximum variability occurring separately at wavenumbers 1 and 4 rather than being concentrated on wavenumbers 1–3, suggesting that GAMIL1.0 could not effectively capture the intraseasonal variability. However, GAMIL2.0 is able to effectively reproduce both the symmetric and anti-symmetric waves, and the significant spectra of the MJO, Kelvin, and MRG waves are in agreement with observational data, indicating that the ability of GAMIL2.0 to simulate the MJO and other tropical waves is enhanced by improving the cloud microphysics and convective parameterization schemes and implying that such improvements are crucial to further improving this model’s performance.     

The radiative influence of aerosol effects on liquid-phase cumulus and stratiform clouds based on sensitivity studies with two climate models

Aerosol effects on warm (liquid-phase) cumulus cloud systems may have a strong radiative influence via suppression of precipitation in convective systems. A consequence of this suppression of precipitation is increased liquid water available for large-scale stratiform clouds, through detrainment, that in turn affect their precipitation efficiency. The nature of this influence on radiation, however, is dependent on both the treatment of convective condensate and the aerosol distribution. Here, we examine these issues with two climate models—CSIRO and GISS, which treat detrained condensate differently. Aerosol–cloud interactions in warm stratiform and cumulus clouds (via cloud droplet formation and autoconversion) are treated similarly in both models. The influence of aerosol–cumulus cloud interactions on precipitation and radiation are examined via simulations with present-day and pre-industrial aerosol emissions. Sensitivity tests are also conducted to examine changes to climate due to changes in cumulus cloud droplet number (N _c); the main connection between aerosols and cumulus cloud microphysics. Results indicate that the CSIRO GCM is quite sensitive to changes in aerosol concentrations such that an increase in aerosols increases N _c, cloud cover, total liquid water path (LWP) and reduces total precipitation and net cloud radiative forcings. On the other hand, the radiative fluxes in the GISS GCM appear to have minimal changes despite an increase in aerosols and N _c. These differences between the two models—reduced total LWP in the GISS GCM for increased aerosols, opposite to that seen in CSIRO—appear to be more sensitive to the detrainment of convective condensate, rather than to changes in N _c. If aerosols suppress convective precipitation as noted in some observationally based studies (but not currently treated in most climate models), the consequence of this change in LWP suggests that: (1) the aerosol indirect effect (calculated as changes to net cloud radiative forcing from anthropogenic aerosols) may be higher than previously calculated or (2) lower than previously calculated. Observational constrains on these results are difficult to obtain and hence, until realistic cumulus-scale updrafts are implemented in models, the logic of detraining non-precipitating condensate at appropriate levels based on updrafts and its effects on radiation, will remain an uncertainty.