Cloud Microphysical Processes Research Articles

Representation of microphysical processes in cloud‐resolving models: Spectral (bin) microphysics versus bulk parameterization

AbstractMost atmospheric motions of different spatial scales and precipitation are closely related to phase transitions in clouds. The continuously increasing resolution of large‐scale and mesoscale atmospheric models makes it feasible to treat the evolution of individual clouds. The explicit treatment of clouds requires the simulation of cloud microphysics. Two main approaches describing cloud microphysical properties and processes have been developed in the past four and a half decades: bulk microphysics parameterization and spectral (bin) microphysics (SBM). The development and utilization of both represent an important step forward in cloud modeling. This study presents a detailed survey of the physical basis and the applications of both bulk microphysics parameterization and SBM. The results obtained from simulations of a wide range of atmospheric phenomena, from tropical cyclones through Arctic clouds using these two approaches are compared. Advantages and disadvantages, as well as lines of future development for these methods are discussed.

In-situ measurements of cloud-precipitation microphysics in the East Asian monsoon region since 1960

A large number of in-situ measurements of cloud-precipitation microphysical properties have been made since 1960, including measurements of particle size distribution, particle concentration, and liquid water content of clouds and rain. These measurements have contributed to considerable progress in understanding microphysical processes in clouds and precipitation and significant improvements in parameterizations of cloud microphysics in numerical models. This work reviews key findings regarding cloud-precipitation microphysics over China. The total number concentrations of various particles vary significantly, with certain characteristic spatial scales. The size distributions of cloud droplets in stratiform clouds can generally be fit with gamma distributions, but the fit parameters cover a wide range. Raindrop size distributions (RSDs) associated with stratiform clouds can be fit with either exponential or gamma distributions, while RSDs associated with convective or mixed stratiform-cumuliform clouds are best fit with gamma distributions. Concentrations of ice nuclei (IN) over China are higher than those observed over other regions, and increase exponentially as temperature decreases. The particle size distributions of ice crystals, snow crystals, and hailstones sampled at a variety of locations can be reliably approximated by using exponential distributions, while aerosol particle size distributions are best described as the sum of a modified gamma distribution and a Junge power-law distribution. These results are helpful for evaluating and improving the fidelity of physical processes and hydrometeor fields simulated by microphysical parameterizations. The comprehensive summary and analysis of previous work presented here also provide useful guidelines for the design of future observational programs.

Impacts of Cloud Droplet–Nucleating Aerosols on Shallow Tropical Convection

Abstract Low-level warm-phase clouds cover a substantial portion of Earth’s oceans and play an important role in the global water and energy budgets. The characteristics of these clouds are controlled by the large-scale environment, boundary layer conditions, and cloud microphysics. Variability in the concentration of aerosols can alter cloud microphysical and precipitation processes that subsequently impact the system dynamics and thermodynamics and thereby create aerosol–cloud dynamic–thermodynamic feedback effects. In this study, three distinct cloud regimes were simulated, including stratocumulus, low-level cumulus (cumulus under stratocumulus), and deeper cumulus clouds. The simulations were conducted without environmental large-scale forcing, thereby allowing all three cloud types to freely interact with the environmental state in an undamped fashion. Increases in aerosol concentration in these unforced, warm-phase, tropical cloud simulations lead to the production of fewer low-level cumuli; thinning and erosion of the widespread stratocumulus layer; and the development of deeper, inversion-penetrating cumuli. The mechanisms for these changes are explored. Despite the development of deeper, more heavily precipitating cumuli, the reduction of the widespread moderately precipitating stratocumulus clouds leads to an overall reduction in domainwide accumulated precipitation when aerosol concentrations are enhanced.

Evaluation of cloud properties in the NCEP CFSv2 model and its linkage with Indian summer monsoon

Cloud fraction, which varies greatly among general circulation models, plays a crucial role in simulation of Indian summer monsoon rainfall (ISMR). The NCEP Climate Forecast System version 2 (CFSv2) model is evaluated in terms of its simulation of cloud fraction, cloud condensate, outgoing longwave radiation (OLR), and tropospheric temperature (TT). Biases in these simulated quantities are computed using observations from CALIPSO and reanalysis data from MERRA. It is shown that CFSv2 underestimates (overestimates) high- (mid-) level clouds. The cloud condensate is also examined to see its impact on different types of clouds. The upper-level cloud condensate is underestimated, particularly during the summer monsoon period, which leads to a cold TT and a dry precipitation bias. The unrealistically weak TT gradient between ocean and land is responsible for the underestimation of ISMR. The model-simulated OLR is overestimated which depicts the weaker convective activity. A large underestimate of precipitable water is also seen along the cross-equatorial flow and particularly over the Indian land region collocated with a dry precipitation bias. The linkages among cloud microphysical, thermodynamical, and dynamical processes are identified here. Thus, this study highlights the importance of cloud properties, a major cause of uncertainty in CFSv2, and also proposes a pathway for improvements in its simulation of the Indian summer monsoon.

An attempt to improve Kessler-type parameterization of warm cloud microphysical conversion processes using CloudSat observations

Improvements to the Kessler-type parameterization of warm cloud microphysical conversion processes (also called autoconversion) are proposed based on a large number of CloudSat observations between June 2006 and April 2011 over Asian land areas. The emphasis is given to the vertical distribution of liquid water content (LWC), particularly, the threshold values of LWC for autoconversion. The results warrant a new approach to the numerical parameterization of autoconversion in warm clouds. One feature of this new approach is that the autoconversion threshold, which has been treated as a constant in previous parameterization schemes, is diagnosed as a function of altitude by using a relationship between LWC and height (H) derived from CloudSat observations: $$LWC_{dig} = - 500.0\ln \left( {\frac{H} {{9492.2}}} \right)$$ . Under this framework, the threshold LWC decreases with increasing H, allowing autoconversion to occur in clouds with low LWC (approximately 0.3 g m−3) at levels above 5.5 km. Autoconversion rates calculated based on the new parameterization are compared to those calculated based on several commonly used parameterization schemes over a range of LWCs from 0.01 to 1.0 g m−3. The new scheme provides reasonable simulations of autoconversion at various vertical levels.

Aerosol-cloud-precipitation interactions in WRF model: Sensitivity to autoconversion parameterization

Cloud-to-rain autoconversion process is an important player in aerosol loading, cloud morphology, and precipitation variations because it can modulate cloud microphysical characteristics depending on the participation of aerosols, and affects the spatio-temporal distribution and total amount of precipitation. By applying the Kessler, the Khairoutdinov-Kogan (KK), and the Dispersion autoconversion parameterization schemes in a set of sensitivity experiments, the indirect effects of aerosols on clouds and precipitation are investigated for a deep convective cloud system in Beijing under various aerosol concentration backgrounds from 50 to 10000 cm−3. Numerical experiments show that aerosol-induced precipitation change is strongly dependent on autoconversion parameterization schemes. For the Kessler scheme, the average cumulative precipitation is enhanced slightly with increasing aerosols, whereas surface precipitation is reduced significantly with increasing aerosols for the KK scheme. Moreover, precipitation varies non-monotonically for the Dispersion scheme, increasing with aerosols at lower concentrations and decreasing at higher concentrations. These different trends of aerosol-induced precipitation change are mainly ascribed to differences in rain water content under these three autoconversion parameterization schemes. Therefore, this study suggests that accurate parameterization of cloud microphysical processes, particularly the cloud-to-rain autoconversion process, is needed for improving the scientific understanding of aerosol-cloud-precipitation interactions.

Observation and modeling analyses of the macro- and microphysical characteristics of a heavy rain storm in Beijing

Beijing and its surrounding areas experienced a heavy rain event from 21 to 22 July 2012. The event can be divided into two phases: a warm-sector precipitation phase, ahead of the cold front, and a cold front precipitation phase. Observational analyses indicated that this rain event resulted from the cooperation of upper- and lower-level weather systems, and also the development and merging of mesoscale convective storm clusters in cumulus-embedded stratus. Simulation results showed that water vapor and hydrometeors transported into Beijing came mainly from the west and south and then exited from the north and east in general. All hydrometeors except ice crystals showed net inflow during the warm-sector phase, while all hydrometeors showed net outflow during the cold front phase overall. The interactions between cold and warm cloud microphysical processes generated the severe precipitation, with melting of graupel into rainwater contributing the most. Cold cloud processes contributed more to rain in the cold front phase compared to that in the warm-sector phase. The general precipitation and hydrometeor precipitation efficiencies were 67.0% and 86.3% in the warm-sector phase, while those in the cold front phase were 44.0% and 74.6%, respectively.

Explicit representation of subgrid variability in cloud microphysics yields weaker aerosol indirect effect in the ECHAM5-HAM2 climate model

Abstract. The impacts of representing cloud microphysical processes in a stochastic subcolumn framework are investigated, with emphasis on estimating the aerosol indirect effect. It is shown that subgrid treatment of cloud activation and autoconversion of cloud water to rain reduce the impact of anthropogenic aerosols on cloud properties and thus reduce the global mean aerosol indirect effect by 19%, from −1.59 to −1.28 W m−2. This difference is partly related to differences in the model basic state; in particular, the liquid water path (LWP) is smaller and the shortwave cloud radiative forcing weaker when autoconversion is computed separately for each subcolumn. However, when the model is retuned so that the differences in the basic state LWP and radiation balance are largely eliminated, the global-mean aerosol indirect effect is still 14% smaller (i.e. −1.37 W m−2) than for the model version without subgrid treatment of cloud activation and autoconversion. The results show the importance of considering subgrid variability in the treatment of autoconversion. Representation of several processes in a self-consistent subgrid framework is emphasized. This paper provides evidence that omitting subgrid variability in cloud microphysics contributes to the apparently chronic overestimation of the aerosol indirect effect by climate models, as compared to satellite-based estimates.

Dominant cloud microphysical processes of a torrential rainfall event in Sichuan, China

High-resolution numerical simulation data of a rainstorm triggering debris flow in Sichuan Province of China simulated by the Weather Research and Forecasting (WRF) Model were used to study the dominant cloud microphysical processes of the torrential rainfall. The results showed that: (1) In the strong precipitation period, particle sizes of all hydrometeors increased, and mean-mass diameters of graupel increased the most significantly, as compared with those in the weak precipitation period; (2) The terminal velocity of raindrops was the strongest among all hydrometeors, followed by graupel’s, which was much smaller than that of raindrops. Differences between various hydrometeors’ terminal velocities in the strong precipitation period were larger than those in the weak precipitation period, which favored relative motion, collection interaction and transformation between the particles. Absolute terminal velocity values of raindrops and graupel were significantly greater than those of air upward velocity, and the stronger the precipitation was, the greater the differences between them were; (3) The orders of magnitudes of the various hydrometeors’ sources and sinks in the strong precipitation period were larger than those in the weak precipitation period, causing a difference in the intensity of precipitation. Water vapor, cloud water, raindrops, graupel and their exchange processes played a major role in the production of the torrential rainfall, and there were two main processes via which raindrops were generated: abundant water vapor condensed into cloud water and, on the one hand, accretion of cloud water by rain water formed rain water, while on the other hand, accretion of cloud water by graupel formed graupel, and then the melting of graupel formed rain water.

Cloud formation, convection, and stratospheric dehydration

AbstractUsing the Modern‐Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds, temperatures, and anvil cloud ice, we use our domain‐filling, forward trajectory model combined with a new cloud module to show that convective transport of saturated air and ice to altitudes below the tropopause has a significant impact on stratospheric water vapor and upper tropospheric clouds. We find that including cloud microphysical processes (rather than assuming that parcel water vapor never exceeds saturation) increases the lower stratospheric average H2O by 10–20%. Our model‐computed cloud fraction shows reasonably good agreement with tropical upper troposphere (TUT) cloud frequency observed by the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument in boreal winter with poorer agreement in summer. Our results suggest that over 40% of TUT cirrus is due to convection, and it is the saturated air from convection rather than injected cloud ice that primarily contributes to this increase. Convection can add up to 13% more water to the stratosphere. With just convective hydration (convection adds vapor up to saturation), the global lower stratospheric modeled water vapor is close to Microwave Limb Sounder observations. Adding convectively injected ice increases the modeled water vapor to ~8% over observations. Improving the representation of MERRA tropopause temperatures fields reduces stratospheric water vapor by ~4%.

GCMs with implicit and explicit representation of cloud microphysics for simulation of extreme precipitation frequency

The present study aims to develop a general circulation model (GCM) with improved simulation of heavy precipitation frequency by improving the representations of cloud and rain processes. GCMs with conventional convective parameterizations produce common bias in precipitation frequency: they overestimate light precipitation and underestimate heavy precipitation with respect to observed values. This frequency shift toward light precipitation is attributed here to a lack of consideration of cloud microphysical processes related to heavy precipitation. The budget study of cloud microphysical processes using a cloud-resolving model shows that the melting of graupel and accretion of cloud water by graupel and rain water are important processes in the generation of heavy precipitation. However, those processes are not expressed explicitly in conventional GCMs with convective parameterizations. In the present study, the cloud microphysics is modified to allow its implementation into a GCM with a horizontal resolution of 50 km. The newly developed GCM, which includes explicit cloud microphysics, produces more heavy precipitation and less light precipitation than conventional GCMs, thus simulating a precipitation frequency that is closer to the observed. This study demonstrates that the GCM requires a full representation of cloud microphysics to simulate the extreme precipitation frequency realistically. It is also shown that a coarse-resolution GCM with cloud microphysics requires an additional mixing process in the lower troposphere.

Numerical simulation of the flow fields around falling ice crystals with inclined orientation and the hydrodynamic torque

The flow field and orientation of ice particles are fundamental information to understand cloud microphysical processes, optical phenomena, and electric-field induced orientation and to improve remote sensing of ice clouds. The purpose of this study is to investigate the flow fields and hydrodynamic torques of falling ice columns and hexagonal plates with their largest dimension inclined with respect to the airflow. The Reynolds numbers range from 2 to 70 for columns and 2 to 120 for plates. The flow fields are obtained by numerically solving the relevant Navier–Stokes equations under the assumption of air incompressibility. It was found that for the intermediate Reynolds number the streamlines around the inclined crystals exhibit less spiral rotation behind them than those around the stable posture. The vorticity magnitude was larger in the upstream side and broader in the downstream than the one without inclination. For plates, a high-pressure dome on the center of the lower basal face disappears with inclination, possibly leading to an increase of riming there. The torques acting on the crystals have a local maximum over the inclined angle and exhibit almost symmetric around 45° over the range of Reynolds numbers. The torque parameterization was performed under pressures of 300, 500, and 800hPa as a function of Reynolds number and aspect ratio. It was found that the time scale of rotation for plates is smaller than the one for columns. Furthermore, the torque formula was applied to assess alignment of crystals along electric fields. It was found that these crystals of millimeter size require 120kV/m for the electrical alignment, which agrees with previous studies.

Impact of the sea surface temperature rise on storm‐track clouds in global nonhydrostatic aqua planet simulations

AbstractAqua planet experiments were conducted to investigate storm‐track cloud change due to sea surface temperature (SST) rise. Fourteen kilometer mesh global nonhydrostatic model was employed with an explicit cloud microphysical process, and the model output data were composited to the cyclone center. Both the column‐integrated liquid and ice cloud contents are significantly increased around the cyclone center due to the SST rise. The occurrence of low‐level liquid clouds becomes more frequent not only near the cyclone center but also for all of the higher latitudes, which cannot be seen in low‐resolution models. This as well as thicker liquid clouds enhances shortwave cooling. Upper level ice clouds occur more frequently on the east side of the cyclone center, and they partly offset the enhanced shortwave cooling through longwave warming. These results may imply an importance of the cloud‐scale process with cloud microphysics on the storm‐track clouds and their radiative forcing.

Dehydration in the tropical tropopause layer: A case study for model evaluation using aircraft observations

AbstractThe dynamical and microphysical processes that influence water vapor concentrations in the tropical tropopause layer (TTL) are investigated in simulations of ice clouds along backward trajectories of air parcels sampled during three flights of the Airborne Tropical Tropopause Experiment over the central to eastern tropical Pacific in boreal fall 2011. ERA‐Interim reanalysis temperatures interpolated onto the flight tracks have a negligible (−0.09 K) cold bias compared to aircraft measurements of tropical cold point temperature thus permitting case study simulations of TTL dehydration. When the effects of subgrid‐scale waves, cloud microphysical processes, and convection are considered, the simulated water vapor mixing ratios on the final day of 40 day backward trajectories exhibit a mean profile that is within 20–30% of the mean of the aircraft measurements collected during vertical profiling maneuvers between the 350 and 410 K potential temperature levels. Averaged over the three flights, temperature variability driven by subgrid‐scale waves dehydrated the 360–390 K layer by approximately −0.5 ppmv, whereas including homogeneous freezing of aqueous aerosols and subsequent sublimation and rehydration of ice crystals increased water vapor below the 380 K level by about +1 ppmv. The predominant impact of convection was to moisten the TTL, resulting in an average enhancement below the 370 K level by +1 to 5 ppmv. Accurate (to within 0.5–1 ppmv) predictions of TTL water vapor using trajectory models require proper representations of waves, in situ ice cloud formation, and convective influence, which together determine the saturation history of air parcels.

The cloud-microphysical cause of torrential rainfall amplification associated with Bilis (0604)

After its landfall in China’s mainland in 2006, Typhoon Bilis brought about torrential rainfall amplification at the edge of Guangdong, Jiangxi, and Hunan provinces, causing severe disasters. From a cloud-microphysical perspective, we discuss the differences of cloud-microphysical processes before and during the precipitation amplification and possible causes of the rainfall amplification by using high-resolution simulation data. The results show that the cloud-microphysical characteristics during the above two periods are significantly different. With the distinct increase in the rainfall intensity, the cloud hydrometeor contents increase markedly, especially those of the ice-phase hydrometeors including ice, snow and graupel, contributing more to the surface rainfall. The clouds develop highly and vigorously. Comparisons of conversion rates of the cloud hydrometeors between the above two periods show that the distinct increases in the cloud water content caused by the distinct enhancement of the water vapor condensation rate contribute to the surface rainfall mainly in two ways. First, the rain water content increases significantly by accretion of cloud water by rain water, which thus contributes to the surface rainfall. Second, the accretion of cloud water by snow increases significantly the content of snow, which is then converted to graupel by accretion of snow by graupel. And then the graupel melts into rain water, which subsequently contributes to the surface rainfall amplification. In summary, a flow chart is given to clarify the cloud-microphysical cause of the torrential rainfall amplification associated with Bilis.

Natural and anthropogenic aerosols in the Eastern Mediterranean and Middle East: Possible impacts

The physical and chemical properties of airborne particles have significant implications on the microphysical cloud processes. Maritime clouds have different properties than polluted ones and the final amounts and types of precipitation are different. Mixed phase aerosols that contain soluble matter are efficient cloud condensation nuclei (CCN) and enhance the liquid condensate spectrum in warm and mixed phase clouds. Insoluble particles such as mineral dust and black carbon are also important because of their ability to act as efficient ice nuclei (IN) through heterogeneous ice nucleation mechanisms. The relative contribution of aerosol concentrations, size distributions and chemical compositions on cloud structure and precipitation is discussed in the framework of RAMS/ICLAMS model. Analysis of model results and comparison with measurements reveals the complexity of the above links. Taking into account anthropogenic emissions and all available aerosol–cloud interactions the model precipitation bias was reduced by 50% for a storm simulation over eastern Mediterranean.

Impact of cloud microphysics and cumulus parameterization on simulation of heavy rainfall event during 7–9 October 2007 over Bangladesh

In the present study, the Advanced Research WRF (ARW) version 3.2.1 has been used to simulate the heavy rainfall event that occurred between 7 and 9 October 2007 in the southern part of Bangladesh. Weather Research and Forecast (WRF–ARW version) modelling system with six different microphysics (MP) schemes and two different cumulus parameterization (CP) schemes in a nested configuration was chosen for simulating the event. The model domains consist of outer and inner domains having 9 and 3 km horizontal resolution, respectively with 28 vertical sigma levels. The impacts of cloud microphysical processes by means of precipitation, wind and reflectivity, kinematic and thermodynamic characteristics of the event have been studied. Sensitivity experiments have been conducted with the WRF model to test the impact of microphysical and cumulus parameterization schemes in capturing the extreme weather event. NCEP FNL data were used for the initial and boundary condition. The model ran for 72 h using initial data at 0000 UTC of 7 October 2007. The simulated rainfall shows that WSM6–KF combination gives better results for all combinations and after that Lin–KF combination. WSM3–KF has simulated, less area average rainfall out of all MP schemes that were coupled with KF scheme. The sharp peak of relative humidity up to 300 hPa has been simulated along the vertical line where maximum updraft has been found for all MPs coupled with KF and BMJ schemes. The simulated rain water and cloud water mixing ratio were maximum at the position where the vertical velocity and reflectivity has also been maximum. The production of rain water mixing ratio depends on MP schemes as well as CP schemes. Rainfall depends on rain water mixing ratio between 950 and 500 hPa. Rain water mixing ratio above 500 hPa level has no effect on surface rain.

Implementation of an aerosol–cloud‐microphysics–radiation coupling into the NASA unified WRF: Simulation results for the 6–7 August 2006 AMMA special observing period

Aerosols affect the Earth's radiation balance directly and cloud microphysical processes indirectly via the activation of cloud condensation and ice nuclei. These two effects have often been considered separately and independently, hence the need to assess their combined impact given the differing nature of their effects on convective clouds. To study both effects, an aerosol–microphysics–radiation coupling, including Goddard microphysics and radiation schemes, was implemented into the NASA Unified Weather Research and Forecasting model (NU‐WRF). Fully coupled NU‐WRF simulations were conducted for a mesoscale convective system (MCS) that passed through the Niamey, Niger area on 6–7 August 2006 during an AMMA special observing period. The results suggest that rainfall is reduced when aerosol indirect effects are included, regardless of the aerosol direct effect. Daily mean radiation heating profiles in the area traversed by the MCS showed the aerosol (mainly mineral dust) direct effect had the largest impact near cloud tops just above 200 hPa where short‐wave heating increased by about 0.8 K day−1; the weakest long‐wave cooling was at around 250 hPa. It was also found that more condensation and ice nuclei as a result of higher aerosol/dust concentrations led to increased amounts of all cloud hydrometeors because of the microphysical indirect effect, and the radiation direct effect acts to reduce precipitating cloud particles (rain, snow and graupel) in the middle and lower cloud layers while increasing the non‐precipitating particles (ice) in the cirrus anvil. However, when the aerosol direct effect was activated, regardless of the indirect effect, the onset of MCS precipitation was delayed about 2 h, in conjunction with the delay in the activation of cloud condensation and ice nuclei. Overall, for this particular environment, model set‐up and physics configuration, the effect of aerosol radiative heating due to mineral dust overwhelmed the effect of the aerosols on microphysics.

The Impact of Ice Phase Cloud Parameterizations on Tropical Cyclone Prediction

Abstract The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

Simulations of an isolated two-dimensional thunderstorm: Sensitivity to cloud droplet size and the presence of graupel

Cloud Resolving Models (CRMs) which are used increasingly to make operational forecasts, employ Bulk Microphysics Schemes (BMSs) to describe cloud microphysical processes. In this study two BMSs are employed in a new Nonhydrostatic σ-coordinate Model to perform two hour simulations of convection initiated by a warm bubble, using a horizontal grid resolution of 500 m. Different configurations of the two BMSs are applied, to test the effects of the presence of graupel with one scheme (2-configurations) and of changing the cloud droplet sizes in the second scheme (4-configurations), on the simulation of idealised thunderstorms. Maximum updrafts in all the simulations are similar over the first 40 minutes, but start to differ beyond this point. The first scheme simulates the development of a second convective cell that is triggered by the cold pool that develops from the outflow of the first storm. The cold pool is more intense in the simulation with graupel because of melting of graupel particles, which results in relatively large raindrops, decreases the temperature through latent heat absorption, causing stronger downdrafts, which all contribute to the formation of a more intense cold pool. The second scheme simulates the development of a second cell in two of its configurations, while two other configurations do not simulate the redevelopment. Two configurations that simulate the secondary redevelopment produce a slightly stronger cold pool just before redevelopment. Our results show that small differences in the microphysics formulations result in simulations of storm dynamics that diverge, possibly due nonlinearities in the model.